Research On Intelligent Control Of Space Precision Parts Pretreatment Equipment

Space precision parts require surface cleaning pre-treatment before use.At present,the pre-treatment process is manually completed by ultrasonic cleaning machines.In order to improve the automation level of the cleaning process and reduce the problems caused by manual participation,this subject designs a space precision parts preprocessing equipment with an ultrasonic cleaning machine as the core,and combines intelligent control technology to achieve full process automation of the preprocessing process.According to the pretreatment requirements of space precision parts,in order to complete the cleaning treatment of large and small parts,the mechanical structure of the pretreatment equipment was designed,and the dynamic analysis of the six degrees of freedom manipulator was carried out using D-H parameters,and its working radius was solved.The space precision parts preprocessing equipment can achieve the functions of grabbing and transporting cleaning beakers and parts cleaning baskets,adding cleaning solvents,collecting cleaning solvent waste liquid,cleaning beakers,ultrasonic cleaning of parts,and air drying of parts.The control system of the preprocessing equipment consists of an upper computer system and a lower computer system.The hardware platform of the lower computer control system consists of Siemens ET200 SP PLC,V90 servo system,robotic arm,and sensors.The use of servo motor linear module and manipulator cooperation to achieve multi station cleaning beaker and parts cleaning basket grasping and handling work.The peristaltic pump and solvent weighing sensor are used to achieve high-precision filling of cleaning solvent,and to achieve beaker cleaning.To prevent the impact of mechanical vibration on the accuracy of the counterweight,a mean filtering algorithm is used to filter the analog quantity data to ensure that the amount of cleaning solvent injected meets the accuracy requirements.Perform hardware configuration and communication settings on the PLC using Siemens TIA software,and complete the development of the lower computer control program..The upper computer intelligent control system is developed using C++language through Qt to achieve equipment cleaning process selection,mechanical arm inching control,workstation image recognition and detection,parameter setting,and operation status display.Human-computer interaction is achieved through industrial tablets.Workstation image recognition and detection is based on deep learning technology,using the YOLOv5 s neural network target detection algorithm,using 8000 images to train the target detection network to convergence through 300 epochs.With a confidence threshold of 0.5,the accuracy rate reaches 92.4%.using image acquisition to achieve work piece seat recognition and positioning,the safety issues caused by the use of photoelectric sensors when solvent splashes may occur are solved.The upper computer communicates through TCP network and realizes the control of the lower computer based on Modbus protocol.Install and debug the hardware and software of the mechanical equipment and control system.Field experiments show that the research content of this article meets the needs of practical applications,effectively reducing labor costs,improving cleaning efficiency,and has certain practical engineering application value.