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Acoustic Diagnosis of a Pump by Using Neural Network  

Lee, Sin-Young (School of Mechanical Engineering, Kunsan National University)
Publication Information
Journal of Mechanical Science and Technology / v.20, no.12, 2006 , pp. 2079-2086 More about this Journal
Abstract
A fundamental study for developing a fault diagnosis system of a pump is performed by using neural network. Acoustic signals were obtained and converted to frequency domain for normal products and artificially deformed products. The neural network model used in this study was 3-layer type composed of input, hidden, and output layer. The normalized amplitudes at the multiples of real driving frequency were chosen as units of input layer. And the codes of pump malfunctions were selected as units of output layer. Various sets of teach signals made from original data by eliminating some random cases were used in the training. The average errors were approximately proportional to the number of untaught data. Neural network trained by acoustic signals can detect malfunction or diagnose fault of a given machine from the results.
Keywords
Acoustic Diagnosis; Pump; Neural Network; Deformed Cases; Frequency Domain;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
Times Cited By Web Of Science : 0  (Related Records In Web of Science)
Times Cited By SCOPUS : 0
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