Paper Title:

Reciprocating Compressor Fault Classify Base on Multi-Component Singular Entropy

Periodical Advanced Materials Research (Volume 505)
Main Theme Manufacturing Engineering and Process
Edited by Xiaoxiao Zhou
Pages 221-226
DOI 10.4028/www.scientific.net/AMR.505.221
Citation Yu Yuan et al., 2012, Advanced Materials Research, 505, 221
Online since April, 2012
Authors Yu Yuan, Ting Yu Wang, Bao Liang Li
Keywords ANFIS, Fault Diagnosis, IMF, Local Wave, Singular Entropy
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Abstract

Condition monitoring of reciprocating machines through the analysis of their vibrations has been recognized to be a difficult issue, essentially because of the strong nonlinearity of the vibration signals. A new method of multi-component singular entropy is put forward to resolve this problem. Local Wave method is combined with Singular Entropy to extract features from the IMF of the vibration signals of reciprocating machines. And the features will be used as the input of ANFIS to classify and recognize the fault mode. The results are classified correctly. The conclusion shows that this method is feasible.