Table 3 - uploaded by Gerhard Geiger
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Many fluids transported by pipelines are Hazardous. It is therefore often necessary to install leak detection (and localization) systems (LDS), particularly due to legal regulations such as - the "Code for Federal Regulations (CFR) Title 49 Part 195" [1], API 1130 2nd Ed. [2], both for the USA, or - the "Technische Regel für Fernleitungen" (TRFL) (...
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Citations
... The first methods include acoustic monitoring [12,13] and non-acoustic techniques [14][15][16][17]. The advancement of technology has led to the development of inline inspection methods for pipeline surveys [18][19][20][21]. Progress in software and measurement tools has enabled water utilities to easily calculate water volume balance [22] and apply statistical analysis to predict leakage [23]. ...
This paper provides a comprehensive review of the methods and techniques developed for detecting leaks in water distribution systems, with a focus on highlighting their strengths, weaknesses, and areas for future research. Given the substantial economic, social, and environmental impacts of undetected leaks, timely detection and precise location of leaks are critical concerns for water authorities. This review categorizes existing methods into traditional approaches, such as manual sounding, and modern techniques involving smart water management and sensor technologies. A multidimensional bibliometric analysis was employed to systematically identify, select, and evaluate 600 scholarly articles on water leak detection, sourced from the Scopus database over a 23-year period (2000–2023). The paper evaluates each method based on leak sensitivity, burst detection, continuous monitoring, alarm accuracy, and implementation costs. Novel insights include an analysis of emerging smart water technologies and their integration into real-world water distribution networks, offering improved efficiency in leak detection. The paper also identifies key gaps in current research and suggests future directions for advancing the accuracy and cost-effectiveness of these technologies.
... The response time of this method depends on the speed of sound (Jia et al. 2018;Lim et al. 2016;Png et al. 2018;Mpesha et al. 2001;Silva et al. 1996). 5. Pressure point analysis: This method involves measuring the statistical pressure of the flow at various points and analyzing this data to determine the presence of a leak (He et al. 2017;Tian et al. 2016). However, this method is inaccurate, especially for transient flows, and cannot detect small leaks ( Geiger et al. 2006). In this method, both statistical and dynamic points of view are considered to find pipeline leakages (Kay 2013). ...
The pipeline is the fundamental means of transporting natural gas between the reservoir and the point of consumption. Despite the systems’ low cost and high reliability, potential pipeline failures would cause serious human injury, environmental impact, and financial costs. In order to reduce these damages, it is essential to study risk factors and investigate high-risk locations using existing risk factors. Spatial analysis is an appropriate method for studying environmental phenomena. Considering the extent of various factors influencing pipeline risk and their spatial dependence, we conducted a spatial analysis using ArcGIS to identify vulnerable areas and high-risk points in natural gas pipelines. For this purpose, the local influencing factors and their impact distance were determined by reviewing previous studies and then scored according to the risk level using the analytic hierarchy process (AHP) method. The risk of natural gas pipelines was then analyzed using these scores, the relationships developed, and the maps produced from the various factors. The results showed that most gas pipelines are exposed to various risks including dangers and geographical risks. Among these risks, faults play an important role, affecting about 97% of natural gas pipelines. In general, out of 13,875 km of general Iranian natural gas pipelines, 13,411 km are in various risk areas and 1,054 km are in high-risk areas, which are located at more than 4,300 points. The study of planned pipeline routes for future development also showed that these lines are located in relatively suitable areas. However, some changes to the routes could reduce the risks. Identifying the type and amount of risk on each pipeline helps experts choose a method with reasonable cost and sufficient efficiency for monitoring the pipeline according to the need.
... Other authors (Wang 2002) classify them as online and offline surveillance, or continuous and noncontinuous methods (Fiedler 2014). However, most of the classifications (Alaska 1999; Carpenter, 2016;Geiger 2006) consider only the position of the detection method, being internally based or externally based related to the pipeline (Fig. 1). ...
... Externally based methods use local sensors to generate leak alarm (Geiger 2003). System costs and complexity are usually high. ...
... As mentioned by Geiger (Geiger 2003), leak detection is a detection problem, or a classification/recognition problem, and leak localization is an estimation problem. ...
