Abstract
A hybrid method for optimal sensor placement is introduced to position detection sensors on hydro-structures to maximize the monitored structural dynamic information. In the hybrid method, modal assurance criterion matrices and effective independence vectors were applied as the optimization principle for adding and eliminating potential sensor locations in coordinate sets. The energy revision factor was implemented to measure the modal strain energy and ensure the arrangement of sensors at the large energy locations. QR decomposition of the modal matrix was employed to decrease the influence of the initial sensor positions. A computational simulation of an arch dam model, considering 20 sensors and the first six orders of modal vibrations, was used to demonstrate the feasibility of the method. The advantages and disadvantages of existing methods were demonstrated by comparison criteria including the modal assurance criterion, modal kinetic energy criterion, Fisher information matrix, and root-mean square error criterion. The results showed that the method proposed in this article provides linear independent and orthogonal modal vectors, minimizing the relative mean square error of the measured vibration modes, which fundamentally indicates that the identified vibration characteristics of the concrete arch dam are accurate and reasonable.
Highlights
A hydro-structure, such as a dam, is a large-scale concrete water retaining structure
This suggests that the hybrid and modal strain energy (MSE)-effective independence (EI) methods contain more modal information, which is beneficial for modal parameter identification of concrete arch dam structures
This article focuses on the optimal placement of dynamic response monitoring points of a high arch dam
Summary
A hydro-structure, such as a dam, is a large-scale concrete water retaining structure. The measuring points with the minimum maximum off-diagonal MAC matrix element values were selected successively from the remaining degrees of freedom until reaching the threshold value and obtaining the OSP. 3. Perform QR decomposition for the modal matrix, acquire the initial sensor deployment, and calculate the corresponding MAC matrix and its maximum off-diagonal element value max. The contribution of these close points to the variation of the MAC matrix maximum off-diagonal element value is calculated separately, and the sensor measurement location with a smaller contribution is removed. In the EI and MSE-EI methods, the minimum diagonal element value of the idempotent matrix E increases as points are excluded gradually, which means that the contribution from the remaining sensors to the modal vector linear independence increases gradually. The evaluation criteria include the MAC, modal kinetic energy criterion, Fisher information matrix, and root-mean-square error criterion.[26]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Distributed Sensor Networks
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
