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http://dx.doi.org/10.12989/sss.2020.25.2.255

Defect classification of refrigerant compressor using variance estimation of the transfer function between pressure pulsation and shell acceleration  

Kim, Yeon-Woo (Department of Mechanical Engineering, Pusan National University)
Jeong, Weui-Bong (Department of Mechanical Engineering, Pusan National University)
Publication Information
Smart Structures and Systems / v.25, no.2, 2020 , pp. 255-264 More about this Journal
Abstract
This paper deals with a defect classification technique that considers the structural characteristics of a refrigerant compressor. First, the pressure pulsation of the refrigerant flowing in the suction pipe of a normal compressor was measured at the same time as the acceleration of the shell surface, and then the transfer function between the two signals was estimated. Next, the frequency-weighted acceleration signals of the defect classification target compressors were generated using the estimated transfer function. The estimation of the variance of the transfer function is presented to formulate the frequency-weighted acceleration signals. The estimated frequency-weighted accelerations were applied to defect classification using frequency-domain features. Experiments were performed using commercial compressors to verify the technique. The results confirmed that it is possible to perform an effective defect classification of the refrigerant compressor by the shell surface acceleration of the compressor. The proposed method could make it possible to improve the total inspection performance for compressors in a mass-production line.
Keywords
defect classification; linear compressor; transfer function; frequency analysis; variance minimize; mass-production inspection; FDR;
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Times Cited By KSCI : 5  (Citation Analysis)
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