Continuous Acoustic Monitoring of Electrical Machines; Processing Signals from USB Microphone & Mobile Smartphone Sensors Detecting DC Motor Controller Fault

Grebenik, Jarek and Bingham, Chris and Srivastava, Saket (2018) Continuous Acoustic Monitoring of Electrical Machines; Processing Signals from USB Microphone & Mobile Smartphone Sensors Detecting DC Motor Controller Fault. In: 5th International Conference on Control, Decision & Information Technologies (CoDIT) 2018, 10/04/18 - 13/04/18, Thessaloniki, Greece.

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Continuous Acoustic Monitoring of Electrical Machines; Processing Signals from USB Microphone & Mobile Smartphone Sensors Detecting DC Motor Controller Fault
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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive

Abstract

Transient current instability is one of the most common faults evident in Pulse Width Modulation (PWM) controlled brushless DC motors. This paper explores the under-developed field of real-time acoustic diagnostics for electrically based faults using consumer grade sensors. Current instabilities produce an audible torque transient on the motor, easily detectable using consumer acoustic sensors; a USB microphone and smartphone in this case. Two time-frequency signal processing techniques, Wavelet Packet Transform (WPT) and Empirical Mode Decomposition (EMD), are used to isolate information pertaining to the fault and are assessed for computational performance. This gives four processed signals to search for instabilities using a peak finding technique. We then compare the performance of each method. With the USB microphone WPT signal correlating the best results (93%), a simplistic logarithmic predictive model is used to estimate the durations for the next experimental run, in real-time. The results prove that readily accessible and affordable consumer acoustic sensors can be used for real-time fault diagnostics with a high degree of accuracy.

Keywords:acoustic; electric; electrical; fault; detection; diagnosis; smartphone; consumer; microphone; motor; real-time; online; signal processing; wavelet packet transform; WPT; empirical mode decomposition; EMD; time-frequency analysis
Subjects:H Engineering > H360 Electromechanical Engineering
H Engineering > H661 Instrumentation Control
H Engineering > H100 General Engineering
H Engineering > H341 Acoustics
Divisions:College of Science > School of Engineering
ID Code:32000
Deposited On:20 Oct 2018 20:44

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