... [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30] These approaches are categorized using different frameworks basically into two categories: hardware and software. [31][32][33][34] The methods are further extended into three main areas: internal, nontechnical or non-continuous, and external methods [35][36][37][38][39][40][41][42] ; more study has been done to classify available leak detection systems. [2][3][4] The present study will classify the following categories: external, visible or biological, internal or computing. ...
... When leakage occurs, vapor or gas diffuses into the pipeline due to the concentration gradient, which generates a signal of hydrocarbon flashing in the tube environment after some time. 37 The leak peak likewise increases with the increased gas concentration. The higher the gas concentration in the tube, the greater the leakage. ...
An extensive network of pipelines is extensively employed worldwide to carry oil and gas fluids over millions of kilometers. The pipeline channel was constructed to resist environmental dynamic loading conditions to provide safe and reliable oil and gas fluids transportation from the production well sites to depot stations installed at sea coastlines. However, pipeline infrastructure damages such as fractures, cracks, leakages, etc., are significant sources of economic losses in pipeline operations. Moreover, pipeline failures can cause considerable ecological catastrophes, human deaths, and financial loss. Important research initiatives have been committed to establishing pipeline breach detection and localization using various techniques to avoid these threats and maintain a secure and dependable pipeline network. This paper reviews different state-of-the-art damage detection methods and their recent advancement with a case study explaining the application of light detection and ranging for pipeline damage detection. The pros and cons of diverse damage detection methods in pipeline networks are also discussed. Research gaps for pipeline damage detection systems are also provided for better understanding and future research.
... These methods have been classified in different ways, for instance, some researchers have divided them into two main categories namely hardware and software-based approaches [13,14]. While other researchers have distinguished the methods based on technical aspects and categorised them into three main groups: internal, external, and non-technical methods [14,15]. ...
The aim of this paper is to numerically investigate Vibration-Based Leak Detection (VBLD) method in pipeline systems based on Fluid–Structure Interaction (FSI) analysis to predict leakages. In previous investigations, laboratory tests were widely used to study the VBLD technique in small-diameter water loop system pipes. The current project uses Ansys Workbench to extend these findings by integrating Computational Fluid Dynamics (CFD) with Finite Element Analysis (FEA). The study outlines a numerical method for VBLD to identify leakages in a 90-degree pipe elbow by predicting variations in vibration signals, with applications in the oil and gas industry. Firstly, changes in fluid behaviour (centrifugal force, pressure drop, secondary flow, and frictional force) experienced in the internal pipe wall resulting from a probable leakage (modelled as an additional outlet) are determined using CFD. Subsequently, the CFD results are coupled with FEA to model structural responses of the pipe walls subjected to different forces. This in turn allows the variations in vibration signals to be measured. The numerical approach presented in this paper based on FSI and incorporating the VBLD method provides a practical and convenient early detection tool that can complement physical vibration monitoring equipment in the field.
... Existing real-time leak detection methods can be broadly classified into external based methods and internal or computational based methods [1] . External based methods rely on physical detection of product that escapes the pipeline through sensors. ...
Real-time leak detection on short liquid pipelines is challenging due to system fluctuations of a few seconds or less. This presentation reviews a leak detection system for short liquid lines involving rapid pressure and flow sensors at pipeline ends, coupled with a fast simulator based on water hammer principles, implemented computationally by the Method of Characteristics (MOC). The effect of data fidelity and sampling rates on leak identification – magnitude and location – is studied to specify appropriate instrumentation. Leak detection performance is evaluated by means of in-house laboratory experiments, scaled to represent commercial liquid ammonia pipelines.
... Other investigations utilized tethered acoustic systems, 113 pig-mounted acoustic sensing, 111 leak noise correlators, 118 and camera inspection systems, the majority having been utilized in district meter areas of WDNs and were obtainable commercially. In recent times, a leak location algorithm that reduces human involvement was proposed by Geiger 119 and categorized as a wave propagation method and a gradient intersection method. The first is possible since leaks modify the pressure gradient along a pipe in a typical way. ...
... If a leak is present, the pressure causes a defect at the leakage point. 119 The site of the leakage is determined by calculating the position at which the pressure profiles cross upstream or downstream of the leakage, as shown in Figure 13. ...
