Probabilistic Condition Monitoring of Azimuth Thrusters Based on Acceleration Measurements
نویسندگان
چکیده
Drill ships and offshore rigs use azimuth thrusters for propulsion, maneuvering steering, attitude control dynamic positioning activities. The versatile operating modes the challenging marine environment create demand flexible practical condition monitoring solutions onboard. This study introduces a algorithm using acceleration shaft speed data to detect anomalies that give information on defects in driveline components of thrusters. Statistical features vibration are predicted with linear regression models residuals then monitored relative multivariate normal distributions. method includes an automated selection approach identifies distributed operational areas from training based residuals. During monitoring, squared Mahalanobis distance identified distributions is calculated defined ranges, providing thruster condition. performance was validated two compared reference classifiers. results suggest could changes during online monitoring. Moreover, it had high accuracy bearing related binary classification tests. In conclusion, has properties exhibit suitability application.
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ژورنال
عنوان ژورنال: Machines
سال: 2021
ISSN: ['2075-1702']
DOI: https://doi.org/10.3390/machines9020039