Analysis of starting and synchronization process for line start IPM motors
This paper presents an improved analytical method for determining the synchronizing capability of a line start interior permanent magnet (IPM) synchronous motor. Approximate solution techniques based on average torque analysis for determining the critical slip and maximum inertia are also presented. A dynamic d-q axis model of the motor is developed to investigate the run-up response as well as synchronization capability of line start IPM synchronous motors. The start-up and synchronization performances of a 1hp 208V 4-pole line start IPM motor for various loads have been obtained using MATLAB. Experimental investigations have been also carried out for the same 1 hp IPM motor and test results are presented to support simulation results.
Evaluation of synchronization capability in line start permanent magnet synchronous motors
Synchronization capability of line start permanent magnet synchronous (LSPMS) motors is a key factor in design and optimization of these motors. This paper presents a simple analytical method for finding critical slip in synchronization assessment of LSPMS motors. Appropriate approximations are employed in the method resulting in significant simplification of the method with reasonable accuracy. The proposed method is time efficient and can be easily included in iterative design procedures. Accuracy of the proposed method is evaluated by dynamic analysis of two different motors. Also, the experimental results are presented to support the analytical and simulation results.
Detection of Fractures Based on Directional Filtering in Image Logging
According to the feature of the direction of fractures in image logging, a method of fracture detection in image logging based on directional filtering is presented in this paper. The fracture image is filtered by the corresponding filter based on the local direction of fractures, which enhances the fracture traces in the direction of fractures in image logging. The final fracture traces are extracted by the combination of the results of both directional filtering and the threshold segmentation. Experimental results show this method effectively detect the fractures in image logging.