The effective operation of water management systems is contingent upon leak localization and detection – a common problem that is more acute in large networks. This paper reviews the salient literature in this context and demonstrates the effectiveness of leakage location methods (LLMs) and leakage detection methods (LDMs). Although there is a significant amount of literature that discusses leakage localization and detection technologies, an academic lacuna still exists concerning the linkage between degradation mechanisms and LDMs and do not cover or connect past efforts from the start of a degradation mechanism that leads to changes in the mechanical strength (such as a reduction in fracture toughness) of pipes and results in crack propagation and leakage. This review focuses on these issues in the context of degradation mechanisms and common detection methods.
... Some of these methods include flow rate monitoring, pressure point analysis, negative pressure wave, distributed fiber optic sensing, acoustic sensing, real-time transient modeling, model simulation, infrared cameras, and lidar systems ( Bai et al., 2004 ;Liang et al., 2018 ;Ling et al., 2016 ;Meng et al., 2017 ;Reddy et al., 2016 ;Sheltami et al., 2016 ;Yu et al., 2009 ). The classification of the existing methods takes several forms and can broadly be classified into externally based methods, internally/computational based methods, and visual/inspection methods ( Geiger, 2006 ;Xu et al., 2013 ;Zhang et al., 2013 ). Internally/computational leak detection methods operate based on a model or algorithmic principle that monitors the flow parameters in real-time, whereas the externally based leak detection methods operate on the non-algorithmic principle of physical detection of an escaping commodity using dedicated external sensors ( API, 2007 ;Baptista and conducted in the second week of September 2021, and another search was conducted in May 2022. ...
A pipeline burst or rupture causing a leak may significantly impact the environment and the reputation of the company operating the pipeline. In recent years oil and gas pipelines are expected to be equipped with leak detection systems for monitoring the operations and detecting the leaks. Although the leak detection methods used today may not prevent leaks from happening, they play a crucial role in limiting the impact of leak. There is a wide variety of leak detection methods developed and tested. This paper reviews these methods, analyze their advantages and limitations. It ends by highlighting the opportunities for future work to improve reliability and adaptability of leak detection methods in subsea region.
... However, all the systems were rigid. Different methods to determine the leakage were presented in [20]. One of them used the pressure drop in the pipeline, again considering rigid pipes in industrial applications. ...
Current enteroscopy techniques present complications that are intended to be improved with the development of a new semi-automatic device called Endoworm. It consists of two different types of inflatable cavities. For its correct operation, it is essential to detect in real time if the inflatable cavities are malfunctioning (presence of air leakage). Two classification predictive models were obtained, one for each cavity typology, which must discern between the “Right” or “Leak” states. The cavity pressure signals were digitally processed, from which a set of features were extracted and selected. The predictive models were obtained from the features, and a prior classification of the signals between the two possible states was used as input to different supervised machine learning algorithms. The accuracy obtained from the classification predictive model for cavities of the balloon-type was 99.62%, while that of the bellows-type was 100%, representing an encouraging result. Once the models are validated with data generated in animal model tests and subsequently in exploratory clinical tests, their incorporation in the software device will ensure patient safety during small bowel exploration.
... Leakage monitoring systems are roughly divided into two types: software-based and hardware-based [6][7][8][9]. The software-based system uses mathematical methods to infer the occurrence of leakage according to the abnormity of pipeline internal parameters (such as pressure, temperature, flow rate, etc). ...
A simulation test on gas pipeline leakage by using distributed acoustic sensing technology (DAS) was designed. An optical sensing cable with a spiral structure was adopted to improve the sensitivity of leakage monitoring. The method of pipeline leakage signal identification and location based on fast Fourier transform (FFT) is proposed. By analyzing the vibration of the optical fiber in the time and frequency domains, the leakage signal can be accurately monitored. According to the variation in the spectral average amplitude of each sensing channel, the leakage point can be located, and the positioning equation is given. The size of the leakage hole and the direction of leakage on the spectral characteristics of the leakage signal are discussed. The average absolute amplitude in the time domain and spectral average amplitude in the frequency domain of the leakage signal decrease with the size of the leakage hole. As the angle between the leakage direction and the direction from the pipeline to the optical sensing cable increases, the spectral average amplitude of the leakage signal gradually decreases. The effect of the distance from the leakage hole on the leakage signal is discussed. The average absolute amplitude of the leakage signal decreases with the relative distance between the leakage hole and the optical sensing cable.
