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Condition Monitoring of the Starter Motor Using Sound Signals and Fuzzy Logic
Journal: Journal of Automotive and Applied Mechanics
Issue: Journal of Automotive and Applied Mechanics (Volume: 4, Issue: 1)
Author: Rashid Nasir Abadi , Mohammad Reza Asadi , Amir Hossein Zaeri
Keywords : Condition Monitoring , Sound Signals , Starter Motor , Fuzzy Logic
Abstract:

Today, with technology advances, machinery and industrial equipment are getting more complicated day by day, and parallel to this complexity, they become more sensitive and require more attention, subsequently; since damage to them and their downtime may cost a lot. This study attempts to help increase the accuracy of predicting the defects of the starter motor using various data mining techniques, and finally introduce the best data mining technique which leads to the highest accuracy. To this end, firstly, a system was designed to gather data, then using a small microphone, vibration data have been received, and finally, the data were processed. According to this research the overall results can be summarized as: Detecting the condition of the starter motor is possible through comparing the change domain in the graphs which present different conditions of the starter motor using sound signals in the frequency domain, also the use of the statistical parameters of the sound spectra, is a simple and practical method for extracting the features of the spectrum and the overall classification compliance degree was 91/6 percent which is acceptable from the engineering perspective.

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