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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/42010

Title: A novel signal processing approach for valve health condition classification of a reciprocating compressor with seeded faults considering time-frequency partitions
Authors: Y.-H. Lin;W.-S. Lee;C.-Y. Wu
Contributors: 國立臺灣海洋大學:機械與機電工程學系
Date: 2013-10
Issue Date: 2017-04-20T01:02:41Z
Publisher: Journal of Marine Science and Technology
Abstract: Abstract:This study deals with a novel signal processing approach for automated valve condition classification of a reciprocating compressor with seeded faults. The classification system consists of a front end time-frequency analysis platform for the vibration signal measured, fault feature vectors for making the formidable amount of time-frequency data manageable, and a probabilistic neural network for automatic classification without the intervention of human experts. Rather than representing each time-frequency data set with one single feature vector comprising three indices, namely time, frequency, and amplitude, the time-frequency plane is further partitioned into an appropriate number of sub-regions to enhance the characteristics representation of the time-frequency data. This study shows that a flawless classification can be realized by using the proposed approach with appropriate selections of index modification method and number of time-frequency subregions without resorting to the removal of similar fault cases .
Relation: 21(5), pp.578-585
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/42010
Appears in Collections:[機械與機電工程學系] 期刊論文

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