Published on: April 2026
INTELLIGENT FAULT DIAGNOSIS OF ROLLING ELEMENT BEARINGS USING FINITE ELEMENT ANALYSIS
Pratiksha Jadhav
Patil Mangesh
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Abstract
: Rolling element bearings play a vital role in rotating machines such as motors, pumps, turbines, and gearboxes. Any malfunction in these components can cause sudden equipment failure, unplanned downtime, loss of production, and increased repair expenses. Therefore, timely and reliable fault detection is necessary to maintain operational safety and enhance system dependability. This study proposes an intelligent fault diagnosis method for rolling element bearings based on transient Finite Element Analysis (FEA). A transient FEA model is constructed to capture the time-dependent dynamic behavior of the bearing under varying loads, rotational speeds, and defect conditions. The model allows detailed investigation of parameters such as stress distribution, deformation, contact interactions, and vibration characteristics throughout the operating cycle. Different fault types, including defects in the inner race, outer race, and rolling elements, are introduced into the simulation to obtain distinctive dynamic patterns that assist In accurate fault identification. The dynamic responses obtained from the simulations are further analyzed using advanced signal processing methods and intelligent computational techniques. Relevant features are extracted from the time-domain and frequency-domain signals and supplied to machine learning models for automatic identification of fault categories and their severity levels. This approach achieves reliable diagnostic performance while minimizing the need for extensive experimental testing and physical trials. In addition, it supports predictive maintenance by enabling early detection of potential defects before serious damage occurs. The findings confirm that the integration of transient Finite Element Analysis with intelligent data-driven analysis forms a robust and efficient framework for condition monitoring and timely fault diagnosis of rolling element bearings in industrial environments.
How to Cite this Paper
Jadhav, P. (2026). Intelligent Fault Diagnosis of Rolling Element Bearings using Finite Element Analysis. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(04). https://doi.org/10.55041/ijcope.v2i4.501
Jadhav, Pratiksha. "Intelligent Fault Diagnosis of Rolling Element Bearings using Finite Element Analysis." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijcope.v2i4.501.
Jadhav, Pratiksha. "Intelligent Fault Diagnosis of Rolling Element Bearings using Finite Element Analysis." International Journal of Creative and Open Research in Engineering and Management 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijcope.v2i4.501.
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- •Published on: Apr 20 2026
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