Multi-scale damage identification method based on wireless sensor network

Zhuo Zhou; YaWen Dai

doi:10.1117/12.2661026

16 December 2022 Multi-scale damage identification method based on wireless sensor network

Zhuo Zhou, YaWen Dai

Proceedings Volume 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022); 125003Y (2022) https://doi.org/10.1117/12.2661026
Event: 5th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022, Chongqing, China

Abstract

Due to the threat of natural disasters such as earthquakes and floods, as well as the influence of the aging of civil engineering structures, the safety of long-term service structures cannot be guaranteed. In order to monitor the working status of structural engineering in real time and capture its damage information, a multi-scale damage identification method based on wireless sensor network is proposed in this paper. Autocorrelation analysis of time series data is carried out through nonlinear autoregressive network with exogenous inputs (NARX) neural network, the overall health of the structure is initially diagnosed locally at the node, and the sensor nodes are divided into different monitoring subnetworks according to the spatial location when the structure is damaged, and the empirical mode decomposition (EMD) method is used. The time-series data were preprocessed to further locate and quantify damage. Experiments show that the method can accurately identify and locate structural damage and can visually represent the amount of structural damage.

Citation Download Citation

Zhuo Zhou and YaWen Dai "Multi-scale damage identification method based on wireless sensor network", Proc. SPIE 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 125003Y (16 December 2022); https://doi.org/10.1117/12.2661026

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KEYWORDS

Neural networks

Sensors

Error analysis

Data modeling

Neurons

Statistical analysis

Sensor networks

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