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An application of soft computing in oil condition monitoring

Afsharnia, F ; Sharif University of Technology | 2023

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  1. Type of Document: Article
  2. DOI: 10.1007/978-981-19-9909-3_5
  3. Publisher: Springer , 2023
  4. Abstract:
  5. Preventive maintenance strategy can reduce the exorbitant costs of purchasing spare parts, repairs, and consequently downtime, as well as increase efficiency and income by reducing downtime. Oil monitoring is one of the most important policies for preventive maintenance of equipment. This chapter aimed to develop a fuzzy program based on engine oil analysis to investigate the erosive behavior of the engine as well as identify the engine condition. Once 1500 engine oil samples were analyzed, the wear debris was measured in oil including iron, copper, aluminum, lead, tin, silicon, PQ, water content, viscosity, and alkalinity of oil, and the suitable information for analysis was obtained. The findings of this chapter indicate a specific pattern appropriate to the wear debris of oil that can be found by applying fuzzy logic and creating a series of fuzzy rules. Then, using fuzzy logic, it diagnosed and predicted the defects, failures, and conditions of the sugarcane harvester engine. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023
  6. Keywords:
  7. Engine ; Fuzzy logic ; Oil analysis ; Sugarcane harvester
  8. Source: Industrial and Applied Mathematics ; Volume Part F2111 , 2023 , Pages 117-129 ; 23646837 (ISSN)
  9. URL: https://link.springer.com/chapter/10.1007/978-981-19-9909-3_5