Sparse filtering based domain adaptation for mechanical fault diagnosis
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.02.049
Abstract: Abstract Recently, machine learning has achieved considerable success in the field of mechanical fault diagnosis. Nevertheless, in many real-world applications, the original vibration data usually collected under different work conditions which lead to large distribution… read more here.
Keywords: sparse filtering; mechanical fault; domain adaptation; fault diagnosis ... See more keywords
Mechanical faults detection for vehicle motors under nonstationary conditions based on Vold-Kalman order tracking method
Sign Up to like & getrecommendations! Published in 2022 at "Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering"
DOI: 10.1177/09544070221078679
Abstract: The fault diagnosis and health management of motors are the key technology that needs to be resolved in the future with the development of electric vehicles. The drive motors usually working under nonstationary conditions. Moreover,… read more here.
Keywords: vold kalman; vehicle motors; detection; fault ... See more keywords
Mechanical Fault Prognosis through Spectral Analysis of Vibration Signals
Sign Up to like & getrecommendations! Published in 2022 at "Algorithms"
DOI: 10.3390/a15030094
Abstract: Vibration signal analysis is the most common technique used for mechanical vibration monitoring. By using vibration sensors, the fault prognosis of rotating machinery provides a way to detect possible machine damage at an early stage… read more here.
Keywords: vibration; fault prognosis; analysis; mechanical fault ... See more keywords