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Analysis of Tunnel Monitoring Results Based on the Modulus Maxima Method of Wavelet Transform

机译:基于小波变换模极大值法的隧道监测结果分析

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In recent years, the theory and method of wavelet analysis is widely used in signal processing, pattern recognition, data compression, image processing, and quantum physics. Compared with modulus maxima, wavelet packet decomposition and coefficient shrinkage de-noising method of wavelet transform, their advantages and disadvantages are analysed and summarized, and their respective scopes are obtained. The Noissin chosen as the original signal with noise is analysed and de-noised by the modulus maxima method of wavelet transform, meanwhile the usage conditions and key computing parameters are also obtained. Finally, the modulus maxima method of wavelet transform are successfully adopted to de-noised the monitoring results of shield tunnel, the data revised are reliably provided for tunnel healthy diagnosis.
机译:近年来,小波分析的理论和方法被广泛应用于信号处理,模式识别,数据压缩,图像处理和量子物理学中。通过与模极大值,小波包分解和小波变换的系数收缩降噪方法相比较,总结和总结了它们的优缺点,并得出了各自的范围。利用小波变换的模极大值法对被选作有噪声原始信号的Noissin信号进行了分析和去噪,同时获得了使用条件和关键计算参数。最后,成功地采用小波变换的模极大值方法对盾构隧道的监测结果进行消噪,可靠地提供了修正后的数据,用于隧道的健康诊断。

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