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Optimal Sensor Placement Based on Bisect K-means Clustering Algorithm

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DOI: 10.23977/msmee.2018.72138

Author(s)

Zhaolan Wei, Jing Xia

Corresponding Author

Zhaolan Wei

ABSTRACT

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.

KEYWORDS

Sensor, k-means clustering algorithm, measurement point

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