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In this paper a new technique for broken rotor bars diagnosis in induction machine at low load and non stationary state is proposed. The technique is used in order to remedy the problem from using the classical signal-processing technique FFT by analysis of stator current envelope. The proposed method is based from using discrete wavelet transform (DWT) and Hilbert transform. The Hilbert transform is used to extract the stator current envelope. Then this signal is processed via DWT. The efficiency of the proposed method is verified by simulation tests.

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This paper presents the design of mobile robot visual navigation system in indoor environment based on fuzzy logic controllers (FLC) and optical flow (OF) approach. The proposed control system contains two Takagi-Sugeno fuzzy logic controllers for obstacle avoidance and goal seeking based on video acquisition and image processing algorithm. The first steering controller uses OF values calculated by Horn-Schunck algorithm to detect and estimate the positions of the obstacles. To extract information about the environment, the image is divided into two parts. The second FLC is used to guide the robot to the direction of the final destination. The efficiency of the proposed approach is verified in simulation using Visual Reality Toolbox. Simulation results demonstrate that the visual based control system allows autonomous navigation without any collision with obstacles.

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