Fault diagnosis of active magnetic bearings based on Gaussian GLRT detector

Leon Nagel, Roberto Galeazzi, Andreas Jauernik Voigt, Ilmar Santos

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Active magnetic bearings are progressively replacing conventional bearings in many industrial applications, particularly in the energy sector. Magnetic bearings have many advantages such as contactless support and clean operation; however their use also poses some challenges connected to their inherent open loop instability. Occurrence of faults in one or more components of an active magnetic bearing may lead to loss of control of the rotor. Timely detection and isolation of faults in an active magnetic bearing could prevent hazardous system behaviour by enabling proper reconfiguration of the control system. A structural model of the bearing-rotor system is presented and used to perform a detectability and isolability analysis of faults in the magnetic actuator. Structural detectability and group-wise isolability is concluded for single and multiple faults in the actuators. A Gaussian generalized likelihood ratio test is proposed for detecting faults striking the electromagnet. The detector is capable of detecting and isolating the occurrence of faults in e.g. the windings of bearing by tracking changes in the mean value of a Gaussian distribution. The statistical distribution of the residuals in non faulty condition is characterized by experimental data of a full-scale bearing-rotor system. Verification of the detection performance is done through simulated data of a nonlinear model of the magnetic bearing calibrated against the real system.
Original languageEnglish
Title of host publication3rd Conference on Control and Fault-Tolerant Systems (SysTol 2016)
Publication date2016
ISBN (Electronic)978-1-5090-0658-8
Publication statusPublished - 2016
Event3rd International Conference on Control and Fault-Tolerant Systems - Barcelona, Spain
Duration: 7 Sep 20169 Sep 2016


Conference3rd International Conference on Control and Fault-Tolerant Systems


  • Active magnetic bearing
  • Actuator fault diagnosis
  • Gaussian distribution
  • Generalized likelihood ratio test

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