桥(图论)
方位(导航)
加速度
结构工程
计算机科学
贝叶斯概率
环境科学
工程类
人工智能
物理
医学
经典力学
内科学
作者
Eugene J. O’Brien,Simon Wilson,Jennifer Keenahan,Yifei Ren
标识
DOI:10.1142/s0219455424500408
摘要
This paper presents a new way to determine road profile and detect bridge damage using accelerations from a fleet of passing vehicles. Using off-bridge data, a Bayesian approach updates estimates of the road profile and vehicle properties. The profile elevations and vehicle properties are shown to be insensitive to random noise in acceleration measurements. On-bridge data, with recently updated vehicle properties, are used to estimate bridge damage. Bearing damage and local crack damage in a bridge are simulated. For bearing damage, the results show that this method can quantify the damage level of a bearing and infer other bridge properties. For local crack damage, the levels and the location of the damage are inferred from the simulated measurements.
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