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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Uncertain texture features fusion based method for performance condition evaluation of complex electromechanical

Rongxi Wang1, Xu Gao2, Jianmin Gao1

  • 1State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.

ISA Transactions
|December 19, 2020
PubMed
Summary

Evaluating complex electromechanical systems (CESs) is challenging. This study introduces a novel method using data-graph conversion and texture analysis for accurate performance condition evaluation, enhancing reliability.

Keywords:
Accurate condition evaluationComplex electromechanical systemsFeatures fusionTexture analysisUncertainty handling

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Area of Science:

  • Engineering
  • Data Science

Background:

  • Maintaining operating reliability and preventing damage in complex electromechanical systems (CESs) is crucial but challenging.
  • Conventional time-series analysis methods struggle with uncertain features in CES performance evaluation.

Purpose of the Study:

  • To develop an advanced method for accurate performance condition evaluation of CESs.
  • To address challenges in handling uncertain features and large-scale data in system diagnostics.

Main Methods:

  • A novel method inspired by uncertain features fusion is proposed.
  • Utilizes data-graph conversion, texture analysis, and improved evidence fusion.
  • Constructs 2D color-spectrums without information loss, extracting and fusing texture features.

Main Results:

  • The proposed method effectively evaluates performance conditions of CESs.
  • Demonstrated effectiveness through actual evaluation applications.
  • Successfully handles uncertainty and large-scale, high-dimensional data.

Conclusions:

  • The developed method offers a new approach for CES performance condition evaluation.
  • Provides a viable strategy for large-scale high-dimensional data processing and decision-making.
  • Offers insights into uncertainty handling for broader engineering applications.