Research And Development Of Electrostatic Spray Controller

Electrostatic spraying technology is widely used in automotive,marine,aerospace and other fields because of its advantages of green environment protection,good quality of coating film,high yield and high reutilisation rate of paint.As the core component of the electrostatic spraying control system,the function and performance of the electrostatic spraying controller directly affects the spraying effect.At present,the domestic research and design of electrostatic spraying controller is relatively small,domestic electrostatic spraying controller still exists a series of problems.Firstly,most electrostatic spray controllers still use off-line parameter settings,making it very inconvenient to adjust parameters when multiple controllers are working together.Secondly,most controllers still use open-loop control of the output gas flow rate,which cannot guarantee a stable output gas flow rate in the case of fluctuating gas sources.Thirdly,due to the Faraday cage shielding effect and the anti-ionisation phenomenon,the powder rate on the bottom of the groove is seriously low when spraying the groove workpiece with the controller developed so far.Fourth,when spraying groove workpieces,the spraying parameter setting method,which relies on manual experience,lacks scientificity and requires several spraying experiments in order to achieve the target film thickness at the bottom of the groove workpiece.In order to solve the above problems,an electrostatic spraying controller was designed,which realized the functions of on-line parameter setting,closed-loop control of output gas flow,closed-loop control of output electrostatic,optimization of spraying of workpiece in groove and prediction of film thickness at the bottom of groove based on BP neural network.The main research contents are summarized as follows:Firstly,the selection of embedded chips is completed by analysing the characteristics of mainstream embedded chips.According to the functional requirements of electrostatic spraying controller,the hardware architecture of electrostatic spraying controller was designed.According to the hardware architecture,the power management circuit,electrostatic generating circuit,electrostatic current detection circuit,electrostatic voltage detection circuit,stepper motor driving circuit and air pressure detection circuit were designed to complete the development of electrostatic spraying controller hardware circuit.Secondly,the software architecture of electrostatic spraying controller was designed based on ?COS-? real-time system,and the transplantation of ?COS-? real-time system was completed.The communication content between host and electrostatic spraying controller was developed,and the CANopen object dictionary was created according to the communication content,and the transplantation of CANopen protocol was completed.The mathematical model of output gas flow and pressure was established,and the gas flow was collected based on the mathematical model and pressure sensor,and the software of output gas flow closedloop control was developed.The collected electrostatic signals were filtered based on the Kalman filter algorithm and the software development of the output electrostatic closed loop control function was completed using the PID algorithm.Once again,the main reasons affecting the powder rate on the bottom of the groove workpiece were analysed,an innovative coating method with intermittent electrostatic output was proposed and its optimisation principle was described,the software programme design of the intermittent electrostatic output method was completed,the experiments were carried out to measure the range of values of the spraying parameters of the intermittent electrostatic output method,which provide a rational basis for the setting of coating parameters when applying the electrostatic intermittent output method.Then,to address the problem of the lack of scientific setting of spraying parameters,a BP neural network-based method for predicting the thickness of the coating film at the bottom of the groove was proposed based on the characteristics of the BP neural network with strong ability of nonlinear approximation and high operational efficiency.A three-layer fullyconnected neural network was constructed,the software program of the neural network model was designed,and the neural network training samples were collected and trained.The neural network can accurately and quickly calculate the thickness of the coating film at the bottom of the groove under different spraying parameters,providing an accurate reference basis for the setting of spraying parameters.Finally,a test host was developed based on QT and the controller was tested and applied on the electrostatic spraying production line of a Guangdong coating technology company.The experimental results show that the electrostatic intermittent output method can effectively improve the powder rate at the bottom of the groove,and the neural network can accurately predict the film thickness at the bottom of the groove according to different spraying parameters.The electrostatic spraying controller runs stably,and the film quality of the spraying workpiece meets the national standard,which can meet the production requirements of enterprises.