Performance comparison of representative model-based fault reconstruction algorithms for aircraft sensor fault detection and diagnosis

He, Qinming; Zhang, Weiguo; Lu, Peng; Liu, Jinglong

doi:10.1016/j.ast.2019.105649

Cited by 34 publications

(14 citation statements)

References 42 publications

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“…In industrial processes, a major concern is the reliability of sensors and actuators. Various approaches to model-based actuator and sensor fault detection and isolation (FDI) have been developed in the electrical engineering and process control communities [1][2][3][4][5][6][7][8][9][10][11]. These model-based methods can be mainly classified into two categories: those based on state observer [2][3][4][5][6] and those based on parity space [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Structured Residuals Design Techniques for actuator and sensor Fault Detection and Isolation in a Permanent Magnet DC Motor

Antić

Rosić

Djurović

et al. 2023

Preprint

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The reliability of actuators and sensors is an important topic in many electric motor drives. A comparison of structured residual synthesis methods for actuator and sensor fault detection and isolation (FDI) in a permanent magnet (PM) DC motor, applying two different approaches to the design of primary residuals, is presented in the paper. The first method involves a standard approach and is based on system transfer matrix synthesis. The second, more convenient approach involves the synthesis of primary residuals based on the analysis of subsystems that describe the observed system. Both methods are applicable for linear and stationary systems but were successfully applied to a laboratory system that shows nonlinear and non-stationary properties and is affected by a constant disturbance, thanks to the proposed technique of residual translation with the previous design of internal residuals. A real-time experiment performed on a laboratory setup, which consists of a DC motor, an amplifier designed in the form of a linear electronic circuit, and a Compact RIO 9075 real-time processor, is used to illustrate the drawbacks and advantages of the analyzed approaches.

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Section: Introductionmentioning

confidence: 99%

Comparison of Structured Residuals Design Techniques for actuator and sensor Fault Detection and Isolation in a Permanent Magnet DC Motor

Antić

Rosić

Djurović

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Therefore, in some studies, researchers also focused on studying a number of different sensors such as air data parameter sensors (P Lu et al, 2015), engine parameter sensors (Xue, Guo and Zhang, 2007) or other sensors on helicopter UAV (Hajiyev and Soken, 2013). In addition, several methods, including Kalman filters (Xue, Guo and Zhang, 2007;P Lu et al, 2015;He et al, 2020), self-diagnostic (Sullivan, 1988;Tuan, Firsov and Pishchukhina, 2012), adaptive models (Peng , fuzzy tuning (Kim, Choi and Kim, 2008), and machine learning (Baskaya, Bronz and Delahaye, 2017) have been applied to identify faults of sensor operations on AVs.…”

Section: Introductionmentioning

confidence: 99%

Improving Efficiency of Angular Velocity Sensors on Aircraft

Tran¹,

NGUYEN>

VUONG

et al. 2022

IJAST

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With the development of science and technology, intelligent systems on aircraft help users know the device's operating status in real time. Using smart devices shortens the time for maintenance, repair, and operation of ground equipment and aircraft equipment. Therefore, building devices capable of self-diagnosis and warning failure are essential in aeronautical engineering. In many published studies, the authors often use the foundation of classic algorithms such as genetics, neural networks, and AI to solve the problem of identification and troubleshoot some simple devices. In Vietnam, there are currently not many published studies on failure diagnosis in aviation engineering, so the author's research has built the foundation for developing studies on fault diagnosis crash in the future. The primary purpose of the research is to create a complete automatic fault diagnosis and repair system for a specific class of inductance (angular speed sensor). The algorithms proposed in the paper are simulated on Matlab Simulink software, which will prove the feasibility of the proposed algorithm. In future studies, the author will apply new algorithms to build more complex fault diagnosis systems for other objects on the flying device.

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“…The literature includes studies conducted based on the aircraft modeling [3,[19][20][21][22][23][24][25][26]. However, studies based on the aircraft modeling have mostly been carried out for certain sensors and certain fault conditions during the cruise.…”

Section: Introductionmentioning

confidence: 99%

“…He et al (2020) created a model-based fault detection and diagnosis system by using the observer and kalman filter structure separately for the inertial measurement unit in aircraft. While the observer structure gives faster results in fault detection, fault detection can be carried out more precisely in the kalman filtered structure [25]. There are studies that do not detect faults, but are aimed at providing alternative data source based on real flight data using artificial neural networks [4,27].…”

Section: Introductionmentioning

confidence: 99%

Sensor fault detection and reconstruction system for commercial aircrafts

Kilic

Unal

2021

Aeronaut. j.

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The aim morphing of this study is to detect and reconstruct a fault in angle-of-attack sensor and pitot probes that are components in commercial aircrafts, without false alarm and no need for additional measurements. Real flight data collected from a local airline was used to design the relevant system. Correlation analysis was performed to select the data related to the angle-of-attack and airspeed. Fault detection and reconstruction were carried out by using Adaptive Neural Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANN), which are machine-learning methods. No false alarm was detected when the fault test following the fault modeling was carried out at 0–1 s range by filtering the residual signal. When the fault was detected, fault reconstruction process was initiated so that system output could be achieved according to estimated sensor data. Instead of using the methods based on hardware redundancy, we designed a new system within the scope of this study.

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Performance comparison of representative model-based fault reconstruction algorithms for aircraft sensor fault detection and diagnosis

Cited by 34 publications

References 42 publications

Comparison of Structured Residuals Design Techniques for actuator and sensor Fault Detection and Isolation in a Permanent Magnet DC Motor

Comparison of Structured Residuals Design Techniques for actuator and sensor Fault Detection and Isolation in a Permanent Magnet DC Motor

Improving Efficiency of Angular Velocity Sensors on Aircraft

Sensor fault detection and reconstruction system for commercial aircrafts

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