Research On Key Technology Of 6DOF Robotic Assembly And Detection Unit

The level of industrial automation is an important indicator for measuring the degree of modernization of a country and is also a support for the growth of the national economy.This paper starts with the field of industrial automation,focusing on the actual technical requirements,focusing on the key technical issues in the assembly and testing process.The automated production line should not be static,but should be adapted to changes in the outside world.For this reason,the decomposition of each process into units can improve efficiency and reduce costs.In the paper,the upper end of the industrial manipulator is put forward higher requirements.A jaw driven by two motors and capable of moving in the horizontal and vertical directions is designed.The control method of the motor is discussed and the MATLAB tool is used.The box is built with the simulation model of the motor,and the double closed-loop control,that is,the current and speed feedback control method is used.The simulation results show that the motor speed can be adjusted in real time and quickly according to the demand.In this paper,the assembly process of small circuit breakers in low-voltage electrical industry is taken as the research object.The internal composition and assembly steps of the circuit breaker are analyzed.The 6-DOF robot is used to replace the assembly staff,and the assembly sequence is written into the programmable logic controller.The configuration software in the touch screen is programmed to reflect the entire assembly state,thus enabling assembly of the internal parts of the circuit breaker.The article focuses on how to use the remote input and output to control the robot arm and explain how the Omron logic controller communicates with the Kunlun state-of-the-art touch screen.A flexible assembly solution is proposed for the variety of circuit breakers and the small internal structure changes.The assembly unit described in this paper can efficiently carry out the assembly tasks of the internal parts of the miniature circuit breaker on the assembly line during the experiment.Another highlight of this paper is the consideration of quality inspection methods for internal parts.The machine vision was introduced and the image processing method was applied to the quality inspection of the parts.The features of the parts were extracted by Harris and SURF corner detection methods,and the similarity of the two images was compared by image matching algorithm.In this paper,multi-class support vector machine and convolutional neural network classifier are trained respectively by extracting image feature data,and a new feature extraction method called HOGA is proposed.This algorithm can effectively deal with metal surface gloss and improve defects.The representativeness of the features,the accuracy of the identification using the classifier in the experimental process is improved compared with other algorithms.