An In-Pipe Leak Detection Sensor: Sensing Capabilities and Evaluation

2011 ◽  
Author(s):  
Dimitris M. Chatzigeorgiou ◽  
Atia E. Khalifa ◽  
Kamal Youcef-Toumi ◽  
Rached Ben-Mansour
Keyword(s):  
Water Supply ◽  
Environmental Health ◽  
Fresh Water ◽  
Detection System ◽  
Acoustic Emissions ◽  
Leak Detection ◽  
Acoustic Signals ◽  
Clear Understanding ◽  
Water Pipes ◽  
Water Pipeline

In most cases the deleterious effects associated with the occurrence of leak may present serious problems and therefore leaks must be quickly detected, located and repaired. The problem of leakage becomes even more serious when it is concerned with the vital supply of fresh water to the community. In addition to waste of resources, contaminants may infiltrate into the water supply. The possibility of environmental health disasters due to delay in detection of water pipeline leaks has spurred research into the development of methods for pipeline leak and contamination detection. Leaks in water pipes create acoustic emissions, which can be sensed to identify and localize leaks. Leak noise correlators and listening devices have been reported in the literature as successful approaches to leak detection but they have practical limitations in terms of cost, sensitivity, reliability and scalability. To overcome those limitations the development of an in-pipe traveling leak detection system is proposed. The development of such a system requires a clear understanding of acoustic signals generated from leaks and the study of the variation of those signals with different pipe loading conditions, leak sizes and surrounding media. This paper discusses those signals and evaluates the merits of an in-pipe-floating sensor.

scholarly journals Classification Accuracy Enhancement Based Machine Learning Models and Transform Analysis

2021 ◽  
Vol 23 (2) ◽  
pp. C44-C53
Author(s):  
Hanan A. R. Akkar ◽  
Wael A. H. Hadi ◽  
Ibraheem H. Al-Dosari ◽  
Saadi M. Saadi ◽  
Aseel Ismael Ali
Keyword(s):  
Machine Learning ◽  
Mean Squared Error ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Leak Detection ◽  
The Novel ◽  
Denoising Method ◽  
System A ◽  
New Novel ◽  
Water Pipeline

The problem of leak detection in water pipeline network can be solved by utilizing a wireless sensor network based an intelligent algorithm. A new novel denoising process is proposed in this work. A comparison study is established to evaluate the novel denoising method using many performance indices. Hardyrectified thresholding with universal threshold selection rule shows the best obtained results among the utilized thresholding methods in the work with Enhanced signal to noise ratio (SNR) = 10.38 and normalized mean squared error (NMSE) = 0.1344. Machine learning methods are used to create models that simulate a pipeline leak detection system. A combined feature vector is utilized using wavelet and statistical factors to improve the proposed system performance.

scholarly journals Automatic Leak Detection in Buried Plastic Pipes of Water Supply Networks by Means of Vibration Measurements

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Alberto Martini ◽  
Marco Troncossi ◽  
Alessandro Rivola
Keyword(s):  
Water Supply ◽  
Leak Detection ◽  
Distribution Networks ◽  
Vibration Monitoring ◽  
Supply Networks ◽  
Water Pipes ◽  
Water Supply Networks ◽  
Experimental Campaign ◽  
Acceleration Signals

The implementation of strategies for controlling water leaks is essential in order to reduce losses affecting distribution networks of drinking water. This paper focuses on leak detection by using vibration monitoring techniques. The long-term goal is the development of a system for automatic early detection of burst leaks in service pipes. An experimental campaign was started to measure vibrations transmitted along water pipes by real burst leaks occurring in actual water supply networks. The first experimental data were used for assessing the leak detection performance of a prototypal algorithm based on the calculation of the standard deviation of acceleration signals. The experimental campaign is here described and discussed. The proposed algorithm, enhanced by means of proper signal filtering techniques, was successfully tested on all monitored leaks, thus proving effective for leak detection purpose.

scholarly journals Ensemble-based machine learning approach for improved leak detection in water mains

