Stator inter-turn fault detection for seamless fault-tolerant operation of five-phase induction motors

Author(s):  
Vivek M. Sundaram ◽  
Hamid A. Toliyat
Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5905
Author(s):  
Khaled Farag ◽  
Abdullah Shawier ◽  
Ayman S. Abdel-Khalik ◽  
Mohamed M. Ahmed ◽  
Shehab Ahmed

The multiphase induction motor is considered to be the promising alternative to the conventional three-phase induction motor, especially in safety-critical applications because of its inherent fault-tolerant feature. Therefore, the attention of many researchers has been paid to develop different techniques for detecting various fault types of multiphase induction motors, to securely switch the control mode of the multiphase drive system to its post-fault operation mode. Therefore, several fault detection methods have been researched and adapted; one of these methods is the indices-based fault detection technique. This technique was firstly introduced to detect open-phase fault of multiphase induction motors. The main advantage of this technique is that its mathematical formulation is straightforward and can easily be understood and implemented. In this paper, the study of the indices-based fault detection technique has been extended to test its applicability in detecting some other stator and rotor fault types of multiphase induction motors, namely, open-phase, open-switch, bad connection and broken rotor bar faults. Experimental and simulation validations of this technique are also introduced using a 1 kW prototype symmetrical six-phase induction motor.


2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jianyong Yao ◽  
Guichao Yang ◽  
Dawei Ma

The integration of internal leakage fault detection and tolerant control for single-rod hydraulic actuators is present in this paper. Fault detection is a potential technique to provide efficient condition monitoring and/or preventive maintenance, and fault tolerant control is a critical method to improve the safety and reliability of hydraulic servo systems. Based on quadratic Lyapunov functions, a performance-oriented fault detection method is proposed, which has a simple structure and is prone to implement in practice. The main feature is that, when a prescribed performance index is satisfied (even a slight fault has occurred), there is no fault alarmed; otherwise (i.e., a severe fault has occurred), the fault is detected and then a fault tolerant controller is activated. The proposed tolerant controller, which is based on the parameter adaptive methodology, is also prone to realize, and the learning mechanism is simple since only the internal leakage is considered in parameter adaptation and thus the persistent exciting (PE) condition is easily satisfied. After the activation of the fault tolerant controller, the control performance is gradually recovered. Simulation results on a hydraulic servo system with both abrupt and incipient internal leakage fault demonstrate the effectiveness of the proposed fault detection and tolerant control method.


Author(s):  
Saaeede Hazbavi ◽  
Roozbeh Razavi-Far ◽  
Mohammad Mehdi Arefi ◽  
Alireza Khayatian ◽  
Mehrdad Saif

2009 ◽  
Vol 40 (3) ◽  
pp. 289-296 ◽  
Author(s):  
Z. Sun ◽  
J. Wang ◽  
D. Howe ◽  
G.W. Jewell

2015 ◽  
Vol 764-765 ◽  
pp. 740-746
Author(s):  
Hang Yuan ◽  
Chen Lu ◽  
Ze Tao Xiong ◽  
Hong Mei Liu

Fault detection for aileron actuators mainly involves the enhancement of reliability and fault tolerant capability. Considering the complexity of the working conditions of aileron actuators, a fault detection method for an aileron actuator under variable conditions is proposed in this study. A bi-step neural network is utilized for fault detection. The first neural network, which is employed as the observer, is established to monitor the aileron actuator and generate the residual error. The other neural network generates the corresponding adaptive threshold synchronously. Faults are detected by comparing the residual error and the threshold. In considering of the variable conditions, aerodynamic loads are introduced to the bi-step neural network. The training order spectrums are designed. Finally, the effectiveness of the proposed scheme is demonstrated by a simulation model with different faults.


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