MILOUD Bentoumi

KOURICHE Meriem , KHAZAAR Sara

Etude des fuites d'eau et contribution au développement d'une méthode de leurs détections et localisations

-DJEDDI Safinez , BADA Aya, BENDAOUD Chaima

Détection de fuite dans les réseaux de distribution d'eau par application de nouvelles techniques

sabir MEFTAH

Développement d'un système de détection et de localisation de fuites basé sur les modèles paramétriques

YETTOU ASSIA

Design and Modeling of Ka band Wilkinson Power divider

DAHMANI Zeyneb , BEN MIMOUNA Afaf, BELARIBI Nesrine

Conception et réalisation d’un détecteur de fuite d’eau dans les réseaux de distribution

1. MELIANI Nassim safwan , 2. ZOUAOUI Chahinez

Etude et implémentation d’un système de détection de fuite d’eau basé sur un modèle développé

BOUCHELIG Siham , CHAKER Amina

Conception d’une antenne bi-bande pour les applications 5G

GUELMINE, Nora Sakina , LADEJNEF, Manel

Simulation et conception d'un filtre pour des applications médicales ( signaux ECG)

CHARIKH, YOUSRA , DOUCENE, HAFSA

Implémentation d’un système de détection De fuite autour d’un système de traitement De signal numérique

LAGUEAGUE Seyfeddine , OUALI Elhadj Taieb

Détection des fuires dans les réseaux de distribution d'eau

ZEGAAR Imane , GHERBI Aicha

Etude et conception d’un filtre passe bande à base de résonateur à saut d’impédance pour les systèmes de communication sans fil

Leak detection in water distribution networks is often hindered by noise and distortions in pressure signals, which can lead to false alarms and inaccurate localization. This study investigates the application of intelligent filtering techniques for denoising non-stationary transient pressure signals collected from a hydraulic prototype with leak size of 4mm. Pressure data were acquired using high-precision transmitters and processed through both the Savitzky–Golay (S.G) filter and the Kalman filter. The performance of these filters was evaluated using three statistical criteria: signal-tonoise ratio (SNR), correlation coefficient (CC), and percentage root mean square difference (PRD). The results demonstrate that the S.G filter achieves superior denoising performance compared to the Kalman filter, as it preserves transient signal characteristics more effectively while reducing noise. These findings highlight the potential of the S.G filter as a reliable tool for enhancing data quality in leak detection applications, thus contributing to more accurate fault diagnosis in water distribution systems.

Citation

Miloud BENTOUMI , ,(2025-12-10), Enhancement of Transient Signal Quality in Leak Detection Applications via Savitzky-Golay and Kalman Filtering,ICATEEE2025,M'sila

Leaks in water distribution networks (WDN) pose serious challenges, leading to water losses, a deterioration in quality through the penetration of contaminants causing waterborne diseases harmful to public health, and significant financial and environmental impacts. Timely and accurate leak detection is essential for efficient water management and infrastructure sustainability. This study presents a robust methodology for leak detection, localization, and volume rate estimation in pipelines, primarily leveraging analysis of internal pressure signals. The approach utilizes real-time pressure monitoring to identify anomalies indicative of a leak. Leak detection is achieved by observing characteristic pressure drops, which are clearly distinguishable from normal operating conditions. Furthermore, the precise location of a leak is determined by analyzing the transient pressure wave propagation. For volume rate estimation, the Area Under the Curve (AUC) of the pressure-time signal is employed as a key metric. Experimental results demonstrate that the AUC provides a quantifiable measure highly correlated with leak size; specifically, a defined baseline AUC for "no-leak" conditions 497.10 PSI.S significantly deviates from AUC values observed during leak events ranging from 451.03 PSI.S for smaller leaks to 430.20 PSI.S for larger leaks. All leak scenarios consistently fall below a pre-established detection threshold 492.10 PSI.S, confirming the effectiveness of the method. This integrated framework offers a practical and accurate solution for proactive pipeline management, enabling rapid identification and characterization of leaks to minimize their impact.

Citation

Miloud BENTOUMI , ,(2025-12-10), Leak Detection and Localization in Pipelines with Volume Rate Estimation Based on Pressure Signals,ICATEEE2025,M'sila

Water distribution systems (WDS) are critical infrastructure that supply water to communities, but leaks often occur in these systems and can lead to significant water losses and operational inefficiencies. Traditional leak detection methods often strugglewith environmental noise and limited scalability. This research proposes a data-driven approach for leak detection using pressure transducers and machine learning (ML). The research contribution is the design of a low-cost, noise-resistant leak detection framework and a comparative analysis of multiple ML classifiers based on experimental data. To facilitate data acquisition, we constructed a prototype PEHD hydraulic circuit that measures 100 meters in length and 40 mm in diameter, on which two pressure transmitters were installed. Data were collected via a dSPACE acquisition system during both normal and leak-induced conditions. Six ML models—support vector machine (SVM), decision tree (DT), random forest (RF), naïve Bayes (NB), logistic regression (LR), and k-nearest neighbors (KNN)—were trained and evaluated using standard classification metrics. LR outperformed all other models, achieving 100% across accuracy, precision, recall, and F1-score. This result may be attributed to the linear separability of the leak signatures in the experimental setup. However, further validation is necessary to assess model generalizability under real-world conditions with varying pipe materials, flow rates, and noise levels. The study demonstrates that integrating pressure transducers with ML can enable reliable leak detection in WDNs, offering a scalable, hardware-efficient monitoring solution. Future work will focus on expanding the dataset and evaluating system performance in live environments.

Citation

Miloud BENTOUMI , , (2025-11-20), Enhance the Effectiveness of Leak Detection in Water Distribution Networks (WDNs) Using Machine Learning (ML) and Pressure Transducers, International Journal of Robotics and Control Systems, Vol:5, Issue:4, pages:2218-2245, assocoation for scientific computing electronics and engineering

A composite material made of Copper (II) Oxide (CuO) and Barium Titanate (BT) particles in powder form, with different quantities dispersed within an epoxy resin (RE) matrix, has been prepared. The time-domain spectroscopy (TDS) bench and the discrete Fourier transform (DFT) calculated using the Samulon approach are used to obtain the dielectric permittivity spectrum in the frequency band up to 3 GHz. The results obtained confirm that the permittivity of the composite can be predicted by the Lichtenecker law and the grain effect highlighted by the form factor of the modified Lichtenecker formula. The alternating current (AC) conductivity depends on frequency, fits Jonsher’s behavior law, and shows a plateau in the low-frequency range. An increase in was observed as the frequency increased. The static conductivity is affected by the volume fraction of CuO. The impedance spectra exhibit both grain and grain-border effects. The high concentration of CuO also confirms the grain effect on conductivity. The manufactured dielectric composites exhibit great stability as a function of frequency, which is essential in radio frequency (RF) and microwave applications, next-generation communication systems, radars, aerospace applications, antennas, RF filters, substrates, and modern wireless technologies.

