• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.7
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• pp.665-671
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• 2015

The performance of fault diagnostics for a planetary gearbox depends on vibration modulation characteristics, which can vary with manufacturing & assembly tolerance, and load condition. In this paper, a fault diagnostics technique that considers vibration modulation characteristics is proposed for the effective fault detection of planetary gearboxes in wind turbines. For identifying the vibration modulation characteristics in practice, re-sampled vibration signals are processed with narrow band-pass filters. Thereafter, the optimal position of the vibration extraction window is identified for effective detection of faulty signals under the varying vibration modulation characteristics. The proposed diagnostics technique makes it possible to perform robust diagnostics of the planetary gearbox with regard to the changeable vibration modulation effect. For demonstrating the proposed fault diagnostics technique, a 2-kW WT testbed is designed with two DC motors and gearboxes. A faulty gear with partial tooth breakage is machined and assembled into the gearbox.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.6
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• pp.447-454
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• 2013

A model-based method is proposed to diagnose the gear crack in the gearbox under variable loading condition with the objective to apply it to the wind turbine CMS(Condition Monitoring System). A simple test bed is installed to illustrate the approach, which consists of motors and a pair of spur gears. A crack is imbedded at the tooth root of a gear. Tachometer-based order analysis, being independent on the shaft speed, is employed as a signal processing technique to identify the crack through the impulsive change and the kurtosis. Lumped parameter dynamic model is used to simulate the operation of the test bed. In the model, the parameter related with the crack is inversely estimated by minimizing the difference between the simulated and measured features. In order to illustrate the validation of the method, a simulated signal with a specified parameter is virtually generated from the model, assuming it as the measured signal. Then the parameter is inversely estimated based on the proposed method. The result agrees with the previously specified parameter value, which verifies that the algorithm works successfully. Application to the real crack in the test bed will be addressed in the next study.