Education, Science, Technology, Innovation and Life
Open Access
Sign In

Optimal Sensor Placement Based on Bisect K-means Clustering Algorithm

Download as PDF

DOI: 10.23977/msmee.2018.72138


Zhaolan Wei, Jing Xia

Corresponding Author

Zhaolan Wei


Sensor placement is a combinatorial optimization problem. Considering the number of factors, the selection of measuring points is easy to cause information redundancy and low signal-to-noise ratio. In order to solve this problem, according to the matrix of structure's frequency response, bisect K-means clustering algorithm is designed to classify the degrees of freedom according to the similarity of response. This method is applied to the steel truss arch bridge with the background of Nanjing Dashengguan Yangtze River Bridge. The results show that the proposed method in this paper can better classify the degrees of freedom with similar vibration characteristics, make the sensor more balanced in the overall structure, overcome the redundant information among the sensors, and improve the signal-to-noise ratio at the measurement point.


Sensor, k-means clustering algorithm, measurement point

All published work is licensed under a Creative Commons Attribution 4.0 International License.

Copyright © 2016 - 2031 Clausius Scientific Press Inc. All Rights Reserved.