Leakage Detection in Pipeline using Wavelet Transform Method

This research project is focusing on the leakage detection in the pipelines using wavelet and cepstrum analysis. To fully complete this research project, experimental and analysis by using signal processing are required. This research project proposed a technique which is a transient method. The basic principle is the fact that water spouting out of a leak in a pressurized pipe generates a signal, and this signal contains information to whether a leak exists and where it is located. The present transient methods for finding leaks are mainly based upon correlation analysis, where one sensing device is installed at each side of a leak. This method is hard to operate because it needs many operators to operate it due to equipment in different place. This research project proposed a wavelet transform method to detect leakage in the pipeline system. The experimental results show appears  to improve the ability of the method to identify features in the signal

Leakage Detection In Pipeline Using Wavelength

Nowadays natural gas transport and distribution is a complex and currently growing and increasing. Natural gas produced from well need to transport in a great distance before reaching it point of use. The pipeline is designed to quickly and efficiently transport the gas from its origin to the high demand area. Either pipelines transportation for water supply or natural gas, leakage is unacceptable problem. Small leak along the pipeline is hard to detect. The objective of this study is to build the test rig galvanized iron and MDPE pipelines. Besides that, the main objective is to determine the leak detection in gas pipeline using wavelet-based filtering. . Main point of each journal is compared in order to determine the problems arise from the previous research. It is then follow by the methodology which will discuss further in this chapter. From methodology, it is known that the data taken can be analysing through Daisy Lab and Math lab software  Wavelet and cross correlation is used to analyse the signal in Matlab. From the result, it show that the leak can be identified based on the peak of amplitude of the signal. The result for galvanized iron pipe is not acceptable due to short pipeline length. Thus it can be concluded that leak can be determined using wavelet-based filtering. As the conclusions, the propose technique can be used to determine the leak in pipeline

Leak detection using instantaneous frequency analysis

Leaking pipes are a primary concern for water utilities around the globe as they compose a major portion of losses. Contemporary interest surrounding leaks is well documented and there is a proliferation of leak detection techniques. Although the reasons for these leaks are well known, some of the current methods for leak detection and location are either complicated, inaccurate and most of them are time consuming. Transient analyses offer a plausible route towards leak detection due to their robustness and simplicity. These approaches use the change of pressure response of the fluid in a pipeline to identify features. The method used in the current study employ a single pressure transducer to obtain the time domain signal of the pressure transient response caused by a sudden opening and closing of a solenoid valve. The device used is fitted onto a standard UK hydrant and both cause a pressure wave and acquire the pressure history. The work described here shows that the analysis using Hilbert transform (HT), Hilbert Huang transform (HIHT) and EMD based method is a promising tool for leak detection and location in the pipeline network. In the first part of the work, the analysis of instantaneous characteristics of transient pressure signal has been calculated using HT and HHT for both simulated and experimental data. These instantaneous properties of the signals are shown to be capable of detecting the reflection from the features of the pipe such as leakages and outlet. When tested with leak different locations, the processed results still show the existing of the features in the system. In the second part of the work, the study is based on newly method of analysing nonstationary data called empirical mode decomposition (EMD) for instantaneous frequency calculation for leak detection. First, the pressure signals were filtered in order to remove the noise using EMD. Then the instantaneous frequency was calculated and compared using different methods. With this method, it is possible to identify the leaks and also the features in the pipeline network. These were tested at different locations of a real water distribution system in the Yorkshire Water region

Comparative study of instantaneous frequency based methods for leak detection in pipeline networks

Methods of pressure transient analysis can be seen as a promising, accurate and low-cost tool for leak and feature detection in pipelines. Various systems have been developed by several groups of researchers in recent years. Such techniques have been successfully demonstrated under laboratory conditions but are not yet established for use with real field test data. The current paper presents a comparative study of instantaneous frequency analysis techniques based on pressure transients recorded within a live distribution network. The instantaneous frequency of the signals are analysed using the Hilbert transform (HT), the Normalised Hilbert transform (NHT), Direct Quadrature (DQ), Teager Energy Operator (TEO) and Cepstrum. This work demonstrates the effectiveness of the instantaneous frequency analysis in detecting a leaks and other features within the network. NHT and DQ allowed for the identification of the approximate location of leaks. The performance TEO is moderate, with Cepstrum being the worst performing method. © 2011 Elsevier Ltd. All rights reserved

