ANN based double stator asynchronous machine diagnosis taking torque change into account

In this work the strategy of the artificial intelligence (neural networks) is used to detect and localize the defects of the double stator asynchronous machine. In fact, several neural networks have been applied to the detection of defects. Then, we used a selector which allows activating only one network at a time. In this case, the selected network detects only defects corresponding to the torque developed by asynchronous machine. Finally, the simulation results were presented to show the effectiveness of artificial neural networks for automatic fault diagnosi

Sigmoid function approximation for ANN implementation in FPGA devices

The objective of this work is the implementation of Artificial Neural Network on a FPGA board. This implementation aim is to contribute in the hardware integration solutions in the areas such as monitoring, diagnosis, maintenance and control of power system as well as industrial processes. Since the Simulink library provided by Xilinx, has all the blocks that are necessary for the design of Artificial Neural Networks except a few functions such as sigmoid function. In this work, an approximation of the sigmoid function in polynomial form has been proposed. Then, the sigmoid function approximation has been implemented on FPGA using the Xilinx library. Tests results are satisfactor

Sensorless speed field-oriented control of induction motor tacking core loss into account

In field-oriented controlled induction motor drives, the instantaneous rotor speed is measured using whether sensors or estimators. Since the basic Kalman filter is a state observer, its use in vector controlled schemes has received much attention. However, these schemes are based on the assumption that the existence of iron loss in the induction motor may be neglected. The paper shows the effect of iron loss on the extended Kalman filter performance that is designed on the basis of the classical dq model. Original simulation results are carried out to demonstrate this effect as well as the effectiveness of the suggested approach to minimise the speed estimation error without modifying the EKF's algorithm