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Study on Monitoring Analysis and Time Forecasting of Landslide Based on Fourier Transform and Wavelet Analysis

机译：基于傅里叶变换和小波分析的滑坡监测分析和时间预测研究

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摘要

The monitoring data of landslide displacement are usually disturbed by the impact of rainfall or engineering construction. As a result, the curve of displacement monitoring is always characteristic of step-like. In order to achieve a full understanding of the step-like phenomenon, Fourier transform and wavelet analysis methods were introduced to find out the causes in this study. Firstly, Fourier transform method was used to extract frequency component from the original monitoring data of displacement; secondly, the wavelet transform modulus maxima method was adopted to detect the breakpoint between different frequency components. Based on the detected frequency component and the position of the breakpoint, the quasi-periodic noise could be simulated. Finally, the time-displacement curve without the impact of noise was obtained by subtracting the noise component from the original curve of displacement monitoring. It is suggested that periodic rainfall is the main reason that induces the step-like catastrophic break points in the curve of displacement monitoring. These results provide a reasonable explanation to the occurring of step-like phenomenon in the curve of displacement monitoring and propose a new analysis way for the time forecasting of landslides.
机译：滑坡位移的监测数据通常因降雨或工程建设的影响而受到干扰。结果，位移监测的曲线始终是阶梯状的特征。为了能够完全理解阶梯状现象，引入了傅里叶变换和小波分析方法，以了解本研究中的原因。首先，使用傅里叶变换方法从位移的原始监测数据中提取频率分量;其次，采用小波变换模量最大值法检测不同频率分量之间的断点。基于检测到的频率分量和断点的位置，可以模拟准周期性噪声。最后，通过从位移监测的原始曲线中减去噪声分量来获得没有噪声影响的时间位移曲线。建议，周期性降雨是诱导位移监测曲线中的阶梯状灾难性断裂点的主要原因。这些结果对位移监测曲线中的阶梯状现象的发生方法提供了合理的解释，并提出了一种新的分析方式，用于山体滑坡的时间预测。

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