Detection of faults in a gearbox is a first and foremost step before diagnostic and prognostic operations are performed. This paper proposes a novel gearbox fault detection and feature extraction technique. The proposed method adaptively filters the vibration signals emanating from a gearbox. A bandpass filter is designed and optimized through particle swarm optimization (PSO) to maximize kurtosis as an objective function. Gearbox health-related features are extracted from the filtered signals using second-order transient analysis. The method is validated on experimental data collected from a running gearbox in healthy and faulty conditions. The proposed method has successfully identified the faulty conditions inside the gearbox.
Fault Diagnosis of Gearbox Using Particle Swarm Optimization and Second-Order Transient Analysis
Contributed by the Technical Committee on Vibration and Sound of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received May 12, 2016; final manuscript received November 21, 2016; published online February 22, 2017. Assoc. Editor: Philippe Velex.
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Hussain, S. (February 22, 2017). "Fault Diagnosis of Gearbox Using Particle Swarm Optimization and Second-Order Transient Analysis." ASME. J. Vib. Acoust. April 2017; 139(2): 021015. https://doi.org/10.1115/1.4035379
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