偏转(物理)
桥(图论)
结构工程
方位(导航)
加速度
轴
缩小
歪斜
工程类
计算机科学
物理
人工智能
光学
内科学
电信
经典力学
程序设计语言
医学
作者
Eugene J. O'Brien,Daniel McCrum,Shuo Wang
标识
DOI:10.1142/s0219455423400035
摘要
This paper introduces a new bridge damage indicator, the moving reference influence function (MRIF), to detect bridge bearing damage using deflections inferred from vehicle accelerations. Recently, vehicle acceleration has been used to find the apparent profile (AP) of a bridge when a vehicle passes. This AP consists of bridge profile elevations and bridge deflection components. To describe the relationship between these deflection components and load, a MRIF is proposed for the first time in this paper. An error minimization process is used to find the MRIF and the road surface profile on the bridge. The vehicle acceleration signals used in the paper are assumed to be collected from a partially instrumented vehicle fleet. In the fleet, only the first axle acceleration is collected from each vehicle. To simplify the minimization process, both the MRIF and the bridge profile are represented by kernel density functions. The results show that the bridge profile can be accurately obtained and that bridge bearing damage can be identified from the MRIF. Both area and skewness of the MRIF are damage sensitive and can be used together to find the location and severity of bridge bearing damage.
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