Citation

Miloud BENTOUMI , , (2025-08-20), Examination of Copper Oxide’s Effect on the RE-BT-CuO Composite’s Dielectric Properties, ECS Journal of Solid State Science and Technology,, Vol:14, Issue:8, pages:2218-2245, Published on behalf of ECS by IOP Publishing Limited.

Water distribution networks (WDNs) are vital infrastructure systems responsible for delivering water to communities. However, they are vulnerable to leaks that can lead to substantial water loss, infrastructure deterioration, and elevated operational costs, highlighting the need for advanced monitoring solutions. This study presents an Artificial Intelligence (AI)-driven leak detection approach designed to improve the accuracy of leak identification in WDNs. A prototype pipeline constructed from high-density polyethylene (PEHD) was equipped with pressure transducers and connected to a dSPACE data acquisition system for real-time pressure monitoring. The collected pressure data, encompassing both leak and non-leak scenarios, were transformed into 2D image representations using the Continuous Wavelet Transform (CWT). These images were then analyzed using deep learning, specifically the ResNet50 convolutional neural network (CNN), to extract discriminative spatial and temporal features. The features were subsequently classified using high-performance machine learning algorithms including Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and XGBoost across different data split scenarios (80%-20%, 70%-30%, 60%-40%). The combined use of deep feature extraction and traditional ML classifiers demonstrated excellent leak detection performance, achieving up to 100% accuracy. These results confirm the effectiveness and reliability of the proposed AI-based system for enhancing leak monitoring in WDNs.

Citation

Miloud BENTOUMI , ,(2025-05-06), Leaks Detection in WDNs Using Pressure Signals Based on CWT and CNN,NC-REAEE’25,M'sila

Water distribution networks (WDNs) are critical infrastructure for supplying water to communities but are susceptible to leaks, leading to significant water losses, infrastructure damage, and increased operational costs. Effective monitoring and maintenance solutions are essential to address these challenges. This study presents an advanced leak detection system incorporating an artificial intelligence (AI)-based algorithm to enhance accuracy in identifying water leaks. Real-time pressure variations are sensed using pressure transducers, designed to resist environmental noise, thereby improving system reliability. To facilitate deep data learning (DL), a prototype PEHD hydraulic pipeline was built, measuring 100 m in length and 40 mm in diameter with a thickness of 2.4 mm, on which two pressure transmitters were installed at previously known positions linked to a dSPACE acquisition system. Pressure data, including leakage and no-leakage scenarios, is collected and transformed into 2D images using continuous wavelet transform (CWT). These 2D images are used to trainconvolutional neural networks (CNNs), optimized for extracting spatial and temporal features from image-based data. Transfer learning techniques, leveraging pretrained models like DenseNet, MobileNet, ResNet, and Xception, further enhance feature extraction. Additionally, machine learning (ML) classifiers such as SVM, KNN, and XGBoost are integrated with the CNN framework to improve classification accuracy under dataset splits (80%-20%). A hybrid approach, combining deep feature extraction with traditional classification methods, is proposed as an efficient and accurate solution for leak detection in WDNs.

Citation

Miloud BENTOUMI , ,(2025-04-22), Enhancing Leak Detection in WDNs with CWT and CNN Applied to Pressure Signals.,NC2ET’25,Mascara

Water Distribution Networks (WDNs) are essential infrastructures responsible for delivering water to communities. However, they are highly susceptible to leaks, which result in considerable water losses, increased operational costs, and potential damage to the infrastructure. Accurate and efficient leak detection is therefore critical for ensuring the sustainability of these systems. This study introduces the Empirical Mode Decomposition (EMD) method as an advanced approach to enhance pipeline leak detection. Leaks in pipelines generate acoustic and vibration signals that propagate at low frequencies, exhibiting nonlinear and nonstationary characteristics. To address this, we constructed a prototype hydraulic circuit made of Polyethylene High-Density (PEHD) material, measuring 100 m in length and 40 mm in diameter. The circuit was equipped with vibration transducers and an advanced dSPACE based acquisition system to capture high-resolution data. Traditional signal analysis techniques, such as Fast Fourier Transform (FFT), correlation, and cepstrum analysis, often miss crucial information due to their dependence on narrow frequency bands and the assumption of signal stationarity. EMD, a time-domain decomposition method designed for nonstationary signals, resolves these issues by extracting Intrinsic Mode Functions (IMFs), enabling the separate analysis of signal components. Our experiments involved testing the EMD method on various leak scenarios and comparing it with conventional techniques. The results demonstrate that EMD provides superior leak detection capabilities by effectively analyzing the complex and nonstationary nature of pipeline signals. This approach offers a promising solution for real-time monitoring and maintenance of WDNs, ensuring their operational efficiency and sustainability.

Citation

Miloud BENTOUMI , ,(2024-12-23), Leak Detection in WDNs with PEHD Pipes Using Vibration Signals and EMD,5th International Conference on Scientific and Academic Research,Konya-Turkey

Water Distribution Networks (WDNs) are critical infrastructure for delivering water to populations. However, leaks in these networks can result in significant water losses, increased operational costs, and damage to infrastructure. Traditional leak detection methods often lack the precision for timely and accurate identification. This study proposes an innovative approach combining Discrete Wavelet Transform (DWT) and Convolutional Neural Networks (CNN) for detecting leaks using pressure signals recorded from WDNs. DWT is employed to decompose pressure signals into multi-scale components, enabling the isolation of features relevant to detecting leaks. By converting raw pressure data into a structured representation. DWT enhances the clarity of signal patterns associated with leakage events. These decomposed signals are subsequently analyzed using a CNN, which extracts spatial and temporal features to classify signals into leaky and non-leaky categories. The integration of DWT and CNN ensures that both fine-grained signal variations and broader contextual patterns are effectively captured. The proposed method was validated on a dataset of pressure signals collected from real-world WDNs, demonstrating high accuracy, precision, and recall. Compared to existing techniques, this approach offers superior performance in distinguishing between leakage and non-leakage scenarios, even in complex environments. The results highlight the potential of combining advanced signal processing and deep learning (DL) methods to improve leak detection capabilities significantly reduce water losses and enhance system reliability. Future work will focus on expanding the dataset, integrating additional sensors, and exploring further improvements to detection accuracy and robustness.

