Adaptive ultrasound reflectometry for lubrication film thickness measurements

Kaeseler, R L and Johansen, P (2019) Adaptive ultrasound reflectometry for lubrication film thickness measurements. Measurement Science and Technology, 31 (2). 025108. ISSN 0957-0233

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Abstract

Adaptive ultrasound reflectometry methods for lubrication film thickness measurements is of great use for condition monitoring and prognostics of systems which have high repair costs and are remotely located, such as off-shore systems, as they recursively calibrate the incident ultrasound wave. Typical manual calibration requires a constant incident wave over the life-cycle of the system, or until new manual calibration can be conducted. Auto-calibration accounts for the changes in the incident ultrasound wave caused by changing environmental conditions, occurring over longer periods of time. The vision of adaptive ultrasound reflectometry methods is therefore increased robustness of lubrication film thickness measurements in a range of applications. In this article an adaptive scheme is proposed. The scheme is based on a thin-layer time-of-flight method for thickness determination, and an extended Kalman filter for estimation of the incident wave spectrum. The adaptive scheme is experimentally tested, and the feasibility of the algorithm is established, but serious issues regarding the robustness and reliability of the method are revealed by a disturbance analysis. However, the experiments and a theoretical layer phase-lag sensitivity analysis reveal that the estimation of the incident wave phase is of high importance for layer thicknesses above m, and for very thin layers below m the estimation of the magnitude dominates the measurement accuracy. This entails that the research in adaptive schemes should be directed towards phase- or magnitude-tracking performance, depending on the working range of the layer thickness, such that sufficient robustness and reliability of the algorithms can be assured.

Item Type: Article
Subjects: EP Archives > Computer Science
Depositing User: Managing Editor
Date Deposited: 09 Jul 2023 03:29
Last Modified: 09 Oct 2023 05:58
URI: http://research.send4journal.com/id/eprint/2479

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