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Study on Pattern Recognition of Storage Tank Bottom Corrosion Signal Based on Acoustic Emission

Author: XingFeiFei
Tutor: JinShiJiu
School: Tianjin University
Course: Precision instruments and machinery
Keywords: Tank Corrosion of the tank bottom Acoustic emission Feature Extraction Pattern Recognition
CLC: TP274.4
Type: Master's thesis
Year: 2008
Downloads: 225
Quote: 10
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Abstract


Currently, the sustained and rapid development of China's national economy is increasingly urgent demand for energy, especially oil and gas resources. Large-scale atmospheric tank as the petrochemical industry, oil storage facilities, is widely used special equipment and more prone to accidents. It there are two major problems of the safety of the use and detection of economy. Large atmospheric storage tanks in the natural environment and the level change conditions for many years run by a variety of adverse factors inevitably affected by a variety of injuries. Is the corrosion perforation triggered by environmental chemical and electrochemical corrosion, crack propagation and rupture, resulting in leakage of the medium, causing serious disasters and environmental pollution, causing huge losses to state property. However, the conventional storage tank bottom detection methods to stop the tank the transceiver job and cleaning tank, rust, or even dismantle the insulation processes, the high cost of oil loss and construction measures and time-consuming, and inefficient. Therefore, the tank line detection of acoustic emission technique has been widely recognized and studied. In this paper, the access to a large number of domestic and international acoustic emission research literature on the basis of their own build a experimental platform for acoustic emission signals tank to tank bottom corrosion and corrosion, cracks and tank storage bottom depth study on this basis, within the perturbation of the acoustic emission signal processing and analysis methods. Wavelet feature extraction acoustic emission signal processing and artificial neural network combined storage bottom feasibility of the method is verified by a large number of data test. In this paper, following research work: 1, analyze the causes and mechanism of corrosion takes place at the end of the storage tank, and the corrosion experiment platform is designed based on a set of tanks tank bottom, the corrosion electrochemical methods excitation can be controlled the pitting signal. Human manufacture of crack propagation and the tank oil perturbations of acoustic emission signals on the same platform as a follow-up experiment comparison signal. 2, the acoustic emission signal characteristics based on wavelet decomposition and wavelet packet decomposition extraction method used for the Tank bottom acoustic emission detection signal feature extraction, and analysis of the effect of the two methods of feature extraction. , Both BP neural network and RBF neural network pattern recognition method for identification of the type of acoustic emission signals of the tank bottom of the tank, and construct engineering practice common small sample training, can not get a large number of known mode data and two neural network test correct rate. 4, through a large number of on-site verification of experimental data to determine a more reasonable ideas for further research on the bottom of the storage tank acoustic emission detection technology.

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Data processing, data processing system > Centralized testing and roving detection system
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