Fault Diagnosis of a Pump Using Analysis of Noise

작동음의 분석을 이용한 펌프의 고장진단

  • Published : 2003.12.01

Abstract

We should maintain the maximum operation capacity for production facilities and find properly out the fault of each equipment rapidly in order to decrease a loss caused by its failure. The acoustic signals of a machine always carry the dynamic information of the machine. These signals are very useful for the feature extraction and fault diagnosis. We performed a fundamental study which develops a system of fault diagnosis for a pump. We obtained noises by a microphone, analysed and compared the signals converted to Sequency range for normal products, artificially deformed products. We tried to search a change of noise signals according to machine malfunctions and analyse the type of deformation or failure. The results showed that acoustic signals as well as vibration signals can be used as a simple method for a detection of machine malfunction or fault diagnosis.

Keywords

References

  1. Asakura, T., Kobayashi, T., Xu, B. and Hayashi, S., 2000, 'Fault Diagnosis System for Machines Using Neural Networks', Int. J. of JSME, Series C, Vol. 43, pp. 364-371 https://doi.org/10.1299/jsmec.43.364
  2. Staroswiecki, M., 2000, 'Quantitative and Qualitative Models for Fault Detection and Isolation', J. of MSSP, Vol. 14, pp. 301-325
  3. Lee, S. H., Kim, J. S., Kim, B. S., Song, J. Y., Lee, S. W., Park, H. Y. and Park, J. K., 2000, 'A Studty on Failure Mode Analysis for Reliability Assesment of Maching Center', Trans. of KSPE, 00F228, pp. 1010-1013
  4. Lee, S. W., Song, J. Y., Kang, J. H., Hwang, L. H., Lee, H. Y. and Park, H. Y., 2000, 'Evaluation of Reliability for Critical Unit of Machinery System', Trans. of KSPE, 00F229, pp. 1014-1017
  5. Lin, J. and Qu, L., 2000, 'Feature Extraction Based on Morlet Wavelet and Its Application for Mechanical Fault Diagnosis', J. of Sound and Vibration, Vol. 234, pp. 135 -148 https://doi.org/10.1006/jsvi.2000.2864
  6. Zang, C., and Imregun, M., 2001, 'Structural Damage Detection Using Artificial Neural Networks and Measured FRF Data Reduced via Principal Component Projection', J. of Sound and Vibration, Vol. 242, pp. 813-827 https://doi.org/10.1006/jsvi.2000.3390
  7. Jung, W. S., 2000, Fault Diagnosis of a Pump Using Analysis of Vibration Signal, Master Thesis, Kunsan National University
  8. Danai, K. and Chin, H., 1991, 'Fault Diagnosis With Process Uncertainty', J. of DSMC, Vol. 113, pp. 339-343
  9. Maeng, M. J. and Chung, J. K., 2001, 'Wear Detection of Coated Tool Using Acoustic Emission', Trans. of KSMTE, Vol. 10, No. 5, pp. 9-16
  10. Cho, D. H., Lee, S. T., Won, J. S. and Jung, Y. G., 2000, 'Monitoring of Chatter Vibration by Frequency Analysis of AE Signals', Trans. of KSMTE, Vol. 9, No. 5, pp. 157-164