The function of the filling machine is to fill drinks into containers and seal them. It is widely used in the food industry, such as filling and pouring soda, beer, juice drinks and other products. The filling process is mainly divided into five steps: centering the bottle valve, opening the valve to inflate and equalize pressure, feeding liquid and returning air, closing the valve to relieve pressure, and finishing filling. After filling, the bottle enters the capping machine through the intermediate pulsator and rotates with the capping turntable to complete the capping during operation. It can be said that the filling and capping machine is an important part of beverage packaging machinery, and its working efficiency will affect the overall efficiency of the filling machine. The working principle of the capping machine is “filling with a bottle opening valve, but without a bottle opening valve”. Its model has many functions. By replacing different accessories, it can complete the anti-theft and rolling of the caps of oral liquid and liquor, the screwing of various plastic caps, and the capping of crown caps such as soda beer. It is difficult to control the sealing pressure of the traditional filling and sealing machine, and it is difficult to intensively control the quantitative indicators. Excessive pressure will lead to damage and even failure of the sealing, while too small pressure will lead to problems such as lax sealing of the sealing and unqualified product quality.
In view of the problem that the capping pressure is difficult to control, many scholars have studied it. If PID control algorithm with the dead zone is adopted.
Pressure tracking control method of pressure vessel: The main steam pressure control method based on the Smith-RBF neural network with mismatch compensation is designed. However, after practical application, it is found that these two methods cannot effectively guarantee the stability of dynamic pressure control. Programmable Logic Controller (PLC) provides the possibility to solve this problem. PLC is a digital operation electronic system specially designed for application in an industrial environment. Its programming appears in the form of a ladder diagram, and its main functions include the shutdown of the main engine, inching debugging, cleaning of broken bottles, control of switches, failure shutdown, etc. PLC has the advantages of flexible structure, simple maintenance and small volume. Therefore, aiming at the shortcomings of traditional methods, PLC is used to dynamically control the capping pressure of the filling capping machine, and a PL controller is electrically connected with the filling capping machine to improve the capping pressure control of the filling capping machine. The parameter self-tuning fuzzy PID control algorithm is used to effectively solve the problem of poor pressure control effect caused by the fact that the conventional PLC controller can only realize static coupling and eliminate steady-state errors, so as to effectively reduce the use cost of machinery, ensure the safe and stable operation of equipment, improve the automation efficiency and quality of production and ensure economic benefits.
1. Design of dynamic control method for capping
1.1 Composition of PLC
PLC structure = the core is the central processing unit, which is managed and controlled by the system program.
The PLC compiles a user program by analyzing the pressure of the controlled object, and the CPU saves the compiled program and related settings of the controlled object and processes the saved information according to the compiled user program. The actuator of the capping machine sends work orders to the input interface, and the information is processed by the CPU of the central processing unit and fed back to the actuator by the output interface in the form of output signals to complete the work orders. At the same time, the PLC can also receive signals from the expansion unit through the expansion interface and signals from other PLCs, programmers, monitoring equipment, external storage and other equipment through the external equipment interface during operation.
1.2 Control algorithm
The application of parameter self-tuning fuzzy PID control algorithm in PLC can realize the static coupling control of capping pressure and eliminate the steady-state error, and eliminate the dynamic coupling through the strong adaptive ability of fuzzy control.
After applying the fuzzy PID control algorithm of parameter self-tuning, the PLC controller can accelerate the response speed when the pressure deviation is large through fuzzy control, and can also switch to PID control when the pressure deviation is small, thus eliminating static error and improving control accuracy.
After initializing the canning and capping machine, the capping pressure of the capped pressure controlled object is controlled by PLC controller, the start button is pressed, the electromagnetic valve and vacuum pump are started to control the capping pressure of the controlled target, and whether the pressure value reaches the rated value is judged by parameter setting of the PLC controller’s parameter self-tuning fuzzy PID control algorithm. If not, continue to perform parameter tuning until the pressure reaches the rated value, thus completing the dynamic control of the sealing pressure.
2. Results and analysis
In order to verify the practical application performance of the dynamic control method of capping pressure of filling capping machine based on PLC, a simulation test was designed to verify it.
2.1 Test equipment
Taking the filling and capping machine as the test object, the electrical connection was formed between the filling and capping machine and the PLC controller, so as to explore the dynamic control performance of the capping pressure of the test method. Parameters of the capping machine are as follows: machine power 370 W, machine mass 65 kg, production capacity 25 pieces /min, applicable range: tank diameter 39-150 mm, tank height 30-150 mm.
