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Review and comparison of tacholess instantaneous speed estimation methods on experimental vibration data

Journal

MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 129, Issue -, Pages 407-436

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2019.02.031

Keywords

Tacholess; Speed estimation; Phase demodulation; Multi-order probabilistic approach; Teager-Kaiser Energy Operator; Maximum tracking; Vold-Kalman filter

Funding

  1. FWO
  2. agency for Innovation by Science and Technology in Belgium
  3. Grainger Foundation
  4. MIT-ExxonMobil collaboration through the MIT Energy Initiative
  5. Office of Naval Research Structural Acoustics Program

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Instantaneous speed estimation has become a key part of many condition monitoring procedures for rotating machinery. The ability to track the rotational speed of a system is a critical requirement for the majority of vibration-based condition monitoring methods. Information about the speed enables compensating for potential speed variations that would otherwise impair conventional frequency-based methods. The problem of instantaneous speed estimation based on the vibration signals themselves is one that has received a significant amount of attention in recent years. Installing encoders or tachometers has become a lot less attractive due to the potential cost savings that can be obtained by simply utilizing an accelerometer instead. However, trying to find a speed estimation method that fits a certain application best is not so straightforward if one inspects the available literature. It turns out that there are many articles that present slight variations or extensions to already existing techniques. This paper targets a general overview of the available knowledge regarding vibration-based speed estimation techniques. It also aims to review some of the most commonly used techniques by means of a performance comparison of seven speed estimation methods on three different experimental data sets. The resulting speed estimation data of all tested methods is made publicly available such that it can help in forming a benchmark for future speed estimation methods. (C) 2019 Elsevier Ltd. All rights reserved.

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