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基于动力指纹的结构损伤识别可靠度方法研究

A Study on Reliability Method for Structural Damage Identification Based on Dynamic Fingerprints

【作者】 谭林

【导师】 苏成;

【作者基本信息】 华南理工大学 , 结构工程, 2010, 博士

【摘要】 结构损伤识别是结构健康监测系统的一个重要组成部分,也是目前结构健康监测领域的一个研究热点和难点。在传统的损伤识别方法中,结构损伤可根据确定性结构模型和静动力响应测试数据进行识别,识别结果是确定性的。然而,结构建造和运营以及结构响应的测试往往受到许多不确定因素的影响,导致结构参数和测试参数均具有一定的随机性,这会使结构损伤识别结果出现概率意义下的偏差,产生损伤误判等现象,严重影响损伤识别结果的可靠性。在识别结果可靠性过低的情况下,损伤识别方法会因失去对结构损伤的辨识能力而不再具有实际意义。本文在这一方面作一尝试,在结构可靠度理论和损伤识别动力指纹法辨识原理的基础上,开展基于动力指纹的结构损伤识别可靠度方法研究。本文的主要工作包括:(1)扼要介绍了结构健康监测系统的概念和组成,以及结构损伤识别方法。系统介绍了结构损伤识别的动力指纹法,包括动力指纹法的识别原理和各种动力指纹的优缺点等。对结构损伤识别中的概率分析方法进行了全面的综述。(2)详细介绍了结构可靠度的基本概念,如可靠性、可靠度、极限状态、功能函数、失效概率及可靠指标等,以及常用的结构可靠度计算方法,包括一次二阶矩法、JC法、正态随机变量相关时的可靠度计算方法、响应面法以及蒙特卡罗法等,并讨论了各种方法的优缺点。(3)介绍了平均曲率模态差损伤因子、平均模态应变能变化率和柔度差曲率损伤因子三种动力指纹的计算方法。系统给出了基于动力指纹的结构损伤识别确定性方法,重点提出了基于有限元法和样条拟合技术的损伤程度与动力指纹关系的确定方法,以及基于动力指纹的结构多处损伤程度确定性识别迭代算法。通过一简支梁桥数值算例,检验了所提出方法的正确性和实用性。(4)在考虑测试参数和结构参数变异的情况下,明确给出了结构损伤识别可靠度的严格定义。在此基础上,结合响应面法、蒙特卡罗法等结构可靠度分析方法,以及确定性结构损伤识别动力指纹法,系统提出了一套基于动力指纹的结构损伤识别可靠度方法,包括结构损伤识别可靠度的计算方法以及基于可靠度的结构损伤识别方法两方面,并编制了相应的计算程序。从概率分析的角度提出了动力指纹抗噪性评价和随机参数敏感性分析的新思路。以简支梁桥为例,利用所提出的方法对结构进行了全面的损伤识别统计分析,基于不同的动力指纹获得了损伤程度、损伤识别可靠度、损伤识别精度以及参数噪声水平等因素之间的相互影响规律,并对所研究的动力指纹的抗噪性能以及各种随机参数对损伤识别结果的敏感性进行了分析,检验了所提出的结构损伤识别可靠度方法的正确性和实用性,并得到了有价值的结论。(5)介绍了大跨度拱桥结构损伤的特点及其原因。采用本文提出的基于动力指纹的结构损伤识别可靠度方法,对主跨428m的大跨度拱桥的主跨拱肋损伤识别进行了全面的概率分析。在噪声环境下,计算得到了在给定损伤精度情况下的主跨拱肋损伤识别可靠度,以及在给定损伤识别可靠度情况下的主跨拱肋损伤识别结果分布区间,检验了所提出方法在工程应用方面的有效性。在此基础上,还对大桥主跨拱肋和主跨桥面两个部位的动力指纹的识别能力进行了评价。本文的主要创新点包括:(1)提出了基于有限元法和样条拟合技术的损伤程度与动力指纹关系的确定方法,以及基于动力指纹的结构多处损伤程度确定性识别迭代算法。(2)提出了噪声环境下结构损伤识别可靠度的概念,并给出了明确的定义。在响应面法、蒙特卡罗法等结构可靠度分析方法的基础上,以确定性结构损伤识别动力指纹法作为构造响应面函数的具体实现工具,系统提出了基于动力指纹的结构损伤识别可靠度方法。(3)从概率分析的角度,提出了动力指纹抗噪性评价和随机参数敏感性分析的新思路,更加客观地评价了各种动力指纹的识别能力和各种参数噪声对识别结果的影响程度。

