Volume 8, No. 4, July 2019

General Information

  • ISSN: 2278-0149 (Online)
  • Abbreviated Title:  Int. J. Mech. Eng. Robot. Res.  
  • Editor-in-Chief: ​Prof Richard (Chunhui) Yang, Western Sydney University, Australia
  • Associate Editor: Prof. B.V. Appa Rao, Andhra University; Prof. Ian R. McAndrew, Capitol Technology University, USA
  • Managing Editor: Murali Krishna. B
  • DOI: 10.18178/ijmerr
  • Abstracting/Indexing: Scopus (since 2016), CNKI, Google Scholar, Crossref, etc.
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International Journal of Mechanical Engineering and Robotics Research
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Soft-Computing Method for Detection of Abnormal Status of Plant Equipment

Seong-Joo Kim, Young-Joo Kim and Joo-Hoon Kim
Dae-Heung Industrial Gases Co., Ltd., Gunsan, South Korea

Abstract—Currently, the safety monitoring process in a complex plant environment is proceeded by the human. Sometimes, human error that may occur in a filed causes a severe problem. This paper introduces a soft-computing method for detection of the abnormal status of plant equipment using sound information and neuro-fuzzy theory that is one of the intelligent theories. The sound for testing is acquired from the cylinder valve, compressor operation, safety valve open. In this paper, the high-pressure gas filling plant will be used as a test plant. The resulting system will be widely applied to more complex plant environments. 

Index Terms—safey monitoring, sound analysis, neuro-fuzzy logic, intelligence, detection

Cite: Seong-Joo Kim, Young-Joo Kim and Joo-Hoon Kim, "Soft-Computing Method for Detection of Abnormal Status of Plant Equipment" International Journal of Mechanical Engineering and Robotics Research, Vol. 8, No. 4, pp. 570-575, July 2019. DOI: 10.18178/ijmerr.8.4.570-575