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首页> 外文期刊>Advances in Mechanical Engineering >The Optimum Wavelet Base of Wavelet Analysis in Coal Rock Microseismic Signals
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The Optimum Wavelet Base of Wavelet Analysis in Coal Rock Microseismic Signals

机译：煤岩微震信号中小波分析的最优小波基

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摘要

Coal rock rupture microseismic signal is characterized by time-varying, nonstationary, unpredictability, and transient property. Wavelet transform is an important method in microseismic signals processing. However, different wavelet bases yield different results when analyzing the same signal. To study the comparability of different wavelet bases in analyzing microseismic signals, the current paper uses the microseismic signals released from coal rock bursting as the research subject. Through the analysis of the properties of commonly used wavelet basis functions and the characteristics of coal rock microseismic signals, the current study found that Coiflet and Symlet wavelets are suitable for analyzing coal rock microseismic signals. Sym 8 and Coif 2 wavelets were found to be suitable for analyzing and denoising coal rock microseismic signals. After Sym 8 wavelet denoising, signal-to-noise ratio (SNR) and the root mean square error were 30.4184 and 1.3109E - 07, respectively. After Coif 2 wavelet denoising, the SNR and the root mean square error values were 35.2176 and 1.0312E - 07, respectively. The results will aid in the analysis and extraction of coal rock microseismic signals.
机译：煤岩破裂微震信号具有时变，不平稳，不可预测和瞬变特性。小波变换是微震信号处理中的一种重要方法。但是，在分析同一信号时，不同的小波基会产生不同的结果。为了研究不同小波基在微震信号分析中的可比性，本文以煤岩爆破释放的微震信号为研究对象。通过对常用的小波基函数特性和煤岩微震信号特征的分析，发现目前的Coiflet和Symlet小波适用于分析煤岩微震信号。发现Sym 8和Coif 2小波适用于分析和去噪煤岩微地震信号。 Sym 8小波去噪后，信噪比（SNR）和均方根误差分别为30.4184和1.3109E-07。在Coif 2小波去噪之后，SNR和均方根误差值分别为35.2176和1.0312E-07。研究结果将有助于分析和提取煤岩微震信号。

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