期刊
PROCEEDINGS OF THE 2019 31ST CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2019)
卷 -, 期 -, 页码 2679-2684出版社
IEEE
DOI: 10.1109/ccdc.2019.8833147
关键词
Leakage detection; Gas pipeline; SST; SCAE
资金
- National Nature Science Foundation [51605022]
Because of uncertainty, the diagnosis of gas pipeline leakage is a difficult problem. In order to solve the difficult problem to distinguish leakage in gas pipelines, an approach of leakage detection using Synchrosqueczed Wavelet Transform (SST) and Stacked Contractive Auto-encoder (SCAE) was proposed. First, the sound signal in gas pipelines is subjected to simultaneous compression wavelet transform to obtain time-frequency images n grey-scale and normalized the image. Then, the time-frequency representations were compressed to the appropriate size. The compressed time-frequency matrix should be expanded into a column as the SCAE's input. The classification model of SCAE and SoftMax was established to realize the leakage detection in pipelines. The experimental results indicated that this method could effectively identify small leakage in pipelines, and the method could effectively improve the fault recognition rate and reduce the training cost.
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