基于小波变换和粒子群优化的车用桥梁结构裂纹识别方法

Q2 Physics and Astronomy Advances in Acoustics and Vibration Pub Date : 2013-06-15 DOI:10.1155/2013/634217
Hakan Gökdağ
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引用次数: 2

摘要

本文提出了一种承载移动车辆的桥梁型结构的裂缝识别方法。该桥梁被建模为欧拉-伯努利梁,在梁的几个点上存在开缝。车辆采用半车模式。采用Newmark-Beta法求解了梁-车系统的耦合方程,得到了梁的动力响应。利用这些和参考位移,导出了目标函数。通过求解优化问题确定裂纹的位置和深度。为此,采用了一种鲁棒进化算法——粒子群优化算法(PSO)。为了提高该方法的性能,利用离散小波变换(DWT)的多分辨率特性对测量位移进行去噪。结果表明,在噪声干扰为5%的情况下,该方法仍能检测出深度比为0.1的小裂纹。
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A Crack Identification Method for Bridge Type Structures under Vehicular Load Using Wavelet Transform and Particle Swarm Optimization
In this work a crack identification method is proposed for bridge type structures carrying moving vehicle. The bridge is modeled as an Euler-Bernoulli beam, and open cracks exist on several points of the beam. Half-car model is adopted for the vehicle. Coupled equations of the beam-vehicle system are solved using Newmark-Beta method, and the dynamic responses of the beam are obtained. Using these and the reference displacements, an objective function is derived. Crack locations and depths are determined by solving the optimization problem. To this end, a robust evolutionary algorithm, that is, the particle swarm optimization (PSO), is employed. To enhance the performance of the method, the measured displacements are denoised using multiresolution property of the discrete wavelet transform (DWT). It is observed that by the proposed method it is possible to determine small cracks with depth ratio 0.1 in spite of 5% noise interference.
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期刊介绍: The aim of Advances in Acoustics and Vibration is to act as a platform for dissemination of innovative and original research and development work in the area of acoustics and vibration. The target audience of the journal comprises both researchers and practitioners. Articles with innovative works of theoretical and/or experimental nature with research and/or application focus can be considered for publication in the journal. Articles submitted for publication in Advances in Acoustics and Vibration must neither have been published previously nor be under consideration elsewhere. Subject areas include (but are not limited to): Active, semi-active, passive and combined active-passive noise and vibration control Acoustic signal processing Aero-acoustics and aviation noise Architectural acoustics Audio acoustics, mechanisms of human hearing, musical acoustics Community and environmental acoustics and vibration Computational acoustics, numerical techniques Condition monitoring, health diagnostics, vibration testing, non-destructive testing Human response to sound and vibration, Occupational noise exposure and control Industrial, machinery, transportation noise and vibration Low, mid, and high frequency noise and vibration Materials for noise and vibration control Measurement and actuation techniques, sensors, actuators Modal analysis, statistical energy analysis, wavelet analysis, inverse methods Non-linear acoustics and vibration Sound and vibration sources, source localisation, sound propagation Underwater and ship acoustics Vibro-acoustics and shock.
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