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Performance Analysis on Early Detection of Fault Symptom of a Pump with Abnormal Signals
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 Title & Authors
Performance Analysis on Early Detection of Fault Symptom of a Pump with Abnormal Signals
Jung, Jae-Young; Lee, Byoung-Oh; Kim, Hyoung-Kyun; Kim, Dae-Woong;
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As a method to improve the equipment reliability, early warning researches that can be detected fault symptom of an equipment at an early stage are being performed out among developed countries. In this paper, when abnormal signal is input to actual normal signal of a pump, early detection studies on pump`s fault symptom were carried out with auto-associative kernel regression as an advanced pattern recognition algorithm. From analysis, correlations among power of motor driving pump, discharge flow of pump, power output of pump, and discharge pressure of pump are exited. When the abnormal signal is input to one of those normal signals, the other expected values are changed due to the influence of the abnormal signal. Therefore, the fault symptom of pump through the early-warning index is able to detect at an early stage.
Equipment Reliability;Early Warning;Fault Symptom;Pattern Recognition;Auto-Associative Kernel Regression(AAKR);Correlation;Early-warning Index;
 Cited by
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