Sensor fault isolation and detection of smart structures

2010 ◽  
Vol 19 (10) ◽  
pp. 105001 ◽  
Author(s):  
Reza Sharifi ◽  
Yeesock Kim ◽  
Reza Langari
2016 ◽  
Vol 27 (8) ◽  
pp. 1260-1283 ◽  
Author(s):  
Feng Xu ◽  
Sorin Olaru ◽  
Vicenc Puig ◽  
Carlos Ocampo-Martinez ◽  
Silviu-Iulian Niculescu

2017 ◽  
Vol 64 (8) ◽  
pp. 6763-6774 ◽  
Author(s):  
Kangkang Zhang ◽  
Bin Jiang ◽  
Xing-Gang Yan ◽  
Zehui Mao

Author(s):  
Reza Sharifi ◽  
Reza Langari ◽  
Yeesock Kim

This paper proposes a novel principal component analysis (PCA)-based sensor fault detection methodology for smart structures employing magnetorheological (MR) dampers. The MR damper is operated by a semiactive nonlinear fuzzy controller (SNFC) that is developed by integration of a set of Lyapunov optimal controllers, Kalman filters, and a semiactive converter with the fuzzy interpolation method. A numeric residual generator is found using the PCA analysis of ten measurements obtained from the structure-MR damper system for sensor fault detection. Using the matrix of this residual generator, the detectability and isolability of each sensor has been analyzed and the detection and isolation algorithm is applied to the smart structural system with different levels of artificially added faults. The simulation demonstrated that the proposed PCA-based sensor fault detection approach is effective in identifying the sensor faults of large smart structures employing MR dampers.


Author(s):  
Jian Li ◽  
Kunpeng Pan ◽  
Qingyu Su

The main purpose of this article is to study the sensor fault isolation for DC-DC converters, taking the single-ended primary industry converter as an example. To achieve the purpose of the research, we model the DC-DC converters as switched affine systems and design a bank of sliding mode observers for each corresponding sensor fault. By comparing the threshold with the residual estimation function produced by each sliding model observers, we can diagnose which sensor faults are occurring. Finally, three sensor faults are given as simulation examples to verify the feasibility of the proposed scheme.


2019 ◽  
Vol 86 ◽  
pp. 144-154 ◽  
Author(s):  
Hongquan Ji ◽  
Keke Huang ◽  
Donghua Zhou

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gulay Unal

Purpose Fault detection, isolation and reconfiguration of the flight control system is an important problem to obtain healthy flight. This paper aims to propose an integrated approach for aircraft fault-tolerant control. Design/methodology/approach The integrated structure includes a Kalman filter to obtain without noise, a full order observer for sensor fault detection, a GOS (generalized observer scheme) for sensor fault isolation and a fuzzy controller to reconfigure of the healthy sensor. This combination is simulated using the state space model of a lateral flight control system in case of disturbance and under sensor fault scenario. Findings Using a dedicated observer scheme, the detection and time of sensor fault are correct, but the sensor fault isolation is evaluated incorrectly while the faulty sensor is isolated correctly using GOS. The simulation results show that the suggested approach works affectively for sensor faults with disturbance. Originality/value This paper proposes an integrated approach for aircraft fault-tolerant control. Under this framework, three units are designed, one is Kalman filter for filtering and the other is GOS for sensor fault isolation and another is fuzzy logic for reconfiguration. An integrated approach is sensitive to faults that have disturbances. The simulation results show the proposed integrated approach can be used for any linear system.


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