Abstract
Gear box is one of the most important transmission components in mechanical systems. Fault diagnosis and state monitoring techniques for gear box have been studied for years. But in practical, gear box usually works under varying work conditions which has not been considered in most studies. In this paper, a novel state monitoring method is proposed for monitor gear box work with varying conditions. The vibration signal is de-nosied by morphological filtering. Then gear-mesh frequency band is extracted by wavelet transform. Dimensionless time indexes are used as state monitoring features. A regularization method is proposed to calculate gear tooth health index. Simulate and experiment signal are presented to illustrate the effectiveness of the method. The result indicates that, morphological filtering is an efficient method to de-nosie the vibration signal; wavelet transform can extract the gear-mesh frequency band; gear tooth health index can monitor gear tooth state based on vibration signal.
Highlights
Gear transmission is widely used in rotating machines for its compacter structure and higher transition efficiency compared to other transmission types
EMD (Empirical Mode Decomposition) denoise method [1] has difficult to determine the physical significance of IMF (Intrinsic Mode Function) which restricted its use in application
Morphological filtering is a non-linear filter method based on mathematical morphology
Summary
Gear transmission is widely used in rotating machines for its compacter structure and higher transition efficiency compared to other transmission types. Gear transmission often used in different critical conditions. The important structure and economic status of gear transmission makes it necessary to study its diagnosis and monitoring technologies. The vibration signal based method is the most widely used diagnosis and monitoring technology. Because the signal collected usually contains a lot of noises from varying vibration sources, the de-noise technologies has been discussed and studied widely and profundity. Morphological filtering is a non-linear filter method based on mathematical morphology It decomposes the signal into different physical meaning parts by mathematical morphology change. A novel multiscale and multielement morphological filtering method is proposed to effectively filtering multi types of nosies and well reserve the details of signal characteristics. For gear work in vary conditions, we propose a gear tooth failure diagnosis technology and gear state monitoring method
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