A new tool for model examination: Estimation of the mediator transfer function between the model and measured signals. (31st March 2023)

• Record Type: Journal Article
• Authors: Matania, Omri; Zamir, Or; Bortman, Jacob
• Is Part Of: Journal of sound and vibration. Volume 548(2023)
• Publication Date: 2023-03-31
• Subjects: Measurement technique -- Realistic model validation -- Mean squared error -- Transfer function estimation -- Rotating machinery; DFT discrete Fourier transform -- EMTF estimation of the mediator transfer function -- IDFT inverse discrete Fourier transform -- MSE mean squared error -- NMSE normalized mean squared error -- RPS revolutions per second -- SA synchronous average; Sound -- Periodicals; Vibration -- Periodicals; Son -- Périodiques; Vibration -- Périodiques; Sound; Vibration; Periodicals; Electronic journals; 620.205
• DOI: 10.1016/j.jsv.2023.117560
• Languages: English
• ISSNs: 0022-460X

Abstract

Highlights: Quantitative validation of realistic models. Estimation of the transfer function effects. A new tool for model examination. Abstract: Understanding the phenomenon underlying the behavior of rotating machinery by models can foster the development of algorithms for prognostic health monitoring. Model development is based on several assumptions and results in differences between the simulated and measured signals. In every system, there is always a transfer function between the rotating component and the sensor. The transfer function is one of the main possible sources of differences between the simulated and measured signals, making interpretation of physical results or further model development difficult. In this paper, a new paradigm is proposed to mitigate this problem. The new paradigm facilitates a quantitative comparison between models and elucidates the components that need further development or meticulous re-examination. We examine the performance of the paradigm using measured signals and transfer functions, and demonstrate it on a physical model of a gearbox with its corresponding measured signals.