New Prognostic Method Based on Spectral Analysis Techniques Dealing with Motor Static Eccentricity for Aerospace Electromechanical Actuators

The prognostic algorithms are important to identify the precursors of incipient failures of electromechanical actuators (EMA) applied to aircraft primary flight controls. Keeping in mind the risk related to the performed functions of these actuators the anticipation of an incoming failure is really useful: a correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement, increasing the aircraft safety and reliability. In this paper the authors propose an innovative prognostic model-based approach, able to recognize the symptoms of an EMA degradation before the explicit exhibition of the anomalous behavior. The identification/evaluation of the considered incipient failures is performed analyzing proper critical system operational parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. Subsequently, these operational parameters are correlated with the actual health condition of the considered system by means of failure maps created by a reference monitoring model-based algorithm. In the present work, the proposed method has been applied to an EMA with a brushless DC motor affected by a progressive increase of the static eccentricity of the rotor. In order to evaluate the performances of the aforesaid prognostic method a test simulation environment, able to manage different failure modes, has been defined. This numerical test case simulates the dynamic behaviors of the EMA taking into account nonlinear effects related to different kinds of progressive mechanical failures (such as transmission backlash, friction, and rotor static eccentricity). Results show that the method exhibit adequate robustness and a high degree of confidence in the ability to early identify a malfunctioning, minimizing the risk of fake alarms or unannounced failures.

[1]  T. A. Haskew,et al.  "Two-phase on" drive operation in a permanent magnet synchronous machine electromechanical actuator , 1999 .

[2]  Matteo Davide Lorenzo Dalla Vedova,et al.  Model based analysis of precursors of electromechanical servomechanisms failures using an artificial neural network , 2015 .

[3]  Matteo Davide Lorenzo Dalla Vedova,et al.  Proposal of Prognostic Parametric Method Applied to an Electrohydraulic Servomechanism Affected by Multiple Failures , 2014 .

[4]  Matteo Davide Lorenzo Dalla Vedova,et al.  Parametric Methods for Fault Analysis Applied to a Servomechanism Affected by Multiple Failures , 2014 .

[5]  T. Rajesh,et al.  Speed control of brushless DC motor drive employing hard chopping PWM technique using DSP , 2006, 2006 India International Conference on Power Electronics.

[6]  BYOUNG-KUK LEE,et al.  Advanced Simulation Model for Brushless DC Motor Drives , 2003 .

[7]  K. Ramar,et al.  Fault characterisation and classification using wavelet and fast Fourier transforms , 2008 .

[8]  N. Ahmed,et al.  FAST TRANSFORMS, algorithms, analysis, applications , 1983, Proceedings of the IEEE.

[9]  F. Harris.  On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.

[10]  Matteo Davide Lorenzo Dalla Vedova,et al.  New asymmetry monitoring techniques: Effects on attitude control , 2009 .

[11]  Matteo Davide Lorenzo Dalla Vedova,et al.  A Prognostic Model for Electrohydraulic Servovalves , 2009 .

[12]  Huaqing Wang,et al.  Fault diagnosis method based on kurtosis wave and information divergence for rolling element bearings , 2009 .

[13]  Mehmet Akar,et al.  Detection of static eccentricity for permanent magnet synchronous motors using the coherence analysis , 2010 .

[14]  J. Tukey,et al.  An algorithm for the machine calculation of complex Fourier series , 1965 .

[15]  Alan V. Oppenheim,et al.  Discrete-time Signal Processing. Vol.2 , 2001 .

[16]  Omer Aydogdu,et al.  Realization of Fuzzy Logic Controlled Brushless DC Motor Drives Using Matlab/Simulink , 2010 .

[17]  A. Vahedi,et al.  Modeling, simulation and implementation of four-switch, Brushless DC motor drive based on switching functions , 2009, IEEE EUROCON 2009.

[18]  Matteo Davide Lorenzo Dalla Vedova,et al.  A dry friction model and robust computational algorithm for reversible or irreversible motion transmission , 2012 .