
基于形态提升小波的机械状态监测数据压缩研究
Research on machinery condition monitoring data compression based on morphological lifting wavelet transform
In order to solve the problem of mass data transmission that distributed condition monitoring of large-scale electromechanical equipment was faced of, a method on data compression of vibration signal based on lifting wavelet transform and morphological lifting wavelet transform was studied contrastively. For actual floating-point vibration signal, a method on data compression of mechanical vibration signal based on lifting wavelet transform was put forward by taking advantage of wavelet sparse decomposition characteristic. The effects of data compression after threshold were improved greatly through optimum organization of transformed wavelet coefficients and code improvement. To overcome the weak point that the data included much redundant information, a method on data compression based on morphological lifting wavelet transform was proposed for condition monitoring. The pretreatment of network monitoring vibration signal achieved during the process of data compressed transmission by taking advantage of the non-linear characteristic of the morphological filter, then the noise was reduced and the useful component of the signal was reserved. A maximum differential capacity criterion was proposed for selecting the number of decomposition. By comparing these two methods on data compression, the morphological lifting wavelet transform had the advantages of simple calculation, fast analysis and high compression ratio.
形态滤波器 / 提升小波 / 数据压缩 / 机械振动 / 状态监测 {{custom_keyword}} /
morphological filter / lifting wavelet transform / data compression / machinery vibration / condition monitoring {{custom_keyword}} /
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