An algorithm of auto-searching weld line for welding mobile robot is presented. Auto-searching weld line is that the robot can automatically recognize a weld groove according to the characteristics of the weld groove ...An algorithm of auto-searching weld line for welding mobile robot is presented. Auto-searching weld line is that the robot can automatically recognize a weld groove according to the characteristics of the weld groove before welding, and then adjust itself posture to the desired status preparing for welding, namely, it is a process that the robot autonomously aligns itself to the center of welding seam. Firstly, the configuration of welding mobile robot with the function of auto-searching weld line is introduced, then the algorithm and implementation of auto-searching weld line are presented on the basis of kinematics model of the robot, at last trajectory planning among auto-searching weld line is investigated in detail. The experiment result shows that the developed welding mobile robot can successfully implement the task of auto-searching weld line before welding, tracking error precision can be controlled to approximate ±1.5 mm, and satisfy the requirement of practical welding project.展开更多
The development of welding robots suitable for specially unstructured working enviroments has been become an important development direction of industrial robot application because large-scale welding structures have ...The development of welding robots suitable for specially unstructured working enviroments has been become an important development direction of industrial robot application because large-scale welding structures have been used more and more widely in modern industry. In this paper, an intelligent mobile robot for welding of ship deck with the function of autosearching weld line was presented. A wheeled motion mechanism and a cross adjustment slider are used for the welding robot body. A sensing system based on laser-PSD (position sensitive detector) displacement sensor was developed to obtain two dimensional deviation signals during seam tracking. A full-digital control system based on DSP and CPLD has also been realized to implement complex and high-performance control algorithms. Furthermore, the system has still the function of auto-searching weld line according to the characteristics information of weld groove and adjusting posture itself to the desired status preparing for welding. The experiment of auto-searching welding line shows that the robot has high tracing accuracy, and can satisfy the requirement of practical welding project.展开更多
Three kinds of methods for processing the data of the multi-wavelength pyrometer are presented in this paper and are named curve auto-search method, curve auto-regression method and neural network method. Tbe experime...Three kinds of methods for processing the data of the multi-wavelength pyrometer are presented in this paper and are named curve auto-search method, curve auto-regression method and neural network method. Tbe experimental results indicate that the calculated temperature and the spectral emissivity compared with the true target temperature and spectral emissivity have significant deviation using the curve auto-search and the curve auto-regression methods. However, the calculated temperature and the spectral emissivity with higher accuracy can be obtained using the neural network method.展开更多
基金This project is supported by Program of International Science and Technology Cooperation(No.2004 DFA02400).
文摘An algorithm of auto-searching weld line for welding mobile robot is presented. Auto-searching weld line is that the robot can automatically recognize a weld groove according to the characteristics of the weld groove before welding, and then adjust itself posture to the desired status preparing for welding, namely, it is a process that the robot autonomously aligns itself to the center of welding seam. Firstly, the configuration of welding mobile robot with the function of auto-searching weld line is introduced, then the algorithm and implementation of auto-searching weld line are presented on the basis of kinematics model of the robot, at last trajectory planning among auto-searching weld line is investigated in detail. The experiment result shows that the developed welding mobile robot can successfully implement the task of auto-searching weld line before welding, tracking error precision can be controlled to approximate ±1.5 mm, and satisfy the requirement of practical welding project.
文摘The development of welding robots suitable for specially unstructured working enviroments has been become an important development direction of industrial robot application because large-scale welding structures have been used more and more widely in modern industry. In this paper, an intelligent mobile robot for welding of ship deck with the function of autosearching weld line was presented. A wheeled motion mechanism and a cross adjustment slider are used for the welding robot body. A sensing system based on laser-PSD (position sensitive detector) displacement sensor was developed to obtain two dimensional deviation signals during seam tracking. A full-digital control system based on DSP and CPLD has also been realized to implement complex and high-performance control algorithms. Furthermore, the system has still the function of auto-searching weld line according to the characteristics information of weld groove and adjusting posture itself to the desired status preparing for welding. The experiment of auto-searching welding line shows that the robot has high tracing accuracy, and can satisfy the requirement of practical welding project.
基金Sponsored by the National Natural Science Foundation of China(Grant No. 60377037)the Scientific Research Foundation of Harbin Institute of Technol-ogy (Grant No. HIT. 2002. 18)the Spaceflight Support Foundation.
文摘Three kinds of methods for processing the data of the multi-wavelength pyrometer are presented in this paper and are named curve auto-search method, curve auto-regression method and neural network method. Tbe experimental results indicate that the calculated temperature and the spectral emissivity compared with the true target temperature and spectral emissivity have significant deviation using the curve auto-search and the curve auto-regression methods. However, the calculated temperature and the spectral emissivity with higher accuracy can be obtained using the neural network method.