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| Parallel Six-Axis Force Sensor with Heavy-load Capacity and Static Calibration |
| CAI Da-jun1,3,YAO Jian-tao1,2,LI Ying-kang1,YI Wang-min4,XU Yun-dou1,2,ZHAO Yong-sheng1,2 |
1. Parallel Robot and Mechatronic System Laboratory of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Key Laboratory of Advanced Forging ＆ Stamping Technology and Science, Ministry of Education of China, Yanshan University, Qinhuangdao,Hebei 066004, China
3. Engineering Training Center of Yanshan University, Qinhuangdao, Hebei 066004, China
4.Beijing Institute of Spacecraft Environment Engineering, Beijing 100094 |
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Abstract Aim at the requirements of the sensor on heavy load and small size, a hybrid branch parallel six-axis force with havey-load capacity is proposed, the structural characteristics and measuring mechanism are also explained. The calibration system of six-axis force sensor is built, and in order to improve the effect of dimensional coupling and manufacturing error on the measurement accuracy of the sensor, the model optimization of calibration algorithm is studied. The least square method and BP neural network calibration algorithm are respectively used to calibration analyze the loading experimental data, the results show that the BP neural network algorithm is better than the least square method, and the correctness of analysis results is proved by the grouping test of random data. Based on the BP neural network, a BP neural network algorithm based on artificial fish swarm algorithm is proposed, and the calibration data is calculated and analyzed by using the optimized BP neural network algorithm, the results show that the BP neural network algorithm based on artificial fish swarm algorithm is more stable and difficult to fall into local extremum.
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Received: 10 December 2019
Published: 20 August 2021
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2021, Vol. 42 
