Kalman Filters for Leak Diagnosis in Pipelines: Brief History and Future Research

Abstract

The purpose of this paper is to provide a structural review of the progress made on the detection and localization of leaks in pipelines by using approaches based on the Kalman filter. To the best of the author’s knowledge, this is the first review on the topic. In particular, it is the first to try to draw the attention of the leak detection community to the important contributions that use the Kalman filter as the core of a computational pipeline monitoring system. Without being exhaustive, the paper gathers the results from different research groups such that these are presented in a unified fashion. For this reason, a classification of the current approaches based on the Kalman filter is proposed. For each of the existing approaches within this classification, the basic concepts, theoretical results, and relations with the other procedures are discussed in detail. The review starts with a short summary of essential ideas about state observers. Then, a brief history of the use of the Kalman filter for diagnosing leaks is described by mentioning the most outstanding approaches. At last, brief discussions of some emerging research problems, such as the leak detection in pipelines transporting heavy oils; the main challenges; and some open issues are addressed.

A Distributed Computing Solution Based on Distributed Kalman Filter for Leak Detection in WSN-Based Water Pipeline Monitoring

“…A lot of research efforts have been dedicated to the development of a vast variety of techniques for leak detection and localization to minimize water losses caused by leaks [ 30 ]. Based on their technical approach, Adedeji et al [ 20 ], Baroudi et al [ 36 ], Adegboye et al [ 59 ], and Torres et al [ 29 ] in their survey papers on pipeline monitoring categorized leak detection techniques in water pipelines as either external or internal. In other surveys, Ismail et al [ 25 ] classified leak detection techniques into software-based methods and hardware-based methods while Chan et al [ 60 ] classified them as active and passive systems.…”

“…In other surveys, Ismail et al [ 25 ] classified leak detection techniques into software-based methods and hardware-based methods while Chan et al [ 60 ] classified them as active and passive systems. The software-based and hardware-based methods of Ismail et al [ 25 ] and active and passive systems of Chan et al [ 60 ] are likened to the internal and external methods of [ 20 , 29 , 36 , 54 ], respectively, as shown in Figure 1 . In another study, El-Zahab et al [ 30 ] classified leak detection systems into two major classes, i.e., static leak detection systems and dynamic leak detection systems.…”

“…The software-based methods use field sensors to monitor the operational and hydraulic conditions of the pipeline, such as the measurement of the flow, pressure and temperature [ 16 , 25 , 36 , 54 ] and smart computational algorithms to process the measurements in order to detect and localize the occurrence of leaks on the pipeline [ 29 ]. Some of the software-based methods available in the literature include methods based on model estimation (e.g., Kalman filter [ 19 , 29 , 61 ], state observer [ 62 ], system identification [ 63 ], the impedance method [ 64 ]), methods based on signal processing (Negative Wave Pressure [ 32 ], Mass Balance [ 65 ], Pressure Point Analysis [ 66 ], Acoustic Correlation Analysis [ 67 ], Spectral Analysis Response [ 68 ]) and data-driven methods (Support Vector Machine [ 69 ], K-nearest neighbor [ 70 ], Naïve Bayes [ 69 ]). They involve the use of either intrusive sensors or non- intrusive sensors to monitor the internal pipeline parameters.…”

“…The hardware-based methods detect the presence of leaks from outside the pipeline by visual observation or by using specialized equipment that range from simple listening rods to more sophisticated approaches as inspection gauges sending magnetic fields, electromagnetic waves or ultrasound through a pipeline’s walls [ 16 , 25 , 36 , 54 ] for physical monitoring. They use local sensors to send an alarm when a leak occurs, and do not perform computation for diagnosing a leak [ 29 ]. Some examples available in the literature include acoustic techniques [ 71 ], tracer gas techniques, fiber optic sensing techniques [ 72 ], ground-penetrating radar techniques [ 73 ], magnetic induction techniques [ 74 ], etc.…”

“…The scarcity of water thus requires that water losses due to leaks be minimized by accurately detecting and localizing leakages in real time, each time they occur. This has led to enormous research over the years in the field [ 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 ], providing a wide range of methods for detecting and locating leaks in water pipelines.…”