Bidirectional LSTM-Based Soft Sensor for Rotor Displacement Trajectory Estimation

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date

2021-12-16

Department

Department of Energy and Mechanical Engineering
Department of Computer Science

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Language

en

Pages

14

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IEEE Access, Volume 9, pp. 167556-167569

Abstract

Constant rotor system monitoring enables timely control and maintenance actions that decrease the likelihood of severe malfunctions and end product quality deficits. Soft sensors represent a promising branch of solutions enhancing rotor system monitoring. A soft sensor can substitute a malfunctioning physical sensor and provide estimates of a quantity that is difficult to measure. This research demonstrates a soft sensor based on bidirectional long short-term memory (LSTM), and a training procedure for rotor system monitoring at high sampling frequency and varied operating conditions. This study adopts a large rotor and bearing vibration dataset. The soft sensor accurately estimates lateral displacement trajectories of the rotor from the bearing reaction forces over a large range of constant rotating speeds and constant support stiffnesses. The mean absolute error (MAE) of the LSTM-based soft sensor is 0.0063 mm over the test trajectories in the complete operating condition space. The soft sensor performance is shown to decrease significantly to a MAE of 0.0442 mm, if the training dataset is limited in the rotating speed range.

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Keywords

Soft sensors, Rotors, Vibrations, Monitoring, Logic gates, Trajectory, Training

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DOI

10.1109/ACCESS.2021.3136155

Citation

Miettinen, J, Tiainen, T, Viitala, R, Hiekkanen, K & Viitala, R 2021, 'Bidirectional LSTM-Based Soft Sensor for Rotor Displacement Trajectory Estimation', IEEE Access, vol. 9, 9654210, pp. 167556-167569. https://doi.org/10.1109/ACCESS.2021.3136155

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https://urn.fi/URN:NBN:fi:aalto-202201101068

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[article-cris] Insinööritieteiden korkeakoulu / ENG