Structural health monitoring using real-time modal parameter identification algorithm

Author(s):  
Tae Lim ◽  
Albert Bosse ◽  
Shalom Fisher
2020 ◽  
Vol 198 ◽  
pp. 02020
Author(s):  
Yifan Zhao

Since there is not much research on structural health monitoring (SHM) applications in tall buildings nowadays, this paper gives a proposal of how it can be applied on skyscrapers. Covering the whole process of SHM, this paper focuses more on the diagnostic algorithms, including Structural dynamic index method, Modal parameter identification method Neural network algorithm and Genetic algorithm and how these algorithms can be used in SHM. After introducing the basic process of SHM, an example is given to show how these principles can be applied in this over 400m building. And after all these introductions, a conclusion can be drawn that the structural health monitoring system can be applied properly in tall buildings following the way proposed in this paper.


Author(s):  
Liping Sun ◽  
Yang Lu ◽  
Xinyue Zhang

Structural health monitoring (SHM) based on vibration measurements in large/complex structures were shown to be promising by researchers. The authors believe that the SHM problem is fundamentally one of statistical pattern recognition. Therefore, the damage detection studies reviewed herein are summarized in the context of a statistical pattern recognition paradigm[1]. This paradigm can be described as a three-part process: (1) Data acquisition and cleansing, (2) Modal parameter identification, (3) Damage identification methods. However, offshore platform structures are very complex, and not easy to excite artificially and they are often suffered from ambient loads that cannot be controlled easily. The thesis focuses on three key issues for structural health monitoring via vibration in real offshore platform structures[2]. In the first part of review, the offshore platform structure health monitoring system basic principle and the composition are discussed. In the second portion, three important processes of structure health monitoring are summarized (Data acquisition and cleansing, modal parameter identification, damage identification methods), and each method good and bad points is pointed out. Next, Application of damage identification and structural health monitoring to offshore platform are in detail produced, the methods are described in general terms including difficulties associated with their implementation. Finally, current and future-planned applications of this technology to offshore platform are summarized. The paper concludes with a discussion of critical issues for future research on damage identification and structural health monitoring for offshore platform.


2014 ◽  
Vol 87 ◽  
pp. 1266-1269 ◽  
Author(s):  
L. Capineri ◽  
A. Bulletti ◽  
M. Calzolai ◽  
P. Giannelli ◽  
D. Francesconi

2021 ◽  
Author(s):  
Igor Razuvaev

Abstract Isothermal Storage Tanks (IST) contains tens thousands tons of the liquefied gases (propane, ethane, ethylene, etc.) at very low temperatures. These are the most dangerous industrial objects. In the report the Integrated Structural Health Monitoring (ISHM) Systems for the management of the integrity of these tanks in real time is considered. The structure of the ISHM Systems, NDT methods, technical characteristics, data verification procedures, a decision-making algorithm and practical results are described.


2000 ◽  
Author(s):  
Jeffrey S. Vipperman ◽  
Deyu Li

Abstract This paper closely examines the nature of the dielectric response of piezoceramics that are used as Adaptive Piezoelectric Sensoriactuators (APSAs). Firstly, it is demonstrated that he APSA possesses real time structural health monitoring abilities, based on the capacitance measurement of the piezoceramic. Secondly, nonideal behavior including lossy, hysteretic, and field dependence is measured in the piezoceramics and a method mitigating some of this response in the Adaptive Piezoelectric Sensoriactuator is proposed.


2020 ◽  
Vol 113 (3) ◽  
pp. 1641-1649
Author(s):  
Bhawani Shankar Chowdhry ◽  
Ali Akbar Shah ◽  
Muhammad Aslam Uqaili ◽  
Tayab Memon

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