Leak Detection And Location In Gas Pipeline

With the development of SCADA and it use in pipelines in recent years, the synthesized software skills based on information disposal has been turned into the hotspot and tide of academe in the world.A leak detection and location system for the Zhejiang province natural gas SCADA system was developed by using RBF artificial neural network, de-noising via wavelet and negative-pressure location formula.Main research work and contributions of this dissertation are as following:1. Pre-processing (Filtering) the measurements from industryWith basic theory about Wavelet Analysis, the primary algorithm was completed including Wavelet Transform and Inverse Wavelet Transform using Matlab. After a brief description of the fundamental theory of wavelet analysis from the view of multiresolution estimating, a method of de-noising via wavelet thresholding was introduced including the selection of wavelet functions and the calculation of threshold. Then an improved method, namely translation invariant de-noising was proposed. Experiment shows the result is practicable. Online multiscale filtering was introduced and applied to the emulational signal from Matlab and process measurements form industry.2. Leak detection and location by RBF artificial neural networkIn this paper, we analyse the algorithm and characteristics of RBF artificial neural network,make some improvements on it and a leak detection system for pipelines is developed by using RBF artificial neural network for leak sizing.3. Improve the negative-pressure location formula...