Predictive Maintenance Approaches for Rotating Machinery: A Review

Maintenance strategies have moved from fixing failures to predicting them. This review describes condition-based and predictive maintenance, the usual data pipeline, and the main modeling approaches. No new experimental data are reported. An AI language model (Claude, Anthropic) was used in preparing this manuscript.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-03
DOI
https://doi.org/10.5281/zenodo.23917625
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

Predictive Maintenance Approaches for Rotating Machinery: A Review

Sahetnur Durdyyev, Yslam Orazov
Zenodo (CERN European Organization for Nuclear Research)
Machine Fault Diagnosis Techniques
article

Predictive Maintenance Approaches for Rotating Machinery: A Review

Sahetnur Durdyyev, Yslam Orazov
article en

Abstract

Maintenance strategies have moved from fixing failures to predicting them. This review describes condition-based and predictive maintenance, the usual data pipeline, and the main modeling approaches. No new experimental data are reported. An AI language model (Claude, Anthropic) was used in preparing this manuscript.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 19%
Machine Fault Diagnosis Techniques
DOIOpen Access PDFOpenAlex
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Predictive Maintenance Approaches for Rotating Machinery: A Review — Sahetnur Durdyyev, Yslam Orazov · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS