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- W2383721302 abstract "The acoustic emission(AE)signals characteristic of nitrogen-added 304NG stainless steel stress corrosion process was studied.Two experiments were performed,one was long term slow strain rate test(SSRT),and the other was short term slow strain rate test.The solution was made of 0.5 mol·L-1 NaCl and 1.5 mol·L-1 H2SO4.By using combined self-organizing maps and K-means cluster algorithm to classify the AE signals in long term SSRT,in which the duration,counts,energy,amplitude,waveform and frequency band energy were analyzed as the AE signals' characteristics,and the crack AE signals were found.The classified signals were trained by using the artificial neural network,so as to identify the different types AE signals in short term SSRT.The result showed that AE test for 304NG stainless steel stress corrosion process would be confirmed by electrochemical noise test.And there were mainly three types of AE signals during 304NG stainless steel stress corrosion process,including crack,pitting and bubbles,which could be classified by using cluster analysis and be provided as template to build artificial neural network to identify the AE signals generated in the same corrosion environment." @default.
- W2383721302 created "2016-06-24" @default.
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- W2383721302 date "2011-01-01" @default.
- W2383721302 modified "2023-09-26" @default.
- W2383721302 title "Cluster analysis of acoustic emission signals during 304NG stainless steel stress corrosion process" @default.
- W2383721302 hasPublicationYear "2011" @default.
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