【作者】 宋廷苏；

【导师】 戴君武；

【作者基本信息】 中国地震局工程力学研究所 ， 防灾减灾工程及防护工程， 2006， 硕士

【摘要】 本文以美国ASCE健康监测的Benchmark模型为对象,利用小波变换分析方法探讨研究了目前结构在线实时损伤识别技术存在的若干基本问题,为结构在线实时损伤识别技术的实用化尝试提供了新的思路。主要工作如下:首先,简要介绍了小波分析的基本理论,包括小波分析的发展、连续小波变换、离散小波变换以及小波变换的快速算法—Mallat算法。其次,针对目前结构实时在线损伤识别研究存在的问题,在ASCE结构健康监测任务组编写的Benchmark模型动力响应计算程序的基础上,修改编制了适用于本文研究目的的数值模拟试验程序。1)修改程序使其可以计算在荷载作用过程中发生突然损伤体系的非线性动力响应,并通过对比分析数值模拟结果,发现王焕定教授提出的高阶单步β(Wang-β)法要明显优于目前最常用的Newmark-β法和Wilsion-θ法;2)改编程序以增加地震动输入下发生突然损伤benchmark模型的动力响应计算功能,使其可以考查不同荷载输入对小波变换损伤识别方法的影响;3)修正了Benchmark源程序中加噪声函数存在的无法准确控制噪声输入水平的问题。大量的数值模拟试验结果表明,对响应加速度信号进行小波变换分析,通过细节信号“尖峰”在时间轴上的位置可以识别系统损伤的时刻,通过“尖峰”的高度可以识别结构损伤的位置。主要结论如下:⑴在线的实时的损伤数值模拟中,结构响应计算应采用高精度的计算方法,如Wang-β法,以获取较高的频率信息。⑵使用离散小波变换的方法进行损伤识别,选取ReverseBior小波效果较好。⑶损伤程度越大,利用小波变换进行损伤识别所需的最低采样频率越小;损伤程度越小,所需的最低采样频率越大。在相同损伤程度下,风荷载作用所需的可识别最低频率,高于地震作用的可识别最低频率。推荐采样频率范围1000～2000Hz。⑷“尖峰”的高度与荷载的强度、损伤程度以及测点(传感器的位置)距损伤位置的距离有关。随着荷载强度的增加,“尖峰”高度增加,随着荷载强度的减小,“尖峰”高度减小。随着损伤程度的增大,“尖峰”高度增大;反之,“尖峰”高度减小。随着测点距损伤位置距离的增加,“尖峰”高度减小;反之,“尖峰”高度增大。⑸实测信号噪声的影响规律为:对于在低荷载强度激励下,微小损伤的识别要求传感器有非常高的精度。在测点离损伤位置很远的情况下,传感器自身的噪声可能将微小损伤信号的“尖峰”淹没;在较大损伤或较强的荷载激励下,噪声的影响则非常小。更多还原

【Abstract】 Taking the ASCE health monitoring Benchmark model as the research object, several basic problems about the wavelet transform method used in real-time online damage identification for structures had been studied in this thesis. A tentative new approach is also developed for the application practice of the real-time online damage identification for structures. The main works are as follows:Firstly, the wavelet analysis theory is introduced briefly, including the development history of wavelet analysis, continuous wavelet transform, discrete wavelet transform and the fast“Mallat algorithm”for wavelet analysis.Secondly, for satisfying the research purpose of this thesis, a numerical simulation program has been developed to fix several critical problems in real-time online damage identification for structures. This program is modified and updated based on the simulation program developed by ASCE Task Group on Health Monitoring to simulate the dynamic response of Benchmark model. That is, the source program is modified and updated to be able to 1) calculate the nonlinear dynamic response of the Benchmark model with“sudden damage”during a certain loading excitation, in which numerical simulation results shows that the high order single-stepβ(Wang-β) method developed by professor Wang Huanding is obviously much accurate in calculation of the nonlinear response than most commonly used other two methods: Newmark-βmethod and Wilsion-θmethod; 2) calculate the dynamic response of the Benchmark model with“sudden-damage”characteristic under earthquake excitations to satisfy the purpose of examining the influence of different type of load excitation to the wavelet transform method used in structural damage identification; 3) rectify the error using of the noise adding function in the source program to provide accurate input noise level for examining the noise effects in wavelet analysis for damage identification.Mounts of numerical simulation test results indicates that, through carrying on wavelet transform to the time history of the response acceleration, the accurate damage instant can be read from the appearing of the spike in the time axis as well as the damage location can be predicted from the height of related spikes.Following conclusions are obtained through abovementioned studies: (1) In numerical simulations of the real-time online damage identification for structures, high accuracy method such as Wang-βmethod should be used in order to obtain high frequency information from structural responses.(2) The ReverseBior wavelet should be used as the mother wavelet since it’s much better than others when discrete wavelet transform is used for damage identification.(3) Generally, the severer of the structural damage, the lowest identifiable sampling frequency will be relatively lower by using the wavelet transform. As well, the slighter of the structural damage, the lowest identifiable sampling frequency will be much higher. At the same damage level, the lowest identifiable sampling frequency under wind loading is relatively higher than that of under earthquake in damage identification simulation. Here, a reasonable sampling frequency range from 1000Hz to 2000Hz is suggested to be used in wavelet analysis.(4) The height of the identified signal spike is strongly related with the load intensity, the severity of damage as well as the distance from the measuring point (sensor position) to the damage location. With the increase of the excitation intensity, the height of the spike increases; With the decrease of the load intensity, the height of the spike decreases; With the increase of severity of the structural damage, the height of the spike increases, Contrariwise, the spike height decreases; With the increase of the distance from the measuring point to the damage location, the height of the spike decreases, Contrariwise, the spike height increases.(5) The noise effects of the measuring signal are: for identifying of the minus damage at a relatively lower excitation level, the sensors with very high precision are required. If the distance from the measuring point to the damage location is relatively large, the spike representing the minus damage might be submerged by the noise. If the damage is quite severe or the excitation level is quite large, the influence of the noise to the identified spike will be very slight.更多还原