A Fault Diagnosis Approach for Electromechanical Actuators with Simulating Model under Small Experimental Data Sample Condition

Zhaoqin Peng,Juan Chen,Enrico Zio,Jia Li,Zhengyi Sun,Zilong Ping,Kunyu Dong,Yongling Fu

doi:10.3390/act11030066

Abstract

Electromechanical actuators (EMAs) have shown a high efficiency in flight surface control with the development of more electric aircraft. In order to identify the abnormalities and potential failures of EMA, a methodology for fault diagnosis is developed. A simulating model of EMA is first built to perform different working states. Based on the modeling of EMA, the corresponding faults are then simulated to re-generate the fault data. Afterwards, a gated recurrent unit (GRU) and co-attention-based fault diagnosis approach is proposed to classify the working states of EMA. Experiments are conducted and a satisfying classification accuracy on simulated data is obtained. Furthermore, fault diagnosis on an actual working system is performed. The experimental results demonstrate that the proposed method has a high efficiency.

Highlights

More electric aircraft (MEA) initiatives have focused on increasing the penetration of the electrical systems into the aircrafts, in order to decrease the weight and increase the overall efficiency [1,2]
This paper proposed a methodology on the task of Electromechanical actuators (EMAs) fault diagnosis
This paper proposed on actual the task of EMA

Summary

Introduction

Academic Editor: Ignazio DiminoRecently, more electric aircraft (MEA) initiatives have focused on increasing the penetration of the electrical systems into the aircrafts, in order to decrease the weight and increase the overall efficiency [1,2]. Electromechanical actuators (EMAs) present a solution which exploits a mechanical drivetrain to reach the control surface [3]. Compared with the alternatives (e.g., classical hydraulic systems and electro-hydrostatic actuators), the EMAs control the motor and leverage on a planetary roller screw pair to translate the rotary motion into linear motion, which has brought paradigm shifts to power the MEA transmission. In spite of the reduced complexity and easy maintenance, EMAs are currently used in fewer safety-critical control surfaces or tasks with redundant alternatives [6]. This is due to the fact that the failure risks and accumulated reliability experience are absent [7]. The fault diagnosis of EMA is mostly studied, which paves the way for deeply understanding the fault occurrence and its principle [8,9]

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Discussion

Conclusion