An Approach to Automated Modal Parameter Identification for Structural Health Monitoring Applications

Author(s):  
C. Rainieri ◽  
G. Fabbrocino ◽  
E. Cosenza
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.


Sensors ◽  
2017 ◽  
Vol 17 (2) ◽  
pp. 265 ◽  
Author(s):  
Jun Zhang ◽  
Gui Tian ◽  
Adi Marindra ◽  
Ali Sunny ◽  
Ao Zhao

2013 ◽  
Vol 2013 (CICMT) ◽  
pp. 000020-000025
Author(s):  
Hélène DEBEDA ◽  
Riadh LAKHMI ◽  
Isabelle FAVRE ◽  
Jonathan ARGILLOS ◽  
Mario MAGLIONE ◽  
...  

Using the association of the low-cost screen-printing technology with the sacrificial layer method, the feasibility of totally released piezoelectric thick-films microceramics of gold electroded PZT type is studied. After the deposition of the sacrificial layer on an alumina substrate and subsequent printing and drying of gold, PZT and gold layers, the final firing is performed at low temperature. This is followed by the releasing step of the Au/PZT/Au in diluted acidic solution. Impedance analysis shows that the electrical properties and electromechanical coefficients of poled PZT thick-films are still lower than those of PZT ceramics. This result is correlated to the high porosity rate of the PZT layer. However these piezoelectric microceramics present a good electromechanical behaviour and can be used as sensors when solicited by vibrations or as actuators to generate vibrations in a structure on which they are bonded. Moreover, the successful fabrication associated to a good electromechanical signature on a metallic test structure suggests Structural Health Monitoring applications.


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