Citation

Miloud BENTOUMI , ,(2024-12-13), Advanced Leak Detection in WDNs Using DWT and CNN,4th International Conference on Frontiers in Academic Research,Konya-Turkey

Water Distribution Networks (WDNs) are essential for ensuring the reliable delivery of water to communities. However, they are susceptible to leaks, which can result in substantial water losses, increased operational costs, and damage to the system. Early detection and mitigation of leaks are therefore crucial for maintaining the efficiency and sustainability of WDNs. To detect leaks using pressure signals recorded from WDNs, this study proposes a new method that combines Convolutional Neural Networks (CNN) and Continuous Wavelet Transform (CWT). The CNN can extract significant spatial and temporal information by preprocessing the pressure signals and converting them into time-frequency representations using CWT. The proposed model was trained and evaluated on a dataset of pressure signals from real WDNs, achieving high accuracy, precision, and recall. The results demonstrate the efficacy of integrating CWT for signal processing and CNN for feature extraction to enhance leak detection. This approach provides a promising framework for improving urban infrastructure leak management and maintenance strategies. Future work will focus on validating the model on larger datasets and exploring the integration of additional sensors to enhance detection robustness. This approach not only aids in timely leak identification but also supports proactive maintenance strategies, ultimately reducing water losses and enhancing system reliability. Future research will focus on validating the model on larger and more diverse datasets.

Citation

Miloud BENTOUMI , ,(2024-12-13), Enhancing Leak Detection in WDNs with CWT and CNN Using Pressure Signals,4th International Conference on Frontiers in Academic Research,Konya-Turkey

Detecting leaks in pipeline networks, particularly in water distribution systems, is a critical yet challenging task. Numerous techniques have been proposed for leak detection; however, none have proven entirely suitable for industrial applications due to limitations such as low efficiency or high costs. This study focuses on employing cepstrum analysis as a powerful signal processing technique to detect and locate leaks in pipelines based on pressure signal measurements. The proposed method involves preprocessing pressure signals to remove noise using orthogonal wavelets, followed by the application of cepstrum analysis to extract key features indicative of leaks. Earlier studies have demonstrated that this approach can effectively pinpoint the location of leaks and assess their severity in pipeline systems. Experiments were conducted on a controlled fluid-filled pipeline network, where pressure transducers recorded transient pressure drops triggered by simulated leaks. The analysis demonstrated the ability of cepstrum-based technique to detect accurately the location of leaks across varying pipeline distances. Pressure transducers were used to record pressure signals, with leakage initiated via a push-button mechanism acting on a solenoid valve. The transient pressure drop was captured during the recordings, which were conducted at varying pipeline distances from the leakage point. This work highlights the potential of cepstrum analysis in advancing leak detection methodologies, offering an effective tool for maintaining the integrity and efficiency of pipeline systems.

Citation

Miloud BENTOUMI , ,(2024-12-09), Leak Detection in WDNs Using Cepstrum Analysis of Pressure Signals,1 st Edition of National Conference of Advanced Systems in Electrical Engineering(NCASEE'24),University M'Hamed Bougara of Boumerdes, Algeria

In recent years, the convergence of the Internet of Things (IoT) has driven innovations in pressure sensor development, enhancing accuracy, responsiveness, and efficiency in data handling. IoT connects sensors in real-time, enabling them to transmit vast amounts of pressure data to centralized systems for analysis and decision-making. The development of IoT, the everincreasing number of internet users, and the advancement of data rates and services have produced enormous amounts of data that can be utilized to enhance service delivery. IoT provides opportunities for both gathering and applying this data. This paper explores relationship between IoT and sensors, emphasizing their roles in optimizing various sectors such as Autonomous Vehicles, Industrial Automation, Smart Homes, Healthcare and Medical, Smart City and Agriculture. By integrating advanced technologies, including Machine Learning (ML) algorithms, we also examine the relationship between pressure sensors and IoT in leak detection within Water Distribution Networks (WDNs).

Citation

Miloud BENTOUMI , ,(2024-12-09), Integration of IoT for Effective Leak Detection in WDNs,1 st Edition of National Conference of Advanced Systems in Electrical Engineering(NCASEE'24),University M'Hamed Bougara of Boumerdes, Algeria

Detecting leaks in pipeline networks, particularly in water distribution systems, is a critical yet challenging endeavor. Despite the availability of various detection techniques, many are unsuitable for industrial applications due to limitations such as inefficiency and high costs. This study explores the use of cepstrum analysis, a robust signal processing technique, to detect and locate pipeline leaks by analyzing pressure signal measurements. The method begins with preprocessing pressure signals to eliminate noise using orthogonal wavelets, ensuring the accuracy of subsequent analysis. Cepstrum analysis is then applied to extract key features indicative of leaks. Previous research has shown that this approach can effectively identify leak locations and assess their severity in pipeline systems. Controlled experiments were conducted on a fluid-filled pipeline network, where pressure transducers recorded transient pressure drops caused by simulated leaks. The leaks were initiated using a push-button mechanism that operated a solenoid valve, with pressure signals captured at various pipeline distances from the leakage point. The results demonstrated that the cepstrum-based technique reliably detects and locates leaks with high precision, regardless of the distance from the leak. This study underscores the potential of cepstrum analysis as a valuable tool for improving leak detection methodologies. By providing a cost-effective and efficient solution, this technique can enhance the integrity and operational efficiency of pipeline systems, addressing a critical need in water distribution networks (WDNs).

Citation

Miloud BENTOUMI , ,(2024-12-03), Cepstrum Analysis of Pressure Signals for Effective Leak Detection in WDNs,3rd International Conference on Recent Academic Studies ICRAS 2024,Konya-Turkey

The detection of leaks in water distribution systems is a crucial aspect of conserving and managing water resources. Drawing inspiration from speech and speaker signal processing, this paper explores the application of cepstrum analysis to identify pipeline leaks. The concept is based on the analogy that water flow in pipes is similar to sound waves flowing through the vocal tract, with a leak equivalent to an opening in the vocal tract, such as the mouth or nose. A laboratory-scale prototype pipeline made of steel was used to test the proposed method. The results obtained using cepstrum analysis were compared to those from three conventional methods: autocorrelation, Fast Fourier Transform (FFT), and the logarithm of FFT. The comparative results demonstrate the effectiveness of the proposed method in tracking leaks in various scenarios, characterized by clear peaks at the same frequency and moment, outperforming the three considered methods

Citation

Miloud BENTOUMI , ,(2024-11-24), Cepstral Analysis-Based Method for Detecting Leaks in Water Supply Networks,The 2nd National Conference on Electronics, Electrical engineering, Telecommunication, and computer vision,Abdelhafid Boussouf universitycentre de Mila, algeria

In this research we have proposed an innovative method called the cepstral method for leak detection in water distribution network pipes. The cepstral analysis was chosen because it has a very good performance-complexity ratio. The application was made at the electronics laboratory. In order to simulate the distribution network, a short hybrid prototype channel was used. The acquisition of leak signals was done using a DSK cardc31. The validation tests of the proposed technique have shown its effectiveness

Citation

Miloud BENTOUMI , ,(2024-11-24), Application of the DSK C31 Card for Real-Time Water Leak Detection,The 2nd National Conference on Electronics, Electrical engineering, Telecommunication, and computer vision,Abdelhafid Boussouf universitycentre de Mila, algeria

Abstract—The study presents a novel 2-D hybrid analytical model (HAM) for analyzing dual-rotor permanent-magnet (PM) synchronous machines, integrating semi-analytical Maxwell-Fourier equations with finite-element method (FEM) techniques across all machine regions to provide a thorough and computationally efficient electromagnetic analysis approach. The semi-analytical component employs a rigorous formulation derived from Maxwell's equations, specifically applied for regions with unitary relative permeability. The model applies a finite-element method (FEM) to areas with high magnetic permeability, like the ferromagnetic teeth and yoke components. This approach excels at precisely capturing intricate shapes and variable magnetic behaviors typical of these structures. The analytical model (AM) and finite-element method are connected in both directions of the periodicity and non-periodicity direction. It is found that whatever the iron core relative permeability, the developed hybrid analytical model (HAM) give accurate results for no-load and on-load conditions. Finite- element analysis (FEA) shows very good results of the advanced technique.

