scholarly journals Real-Time Data Acquisition and Structural Health Monitoring System

2016 ◽  
Author(s):  
Akbar Eslami ◽  
Graham Harrison, EIT ◽  
Mark Long
Author(s):  
Xueshan Liu ◽  
Xiaohu Chen ◽  
Jianting Zhou

<p>Rail transit bridges in Chongqing are of considerably complexed structure and enormous scale, thus even a minor impairment of the bridge structural performance could cause significant consequences in the daily operation of rail transit systems. To answer the realistic needs and requests brought up by the rail transit bridges, this paper introduces a framework of structural health monitoring system that is based on Internet of Things (IoT) and intelligent cloud platform. The system is designed to improve the safety of bridges by performing real-time intelligent acquisition and information transmission on subjects such as natural environment, stress status of the bridge structures, status of trains operation, and etc. The system realizes a series of functions: reception and storage of real-time information of the structure’s behavior, remote monitoring, early warning, and etc. Those functions empower the decision-maker to act more efficiently and more effectively in different scenarios, both at management, maintenance and trains operational levels.</p>


Author(s):  
Isaac Farreras-Alcover ◽  
Jacob Egede Andersen ◽  
Preston Vineyard

The Governor Mario M. Cuomo Bridge, also known as the New NY Bridge is a twin cable-stayed bridge that replaces the Tappan Zee Bridge, in the USA. The bridge is equipped with a Structural Health Monitoring System (SHMS) consisting of more than 400 sensors deployed at relevant locations. The sensors capture environmental and operational conditions as well as the associated structural responses. The system is designed to process monitoring data to support data-driven management of the bridge. This is achieved through the system''s different functionalities, which include real-time data visualization via an on-line graphical user interface, customized data processing routines, alert notifications whenever data-based thresholds are exceeded, automatic reporting of pre-defined parameters and characterization of structural responses during extreme events. The present paper describes, as a case-study, the motivation, architecture, functionalities and installation aspects of the SHMS.


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