Frequent failure of the conveyor system gearbox can significantly affect the reliability of rotating equipment. Ultimately, early detection of faults in a gearbox is a key parameter in control and maintenance to avoid catastrophic equipment failure. Specifically, intelligent tools are widely implemented in machine condition monitoring for data analysis and data interpretation. This is of major benefit in ensuring that maintenance of equipment is done in a timeous manner to avoid downtimes and loss of production which could affect customer satisfaction. The purpose of this study is to carry out a desktop survey of the application of Fuzzy logic systems in condition monitoring of a conveyor gearbox. The reviewed studies revealed a prominent use of fuzzy logic systems in gearbox condition monitoring for improving the efficiency and effectiveness of the conveyor system. Although most recent studies focused more on vibration condition monitoring due to the ease of simulating vibration data and the simplicity of diagnosing rotating systems through vibrations, other studies have highlighted the potential and reliability of fuzzy logic systems in oil condition monitoring. However, due to the difficulty of simulating oil analysis data and the limited oil data, fewer studies have been conducted on gearbox fault diagnosis using oil analysis. Therefore, it is recommended that the use of fuzzy logic systems based on oil condition monitoring should be conducted especially for conveyor equipment in freight operation which has not been thoroughly considered in many studies. Also, a study in which various fuzzy logic training methods are compared can be done to explore their suitability in gearbox oil condition monitoring.
A Survey of Fuzzy Logic Systems in Condition Monitoring of Conveyor Gearbox
2022-05-25
461345 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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