Evaluation of the Correlation Coefficient as a Prognostic Indicator for Electromechanical Servomechanism Failures



Published Nov 1, 2020
Matteo D. L. Dalla Vedova Paolo Maggiore Lorenzo Pace Alessio Desando


In order to identify incipient failures due to a progressive wear of a primary flight command electromechanical actuator, several approaches could be employed; the choice of the best ones is driven by the efficacy shown in fault detection/identification, since not all the algorithms might be useful for the proposed purpose. In other words, some of them could be suitable only for certain applications while they could not give useful results for others. Developing a fault detection algorithm able to identify the precursors of the abovementioned electromechanical actuator (EMA) failure and its degradation pattern is thus beneficial for anticipating the incoming malfunction and alerting the maintenance crew such to properly schedule the servomechanism replacement. The research presented in the paper was focused to develop a fault detection/identification technique, able to identify symptoms alerting that an EMA component is degrading and will eventually exhibit an anomalous behavior, and to evaluate its potential use as prognostic indicator for the considered progressive faults (i.e. frictions and mechanical backlash acting on transmission, stator coil short circuit, rotor static eccentricity). To this purpose, an innovative model based fault detection technique has been developed merging several information achieved by means of Fast Fourier Transform (FFT) analysis and proper "failure precursors" (calculated by comparing the actual EMA responses with the expected ones). To assess the performance of the proposed technique, an appropriate simulation test environment was developed: the results showed an adequate
robustness and confidence was gained in the ability to early identify an eventual EMA malfunctioning with low risk of false alarms or missed failures.