2021 ◽  
Author(s):  
Thambirajah Ravichandran ◽  
Keyhan Gavahi ◽  
Kumaraswamy Ponnambalam ◽  
Valentin Burtea ◽  
S. Jamshid Mousavi
Keyword(s):  
Machine Learning ◽  
Detection System ◽  
Leak Detection ◽  
Acoustic Signals ◽  
False Positives ◽  
Classification Model ◽  
Series Data ◽  
Gradient Boosting ◽  
Validation Data ◽  
Water Mains

Abstract This paper presents an acoustic leak detection system for distribution water mains using machine learning methods. The problem is formulated as a binary classifier to identify leak and no-leak cases using acoustic signals. A supervised learning methodology has been employed using several detection features extracted from acoustic signals, such as power spectral density and time-series data. The training and validation data sets have been collected over several months from multiple cities across North America. The proposed solution includes a multi-strategy ensemble learning (MEL) using a gradient boosting tree (GBT) classification model, which has performed better in maximizing detection rate and minimizing false positives as compared with other classification models such as KNN, ANN, and rule-based techniques. Further improvements have been achieved using a multitude of GBT classifiers combined in a parallel ensemble method called bagging algorithm. The proposed MEL approach demonstrates a significant improvement in performance, resulting in a reduction of false positives reports by an order of magnitude.

Kedung Keris Full Well Stream Pipeline Fiber Optic Leak Detection System

2021 ◽  
Author(s):  
Cindy Chairunissa ◽  
Deny Kalfarosi Amanu ◽  
Grizki Astari ◽  
Eska Indrayana
Keyword(s):  
Oil And Gas ◽  
Produced Water ◽  
Fiber Optic ◽  
Detection System ◽  
New Technology ◽  
Cost Savings ◽  
Leak Detection ◽  
Oil Field ◽  
Real Time Analysis ◽  
Water Pipeline

Abstract Kedung Keris (KK) is a sour oil field based in Cepu Block, Indonesia. KK field was originally planned to have a processing facility with separate pipelines to deliver crude & produced water, while the gas was planned to be flared. To reduce cost, this concept was changed to a wellpad with full well stream pipeline with new technology of Fiber Optic Leak Detection Sensing System (LDSS) as a key enabler. The fiber optic LDSS functions by leveraging fiber optic cable attached to the pipeline to detect leak as well as intrusion to the pipeline's Right-of-Way through real-time analysis of physical characteristics of a leak and intrusion, such as changes in temperature, pressure, ground strain and acoustics. The implementation of LDSS, together with other safeguards built into the pipeline design, operations and maintenance, allowed the KK Project to eliminate the separation facility at KK wellpad and an additional water pipeline. It also reduces the flaring by billions of standard cubic feet of gas cumulative until end of PSC life as originally all gas planned to be flared. The change of KK Project concept altogether yielded tens of millions of US dollar gross cost savings (~30% of CAPEX + OPEX reduction) following the KK startup in late 2019. The installed LDSS proven to detect leak for up to few meters location accuracy and has intrusion detection capability. KK Project has pioneered the implementation of fiber optic leak detection system for Indonesia oil and gas companies. This work provided further insight to the utilization of such technology in full well stream pipeline where traditional leak detection system implementation will not be acceptable. Consecutively, full well stream pipeline deployment can lead to future CAPEX + OPEX efficiency in facility project design and operation, as well as flaring reduction opportunity.

scholarly journals Numerical Analysis of a Mobile Leakage-Detection System for a Water Pipeline Network

2021 ◽  
Vol 87 (1) ◽  
pp. 134-150
Author(s):  
Balbir Singh ◽  
Usman Ikhtiar ◽  
Mohamad Firzan ◽  
Dong Huizhen ◽  
Kamarul Arifin Ahmad
Keyword(s):  
Drag Coefficient ◽  
Detection System ◽  
Leak Detection ◽  
Detection Methods ◽  
Detection Accuracy ◽  
New Model ◽  
Pressure Drag ◽  
Pipeline Networks ◽  
Water Pipeline ◽  
And Control

