Fault identification of piezoelectric sensor based on 1DCNN-BiLSTM-cross-attention

CHEN Yongbo; ZHANG Ting

doi:10.12299/jsues.24-0392

Volume 40 Issue 2

Jun. 2026

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Article Navigation > Journal of Shanghai University of Engineering Science > 2026 > 40(2): 174-182

CHEN Yongbo, ZHANG Ting. Fault identification of piezoelectric sensor based on 1DCNN-BiLSTM-cross-attention[J]. Journal of Shanghai University of Engineering Science, 2026, 40(2): 174-182. doi: 10.12299/jsues.24-0392

Citation:

CHEN Yongbo, ZHANG Ting. Fault identification of piezoelectric sensor based on 1DCNN-BiLSTM-cross-attention[J]. Journal of Shanghai University of Engineering Science, 2026, 40(2): 174-182. doi: 10.12299/jsues.24-0392

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Fault identification of piezoelectric sensor based on 1DCNN-BiLSTM-cross-attention

doi: 10.12299/jsues.24-0392

CHEN Yongbo,
ZHANG Ting^,

School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201620, China

Received Date: 2024-12-25
Available Online: 2026-08-19
Publish Date: 2026-06-30

Abstract

Abstract

To address the fault identification problem of macro fiber composite (MFC) piezoelectric sensors, a fault identification method based on a one-dimensional convolutional neural network (1DCNN) and a bidirectional long short-term memory (BiLSTM) network integrated with a cross-attention mechanism was proposed. Different types of sensor faults were experimentally simulated to obtain fault data. The data were processed by fast Fourier transform and by variational mode decomposition with parameters optimized by a particle swarm optimization algorithm, respectively, and the resulting features were combined to obtain mixed time-frequency domain data. Subsequently, fault identification was performed on the data using the 1DCNN-BiLSTM-cross-attention (1DCBCA) model, and an accuracy of 99.4% was obtained. Compared with other models, the proposed model yields superior identification accuracy and is highly applicable to the fault identification of MFC piezoelectric sensors.

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References(15)

References

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