Unbalance detection in rotor systems with active bearings using self-sensing piezoelectric actuators. (1st March 2018)

• Record Type: Journal Article
• Authors: Ambur, Ramakrishnan; Rinderknecht, Stephan
• Is Part Of: Mechanical systems and signal processing. Volume 102(2018)
• Page Start: 72
• Page End: 86
• Publication Date: 2018-03-01
• Subjects: Fault diagnosis -- Piezoelectric actuators -- Self-sensing -- Rotor systems -- Active bearings -- Unbalance detection; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2017.09.006
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: This research work aims to achieve and integrate fault detection and control action. They are realised without sensors using self-sensing piezoelectric actuators. Using virtual displacement signals from them unbalance in a rotor system has been detected. Robustness of the unbalance estimates against outliers in measurements is improved. In a real test bench experiments are performed in stationary, transient and closed loop. Abstract: Machines which are developed today are highly automated due to increased use of mechatronic systems. To ensure their reliable operation, fault detection and isolation (FDI) is an important feature along with a better control. This research work aims to achieve and integrate both these functions with minimum number of components in a mechatronic system. This article investigates a rotating machine with active bearings equipped with piezoelectric actuators. There is an inherent coupling between their electrical and mechanical properties because of which they can also be used as sensors. Mechanical deflection can be reconstructed from these self-sensing actuators from measured voltage and current signals. These virtual sensor signals are utilised to detect unbalance in a rotor system. Parameters of unbalance such as its magnitude and phase are detected by parametric estimation method in frequency domain. Unbalance location has been identified using hypothesis of localization of faults. Robustness of the estimates against outliers in measurements is improved using weighted least squares method. Unbalances are detected in a real test bench apart from simulation using its model. Experiments are performed in stationary as well as in transient case. As a further step unbalances are estimated during simultaneous actuation of actuators in closed loop with an adaptive algorithm for vibration minimisation. This strategy could be used in systems which aim for both fault detection and control action.