An UWB ranging method based on wavelet packet decomposition

Li, Juan; Cui, Xuerong; Zhang, Hao; Gulliver, T. Aaron

doi:10.1016/j.neucom.2016.10.099

Cited by 5 publications

(1 citation statement)

References 14 publications

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“…The variable time window makes the time-frequency window narrower in the low-frequency part and wider in the high-frequency part. The wavelet transform solves the lack of Fourier-transform in the time dimension [ 26 ].…”

Section: Related Work and Foundationsmentioning

confidence: 99%

Research on Voltage Waveform Fault Detection of Miniature Vibration Motor Based on Improved WP-LSTM

et al. 2020

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To solve the problem of vibration motor fault detection accuracy and inefficiency in smartphone components, this paper proposes a fault diagnosis method based on the wavelet packet and improves long and short-term memory network. First, the voltage signal of the vibration motor is decomposed by a wavelet packet to reconstruct the signal. Secondly, the reconstructed signal is input into the improved three-layer LSTM network as a feature vector. The memory characteristics of the LSTM network are used to fully learn the time-series fault feature information in the unsteady state signal, and then, the model is used to diagnose the motor fault. Finally, the feasibility of the proposed method is verified through experiments and can be applied to engineering practice. Compared with the existing motor fault diagnosis method, the improved WP-LSTM diagnosis method has a better diagnosis effect and improves fault diagnosis.

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Section: Related Work and Foundationsmentioning

confidence: 99%