Home › Entities › academia › Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal

Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal

Research article (Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science, 2020) · cited 24× · AI/ML
academia openalex:W3112080178
Press Enter · cited answer in seconds

Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal

Summary

Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal is a scholarly article[1].

Key Facts

  • Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal's instance of is recorded as scholarly article[2].

Related Entities

Chemseddine Rahmoune

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal. Retrieved May 24, 2026, from https://4ort.xyz/entity/fault-prognostics-of-rolling-element-bearing-based-on-feature-extraction-and-supervised-machine-learning-application-to-
MLA “Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fault-prognostics-of-rolling-element-bearing-based-on-feature-extraction-and-supervised-machine-learning-application-to-.
BibTeX @misc{4ortxyz_fault-prognostics-of-rolling-element-bearing-based-on-feature-extraction-and-supervised-machine-learning-application-to-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal}}, year = {2026}, url = {https://4ort.xyz/entity/fault-prognostics-of-rolling-element-bearing-based-on-feature-extraction-and-supervised-machine-learning-application-to-}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Fault prognostics of rolling element bearing based on feature extraction and supervised machine learning: Application to shaft wind turbine gearbox using vibration signal — https://4ort.xyz/entity/fault-prognostics-of-rolling-element-bearing-based-on-feature-extraction-and-supervised-machine-learning-application-to- (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/fault-prognostics-of-rolling-element-bearing-based-on-feature-extraction-and-supervised-machine-learning-application-to- · Last refreshed: