Predicting Mining Equipment Bearing Faults with Machine Learning: A Comparative Study and Deployment Readiness Assessment

This material includes the Python code used in this research and the output results as well.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-03
DOI
https://doi.org/10.5281/zenodo.23922287
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Predicting Mining Equipment Bearing Faults with Machine Learning: A Comparative Study and Deployment Readiness Assessment

Zenodo (CERN European Organization for Nuclear Research)
Machine Fault Diagnosis Techniques
article

Predicting Mining Equipment Bearing Faults with Machine Learning: A Comparative Study and Deployment Readiness Assessment

article en

Abstract

This material includes the Python code used in this research and the output results as well.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 19%
Machine Fault Diagnosis Techniques
DOIOpen Access PDFOpenAlex
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Predicting Mining Equipment Bearing Faults with Machine Learning: A Comparative Study and Deployment Readiness Assessment · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS