The purpose of this paper is to develop a tool image inspection and measuring system by C++ Builder. Firstly, tool images are captured online for geometry analysis via a disassembled inspection mechanism mounted on the Z-axis of a five-axis tool grinding machine. One can use the controller of the machine to set the coordinate location of the mechanism and implement the humanized functions of autofocusing and automatic measurements. The digital images are calculated by the subpixel approach to improve the measurement resolution, and filtered the edge point location by Hough transform to upgrade the precision. The human machine interface (HMI) has a tutoring manner for users to operate the measuring procedures. These proposed functions can measure the geometric dimension such as the diameter, radius, and angle of different end mills or drills after finishing the tool grinding processes. Furthermore, the grinding processes can refer the online measured results to compensate the tool dimension. Therefore, this online image inspection and measuring system can improve the precision of tool grinding, product quality, and reduce the product cost. Finally, experiments are presented to show that the repeatability errors are ± 2 μm and ± 1 μm for the diameter and the radius measurements of end mills, respectively. The percentage error is 0.116% for measuring the point angle of a drill. Thus, the results demonstrate the effectiveness of the proposed method that can be employed to measure tool geometry of different cutting tools.
Based on the passivity theorem, an approach of the rotor resistance estimation and sliding mode position control for induction motor drives is proposed in this paper. Owing to values of the moment of inertia and the viscous coefficient of induction motors are generally small, the load torque disturbance is a critical term to create the chattering phenomenon. The adaptive laws are taken into account for estimating the rotor resistance and the gain of a load torque. Therefore, the chattering associated with the conventional sliding mode controller can be alleviated. The stability analysis of the estimator and the position control system is carried out by employing the passivity theorem. Finally, experimental results are presented to show the performance and robustness of the estimator and the controller with the variations of the motor mechanical parameters, rotor resistance, and load torque disturbances.
This paper proposes the parameters estimation and position control of an induction motor drive by using the composite adaptation scheme. First, in the rotor reference frame, the input-output linearization theory was employed to decouple the mechanical rotor position and the rotor flux amplitude at the transient state. An open-loop current model rotor flux observer was utilized for estimating the flux, and then the adaptive laws for estimating the rotor resistance, moment of inertia, viscous friction coefficient, and load torque. The passive properties of the flux observer, rotor resistance estimator, and composite adaptive position controller were analyzed based on the passivity theorem. According to the properties, the overall position control system was proved to be globally stable without using Lyapunov-type arguments. Experimental results are finally provided to show that the proposed method is robust to variations of the motor mechanical parameters, rotor resistance, and load torque disturbances. Moreover, good position tracking response and characteristics on parameter estimation can be achieved.
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