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- 저자 : Junxia Jiang (검색결과 2 건)
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Junxia Jiang,Haipeng Liao,Yuxiao He,Xinyuan Zhang 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.1
The spent fuel in the nuclear radiation environment is generally transported by transfer vehicles, which are required to be able to run smoothly under high speed and high acceleration. In this paper, dynamic analysis and simulation of a new type of heavy-load transfer vehicle were carried out. Firstly, the design structure of the transfer vehicle was presented, and the theoretical calculation methods for the forces on the V-shaped rollers and the dynamic deflection of the column were proposed. Then the working space of the vehicle was analyzed. And the dynamic model of rigid bodies and flexible bodies were established according to the Lagrange equations. Moreover, the velocity and acceleration of main components and the contact forces of the V-shaped rollers were analyzed by using ADAMS, and the optimal control strategy was proposed. Finally, the motors output torque of the vehicle was tested to validate the accuracy of the theoretical analysis and simulation. The experimental results are in good agreement with the theoretical and simulation results, and the dynamic performance of the transfer vehicle meets the design requirements.
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PSD Integrated Calibration Method Based on Annunciator in Vacuum Environment
Demin Wang,Junxia Jiang,Chen Wang,Jinghua Wang,Lei Bie,Yu Zheng 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.21 No.6
In this paper, an integrated calibration method for position sensitive detector (PSD) of moving support mechanism in vacuum plasma environment is proposed. That is, the PSD is used to track the laser spot to restore the coordinate information of the signal. Firstly, a PSD integrated calibration principle is proposed to reduce the position error of the signaler by tracking laser points with PSD. Then on this basis, due to the spatial declination angle in the PSD imaging model, a spatial declination correction model was established to compensate the spatial declination error. Finally, there are errors occurred in the measurement because of the nonlinearity of PSD, and the improved backpropagation (BP) neural network calibration algorithm is adopted to further correct the errors through the Fletcher–Reeves linear search method to obtain the accurate coordinate information of the annunciator. MATLAB is used to verify the convergence of the calibration algorithm error. Simulation results show that 951 epochs need to be trained by using the traditional BP algorithm to make the position error converge to 0.001 mm. But when using the improved BP algorithm, only 44 epochs are needed.
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