Journal of the Korea Safety Management & Science (대한안전경영과학회지)

Korea Safety Management & Science (대한안전경영과학회)
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Development of Diagnosis of Trouble Model for Effective Operation of Air-compressor

효율적인 공기압축기 운영을 위한 이상진단모델 연구

  • Im, Sang Don (Dept. of Industrial & Management Engineering, Chosun University) ;
  • Jung, Young Deuk (Dept. of Taekwondo and Physical Education, Jeonju Vision University) ;
  • Kim, Jong Rae (Dept. of Industrial & Management Engineering, Chosun University)
  • Received : 2014.03.31
  • Accepted : 2014.09.22
  • Published : 2014.09.30
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Abstract

Most systems used in industrial sites, actually have non-linearity and uncertainty. Therefore there are a lot of difficulties in evaluating conditions of these systems. Generally, the quantitative analysis and expression are found hard because the general public cannot easily make an accurate interpretation on the systems. Thus development of a system that utilizes an expertise from skilled analysts is required. In this research, a real-time sensor signal conditioning system and Fuzzy-expert system have been separately set up into an inference algorithm. So that it ensures a fast, accurate, objective and quantitative operational condition value provided to the manager. Therefore, FE_AFCDM is suggested in this literature, as an effective system for diagnosing the problems related to the air compressor. It can quantify the uncertain and absurd condition to operate the air compressor facilities safely and financially.

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References

  1. B.J. Choi, S.W. Kwak, A. Nabout,"Resundant fuzzy rules Exclusion by Genetic Algorithms," Fuzzy Sets and Systems 100, pp.235-243, 1998. https://doi.org/10.1016/S0165-0114(97)00056-0
  2. Durkin, John, Expert Systems; Catalog of Applications, Intelligent Computer Systems, P.O. Box 4117, Akron, Ohio, 1993.
  3. D.Y. Yoon, "AVR Atmega128 MASTER", Ohm company, 2006.
  4. H.Y. Shin, A Study on the Development of a Rule-Based Expert System for the Automatic Design of Pneumatic Systems, In-ha University, 1997.8.
  5. Kyoung Min Kim(2009), "Development of Sound and Vibration Monitoring System for the basis on Embedded", The Korean Society for Noise and Vibration Engineering Fall Conference Proceeding, pp 763-764.
  6. L.A. Zadeh,"The Role of Fuzzy Logic in the Management of Uncertainty in Expert System",Fuzzy Sets and System, Vol.11, New York: pp199-227,1983. https://doi.org/10.1016/S0165-0114(83)80082-7
  7. Riemer, P.L., Mitchell, J. W., and Beckman, W. A., 2002, The use of series analysis in fault detection and diagnosis methodologies, ASHRAE Transactions, Vol. 108, Pt. 2, pp.384-394.
  8. Stearns, S.D., 1988, Signal Processing Algorithm, Prentice-Hall.
  9. S. Kimon HC, Study on the Plastic Injection Influenced by Injection Condition in the Plastic Mold of Soongsil University, 1991.
  10. Shin, H.Y. A Study on the Development of a Rule-Based Expert System for the Automatic Design of Pneumatic Systems, In-ha University, 1997.8.
  11. Won-Yong Lee, J.M. House, Dong-Ryul Shin, Classification Techniquies for Fault Detection and Diagnosis of an Air Handling Unit, IEA ANNEX34 meeting at Boulder, Sept, 1997.
  12. Zigbee Architecture Overview.(2005). Zigbee Alliance.