The leakages in water pipeline networks sometimes negatively affect the environment, health, and economy. Therefore, leak detection methods play a crucial role in detecting and localizing leaks. These methods are categorized into internal and external detection methods, each having its advantages and certain limitations. The internal system has its detection based on the field sensors to monitor internal pipeline parameters such as temperature and pressure, thereby inferring a leak. However, the mobility of the sensing module in the pipeline is affected by the model drag coefficient. The low drag coefficient causes the module to quickly lost control in the pipeline leading to false detection. Therefore, this study is about designing and numerically analysing a new model to achieve a higher drag value of the sensing system. The drag value of various models is determined with the help of CFD simulations in ANSYS. The outcome of this study is a new model with a drag value of 0.6915. It was achieved by implementing an aerodynamic shape, a more significant surface contact area in the middle, and canted fins at the front of the . Both pressure, drag, and skin friction were increased, so a higher drag value of the sensing module can be achieved. Through this, the mobility and control of modules in the pipeline can be improved, improving leak detection accuracy.

scholarly journals Leak Detection in Plastic Water Supply Pipes with a High Signal-to-Noise Ratio Accelerometer

2018 ◽  
Vol 51 (1-2) ◽  
pp. 27-37 ◽  
Author(s):  
Konstantinos Marmarokopos ◽  
Dimitrios Doukakis ◽  
George Frantziskonis ◽  
Markos Avlonitis
Keyword(s):  
Water Supply ◽  
Wave Attenuation ◽  
Detection System ◽  
Signal To Noise Ratio ◽  
Leak Detection ◽  
Small Distance ◽  
High Signal ◽  
Vibration Frequencies ◽  
Signal To Noise ◽  
Noise Ratio

A method for detecting leaks in plastic water supply pipes through analysis of the pipe’s surface vibration using a high signal-to-noise ratio accelerometer is proposed and examined. The method involves identification of the changes in vibration frequencies caused on the pipe by the leak and is developed from and examined with respect to detailed experiments. The results are promising, showing that leak detection in plastic pipes is possible provided that the sensor is placed at a small distance from the leak, since wave attenuation in plastic is strong. The results indicate that the methodology has the potential to be a new and competitive type of mobile leak detection system.

USE AND PROTECTION OF WATER RESOURCES OF AZERBAIJAN

2017 ◽  
Author(s):  
Ramiz Tagirov ◽  
◽  
Maya Zeynalova ◽  
Keyword(s):  
Water Resources ◽  
Water Supply ◽  
Fresh Water ◽  
Water Consumption ◽  
Cultivated Land ◽  
Per Capita ◽  
The Republic ◽  
Active Temperature

The article examines the problem of fresh water, since in terms of water supply from its own resources per capita and per 1 km2, the republic is 8 times behind Georgia, 2 times behind Armenia. Significant water consumption in Azerbaijan is caused by its arid territory with a predominance of active temperature and a lack of precipitation, which leads to intensive irrigation of crops. At the same time, artificial irrigation is used on 70% of the cultivated land.

Occupational and Environmental Health

2017 ◽  
Keyword(s):  
Public Health ◽  
Occupational Health ◽  
Environmental Health ◽  
Health And Safety ◽  
Practical Experience ◽  
Global Perspective ◽  
Clear Understanding ◽  
Practical Case ◽  
Environmental Sciences ◽  
Wide Range

This thoroughly updated seventh edition is a comprehensive, clearly written, and practical textbook that includes information on both occupational health and environmental health, providing the necessary foundation for recognizing and preventing work-related and environmentally induced diseases and injuries. National and international experts share their knowledge and practical experience in addressing a wide range of issues and evolving challenges in their fields. A multidisciplinary approach makes this an ideal textbook for students and practitioners in public health, occupational and environmental medicine, occupational health nursing, epidemiology, toxicology, occupational and environmental hygiene, safety, ergonomics, environmental sciences, and other fields. Comprehensive coverage provides a clear understanding of occupational and environmental health and its relationships to public health, environmental sciences, and government policy. Practical case studies demonstrate how to apply the basic principles of occupational and environmental health to real-world challenges. Numerous tables, graphs, and photographs reinforce key concepts. Annotated Further Reading sections at the end of chapters provide avenues for obtaining further infomation. This new edition of the book is thoroughly updated and also contains new chapters on climate change, children’s environmental health, liver disorders, kidney disorders, and a global perspective on occupational health and safety.

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