Abstract
Since the vibration signals of gearbox are non-linear and non-stationary, it is difficult to accurately evaluate the working conditions. Therefore, a fault feature extraction technique based on intrinsic characteristic-scale decomposition (ICD) and multi-scale entropy (MSE) is presented in this paper. The measured signals are firstly decomposed into a series of product components (PCs) by ICD. Secondly, the main product component is selected, and then MSE is used to extract the feature vectors from the selected PCs. Finally, the obtained feature vectors of gearbox with different scale factors are adopted as inputs of support vector machine (SVM) to fulfill the fault patterns identification. The superiority of the proposed technique is verified through comparing with three other methods.
Highlights
Rotating machines are playing an important role in the industry field and widely used in automatics, helicopters, railways and transportations, high speed, large load and other conditions can lead to its high damage probability
intrinsic characteristic-scale decomposition (ICD) can self-adaptively decompose a multi-component signal into a small set of product components (PCs), each of which is the product of an amplitude envelope signal and a purely frequency modulated signal [13]
The feature extraction method based on ICD and Multi-scale entropy (MSE) is proposed in this paper, it can be described as follows: 1) The vibration signals are sampled by acceleration sensors at a certain sampling frequency under different working conditions
Summary
Rotating machines are playing an important role in the industry field and widely used in automatics, helicopters, railways and transportations, high speed, large load and other conditions can lead to its high damage probability. The commonly used time-frequency analysis methods are empirical mode decomposition (EMD) [6,7,8] and local mean decomposition (LMD) [9,10,11]. Inspired by the sifting process of LMD and ITD, intrinsic character-scale decomposition (ICD), a new self-adaptive method is proposed in the document [13]. In this paper., MSE is used as feature extractor Based on the above analysis, the demodulation methods LMD and MSE are combined and applied to the gearbox. A FEATURE EXTRACTION METHOD BASED ON ICD AND MSE FOR GEARBOX. The feature extraction procedure based on LMD and MSE is proposed.
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