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate

Pipeline leak detection

In the present research two techniques are applied for leak detection in pipelines. The first method is a hardware-based technique which uses ultrasonic wave\u27s emission for pipeline inspection. Ultrasonic waves are propagated in the pipe walls and reflected signal from leakage will be used for pipe analysis. Several Pipes with various dimensions and characteristics are modeled by finite element method using ANSYS. Second order longitudinal modes of ultrasonic waves are emitted in their walls. For this purpose, excited frequency is calculated such that it excites the second order longitude mode. In order to investigate the behavior of emitted wave in contact with leakage, four sensors are used in outer surface of pipe. Waves are reflected when encountering leakage and the leak location is recognized knowing the wave emission speed and flight time of backscattered signals. Wavelet transform is used for processing these signals and recognizing leak location. This method is tested on several pipe models and it presents satisfactory results for short pipes. The second approach is a software-based method which works based on the transient model of the pipeline. In this method the outputs from simulated pipeline are compared to those measured from flow meters and if their difference goes beyond a threshold value, leak is detected. For leak localization a gradient pressure technique is applied which needs pressure slope measurements at inlet and outlet of the pipeline. Several cases with leak at various positions are studied. This method works well with high accuracy for long pipelines. --Abstract, page iii

Novel Negative Pressure Wave-based Pipeline Leak Detection System Using Fiber Bragg Grating-based Pressure Sensors

In this paper, the design and underpinning technical principles of the novel design of a negative pressure wave (NPW)-based pipeline leak detection (PLD) system has been reported, which is configured using Fiber Bragg Grating (FBG) pressure sensors. To evaluate this, a pipeline leakage test platform has been established and experiments have been conducted, to verify the performance of a system using this FBG-based approach. The results show that a system using FBG-based sensors can accurately determine the pressure change trends along the pipeline and thus allow the calculation of the NPW velocity online. A key comparison is made with traditional NPW detection techniques, showing that the novel detection system is capable of achieving the higher leak-location accuracy and the detection of smaller leakage volumes. This arises from the ability of the FBG-based system to allow an increased number of sensors to be multiplexed along the pipeline. Their corresponding output signals generated show a very satisfactory, high signal-to-noise ratio. The system has been evaluated, especially in its response to extraneous signals and thus disturbances caused by the pump starting or stopping can be eliminated. This was achieved through an analysis of the time sequence of the pressure changes captured by the multi-sensor array being carried out and thus immunity to such effects demonstrated. The system has thus been designed to minimize the instances where a false alarm occurs

Investigation of Internal Gas Leakage on the Gate Valve using Acoustic Signal

The gate valve is primarily used for starting/stopping the flow of fluids. It is suitable for most fluids such as water and chemicals as well as air, steam and gas in petrochemical and refinery plants that require high temperature and low pressure. The aim of this study is to define the frequency domain using AE signals, such as RMS and ASL, to determine the internal gas leakage. The conducted experiment employed a 4-inch diameter gate valve installed in the middle of the pipe length. To simulate industrial applications, the AE signals were observed at low-frequency (between 18.6 kHz to 19.5 kHz), with inlet pressures between 100 to 800 kPa and leakage rates between 0.5 percent to 2 percent. The frequency domain between 18.6 to 19.5 kHz and the inlet pressure of 100 to 800 kPa were displayed as the Root Mean Square (RMS) and Average Signal Limit (ASL). The pressure difference between the inlet and outlet influences the AE signal. The frequency spectrum can be correlated with the pressure leakage, thus providing leakage conditions. Therefore, the obtained results can be employed in industrial applications

Laplace-domain analysis of fluid line networks with applications to time-domain simulation and system parameter identification.

Networks of closed conduits containing pressurised fluid flow occur in many different instances throughout the natural and man made world. The dynamics of such networks are dependent not only on the complex interactions between the fluid body and the conduit material within each fluid line, but also on the coupling between different lines as they influence each other through their common junctions. The forward modelling (time-domain simulation), and inverse modelling (system parameter identification) of such systems is of great interest to many different research fields. An alternative approach to time-domain descriptions of fluid line networks is the Laplace-domain representation of these systems. A long standing limitation of these methods is that the frameworks for constructing Laplace-domain models have not been suitable for pipeline networks of an arbitrary topology. The objective of this thesis is to fundamentally extend the existing theory for Laplace-domain descriptions of hydraulic networks and explore the applications of this theory to forward and inverse modelling. The extensions are undertaken by the use of graph theory concepts to construct network admittance matrices based on the Laplace-domain solutions of the fundamental pipeline dynamics. This framework is extended to incorporate a very broad class of hydraulic elements. Through the use of the numerical inverse Laplace transform, the proposed theory forms the basis for an accurate and computationally efficient hydraulic network time-domain simulation methodology. The compact analytic nature of the network admittance matrix representation facilitates the development of two successful and statistically based parameter identification methodologies, one based on an oblique filtering approach combined with maximum likelihood estimation, and the other based on the expectation-maximisation algorithm.Thesis (Ph.D.) -- University of Adelaide, School of Civil, Environmental and Mining Engineering, 201