【Abstract】 Structural damage identification is an important component of structural health monitoring system, and is also currently a research area of much interest and importance in field of structural health monitoring system. With the traditional structural damage identification methods, structural damages are identified using deterministic data for the structural model and test results of static and dynamic responses, and the identification outcome is treated as deterministic. However, the construction and operation of a structure and the test data collection are subject to the influence of many uncertain factors, making the model data and experiment data both random. Furthermore, the randomness of parameters will lead to the probability deviations of structural damage identification results, causing possible misjudgment of damage and serious affect on the reliability of damage identification results. When the reliability of the damage identification results is too low, the damage identification methods will fail and become useless.In this dissertation, the study on the dynamic fingerprint-based structural damage identification reliability methods is developed on the basis of structural reliability theory and identification principle of dynamic fingerprint methods. The following research results are achieved in this dissertation:(1) Concepts and composition of structural health monitoring system together with structural damage identification methods are briefly introduced, and then various dynamic fingerprint methods of structural damage identification are systematically summarized, including identification principles of various common dynamic fingerprints as well as advantages and disadvantages of them. In addition, probability analysis methods of structural identification theory are comprehensive reviewed.(2) Some basic concepts of structural reliability are presented in detail, such as reliability, degree of reliability, limit state, performance function, failure probability and reliability index. Moreover, some types of conventional reliability analysis methods are described and their advantages and disadvantages are commented, including first-order second-moment method, JC method, reliability calculation method with normal random variables, response surface method and Monte-Carlo method.(3) Three dynamic fingerprint-based damage identification methods are discussed, including Average Curvature Mode Difference Damage Factor (ACMDDF), Average Modal Strain Energy Change Rate (AMSECR) and Flexibility Difference Curvature Damage Factor (FDCDF). Then deterministic methods of dynamic fingerprint-based structural damage identification are systematically presented. In addition, deterministic method for establishing the relationship between damage extents and dynamic fingerprints based on the finite element method and spline fitting is proposed emphatically and an iterative algorithm of multi damage extents deterministic identification based on dynamic fingerprint is developed. Furthermore, the validity and practicality of the method is shown with a numerical example of simply-supported girder bridge.(4) The concept of structural damage identification reliability is clearly defined for the case when the variations of structural parameters and testing parameters are considered. Based on this concept and structural reliability methods consisted of response surface method and Monte-Carlo method as well as deterministic method of dynamic fingerprint-based structural damage identification, a systematic set of dynamic fingerprint-based structural damage identification methods are proposed and implemented, which consist of calculation method of structural damage identification reliability and reliability-based structural damage identification method. Furthermore, a new approach in view of probability analysis is proposed to dynamic fingerprints anti-noise evaluation and random parameters sensitivity analysis. With simply-supported girder bridge as an example, the comprehensive damage statistic analysis are conducted using the proposed methods, and the interaction between different factors such as damage extent, damage identification reliability, damage identification accuracy and noise level are investigated for different dynamic fingerprints. The anti-noise performance of studied dynamic fingerprints and the sensitivity of damage identification results to various random parameters are also analyzed. The validity and practicality of proposed structural damage identification reliability method is validated and the valuable conclusions are made.(5) Characteristics and mechanisms of structural damages in long-span arch bridge are summarized and analyzed. Then the comprehensive probability analysis of main-span arch rib damage of a long-span arch bridge with a 428m main span length is performed using the proposed dynamic fingerprint-based structural damage identification reliability methods. Under the noise environment, the identification reliability of main-span arch rib damage for a given damage accuracy and the distribution intervals of main-span arch rib damage identification results for a given damage identification reliability are calculated. The validity and practicality of proposed methods on the application of engineering is validated. Furthermore, on the above basis, the dynamic fingerprint identification capability of main-span arch rib and main-span deck are evaluated.The major innovative points of this study are as follows: (1) A deterministic method is developed to relate the damage extents and dynamic fingerprints based on the finite element method and spline fitting, and an iterative algorithm is proposed for identifying extents of multiple damages in a structure based on dynamic fingerprint.(2) The concept of structural damage identification reliability under noise environment is proposed and properly defined. Systematically proposing dynamic fingerprint-based structural damage identification reliability method on the basis of structural reliability methods consisted of response surface method and Monte-Carlo method and with the deterministic structural damage identification dynamic fingerprint method as implementation tools to form the response surface function.(3) A new approach in view of probability analysis is proposed for the dynamic fingerprints anti-noise evaluation and random parameters sensitivity analysis. The identification capability of different dynamic fingerprints and the influence of various parameter noises on identification results are evaluated in a more objective way.

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