Citation

Miloud BENTOUMI , ,(2024-11-24), Analytical modeling of magnetic field using a linear hybrid approach with application to permanent magnet synchronous motors,The 2nd National Conference on Electronics, Electrical engineering, Telecommunication, and computer vision,University M'Hamed Bougara of Boumerdes, Algeria

This study uses the empirical mode decomposition (EMD) method to address the issue of pi peline water leak detection. Acoustic and vibration signals that propagate throughout the pipeline at low frequencies are caused by leaks and have nonlinear and non-stationary features. Other potential causes of the received signals with unknown frequencies include the hydraulic pressure, pipe diameter, kind of pipe, and size of the leak. The choice of the narrow periods and causes, and consequently the loss of valuable information, limits the study of such leakage signals using traditional methods for instance the FFT, the correlation, and the cepstrum. Multiple stationary components (IMFs) can be used to treat the received signals independently by allowing the EMD non-stationary time domain decomposition approach. The EMD analysis is applied to a few leak positions in the pipeline and contrasted with the leak methods currently in use. Our experimental findings, when applied to time domain analysis, show that the EMD approach offers superior leak detection capabilities

Citation

Miloud BENTOUMI , ,(2024-11-24), Extraction of relevant leak parameters in WDNs using EMD of vibration signals in HDPE pipes,The 2nd National Conference on Electronics, Electrical engineering, Telecommunication, and computer vision,Abdelhafid Boussouf universitycentre de Mila, algeria

Abstract—In the development of dielectric composite, it is interesting to know the structure-property relationship at nanoscale level and the effect of each phase in the global properties of the material. In this context, we present an experimental analysis in the case of a ternary composite material. Several homogeneous microstructures samples with copper (II) oxide (CuO) and barium titanate (BaTiO3) particles in powder form with various amounts dispersed in a host matrix of Epoxy Resin are prepared. Their dielectric permittivity spectra are measured using time domain Reflectometry (TDR) technique. The experimental data is analyzed by means of electric modulus formalisms. In high frequency, the electrical modulus confirms the presence of two relaxations process. The real part of such composite presents a stability before the frequency where the relaxation phenomena appeared. The addition of the CuO does not affect the real part of permittivity significantly, but its effect is clear in the imaginary part and hence the AC conductivity. The conductivity indicates that the conduction is ionic and due to the ion of CuO primarily. According to results obtained from this study, we can made composite materials with desired characteristics using these two phases in the limits of their dielectric intrinsic permittivity. The manufacturing process of such composite is simple and can be used in manufacture. In addition, the reproducibility of such composite is checked in this study.

Citation

Miloud BENTOUMI , ,(2024-11-24), Study of the effect of the CUO in the dielectric properties of the nanocomposite Epoxy resin,The 2nd National Conference on Electronics, Electrical engineering, Telecommunication, and computer vision,Abdelhafid Boussouf university centre of Mila, algeria

Leakage detection in water distribution systems is an important issue in water resource-saving and management. Inspired by speech and speaker signal processing. In this paper, we apply the cepstrum analysis to identify the leak of the pipeline when this latter occurred. To detect a leak in WDN we consider water flow in pipes similar to the sounds flowing through the vocal tract. The leak can be likened to an opening of the vocal tract, such as the mouth or the nose. A prototype pipeline was made at the laboratory level. The pipeline in our case is made of steel. Experimentally obtained results of the proposed cepstrum methods have been compared to those obtained using three conventional methods: autocorrelation, FFT, and log of FFT. Comparative results prove the effectiveness of the proposed method to track the leaks in different considering cases with very clear peaks and almost in the same frequency (same moment) compared to the three considered methods.

Citation

Miloud BENTOUMI , ,(2024-11-07), APPLICATION OF CEPSTRAL ANALYSIS TO THE LEAKS DETECTION IN WATER DISTRIBUTION NETWORKS,International Conference on Studies in Engineering, Science, and Technology,Istanbul-Turkey

This paper deals with the problem of water leak detection in the pipeline based on the empirical mode decomposition (EMD) method. At low frequencies, leaks produce acoustic and vibration signals propagating along the pipeline, which have nonlinear and non-stationary characteristics. The hydraulic pressure, pipe diameter, the pipe's nature, and the leak's size can also be considered as other sources of the received signals, with unknown frequencies.rnThe analysis of such leakage signals using conventional methods like the FFT, the correlation, and the cepstrum is limited by the choice of the narrow periods and causes, therefore, the loss of useful information. By accommodating the EMD non-stationary time domain decomposition method, the received signals can be treated separately via several stationary components (IMFs). For some leak positions in the pipeline, the EMD analysis is applied and compared with the existing leak methods. Working in the time domain analysis, our experimental results demonstrate that the EMD method provides better leak detection performances.

Citation

Miloud BENTOUMI , ,(2024-11-07), Empirical Modal Decomposition Applied to Leak Detection in a Water Distribution Pipeline,International Conference on Studies in Engineering, Science, and Technology,Istanbul-Turkey

This work introduces an innovative two-dimensional (2-D) hybrid analytical model (HAM) applied for dual-rotor permanent-magnet (PM) synchronous machines. The proposed HAM seamlessly combines the semi-analytical Maxwell-Fourier formulations with finite-element method (FEM) across all machine subdomains, offering a comprehensive and efficient approach to electromagnetic analysis. The semi-analytical component employs a rigorous formulation derived from Maxwell's equations, specifically tailored for regions with unitary relative permeability, enabling high-precision electromagnetic field computations in non-ferromagnetic domains while maintaining computational efficiency. For regions of high magnetic permeability, such as the ferromagnetic teeth and yoke structures, the model employs a finite-element method (FEM) approach, leveraging its superior capability to accurately represent complex geometries and nonlinear magnetic properties. The analytical model (AM) and finite-element method are connected in both directions of the periodicity and non-periodicity direction. It is found that whatever the iron core relative permeability, the developed hybrid analytical model (HAM) give accurate results for no-load and on-load conditions. Finite-element analysis (FEA) demonstrates excellent results of the developed technique. Keywords: Hybrid magnetic model, exact subdomain technique, magnetic equivalent circuit, finiteelement analysis.

