Journal Article


Statistical and sensitivity analysis of ultrasound signals for effective condition monitoring of electro-motors using industrial approach

Abstract

This paper researches the importance of ultrasound methodology for swiftly detecting faults in electric motors and rotating machines. The primary focus of this research is on the intricate signal processing of ultrasound signals from both faulty and fault-free electro-motors. The principal goal is to conduct a comprehensive statistical investigation into signal factors, examining the effects of defect progression on the factors associated with continuously operating faulty electro-motors. In addition to the statistical analysis, this study explores the envelope-frequency spectrum of the signal under both healthy and defective conditions, employing the envelope method alongside Hilbert transformation. The objective is to thoroughly scrutinize the dynamic changes in ultrasound waveform and envelope spectrum of defective states, considering diverse degrees of defect severity over an extended time span. Moreover, the paper meticulously tracks the trajectory of factor changes over a 40-day operational period of a defective electro-motor. Additionally, the study delves into the sensitivity of the ultrasound method to impulse-wise shocks, which are recurrently observed in ultrasound signals, leading to deviations in certain signal factors from their established healthy thresholds. In response to this challenge, this paper conducts a particular analysis of signal factor sensitivity to impulse-wise noises, identifying robust factors that serve as reliable tools for firm condition monitoring. These identified factors are then presented as invaluable contributors to ensuring the precision and reliability of condition monitoring, especially in the presence of disruptive impulse-wise noises.

Attached files

Authors

Mobki, Hamed
Ehsan Shabahang Nia
Azizi, Aydin

Oxford Brookes departments

School of Engineering, Computing and Mathematics

Dates

Year of publication: 2024
Date of RADAR deposit: 2024-10-08


Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License


Related resources

This RADAR resource is Identical to Statistical and sensitivity analysis of ultrasound signals for effective condition monitoring of electro-motors using industrial approach

Details

  • Owner: Joseph Ripp
  • Collection: Outputs
  • Version: 1 (show all)
  • Status: Live
  • Views (since Sept 2022): 73