Abstract
The reason behind the induction motor health monitoring is Induction motor especially three phase induction motor plays vital role in the industry due to their advantages over other electrical motors which is lesser in cost. Therefore, there is a strong demand for their reliable and safe operation. If any fault and failures occur in the motor it can lead to excessive downtimes and generate great losses in terms of revenue and maintenance. Therefore, an early fault detection is needed for the protection of the motor. In the current scenario, the health monitoring of the induction motor are increasing due to its potential to reduce operating costs, enhance the reliability of operation and improve service to the customers. The health monitoring of induction motor is an emerging technology for online detection of incipient faults. The on-line health monitoring involves taking measurements on a machine while it is in operating conditions in order to detect faults with the aim of reducing both unexpected failure and maintenance costs. The best way to avoid machinery failures is to know they’re coming. This is precisely what condition monitoring enables. Condition monitoring is the process of determining the condition of machinery while in operation. The three major steps in a condition monitoring system are data acquisition, data processing, and data assessment for maintenance decision-making and fault diagnostics and prediction. Successfully implementing a condition monitoring programme enables the repair of problem components prior to failure. This not only helps reduce the possibility of catastrophic failure, but also allows you to order parts in advance, schedule manpower, and plan other repairs during the downtime. In the present paper, a comprehensive survey of induction machine faults, diagnostic methods and future aspects in the health monitoring of induction motor has been discussed.
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Siddiqui, K.M., Sahay, K., Giri, V.K.: Health monitoring and fault diagnosis in induction motor-a review
Machine Learning Documentation Initiative-Kenneth Chu and Claude Poirier
Machine Condition Monitoring and Fault Diagnostics
Chris, K.: Mechefske Queen’s University
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Hiremath, P.S., Ram B., K., Patil, S.M., Sabarish, V., Biradar, P., Arunkumar, S. (2020). Machine Health Monitoring of Induction Motors. In: Auer, M., Ram B., K. (eds) Cyber-physical Systems and Digital Twins. REV2019 2019. Lecture Notes in Networks and Systems, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-23162-0_5
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DOI: https://doi.org/10.1007/978-3-030-23162-0_5
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