Fault detection in airliner electro-mechanical actuators via hybrid particle filtering

Mazzoleni, Mirko; Maroni, Gabriele; Maccarana, Yamuna; Formentin, Simone; Previdi, Fabio

doi:10.1016/j.ifacol.2017.08.640

Cited by 18 publications

(7 citation statements)

References 21 publications

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“…Mazzoleni et al. [68] proposed an improved PF observer model. The improved observer model is established by the Observation and Transition Particle Filter (OTPF) algorithm.…”

Section: Ema Dphm Methodsmentioning

confidence: 99%

“…Balaban et al [67] adopted the TRANSCEND algorithm for EMA fault diagnosis and the fault diagnosis observer is established by the PF algorithm. Mazzoleni et al [68] proposed an improved PF observer model. The improved observer model is established by the Observation and Transition Particle Filter (OTPF) algorithm.…”

Section: The Observer-based Fault Diagnosis Methodsmentioning

confidence: 99%

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A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators

Yin

Chen

et al. 2022

IET Electric Power Appl

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As More/All Electric Aircraft gradually become a research hotspot, electromechanical actuators (EMAs), which can directly convert electrical energy into mechanical energy, have gained more and more attention. However, since the reliability of EMA cannot meet the requirements of actual aircrafts, the practical application of EMA is severely limited. Therefore, fault diagnosis, prognosis and health management (DPHM), which can realise condition‐based maintenance (CBM), has become the key technology in the application of EMA. The aim is to summarise the research on EMA fault modes, fault diagnosis, prognosis and health management systematically and comprehensively. First, the basic structure and common fault modes of EMAs are introduced, and the failure mechanism of EMA is studied. Then, the algorithms of DPHM for EMAs are reviewed in detail. The perception strategies of data acquisition are analysed, and the EMA fault diagnosis methods, including model‐based and data‐driven methods, are reviewed. The research of remaining useful life (RUL) prediction and fault‐tolerant control are introduced. After that, some problems of the existing research on EMA DPHM and their potential solutions are put forward. Finally, several possible developing directions of research on EMA DPHM are predicted.

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“…Mazzoleni et al. [68] proposed an improved PF observer model. The improved observer model is established by the Observation and Transition Particle Filter (OTPF) algorithm.…”

Section: Ema Dphm Methodsmentioning

confidence: 99%

Section: The Observer-based Fault Diagnosis Methodsmentioning

confidence: 99%

A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators

Yin

Chen

et al. 2022

IET Electric Power Appl

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“…In [8], a variant of a particle filter algorithm and an extended Kalman filter were utilized for detecting ball-screw faults for flight control EMAs. A data model for each fault scenario was identified as a pre-learning stage.…”

Section: Physical Principlesmentioning

confidence: 99%

“…Health monitoring methods for ball-screw faults of flight control EMA were deeply investigated by [5][6][7][8]. In [5], Balaban et al investigated a neural network method for detecting two ball-screw faults: a partial jam and spalls for a flight control actuator.…”

Section: Introductionmentioning

confidence: 99%

Spall Fault Quantification Method for Flight Control Electromechanical Actuator

2022

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Flight control electro-mechanical actuators (EMAs) are among the primary onboard systems that significantly influence the reliability and safety of unmanned aerial vehicles. Recent reliability studies have shown that the ball-screw element of a flight control EMA is subject to oscillating operating conditions that may initiate rapid degradation, such as fatigue spall defects. Accordingly, detecting and quantifying such faults are crucial for developing efficient fault prognostic and remaining useful life estimation capabilities. In this study, a vibration-based fault quantification method is developed to quantify the fatigue faults of a ball-screw mechanism of an EMA. The method is based on identifying the ball passing instants through a localized surface defect on the vibrational jerk rather than the vibrational acceleration measurement. The jerk is numerically determined from conventional accelerometers using a Savitzky–Golay differentiator. This method was successfully tested for ball bearings and it is adjusted in this paper for ball-screw faults. The experimental validation is investigated on a set of fault-seeded samples on NASA’s Ames Research Center Flyable Electro-Mechanical Actuator test stand.

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“…These joint collaborations are often promoted and incentivized by the European Union (EU) or by the United States (US). As recent examples, authors in [5], [6], [7] provided several different solutions for fault detection of EMAs used in airliner applications, using a large experimental test campaign. The works were related to the FP7 EU-funded HOLMES (Health OnLine Monitoring for Electro-Mechanical actuator Safety) project.…”

Section: Introductionmentioning

confidence: 99%

Condition Monitoring of Electro-Mechanical Actuators for Aerospace Using Batch Change Detection Algorithms

Mazzoleni

Scandella

Maccarana

et al. 2018

2018 IEEE Conference on Control Technology and Applications (CCTA)

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This paper proposes the use of a change detection algorithm to monitor the degradation of mechanical components of Electro-Mechanical Actuators (EMA) employed in the aerospace industry. Contrary to the standard on-line application of change detection methods, the presented approach can be applied in a batch mode, leveraging on the knowledge of when the data were collected. The methodology is applied to data measured during an endurance test campaign on a real EMA employed in aerospace, by means of a developed test bench, progressively bringing the EMA to failure. Three rationales for building an indicator of degradation are tested. Results show how the method is able to assess the degradation of the actuator over time, constituting a first step towards a condition monitoring solution for the more-electric-aircraft of the future.

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Fault detection in airliner electro-mechanical actuators via hybrid particle filtering

Cited by 18 publications

References 21 publications

A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators

A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators

Spall Fault Quantification Method for Flight Control Electromechanical Actuator

Condition Monitoring of Electro-Mechanical Actuators for Aerospace Using Batch Change Detection Algorithms

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