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Abstract
Gearbox condition monitoring (CM) plays a significant role in ensuring the operational reliability and efficiency of a wide range of critical industrial systems such as wind turbines and helicopters. Accurate and timely diagnosis of gear faults will improve the maintenance of gearboxes operating under sub-optimal conditions, avoid excessive energy consumption and prevent avoidable damages to systems. This study focuses on developing CM for a multi-stage helical gearbox using airborne sound. Based on signal phase alignments, Modulation Signal Bispectrum (MSB) analysis allows random noise and interrupting events in sound signals to be suppressed greatly and obtains nonlinear modulation features in association with gear dynamics. MSB coherence is evaluated for selecting the reliable bi-spectral peaks for indication of gear deterioration. A run-to-failure test of two industrial gearboxes was tested under various loading conditions. Two omnidirectional microphones were fixed near the gearboxes to sense acoustic information during operation. It has been shown that compared against vibration based CM, acoustics can perceive the responses of vibration in a larger areas and contains more comprehensive and stable information related to gear dynamics variation due to wear. Also, the MSB magnitude peaks at the first three harmonic components of gear mesh and rotation components are demonstrated to be sufficient in characterizing the gradual deterioration of gear transmission. Consequently, the combining of MSB peaks with baseline normalization yields more accurate monitoring trends and diagnostics, allowing the gradual deterioration process and gear wear location to be represented more consistently.
Highlights
In industrial applications, gearboxes are widely used for transmitting power from one mechanical system to another
4.1 Baseline Acoustic Signatures To confirm that the acoustic measurements contain sufficient information about dynamics of the gears, the spectra of the acoustic signals were compared with that of the vibration signals
It is proven that the acoustic signals measured in such a remote way are adequate and suitable for the condition monitoring of the gearboxes
Summary
Gearboxes are widely used for transmitting power from one mechanical system to another. The progressive material loss from contacting tooth surfaces due to a combination of rolling and sliding motion under mixed or boundary lubrication conditions, is one of the major faults of gears This directly results in strong vibration and noise, dynamic transmission error, and power transmission deficiency [1,2,3]. Gu et al [11] developed an acoustic monitoring method to detect tappet clicks, misfiring and injection timing faults in diesel engines with the use of a discrete wavelet transform signal processing method. Following this pioneering work, Ball et al [12] evaluated the feasibility of using acoustics for fault detection in electrical motors with the discrete wavelet transform and averaging techniques.
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