A NEW DAMAGE DETECTION METHOD FOR BRIDGE CONDITION ASSESSMENT IN STRUCTURAL HEALTH MONITORING

本研究试图挑战新提出的“状态表示法”(SRM)的建立及其在基于桥梁监测数据的桥梁状态评估中的应用。SRM是一种新的工具，可以为桥梁监测系统中的数据挖掘提供一些思路和算法。诸如桥梁结构的系统的状态可以通过从状态表示方程(SRE)计算的状态变量来获得。采用在支持向量机中起重要作用的核函数方法来求解支持向量机。在SRE计算中，需要将其转化为大规模线性约束问题(LSLCP)。针对LSLCP的求解技术，提出了一种新的兼容算法。在使用开关磁阻电机之前，需要从系统中复杂的响应观测数据中提取系统特征。因此，一种称为频率切片小波变换(FSWT)的新的时频分析工具将能够有力地揭示振动信号特征的变化。与传统的小波变换相比，FSWT产生了五个新的性质。因此，本文提出了一种在信号处理中具有广泛应用价值的新方法。在本文中，还将介绍基础设施系统状态的非参数描述的一般理论，并演示如何将SRM应用于实际问题。

This study tried to challenge the establishment of a newly proposed “State Representation Methodology (SRM)” and its application to bridge condition assessment based on the bridge monitoring data. The SRM is a novel tool that can provide some ideas and algorithms for data mining in the bridge monitoring system. The state of a system such as bridge structure can be obtained by a state variable that calculate from a State Representation Equation (SRE). A Kernel function method which plays an important role in the Support Vector Machines (SVM) is applied to get solutions of the SRE. In the computation of the SRE, it needs to be changed into a Large-Scale Linear Constraint Problem (LSLCP). A new compatible algorithm is therefore proposed for solving technique of the LSLCP. Before using the SRM, it is necessary that the system features need to extract from the complex responses observed data in the system. Consequently, a new time-frequency analysis tool, called Frequency Slice Wavelet Transform (FSWT), will be able to powerfully reveal a change of the characteristics in vibration signal. The FSWT produces five new properties in contrast with the traditional wavelet transform. Therefore, the paper will show the new method that can be used widely in signal processing. In this paper, it will also be introduced a general theory for the non-parametric description of the infrastructure system’s state and will demonstrate how to apply the SRM to practical problems.