Wheel load reconstruction using strain gauge measurements on the bogie frame for strain prediction and fatigue assessment. (May 2023)

• Record Type: Journal Article
• Authors: Nieminen, Vesa; Tuohineva, Antero; Autio, Maija
• Is Part Of: International journal of fatigue. Volume 170(2023)
• Publication Date: 2023-05
• Subjects: Load reconstruction -- Bogie frame -- Virtual sensing -- Optimal sensor placement -- Fatigue damage; Materials -- Fatigue -- Periodicals; Materials -- Fatigue; Periodicals; 620.1122
• DOI: 10.1016/j.ijfatigue.2023.107533
• Languages: English
• ISSNs: 0142-1123

Abstract

Highlights: Identification of operational wheel loads of a tram for the bogie stress recovery. Strain gauge placement is solved as an optimization problem. Actual load–strain relationship is verified by physical calibrations. A novel calibration arrangement is presented for the fully equipped bogie. A good correlation of the reconstructed operational stresses with the measured ones. Abstract: Knowledge of actual wheel-rail contact forces under a service environment is critical for fatigue damage prediction of rail vehicle bogies. This paper presents a method for reconstructing operational wheel loads based on the strain gauge measurements on the bogie of a tram. The strain gauge placement is solved as an optimisation problem, and the actual load–strain relationship is verified by physical calibrations. A novel calibration arrangement is presented to produce linearly independent load cases for a fully equipped bogie. A good correlation of the reconstructed operational stresses with the measured stresses indicated that the identified loads are valid for fatigue assessment.