结构健康监测
水准点(测量)
任务(项目管理)
计算机科学
领域(数学)
有限元法
数据挖掘
噪音(视频)
更安全的
工程类
结构工程
系统工程
人工智能
数学
图像(数学)
纯数学
地理
计算机安全
大地测量学
作者
E. A. Johnson,Heung‐Fai Lam,Lambros S. Katafygiotis,J. L. Beck
出处
期刊:Journal of Engineering Mechanics-asce
[American Society of Civil Engineers]
日期:2004-01-01
卷期号:130 (1): 3-15
被引量:385
标识
DOI:10.1061/(asce)0733-9399(2004)130:1(3)
摘要
Structural health monitoring (SHM) is a promising field with widespread application in civil engineering. Structural health monitoring has the potential to make structures safer by observing both long-term structural changes and immediate postdisaster damage. However, the many SHM studies in the literature apply different monitoring methods to different structures, making side-by-side comparison of the methods difficult. This paper details the first phase in a benchmark SHM problem organized under the auspices of the IASC–ASCE Structural Health Monitoring Task Group. The scale-model structure adopted for use in this benchmark problem is described. Then, two analytical models based on the structure—one a 12 degree of freedom (DOF) shear-building model, the other a 120-DOF model, both finite element based—are given. The damage patterns to be identified are listed as well as the types and number of sensors, magnitude of sensor noise, and so forth. MATLAB computer codes to generate the response data for the various cases are explained. The codes, as well as details of the ongoing Task Group activities, are available on the Task Group web site at 〈http://wusceel.cive.wustl.edu/asce.shm/〉.
科研通智能强力驱动
Strongly Powered by AbleSci AI