Modares Mechanical Engineering

Modares Mechanical Engineering

Polymer Gear Fault Detection Based on Audio Signal and Wavelet Packet Transform

Document Type : Original Research

Authors
Islamic Azad University, Shiraz Branch
Abstract
Gears are a very important part of mechanical equipment in industry. Due to the fact that in mechanical processes, the teeth are subjected to long-term load, the surface of their teeth is usually rusty, worn out and even broken. Timely fault detection cannot only increase the life cycle of the gears, however it can even prevent property losses and losses due to breakdowns. Therefore, it is necessary to monitor and diagnose the health of the gears to ensure the normal operation of the invaluable machines in industry. In this research, fault detection in polymer gears using audio signal is considered as a non-contact inspection method. Sound signals were recorded from 50 pairs of gears in normal condition, worn teeth and broken teeth at two speeds of 66 and 99 rpm. In the following, using wavelet packet transformation (WPT), the sound signal is analyzed in the time-frequency domain and 12 statistical features are extracted from the 16 coefficients of the fourth level of WPT. In order to study the performance of the fault detection algorithm, four classifications of linear discriminant analysis, K-nearest neighbor, decision tree and support vector machine have been used. The values of accuracy, true positive rate, true negative rate, positive predictive value, negative predictive value, geometric-mean, F1 score, and Matthews correlation coefficient have shown that by using WPT, a significant distinction can be found between normal and faulty gears. Therefore, the proposed method is a suitable approach for timely error detection of polymer gears used in mechanical equipment.
Keywords

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