Health monitoring of electromechanical flight actuators via position-tracking predictive models

Abstract

This article deals with the development and performance characterisation of model-based health monitoring algorithms for the detection of faults in an electromechanical actuator for unmanned aerial system flight controls. Two real-time executable position-tracking algorithms, based on predictors with different levels of complexity, are developed and compared in terms of false alarm rejection and fault detection capabilities, using a high-fidelity model of the actuator in which different types of faults are injected. The algorithms' performances are evaluated by simulating flight manoeuvres with the actuator in normal operation as well as with relevant faults (motor coil faults, motor magnet degradation, voltage supply decrease). The results demonstrate that an accurate position-tracking monitor allows to obtain a prompt fault detection and fail-safe mode engagement, while more detailed monitoring functions can be used for fault isolation only.

Dynamic Modelling and Experimental Characterization of a Self-Powered Structural Health-Monitoring System with MFC Piezoelectric Patches

“…The experimentally-validated model of the prototype was finally used to test a model-based condition-monitoring algorithm developed by the authors [40,[57][58][59][60][61], in order to assess the system applicability to SHM systems. In model-based condition-monitoring approaches, the detection of faults or anomalies is actually performed by evaluating the deviation of hardware responses from the predictions of a system model related to normal operating conditions.…”

A Novel 2-D Current Signal-Based Residual Learning With Optimized Softmax to Identify Faults in Ball Screw Actuators

“…The concept of "Fly Electric" considers more to all electric flight in terms of electric powered flight along with control surfaces operation, steering nose control, and retractable landing gear; all controlled with electro-mechanical actuators. The data monitoring system for these actuators is being the primary concern for researchers [3,4]. For these systems, actuator data should be monitored after installing in aircraft to ensure system reliability related to acquired data [5] to be as close as compared with conventional systems (hydraulics).…”

“…The developed model was also evaluated on available Paderborn published datasets that comprise multi-stage bearings data. This include data from healthy as well as damaged bearings with real and artificial inner race and outer race damages with low (1), medium (2) and high (3) intensities. For comparison, 6203 type bearing is considered here.…”

An Intelligent Hybrid Scheme for Identification of Faults in Industrial Ball Screw Linear Motion Systems

“…Critical fault modes for these systems available in literature [1] include friction due to inadequate lubrication in bearings and ball screw, backlash and channel jamming in ball screw, wear or spall at bearing and ball screw surface and other structural faults. Accurate identification of these faults is of great industrial concern to ensure system availability and has been considered by many researchers in the past [1], [2], [4], and [5]. For this purpose, dedicated monitoring setups are required which essentially need expertise in electro-mechanics, controls and intelligent systems.…”

“…Fault data monitoring for BS linear systems have been the area of primary concern by various researchers in the past [2], [3]. For this purpose, system input data was monitored after installing linear motion drive on actual system to ensure monitoring of reliable data [4].…”