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Application of Wavelet Transform and Kalman Filtering Based GM(1,1) Model in Analyzing Settlement Deformation of High-Speed Railway Tunnels
(1 Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004; 2 College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004; 3 Guangxi Scientific Experiment Center of Mining, Metallurgy and Environment, Guilin University of Technology, Guilin 541004; 4 Guangxi Zhuang Autonomous Region Surveying and Mapping Geographic Information Product Quality Inspection Station, Nanning 530023)
Abstract Although the settlement deformation of high-speed railway tunnels is not high, it is possible that a settle? ment curve may not reflect actual settlement deformation due to random noise interference. An RLG denoising method combining a wavelet transform with a Kalman filter is put forward that has the functions of noise-related interference removal and multiple resolution analysis by wavelet transform, and also has the advantages of linear unbiased minimum variance estimation to unknown signals by Kalman filtering. By applying the GM(1,1) model to analyze the data after denoising, it is detemined that the GM(1,1) model combining the wavelet transform and Kalman filtering is higher in precision than that of the GM(1,1) model based only on Kalman filtering and can be used for settlement analysis in high-speed railway tunnels.
Abstract：
Although the settlement deformation of high-speed railway tunnels is not high, it is possible that a settle? ment curve may not reflect actual settlement deformation due to random noise interference. An RLG denoising method combining a wavelet transform with a Kalman filter is put forward that has the functions of noise-related interference removal and multiple resolution analysis by wavelet transform, and also has the advantages of linear unbiased minimum variance estimation to unknown signals by Kalman filtering. By applying the GM(1,1) model to analyze the data after denoising, it is detemined that the GM(1,1) model combining the wavelet transform and Kalman filtering is higher in precision than that of the GM(1,1) model based only on Kalman filtering and can be used for settlement analysis in high-speed railway tunnels.
GAO Hong- 1,
3,
4 Wen-Hong-Yan- 1 etc
.Application of Wavelet Transform and Kalman Filtering Based GM(1,1) Model in Analyzing Settlement Deformation of High-Speed Railway Tunnels[J] MODERN TUNNELLING TECHNOLOGY, 2016,V53(4): 84-89
2016, Vol. 53 