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Application Of Wavelet Transform On Structural Damage Identification

Posted on:2007-03-14Degree:MasterType:Thesis
Country:ChinaCandidate:B L LinFull Text:PDF
GTID:2132360182471861Subject:Structural engineering
Abstract/Summary:PDF Full Text Request
In view of complexity and incompleteness of civil engineering structures, the sudden variation information is detected using self-adaptiveness of time-frequency window in wavelet analysis to identify damage in structures. For the beam structure, frame structure and tall transmission tower, the damage and its identification are simulated numerically, the damage precaution, positioning and quantifying are studied for wavelets-transform-based damage identification. The main subjects are summarized as follows:(1) The properties of dynamic parameters are investigated when damage occurs in structure. Damages in cantilever beam and tall transmission tower damage identification are studied by numerical methods and the structural damage precaution can be achieved on line. Aimed at noise polluted for data on site, a kind of noise cancellation method based on wavelet analysis is studied; the results show that precision can be increased.(2) A damage identification method is proposed by wavelet transform using spatial field information, which is verified by the numerical simulation for uniform and non-uniform cantilever beams, The results show that the space domain information wavelet transform can reveal structural damage location very efficiently. Then the proposed method is applied to damage detection of tall transmission tower.(3) The Lipschitzs exponent estimated by the wavelet coefficients is used as a useful indicator of the crack depth. The displacement of a cracked simple-supported beam is analyzed with CWT by using a Mexican-hat fundamental wavelet; the Lipchitz exponent variation is researched with the crack depth, crack location, load position and load magnitude. The proposed method is applied to damage degree detection of tall transmission tower.
Keywords/Search Tags:Wavelets transform, Damage detection, Lipschitz, Transmission tower, Tamage precaution, Health monitoring, White noise
PDF Full Text Request
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