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Abstrakt

Leak detection in transmission pipelines is important for safe operation of pipelines. The probability of leaks may be occurred at any time and location, therefore pipeline leak detection systems play a key role in minimization of the occurrence of leaks probability and their impacts. During the operation of the network there are various accidents or intentional actions that lead to leaks of gas pipelines. For each network failure, a quick reaction is needed before it causes more damage. Methods that are used to detect such network failures are three-staged-: early identification of leakage, an accurate indication of its location and determine the amount of lost fluid. Methods for leak detection can be divided into two main groups: external methods (hardware) and internal methods (software). External leak detection methods require additional, often expensive equipment mounted on the network, or use systems that could display only local damage on the pipeline. The alternative are the internal methods which use available network measurements and signalling gas leakage signal based on the mathematical models of the gas flow. In this paper, a new method of leak detection based on a mathematical model of gas flow in a transient state has been proposed.
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Abstrakt

Detection of leakages in pipelines is a matter of continuous research because of the basic importance for a waterworks system is finding the point of the pipeline where a leak is located and − in some cases − a nature of the leak. There are specific difficulties in finding leaks by using spectral analysis techniques like FFT (Fast Fourier Transform), STFT (Short Term Fourier Transform), etc. These difficulties arise especially in complicated pipeline configurations, e.g. a zigzag one. This research focuses on the results of a new algorithm based on FFT and comparing them with a developed STFT technique. Even if other techniques are used, they are costly and difficult to be managed. Moreover, a constraint in the leak detection is the pipeline diameter because it influences accuracy of the adopted algorithm. FFT and STFT are not fully adequate for complex configurations dealt with in this paper, since they produce ill-posed problems with an increasing uncertainty. Therefore, an improved Tikhonov technique has been implemented to reinforce FFT and STFT for complex configurations of pipelines. Hence, the proposed algorithm overcomes the aforementioned difficulties due to applying a linear algebraic approach.
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