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

本研究试图挑战一种新提出的“状态表示法”的建立及其在桥梁监测数据基础上的桥梁状态评估应用。SRM是一种新型的数据挖掘工具，为桥梁监测系统中的数据挖掘提供了一些思路和算法。桥梁结构等系统的状态可以通过状态表示方程（SRE）计算出的状态变量来获得。采用支持向量机中的核函数方法求解SRE。在SRE的计算中，需要将其转化为一个大规模线性约束问题（LSLCP）。为此，提出了一种新的相容算法用于求解LSLCP问题。在使用SRM之前，需要从系统的复杂响应观测数据中提取系统特征。因此，一种新的时频分析工具，称为频率切片小波变换（FSWT），将能够有力地揭示振动信号的特征变化。与传统小波变换相比，FSWT具有五个新的性质。因此，本文将展示新的方法，可以广泛应用于信号处理。在本文中，它还将介绍一个非参数描述的基础设施系统的状态的一般理论，并将演示如何将SRM应用到实际问题。

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.