Application of time-scale Gaussian wavelet based fast algorithm for vibration transients detection
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This paper discusses a new method for vibration signal analysis using Gaussian wavelet, which possesses the optimal time frequency localisation property. A flexible, efficient and accurate method of Gaussian wavelet filter design is proposed. Based on this fast algorithm, time-scale analyses with the shifting of starting frequency in either low or high frequency orientation are achieved for general analysis, while finer frequency scale decomposition is used for detailed analysis. The effects of shifting starting-frequency in both orientations, together with finer scale analysis, can give an almost arbitrary partitioning of the time-scale plane. Thus all transients can be represented with time information. Furthermore, the significant and natural frequencies can be monitored in the time domain. An example of the application is also demonstrated with the vibration signal measured at a machine spindle nose. When signatures corresponding to certain operation status are recognised by general and detailed analyses, real-time fault detection or condition monitoring can be implemented with this algorithm.