Citation

Miloud BENTOUMI , ,(2024-11-07), LINEAR HYBRID ANALYTICAL MODELING OF MAGNETIC FIELDS APPLIED TO PERMANENT MAGNET SYNCHRONOUS MACHINE,International Conference on Studies in Engineering, Science, and Technology (ICSEST),Istanbul, Turkiye

This paper deals with the problem of water leak detection in the pipeline based on the empirical mode decomposition (EMD) method. At low frequencies, leaks produce acoustic and vibration signals propagating along the pipeline, which have nonlinear and non-stationary characteristics. The hydraulic pressure, pipe diameter, the pipe's nature, and the leak's size can also be considered as other sources of the received signals, with unknown frequencies.rnThe analysis of such leakage signals using conventional methods like the FFT, the correlation, and the cepstrum is limited by the choice of the narrow periods and causes, therefore, the loss of useful information. By accommodating the EMD non-stationary time domain decomposition method, the received signals can be treated separately via several stationary components (IMFs). For some leak positions in the pipeline, the EMD analysis is applied and compared with the existing leak methods. Working in the time domain analysis, our experimental results demonstrate that the EMD method provides better leak detection performances.

Citation

Miloud BENTOUMI , ,(2024-11-07), Empirical Modal Decomposition Applied to Leak Detection in a Water Distribution Pipeline,International Conference on Studies in Engineering, Science, and Technology (ICSEST),Istanbul-Turkey

We always face water leakage problems in underground distribution water networks (DWNs). Existing leak detectors suffer from false alarms due to poor leak signal quality affected by external noise, often collected by acoustic or vibratory sensors. This paper introduces a novel Discrete Wavelet Transform Detector (DWTD) that leverages precise pressure signals non-influenced by environmental noise. Using a prototype of a 100m PEHD pipeline and a diameter of 40mm, Data from two pressure transmitters were collected using a dSPACE MicroLabBox unit. The main idea is to apply the Discrete Wavelet Transform (DWT) with a DONOHO threshold law to cancel noises due to water turbulence fluctuations, ensuring high-quality signals for accurate leak detection and localization.

Citation

Miloud BENTOUMI , , (2024-07-03), Novel Leak Detector Based on DWT an Experimental Study, International Journal of Robotics and Control Systems, Vol:4, Issue:3, pages:1109-1134, Association for Scientific Computing Electronics and Engineering (ASCEE)

The convergence of the Internet of Things (IoT) with pressure sensor technology has revolutionized data acquisition and management, enabling unprecedented accuracy and efficiency in various applications. IoT facilitates real-time connectivity among sensors, allowing them to transmit vast amounts of pressure data to centralized systems for analysis and decision-making. This seamless integration has been fueled by the rapid growth in internet users, advancements in data rates, and enhanced service delivery capabilities. IoT not only enables the collection of large datasets but also opens avenues for their application across diverse industries. This paper highlights the relationship between IoT and pressure sensors, examining their transformative impact on sectors such as autonomous vehicles, industrial automation, smart homes, healthcare, smart cities, and agriculture. By leveraging advanced technologies like Machine Learning (ML), IoT enhances system optimization and operational efficiency. A focal point of this study is the application of IoT and pressure sensors in leak detection with in Water Distribution Networks (WDNs). Integrating ML algorithms with IoT-connected pressure sensors allows for the identification and localization of leaks, ensuring effective system monitoring and maintenance. This approach significantly reduces water loss, operational costs, and downtime, contributing to the sustainability and reliability of WDNs.

Citation

Miloud BENTOUMI , ,(2024-04-03), The Role of IoT and Pressure Sensors for Leak Detection in WDNs,3rd International Conference on Recent Academic Studies ICRAS 2024,Konya-Turkey

Water distribution networks around the world suffer from leaks. These are due to the movements of various agents such as ground movements, and vibrations caused by road traffic without forgetting the nature of the ground. For this, permanent control is needed. In this work, we have developed a LabVIEW interface for the acquisition and processing of signals received from pressure transmitters. A Wifi system for transmitting and receiving signals from the pressure transmitters is used. To analyze signals to remotely detect anomalies that may occur on the network. The work is divided into two parts: a practical or hard part and a soft part. The hard one is used to obtain the signals containing the leakage information. The soft part is based on the application of signal processing techniques for the detection and location of the exact position of the leakage and therefore minimize the amount of water that is lost.

Citation

Miloud BENTOUMI , ,(2023-07-10), Design of leaks detection and localization in WDNs based on LabVIEW and pressure signals,(hybrid ) International Conference on Nonlinear Science and Complexity (ICNSC23,),Istanbul-Turkey

Water is a precious, sometimes scarce resource that is crucial for all kinds of life. In the last two decades, the water demand has far exceeded the supply in many countries. It is also worth mentioning that distribution networks are constantly increasing. According to an international study 20-50% of the produced quantities are lost due to leaks. These leaks can cause significant economic losses and multiple water contaminations that are carried as a major health risk for the citizen. Therefore, network managers are always looking for fast and inexpensive harmless leak detection systems. The rapid detection of a leak in underground pipes is widely taken into account in the performance evaluation of water supply systems. In addition, detection methods should not interfere with the normal operation of water transport. To minimize the effect of false alarms (FA) that have a costly effect on infrastructure. These false alarms are produced by the use of the most widely used acoustic detectors in the world, which are usually based on the signal correlation technique to know the exact location of the leak in relation to one of the sensors. In this work, we present a new leak detector applied to a prototype pipe using highly sensitive pressure transmitters. For this purpose, we have applied the wavelet technique (DWT) for denoising our non-stationary signals from these transmitters. The STFT (Short time Fourier transform) will be used for the analysis of these non-stationary and non-linear signals coming from the leaks to know the exact position of the leak. Validation tests have proven the efficiency of our detector.

