A procedure for the assessment of unknown parameters in modeling defective bearings through multi-objective optimization. (15th February 2023)

• Record Type: Journal Article
• Authors: Gabrielli, Alberto; Battarra, Mattia; Mucchi, Emiliano; Dalpiaz, Giorgio
• Is Part Of: Mechanical systems and signal processing. Volume 185(2023)
• Publication Date: 2023-02-15
• Subjects: Rolling element bearings -- Defect modeling -- Lumped parameter model -- Multi-objective optimization; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2022.109783
• Languages: English
• ISSNs: 0888-3270

Abstract

Abstract: The lumped parameter modeling of a defective rolling element bearing involves the evaluation of several quantities whose values are characterized by a high degree of uncertainty. In this regard, the goal of this paper is to propose a procedure to estimate these unknown values by employing a multi-objective optimization technique. The objective functions to be minimized are global indicators that take into account the discrepancy between signal features computed on the basis of a numerical model and experimental data. The former are obtained by means of a lumped parameter model of a self-aligning ball bearing, while the latter are the outcomes of an extensive experimental study on a dedicated test bench. The values of the unknown parameters are constrained within fixed limits dictated by their physical properties. Furthermore, dependencies between the involved quantities are taken into account by introducing additional analytical relationships based on the physics of the problem. The values estimated through the proposed procedure allow to obtain a good accordance with the experimental results for a variety of test conditions.