Search

We developed a real-time method to detect the dynamic eccentricity of a rotor in a permanent-magnet (PM) motor by monitoring a fault detection signal induced in an additional winding, without performing any further postprocessing, even under a nonstationary rotational speed. After deriving a mathematical equation of the back electromotive force (EMF) induced in a tooth-coil winding, we proposed a fault detection signal, which is the back EMF in an additional winding divided by the rotational speed, when the additional winding is wound around the teeth corresponding to an even number of pole pitches. We used the 2-D finite-element model of a three-phase PM motor with eight poles and 12 slots to verify the proposed method. We also developed an experimental setup which can change the dynamic eccentricity of a PM motor and we performed the experiment for PM motors with dynamic eccentricities of 0%, 25%, and 50% to verify the proposed method. Through the mathematical equation, numerical simulation, and experiment, we confirmed that the fault detection signal proposed in this paper can successfully detect the dynamic eccentricity in a PM motor in real time. [ABSTRACT FROM PUBLISHER]

In this paper, we present a novel image enhancement approach using a color shift model-based multiple color-filter aperture (MCA) camera for digital multifocusing. The proposed image enhancement algorithm consists of three steps; (i) cluster-based region-of-interest (ROI) estimation, (ii) image registration using phase correlation matching (PCM) and fusion, and (iii) image enhancement using spatially adaptive noise smoothing based on the alpha map. The image acquired by the MCA configuration contains color misalignment, which provides additional depth information of objects at different distances. This color misalignment can also provide additional information for blur estimation. The proposed cluster-based image segmentation method can effectively classify ROIs according to the distance from the camera. The segmented regions are aligned by using PCM, and they are fused to generate an in-focused image. For further enhancement of the color-registered image, we use spatially adaptive noise smoothing based on the alpha map. Experimental results show the proposed image enhancement method can significantly enhance the visual quality of the MCA output image, and can be fully or partially incorporated into multifocusing or extended depth of field (EDoF) systems in the form of the finite impulse response (FIR) filter structure. [ABSTRACT FROM AUTHOR]