Abstract
Support Vector Machine (SVM) is a very effective method for pattern recognition. In this article, a intelligent diagnosis system based on SVMs is presented to solve the problem that there is not effective method for reciprocating compressor valve fault detection. The Local Wave method was used to decompose vibration signals, which acquired from valves surface, into sub-band signals. Then the higher-order statistics were calculated as the input features of classification system. The experiment results confirm that the classification technique has high flexibility and reliability on valve condition monitoring.
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Ren, Q., Ma, X., Miao, G. (2005). Application of Support Vector Machines in Reciprocating Compressor Valve Fault Diagnosis. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_13
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DOI: https://doi.org/10.1007/11539117_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
Online ISBN: 978-3-540-31858-3
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