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A New Denoising Method for Belt Conveyor Roller Fault Signals.

Xuedi Hao1, Jiajin Zhang1, Yingzong Gao1

  • 1College of Mechanical and Electrical Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China.

Sensors (Basel, Switzerland)
|April 27, 2024
PubMed
Summary

A new biparameter and trisegment wavelet threshold denoising (BT-WTD) algorithm effectively removes noise from acoustic signals in belt conveyor systems. This method improves fault diagnosis accuracy for intelligent inspection robots.

Keywords:
acoustic signal preprocessingdenoising methodsfault diagnosisinspection robots

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Area of Science:

  • Mechanical Engineering
  • Signal Processing
  • Artificial Intelligence

Background:

  • Belt conveyor systems are crucial in industries but prone to faults.
  • Intelligent inspection using acoustic signals faces challenges due to signal interference and complex environments.
  • Effective signal preprocessing is vital for accurate fault diagnosis.

Purpose of the Study:

  • To propose a novel wavelet threshold denoising algorithm for acoustic signals in belt conveyor systems.
  • To address the limitations of traditional denoising methods in handling strong noise backgrounds.
  • To enhance the accuracy of fault diagnosis in intelligent inspection systems.

Main Methods:

  • Development of a biparameter and trisegment wavelet threshold denoising (BT-WTD) algorithm.
  • Integration of a novel biparameter and trisegment threshold function.
  • Elaboration on parameter optimization and wavelet coefficient processing intervals.
  • Application to simulation and experimental signals from a belt conveyor platform.

Main Results:

  • The BT-WTD algorithm demonstrated superior denoising effectiveness compared to traditional methods.
  • The method successfully preserved useful signal features and avoided signal distortion.
  • Effective preprocessing of idler roller fault signals in noisy environments was achieved.
  • The algorithm showed significant improvements in signal-to-noise ratio.

Conclusions:

  • The proposed BT-WTD algorithm offers an effective solution for denoising acoustic signals in belt conveyor fault diagnosis.
  • This research provides a theoretical foundation for non-contact intelligent fault diagnosis using acoustic signals.
  • The findings support the development of advanced inspection robots for industrial applications.