
Experimental comparison of gearbox fault detection methods using acoustic and vibration signals
For the past three decades, condition monitoring methods used for gearbox applications mainly rely on using vibration signals obtained from vibration sensors attached to the gearbox system. Although the use of vibration signals has been very successful in providing accurate gearbox
fault diagnosis for various fault types, the requirement for contact vibration sensors may restrict the sensor placement, such as in the situation when there are gearbox areas directly exposed to moving components, high temperature or harsh chemicals. The work presented in this paper experimentally
investigates an alternative use of non-contact acoustic sensors for detection of gearbox faults, since acoustic signals generally contain useful information about dynamic states of the gearbox system. An experimental comparative study for evaluating the effectiveness of utilizing either vibration
or acoustic signals for gear fault diagnostics is performed. An experimental gearbox test rig with the broken tooth fault type is constructed with accelerometers and a microphone that acquire vibration and acoustic signals from the operating gearbox. The noise that contaminates the raw acoustic
and vibration signals is filtered by using Time Synchronous Averaging (TSA) Method to remove the asynchronous signal components for improving the accuracy of fault diagnosis. Furthermore, the frequency domain analysis of both vibration and acoustic signals is performed to identify the difference
between the healthy and faulty gearbox systems. The experimental results have shown that the frequency sidebands that indicate the faults in the gearbox can be clearly identified from acoustic signals, similar to those observed from vibration signals. The results demonstrate that acoustic
signals can also provide a reliable fault diagnostic information compared to the commonly used vibration signals, hence providing an alternative solution for gear fault detection.
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Document Type: Research Article
Affiliations: The University of Nottingham Ningbo China, Department of Mechanical, Materials and Manufacturing Engineering, People's Republic of China
Publication date: 07 December 2017
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