Li Xiaoyan, Ruan Huaining, Chen Zhijian. Identification of Abnormal Attribute for Observed Stress in Foundation Pile Based on Wavelets[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2009, 23(6): 292-295. doi: 10.3969/j.issn.1007-2993.2009.06.006
Citation:
Li Xiaoyan, Ruan Huaining, Chen Zhijian. Identification of Abnormal Attribute for Observed Stress in Foundation Pile Based on Wavelets[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2009, 23(6): 292-295. doi: 10.3969/j.issn.1007-2993.2009.06.006
Li Xiaoyan, Ruan Huaining, Chen Zhijian. Identification of Abnormal Attribute for Observed Stress in Foundation Pile Based on Wavelets[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2009, 23(6): 292-295. doi: 10.3969/j.issn.1007-2993.2009.06.006
Citation:
Li Xiaoyan, Ruan Huaining, Chen Zhijian. Identification of Abnormal Attribute for Observed Stress in Foundation Pile Based on Wavelets[J]. GEOTECHNICAL ENGINEERING TECHNIQUE, 2009, 23(6): 292-295. doi: 10.3969/j.issn.1007-2993.2009.06.006
Wavelet has good localization characteristic in time and frequency domain. Strangeness index of data serial can be calculated simply and conveniently with wavelet to detect stochastic jump value. The detected method is correct and effectual by validating test data. Abnormity attribute can be identified automatically, according to distribution rules of jump value of multi-sensors. It states that identification of abnormality attribute based on wavelet analysis is a novel and valid method.