Citation

Miloud BENTOUMI , ,(2023-07-10), DWT and STFT applied to Detect and locate leaks in WDNs,(hybrid ) International Conference on Nonlinear Science and Complexity (ICNSC23,) July 10-15, 2023,Istanbul-Turkey

The design of leak detection systems that occur on water pipes is a priority area of applied research that has an economic and health impact on the future of any nation. The various control systems and tools that currently exist throughout the world are designed to ensure permanent and effective monitoring of natural resources that have become rare and precious. The determining factor for the choice of a good detector is the cost in the first place, flexibility, and speed of processing. In this work, the basic idea is to simultaneously acquire from a new inexpensive electronic device two signals from two pressure transmitters installed on a prototype pipe carried out at the laboratory. These signals are usually immersed in noise. For this, denoising by an appropriate digital filter is indispensable. In our case, the Savitzky-Golay filter (S.G) presents its efficiency. The denoising performances are obtained from the calculation of SNR. The denoised signals are analysed to confirm the presence of the leak in the case of itsexistence. Mathematical equations are applied to determine the exact position of the leak with regards to one of the sensors. Validation tests are required to determine the position of the leak when the difference time between the signals is known

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Miloud BENTOUMI , ,(2022), SG Filter and Speed of pressure wave applied to locate leak in water pipes netwoks,ICATEEE 2022,M'sila

Water distribution systems (WDNs) suffer from leakage problems. The latter can cause damage to infrastructure and also act on public health by the penetration of microbes of waterborne diseases transmissible through the orifices of leaks as soon as a drop in pressure occurs. For this purpose, the network managers always look for the best devices to detect and locate in time the anomaly of the networks as soon as it appears. In order to realize a system of detection and location of leakage a prototype circuit was realized equipped with a pressure sensors and a system of acquisition based on Digital Signal Processor (DSP). Pressure measurements for specific distances were carried out. A digital filter was applied for a denoising. Pairs of pressure values before and after leakage are applied to a mathematical model for localization. We opted to use nonlinear regression (RNL) for the determination of nonmeasurable physical parameters based on pre-localized leak positions. Validation tests are performed to demonstrate the effectiveness of the model. In our study a divergence of the model used was found.

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Miloud BENTOUMI , ,(2022), RNL used for the verification of the efficiency of a localization model in a real WDNs,ICATEEE 2022,M'sila

The pipeline system is the most important part of the transportation of potable water. In other words, pipes are the most important component of the water distribution system. Because of several factors, they suffer from holes in which water is lost, and therefore an economic loss to states and humanity. Responsible for the water distribution networks always try to minimize the damage. By working to find the most effective way to detect leaks in these networks. This article centers on a mathematical model of a hydraulic system that aims to locate leakage in water transmission pipes. Several optimization techniques can be used. We opted for the BBO (biogeographybased optimization) method because of its performance, in particular the execution time of its algorithm. This method is applied to determine the two parameters of the model (friction and dynamic viscosity) to obtain a good localization. We take GA a method of compared method with BBO.

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Miloud BENTOUMI , ,(2022), Parameterization and Validation of the Physical Coefficients of a WDNs by BBO,ICATEEE 2022,M'sila

Nowadays, the generalization of wireless communication systems and the need to miniaturize antennas to allow their integration into small objects at ultra-high frequencies is growing. At these frequencies, the antenna is the bulkiest component and its miniaturization constitutes one of the most important current challenges for designers of communicating objects. The main objective of our work is the design of a dual-band patch antenna working for fifthgeneration systems. For this purpose, we designed a miniature antenna having two resonance frequencies, one around 7GHz and the other around 28GHz. For this, our work is based on a classic rectangular patch antenna. Miniaturization techniques and ground plane deformation (GDS) are used to obtain the best performance. A parametric study was performed to see the most influential parameters to achieve the desired requirements. The influence of the geometrical parameters of the antenna on the resonance frequency, bandwidth, and directivity has been taken into consideration. The results obtained showed a good performance of the designed antenna

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Miloud BENTOUMI , ,(2022), Design of a miniature bi-band patch antenna with asymmetrical feedline for 5G applications,ICATEEE 2022,M'sila

In the present work, a dynamic stochastic method is proposed and used for the synthesis of uniform linear antenna arrays. The proposed method combines the classical invasive weeds optimization (IWO) and the mutation process, which makes it robust, simple and shows flexibility to be adapted. The dynamic IWO applies the mutation process in the calculation of standard deviation during the spatial dispersal process of produced seeds while keeping the mean at the parent plants. In the mutation process, if special conditions were achieved, the standard deviation would be re-initialized. This proposed method tries to achieve an optimal array pattern by acting on the relative amplitude excitation of each element in the linear array for an optimal inter-element spacing. The optimal array pattern has deep or broad nulls in some directions of interferences with low sidelobes level. The objective of the synthesis is to get amplitude excitations with low dynamic range ratio (DRR), which facilitates the design of beamforming feed network. To illustrate the robustness of the proposed method, numerical examples are presented and compared with the obtained results using bees algorithm (BA), bacterial foraging algorithm (BFA), real genetic algorithm (RGA), and the corresponding reference array pattern for each example.

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Miloud BENTOUMI , , (2021), A Dynamic Invasive Weeds Optimization Applied to Null Control of Linear Antenna Arrays with Constrained DRR, Advanced electromagnetics, Vol:10, Issue:1, pages:52-61, AEM journal

This work deals to introduce a new idea inspired from the empirical mode decomposition of the pipe as well as the size of the leak are considered as sources acting on the leakage (EMD) technique in order to detect a leak in water distribution networks (WDN). Welsh’s power spectral density (WPSDE) is used to locate the frequency band in which leaks occur. Leaks produce acoustic and vibration signals propagating along the pipeline, which have nonlinear and non-stationary characteristics. Hydraulic pressure, the nature and diameter signals. The analysis of such leakage signals using conventional methods is limited by the choice of the narrow bands and cause therefore the loss of useful information. EMD is a technique that allows the decomposition of a signal in the time domain as stationary oscillatory signals called intrinsic mode functions (IMFs), which can be processed separately. Experiments were carried out to verify the validity of the proposed method. That shows its best performances in detecting leaks. For the localization, we applied the Short-Time Fourier Transform (STFT) technique that has the potential to locate leaks at greater distances from a measurement point and proved its efficiency.

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Miloud BENTOUMI , , (2020), Welsh DSP Estimate and EMD Applied to Leak Detection in a Water Distribution Pipeline, Instrumentation Mesure Métrologie, Vol:19, Issue:1, pages:35-41, IIETA

The main objective of this paper is to study the dielectric behavior of a ternary composite, made from a mixture of barium titanate (BT), copper oxide (CuO) in the same epoxy resin matrix (RE) maintained at 70% by volume fraction, while those of the other constituents are variable and completing each other in a way to achieve the remaining proportion, i.e. 30%. Random mixtures are made at room temperature and under atmospheric pressure. A dielectric characterization of this mixture type was performed by time-domain spectroscopy (TDS) over a frequency wide band (DC–3GHz). This has been carried out to illustrate the effect of copper oxide (CuO) simultaneously at low frequency (500MHz), in the presence of (BaTiO3), on the composite dielectric behavior. This has led consequently to make a comparison between the present acquired results and those of the ternary composite, where (CuO) act separately. The results obtained so far confirm the AC conductivity frequencies dependence, and fit the Jonscher’s law. In addition, It has been reported an increase of this conductivity σ_ACwhile the frequency goes up. However, the Static conductivity is affected clearly by the presence of CuO particles amount and these results show σ_(DC )plateau in the low frequency range. In fact, these characteristics are useful in many pragmatic engineering areas like microelectronics and telecommunications components manufacturing.