Abstract 154 | PDF Downloads 144



fault detection, EMA, servomechanism, multiple failures, failure maps

Akar, M., Taskin, S., Seker, S., & Cankaya, I. (2010). Detection of static eccentricity for permanent magnet synchronous motors using the coherence analysis. Turkish Journal of Electrical Engineering & Computer Science, vol. 18, n.6, pp. 963-974.
Borello, L., & Dalla Vedova, M. D. L. (2006). Mechanical failures of flap control systems and related position errors: proposal of innovative configuration equipped with centrifugal brakes. International Journal of Mechanics and Control (JoMaC), vol. 07, n. 02, pp. 7-20.
Borello, L., Maggiore, P., Dalla Vedova, M. D. L., Alimhillaj, P. (2009). Dry Fiction acting on Hydraulic Motors and Control Valves: Dynamic Behavior of Flight Controls. XX National Congress AIDAA. Milan, Italy.
Borello, L., Dalla Vedova, M. D. L., Jacazio, G., & Sorli, M. (2009). A Prognostic Model for Electrohydraulic Servovalves. Proceedings of the Annual Conference of the Prognostics and Health Management Society. September 27-October 1, San Diego. USA.
Borello, L., Maggiore, P., Villero, G., & Dalla Vedova, M. D. L. (2010). A comparison between Dry Friction Discontinuous Computational Algorithms.27th International Congress of the Aeronautical Sciences ICAS 2010. September 19-24, Nice, France.
Borello, L., & Dalla Vedova, M. D. L. (2012). A Dry Friction Model and Robust Computational Algorithm for Reversible or Irreversible Motion Transmission. International Journal of Mechanics and Control (JoMaC), vol. 13, n. 02, pp. 37-48, ISSN: 1590-8844.
Borello, L., & Dalla Vedova, M. D. L. (2014). Flaps Failure and Aircraft Controllability: Developments in Asymmetry Monitoring Techniques. Journal of Mechanical Science and Technology (JMST), vol. 28, v. 11, pp. 4593-4603.
Bruzzese, C., & Joksimovic, G. (2011). Harmonic signatures of static eccentricities in the stator voltages and in the rotor current of no-load salient-pole synchronous generators. IEEE Transactions on Industrial Electronics, vol. 58, n. 5, pp. 1606-1624.
Cardona, A., Lerusse, A., & Géradin, M. (1998). Fast Fourier nonlinear vibration analysis. Computational Mechanics, vol. 22, n. 02, pp. 128-142.
Çunkas, M., & Aydogdu, O. (2010). Realization of Fuzzy Logic Controlled Brushless DC Motor Drives using Matlab/Simulink. Mathematical and Computational Applications, vol. 15, n. 02, pp. 218-229.
Dalla Vedova, M. D. L., Jacazio, G., Maggiore, P., & Sorli, M. (2010). Identification of Precursors of Servovalves Failures for Implementation of an Effective Prognostics. International Conference of Recent Advances in Aerospace Actuation Systems and Components. May 5-7, Toulouse, France.
Ginart, A., Brown, D., Kalgren, P., & Roemer, M. (2007). On-line Ringing Characterization as a PHM Technique for Power Drives and Electrical Machinery. Autotestcon, 2007 IEEE, September 17-20.
Ginart, A., Brown, D., Kalgren, P., & Roemer, M. (2008). Inverter Power Drive Transistor Diagnostic and Extended Operation under One-Transistor Trigger Suppression. Applied Power Electronics Conference and Exposition, 2008. APEC 2008. February 24-28.
Gökdere, L. U., Chiu, S. L., Keller, K. J., Vian, J. (2005). Lifetime control of electromechanical actuators. IEEE Aerospace Conference Proceedings. March 5-12, Big Sky, MT. doi: 10.1109/AERO.2005.1559655
Halvaei Niasar, A., Moghbelli, H., & Vahedi, A. (2009). Modelling, Simulation and Implementation of Four- Switch Brushless DC Motor Drive Based On Switching Functions.IEEE EUROCON 2009. May 18-23, St.- Petersburg, Russia.
Haskew,T. A., Schinstock, D. E., & Waldrep E. M. (1999). Two-Phase On” Drive Operation in a Permanent Magnet Synchronous Machine Electromechanical Actuator. IEEE Transactions on on Energy Conversion, vol. 14, n. 02.
Hemanand, T., & Rajesh, T. (2006). Speed Control of Brushless DC Motor Drive Employing Hard Chopping PWM Technique Using DSP. Proceedings of India International Conference on Power Electronics (IICPE 2006). December 19-21, Chennai, India.
Hua, J., & Zhiyong, H. (2008). Simulation of Sensorless Permanent Magnetic Brushless DC Motor Control System. Proceedings of the IEEE International Conference on Automation and Logistics, September, Qingdao, China.
Jeong C. L., & Hur J. (2013). A Fast Diagnosis Technique of Inter-Turn Fault in BLDC motor using Impedance AlgorithmP. 19th International Conference on the Computation of Electromagnetic Fields. June 30 - July 4, Budapest, Hungary.
Kim, B.-W., Kim, K.-T., & Hur, J. (2012). Simplified impedance modeling and analysis for inter-turn fault of IPM-type BLDC motor. Journal of Power Electronics, vol. 12, n. 1, pp. 10-18.
Lee, B. K., & Ehsani, M. (2003). Advanced Simulation Model for Brushless DC Motor Drives. Electric Power Components and Systems, vol. 31, n. 9, pp. 841–868.
MathWorks (2007). Using SIMULINK Manual. The Math- Works Inc.
Shashidhara, S.M., & Raju, P.S. (2013). Stator Winding Fault Diagnosis of Three-Phase Induction Motor by Parks Vector Approach. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (IJAREIEE), vol. 2, n. 7.
Todic, I., Miloš, M., & Pavišic, M. (2013). Position and speed control of electromechanical actuator for aerospace applications. Tehnicki Vjesnik, vol. 20, n. 5, pp. 853-860.
Vachtsevanos, G., Lewis, F. L., Roemer, M., Hess, A., &
Wu, B. (2006). Intelligent fault diagnosis and prognosis for engineering system. Hoboken, NJ: John Wiley & Sons, Inc.
Vichare, N., & Pecht, M. (2006). Prognostics and Health Management of Electronics. IEEE Transactions on Components and Packaging Technologies, vol. 29, 2006, pp. 222-229.
Welch, P. D. (1967). The Use of Fast Fourier Transform for the Estimation of Power Spectra: A Method Based on Time Averaging Over Short, Modified Periodograms. IEEE Transactions on audio and electroacoustics, vol. AU-15, n. 2.
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