Abstract

This paper deals with an experimental investigation of fault diagnosis in a multistage gearbox under transient loads. An induction motor drives the multistage gearbox, which is connected to a DC generator for loading purpose. The signals studied are the vibration transients, recorded from an accelerometer fitted at the tail-end bearing of the gearbox; and the current transients drawn by the induction motor. Three defective cases and three transient load conditions are investigated. Advanced signal processing techniques such as discrete wavelet transform (DWT) and a corrected multiresolution Fourier transform (MFT) are applied to investigate the vibration and current transients. It is observed from the vibration transients that the load removal is a high-frequency phenomenon. With increase in defect severity, not only the defective gear mesh frequency gains energy, but also large impact energy appears in low-frequency regions. Whereas in the current transients, though load removal is a low-frequency phenomenon, a very small transient is observed at high-frequency regions for defective gears. With increase in defect severity, energy is distributed to the sidebands of the gear mesh frequency across supply line frequency. A statistical feature extraction technique is proposed in order to find a trend in detection of defects. A condition monitoring scheme is devised that can facilitate in monitoring vibration and current transients in the gearbox with simultaneous presence of transient loads and defects.

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