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Miloud BENTOUMI , ,(2020), The influence of CUO on the dielectric properties of BATIO3-epoxy resin composite,CNTEA1-2020,M'sila

Water is a vital resource for life as well as for the majority of energy industries. Finding a way to manage this water sustainably is essential at a time when the world’s water resources are already under increasing stress due to population growth and global warming. As a direct implication, saving water is coming very crucial. This work deals with the application of the empirical mode decomposition method to the detection and the localization of the leaks using acoustic signals issued from STM32F4 acquisition card. Firstly, the empirical mode decomposition method has been applied in the denoising of acquired signals leading to two estimated components on which we apply secondly the correlation method to detect and localize the leakage in water distribution network. Experimental obtained results using a developed hydraulic plant as well as the acquisition system confirm the efficiency of the proposed method to detect accurately the leaks compared to conventional leaks detection methods.

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Miloud BENTOUMI , , (2019), Experimental Validation of Hybrid EMD-Correlation Acoustic Digital Leaks Detector in Water Distribution Network System, I2M, Vol:18, Issue:6, pages:535-545, IIETA

Water is a vital resource for life as well as for the majority of energy industries. Finding a way to manage this water sustainably is essential at a time when the world’s water resources are already under increasing stress due to population growth and global warming. As a direct implication, saving water is coming very crucial. This work deals with the application of the empirical mode decomposition method to the detection and the localization of the leaks using acoustic signals issued from STM32F4 acquisition card. Firstly, the empirical mode decomposition method has been applied in the denoising of acquired signals leading to two estimated components on which we apply secondly the correlation method to detect and localize the leakage in water distribution network. Experimental obtained results using a developed hydraulic plant as well as the acquisition system confirm the efficiency of the proposed method to detect accurately the leaks compared to conventional leaks detection methods.

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Haddi BAKHTI , Miloud BENTOUMI , ELhadi KENANE , Abdelghani Harrrag, , (2019), Experimental Validation of Hybrid EMD-Correlation Acoustic Digital Leaks Detector in Water Distribution Network System, Instrumentation Mesure Métrologie, Vol:18, Issue:6, pages:535-545, IIETA

The main goal of the present paper is the study of transmitted power control (TPC) algorithms for mobile cellular systems (UMTS). A novel power control algorithm and some already existing ones have been studied focusing on resolving the near-far problem that affects the performance of the system a whole. Unlike the other existing power control algorithms, and besides the dynamic step size, our Modified Adaptive Power Control algorithm (MAPC) shows its uniqueness in the intelligence added to restrict the oscillations of the estimated signal to interference ratio (SIR) around its target value by using a stabilization zone. Simulations were carried out to evaluate the robustness of the novel algorithm. The results show that the proposed algorithm outperforms the other existing power control algorithms.

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Miloud BENTOUMI , ,(2018), An Adaptive Power Control Algorithm For 3G Cellular Networks,2018 International Conference on Communications and Electrical Engineering (ICCEE),El Oued, Algeria, Algeria

Leakage detection in water distribution systems is an important issue in water ressources saving and management. Inspired by speech and speaker signal processing, in this paper we apply the cepstaml analysis to identify the pipe leak detection by considering water flow in pipes similar to the sounds flowing throwgh vocal tract. the leak can be likened to an opening of the vocal tract, such as the mouth or the nose. Experimental obtained results of the proposed cepstral methods have been compared to those obtained using three conventional methods: autocorrelation, FFT and log of FFT. Comparative results prove thje effectiveness of the proposed method to track the leaks in different considering caseswith very clear peaks and almost in the same frequency (same moment) compared to the othe three considered methods.

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Miloud BENTOUMI , ,(2018), Application of cepstral analysis to the leaks detection in water distribution networks,ICIMM2018,Setif, Algeria

This paper deals with the problem of water leak detection in the pipeline based on the empirical mode decomposition (EMD) method. At low frequencies, leaks produce acoustic and vibration signals propagating along the pipeline which have nonlinear and non-stationary characteristics. The hydraulic pressure, the pipe diameter, the nature of the pipe and the size of the leak can also be considered as other sources of the received signals, with unknown frequencies. The analysis of such leakage signals using conventional methods like the FFT, the correlation and the cepstrum is limited by the choice of the narrow periods and cause therefore the loss of the useful information. By accommodating the EMD non-stationary time domain decomposition method, the received signals can be treated separately via several stationary components (IMFs). For some leak positions in the pipeline, the EMD analysis is applied and compared with the existing leak methods. Working in the time domain analysis, our experimental results demonstrate that the EMD method provides better leak detection performances

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Miloud BENTOUMI , ,(2018), EMPIRICAL MODAL DECOMPOSITION APPLIED TO LEAK DETECTION IN A WATER DISTRIBUTION PIPELINE,ICIMM2018,Sétif, Algeria

The main goal of the present paper is the study of transmitted power control (TPC) algorithms for mobile cellular systems (UMTS). A novel power control algorithm and some already existing ones have been studied focusing on resolving the near-far problem that affects the performance of the system a whole. Unlike the other existing power control algorithms, and besides the dynamic step size, our Modified Adaptive Power Control algorithm (MAPC) shows its uniqueness in the intelligence added to restrict the oscillations of the estimated signal to interference ratio (SIR) around its target value by using a stabilization zone. Simulations were carried out to evaluate the robustness of the novel algorithm. The results show that the proposed algorithm outperforms the other existing power control algorithms.

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ELhadi KENANE , Haddi BAKHTI , Miloud BENTOUMI , Fegriche Fatima zahra, Farid Djahli, ,(2018), An Adaptive Power Control Algorithm For 3G Cellular Networks,International Conference on Communications and Electrical Engineering,El Oued, Algeria

In this study, the authors propose and analyse a novel leak-detection method based on the ‘Haar’ continuous wavelet transform (CWT) and a double thresholding, i.e. CWTDT. Inspired by the idea of the binary integration technique in radar target detection, the algorithm analyses the non-stationary vibration signal issued from a water pipeline through which it decides whether or not there exists a leak in the water conveyance. To achieve this, the signal is first divided into several segments. Partial binary decisions within each segment are then obtained through the use of two preselected thresholds. The final binary decision is obtained by means of the ‘K out of L’ fusion rule. In doing this, the hardware leak system prototype is designed and a number of desirable leak positions in the water pipeline are first created to achieve the two best thresholds and ‘K out of L’ fusion rule. For comparison purposes, the performances of the proposed CWTDT method are assessed experimentally against those of the existing fast Fourier transform- and CWT-based methods under real operating conditions.

