Khalaf Salloum Gaeid

Sensor and sensorless fault tolerant control for induction motors using a wavelet index.

Fault Tolerant Control (FTC) systems are crucial in industry to ensure safe and reliable operation, especially of motor drives. This paper proposes the use of multiple controllers for a FTC system of an induction motor drive, selected based on a switching mechanism. The system switches between sensor vector control, sensorless vector control, closed-loop voltage by frequency (V/f) control and open loop V/f control. Vector control offers high performance, while V/f is a simple, low cost strategy with high speed and satisfactory performance. The faults dealt with are speed sensor failures, stator winding open circuits, shorts and minimum voltage faults. In the event of compound faults, a protection unit halts motor operation. The faults are detected using a wavelet index. For the sensorless vector control, a novel Boosted Model Reference Adaptive System (BMRAS) to estimate the motor speed is presented, which reduces tuning time. Both simulation results and experimental results with an induction motor drive show the scheme to be a fast and effective one for fault detection, while the control methods transition smoothly and ensure the effectiveness of the FTC system. The system is also shown to be flexible, reverting rapidly back to the dominant controller if the motor returns to a healthy state.

Indirect vector control of a variable frequency induction motor drive (VCIMD)

The principle of vector control of electrical drives is based on the control of both the magnitude and the phase of each phase current and voltage. Matlab/ Simulink has been performed for assessment of operating features of the proposed scheme. PI speed controller are designed in this paper, Test response of the developed variable speed drive along with simulated response are given and discussed in detail for torque, speed and current. Modeling of induction motor with the complete vector control scheme (indirect) is investigated to show the optimal response of the control system.

Simulink representation of induction motor reference frames

The simulation of induction motor frames are presented in this paper. The voltage, torque and current waveforms are included in the comparison of the induction motor frames. The main objective of the paper is to propose a Simulink building block model. Students will be able to resolve problems relating to mathematical reference frame transformations will be able to apply reference-frame theory to the analysis of induction motors, will be able to predict motor drive performance using simulation software (Matlab Simulink).

Induction motor fault tolerant control with wavelet indicator

Fault tolerant control of induction motors is proposed using both vector control as the dominant controller and a Voltage-to-Frequency (V/F) controller as the complimentary controller. The system falls back on the V/ F controller when either stator short winding or stator open winding faults occur. The wavelet index is used as fault indicator. To estimate the speed, a novel Boosted Model Reference Adaptive System (BMRAS) is used. To develop a new fault tolerant control algorithm, a protection unit is added to the main circuit to stop the induction motor operation in the case of high severity faults.

Wavelet Fault Diagnosis of Induction Motor

The early 1980s saw the emergence of wavelets, an analysis tool that drew a lot of attention from scientists of various disciplines, mathematicians in particular, due to its promising applications. The roots of wavelet techniques go back to 1807, when Joseph Fourier presented his theories of frequency analysis. By the 1930s, investigations were being carried out on scale-varying basis functions that would conserve energy in the computation of functional energy. Between 1960 and 1980, Guido Weiss and Ronald R. Coifman studied the reconstruction of functional elements using ‘atoms’. Later, Grossman and Morlet would provide a quantum physics definition of wavelets. Stephane Mallat made an important contribution to the development of wavelets through his work in digital signal processing in 1985. The first non-trivial, continuously differentiable wavelets were created by Y.Meyer. Not long after, Ingrid Daubechies constructed a set of orthonormal basis functions that form the foundation of modern day wavelet applications (Nirmesh Yadav et al, 2004). The present demand in the industry is for high performance electric drives that are capable of achieving speed commands accurately. Control methods have had to reach higher levels of sophistication accordingly. Induction motors, with their advantages in terms of size, cost and efficiency, are best suited to meet these growing needs (Khalaf Salloum Gaeid&Hew Wooi Ping, 2010). In costly systems, maintenance and protection are especially essential in the prevention of system breakdowns and catastrophes. Thanks to advances in signal processing technology, it is now possible to utilize wavelet principles to efficiently diagnose and protect industrial induction motors. Motor Current Signature Analysis (MCSA) of the stator current with wavelet to detect the fault in a broken rotor bar in the transient region was done by (Douglas et al, 2003).The analysis of the sensorless control system of induction motor with a broken rotor for diagnostics using wavelet techniques has been presented by (Bogalecka et al, 2009). (Zhang et al, 2007), used the empirical model decomposition(EMD) which deals with nonlinear systems to detect the broken rotor bar using wavelet discrete transform (WDT).(Cao Zhitong et al, 2001), used the multi resolution wavelet analysis (MRA) method to detect broken rotor bars according to the analysis of stator current. The signal was filtered, differentiated and then supplied to the Daubechies wavelet with 5 levels. (Faiz, Ebrahimi et al, 2007) presented a novel criterion to detect the broken rotor bar using time stepping finite element (TSFE) to model the broken bar faults in induction motor. (Yang et al, 2007), presented a novel method to detect the rotor broken bar using Ridge wavelet. In this paper, only one phase of the

Fault tolerant control of induction motor through observer techniques II

In the design of the control law due to sensor and actuator faults, it is very important to implement the fault tolerant control system. Unknown Input Observers (UIO) can be used in model based fault detection and isolation (FDI) schemes to reduce or almost eliminate the effect of unknown disturbances on the MIMO (Multiple-Input and Multiple-Output) plant/system. Furthermore, they can be used to generate residuals that are insensitive to unknown disturbances or noise, and thus, lower the false alarm rate. Design of many faults isolation banks of UIOs has been done. To make sure the best detection and isolation of the faults is provided, these banks generate residuals which are sensitive to only one fault. Fault tolerant control is used to compensate both sensor and actuator faults.