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Miloud BENTOUMI , , (2017), Wavelet DT method for water leak-detection using a vibration sensor: an experimental analysis, IET Signal Processing, Vol:11, Issue:4, pages:396 – 405, IET Digital Library

In the development of dielectric composite,it is interesting to know the structure-property relationship at nanoscale level and the effect of each phase in the global properties of the material. In this context, we present an experimental analysisin the case of a ternary composite material. Several homogeneous microstructures samples with copper (II) oxide (CuO) and barium titanate (BaTiO 3) particles in powder form with various amounts dispersed in a host matrix of Epoxy Resin are prepared. Their dielectric permittivity spectra are measured using time domain Reflectometry (TDR) technique.Theexperimental data isanalyzed by means of electric modulus formalisms.In high frequency, the electrical modulus confirms the presence of two relaxations process.The real part of such composite presents a stability before the frequency where the relaxation phenomena appeared.The addition of the CuO does not affect the real part of permittivity significantly, but its effect is clear in the imaginary part and hence the AC conductivity.The conductivity indicates that the conduction is ionic and due to the ion of CuO primarily. According to results obtained from this study, we can made composite materials with desired characteristics using these two phases in the limits of their dielectric intrinsic permittivity.The manufacturing process of such composite is simple andcan be used in manufacture.In addition, the reproducibility of such composite ischecked in this study.

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Miloud BENTOUMI , ,(2015), Study of the effect of the CuO inthe dielectric properties of the nanocomposites Epoxy resin /BaTiO 3,4 th International Conference on Electrical Engineering (ICEE 2015),Boumerdès, Algeria

Résumé— Dans cet article une étude exhaustive suivi d'une analyse détaillée du comportement électrique de jonctions P+ N réalisées dans un film mince de silicium polycristallain obtenue par un procèdé technologique L.P.C.V.D. Pour ces composants ont doit analyser et caractériser les courbes I(V). Ces derniers sont basées sur des mesures pratiques faites au laboratoire pour différentes températures entre 200K° et 423K°. Dans notre travail nous nous somme basé sur le logiciel (SILVACO), pour faire la simulation électrique d'une diode latérale polycristallain telles que les étapes technologiques , les caractéristiques I(V),

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Miloud BENTOUMI , ,(2015), caractérisation et analyse des diodes latéralesPN+ polycristalinne courant-tension pour des températures elévées sous environnement SILVACO,SNMER'15,El-oued- Algeria

Leak detection of water distribution networks is a problem that arouses theresponsibleauthorities for distribution all around the word. The reason, which involved researchers representing various disciplines to try to find a solution to the problem by implementing efficient devices in this field.Distributions networks are being degraded over time, which can cause leakage.To detect a leakequipment and techniquesare needed. They are constant progress with the development of technology. In this paper, the CWT (continuous wavelet transform) wassuggested as a technique for detecting and locating leaks in water distribution networks. The treatment using the CWT technique was foundas thebest solution for confirmation of the presence of a leakafter trying different signal analysis tools such as transforms (FFT, STFT, etc ....). The application was carried out in the laboratory with a short channel hybrid prototype (a part of steel followed by a part in PVC). Validations tests have shown the effectiveness of the method.

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Miloud BENTOUMI , ,(2014), A WAVELET APPROACH FOR DETECTION AND LOCATION OF LEAKS IN WATER DISTRIBUTION NETWORKS,14th International Multidisciplinary Scientific GeoConference SGEM 2014,Bulgaria

This paper presents an application of the discrete cosine transform compression technique on medical images of the IRM type. The arithmetic coding method is used to encode the coefficients. The tests of this lossy compression/ decompression technique are performed on two IRM images representing the brain, in axial and sagital views, of a patient suffering from a cerebral hemorhage. The obtained results on these images show that the DCT technique permits to considerably improve the compression rate while mainting a good image quality when threshold varies in the interval: 0 les TH les 20 for bloc sizes: [16times16] and [32times32]. However, a severe degradation of the quality of the reconstructed medical image is observed when the threshold is greater than 30.

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Miloud BENTOUMI , ,(2008), Application of the DCT and Arithmetic Coding to Medical Image Compression,2008 3rd International Conference on Information and Communication Technologies: From Theory to Applications,Damascus, Syria

Presented is a fast technique dedicated to the multilevel image thresholding and quantization based on the Shannonpsilas entropy maximization. The elaborated method uses efficiently the cumulative density function for the rapid determination of the optimal thresholds for segmentation. Some simulation results are reported for the aim of illustration and demonstration of its effectiveness.

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Miloud BENTOUMI , ,(2008), A fast technique for gray level image thresholding and quantization based on the entropy maximization,2008 5th International Multi-Conference on Systems, Signals and Devices,Amman, Jordan

Résumé -Dans cet article, la technique de la corrélation acoustique est utilisée comme méthode de détection de fuite d'eau sur les réseaux de distribution. Elle a été implémentée sur deux microordinateurs (P3 et P4) et le processeur de signal TMS320C6201. La fuite d'eau a été simulée par un signal aléatoire se propageant dans les deux sens sur la conduite donnant naissance à deux signaux décalés dans le temps. L'algorithme implémenté est ainsi testé avec ces deux signaux. La fonction corrélation obtenue nous a permis de localiser la fuite à travers le pic de la corrélation obtenue. Des tests de simulation ont par la suite confirmé le bon fonctionnement du système élaboré à l'aide d'exemples de signaux ayant un nombre d'échantillons variant de 64 à 1024. Enfin une comparaison en terme de temps de calcul entre le DSP et les PC confirme la supériorité du DSP.

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Miloud BENTOUMI , ,(2007), Implémentation en Temps Réel d'un Algorithme de Détection de Fuite d'Eau des Réseaux de Distribution sur le Processeur TMS320C6201 en Utilisant la Corrélation Acoustique,4th International Conference on Computer Integrated Manufacturing CIP’2007,Sétif, Algeria

Dans cet article, la technique de la corrélation acoustique est utilisée comme méthode de détection de fuite d'eau sur les réseaux de distribution. Elle a été implémentée sur deux microordinateurs (P3 et P4) et le processeur de signal TMS320C6201. La fuite d'eau a été simulée par un signal aléatoire se propageant dans les deux sens sur la conduite donnant naissance à deux signaux décalés dans le temps. L'algorithme implémenté est ainsi testé avec ces deux signaux. La fonction corrélation obtenue nous a permis de localiser la fuite à travers le pic de la corrélation obtenue. Des tests de simulation ont par la suite confirmé le bon fonctionnement du système élaboré à l'aide d'exemples de signaux ayant un nombre d'échantillons variant de 64 à 1024. Enfin une comparaison en terme de temps de calcul entre le DSP et les PC confirme la supériorité du DSP

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Miloud BENTOUMI , ,(2007), Intégration des composants modernes de traitement des signaux dans des systèmes de détection de fuites d'eau des réseaux de distribution,JSS"07,Guelma