2.2 Result analysis
In order to effectively verify the application performance of the test method to the capping pressure of the filling capping machine and avoid the singleness of the test results, the test method, the pressure tracking control method based on PID control algorithm with dead zone and the pressure control method based on Smith-RBF neural network with mismatch compensation were selected to dynamically control the capping pressure, and the advantages and disadvantages of the test methods were verified by comparing the dynamic control effects of the three methods.
Comparing the step response curves of the capping pressure of the three methods when the capping pressure of the filling machine is set at 3 MPa, the capping pressure controlled by the test method can quickly reach the set value of 3 MPa from the initial point 0; Under the control of the method based on dead-zone PID control algorithm, the sealing pressure fluctuates greatly, which tends to be stable after 30 s, and the stable pressure is close to the set pressure. The fluctuation range of capping pressure controlled by the Smith-RBF neural network based on mismatch compensation is the largest among the three methods, which tends to balance after 40 s and is higher than the set pressure. Compared with the method based on the PID control algorithm with dead zone and Smith-RBF neural network, the capping pressure controlled by the test method has a smaller overshoot and shorter adjustment time. Meanwhile, the test method can also ensure the elimination of small-scale oscillation near the working point and the absence of steady-state error, thus verifying that the capping pressure of the filling capping machine controlled by the test method has a short response time and high automatic control accuracy.
On this basis, the capping pressure was adjusted to 4 MPa, and three methods were applied to dynamically control the capping pressure of the canning capping machine, and the pressure change process was monitored in real-time. When the pressure was set at 4 MPa, the capping pressure fluctuated excessively. In Figure (a), the maximum fluctuation range of the capping pressure caused by excessive fluctuation was 0.36 MPa, which was 9% of the set pressure, indicating that the test method started automatic control at 2: 00 through analysis and calculation. In fig. (b), the maximum fluctuation range of excess value fluctuation caused by the capping pressure is 0.51 MPa, which is 12.75% of the set pressure value, indicating that the method based on PID control algorithm with dead zone starts automatic control by analysis and calculation at 2: 00, and the pressure fluctuation is controlled within the range of -0.1-0.1 MPa after 6 s of control response time. In fig. (c), the maximum fluctuation range of the excess value fluctuation caused by the capping pressure is 0.59 MPa, which is 14.75% of the set value of the pressure, indicating that the method based on Smith-RBF neural network with mismatch compensation starts automatic control by analysis and calculation at 2: 00, and the pressure fluctuation is controlled within the range of -0.2-0.2 MPa after the control response time of 6s. Under the three methods, the pressure of automatic control no longer fluctuates excessively. Although they all tend to be stable, the fluctuation range of the test method is the smallest and the fluctuation range is the most stable. The control errors and time delays of the other two methods are larger than those of the test method.
Adjust the pressure value to 0.5 MPa, and count the performance of automatic sealing pressure control by three methods. The test results are shown in Table 1. It can be seen from Table 1 that the overshoot of the filling and capping machine under the control of the test method is 0.11%, and the capping pressure can be controlled to maintain stability in only 5 s, and its capping pressure control error is small and the time lag is short, which eliminates the steady-state error and solves the contradiction between the improvement of response speed and the reduction of overshoot, and the comprehensive performance is obviously superior to the other two methods.
The test results show that the filling and capping machine using the test method can quickly reach a stable state according to different capping requirements in the actual operation process, and achieve the purpose of dynamic control of capping pressure. In order to verify the suppression ability and stability robustness of the test method to the random disturbance in the pressure control process of the filling and capping machine, the constant disturbance amplitude is set at 5% when the capping pressure is 50s, and random noise is added to it, with the maximum amplitude being 0.5% of the set value. Compared with the comparison method, the amplitude of the corresponding fluctuation caused by random disturbance of the capping pressure of the filling capping machine after the application of the test method is smaller, and the output change amplitude of the corresponding controller is relatively smallest, which can ensure the stable operation of the filling capping machine. Compared with the two comparison methods, the experimental method has better suppression ability and robustness to random disturbances.
The dynamic control method of the capping pressure of the filling capping machine based on PLC was studied, and the capping pressure of the filling capping machine was controlled by using a PLC controller. The superiority of the test method is verified by the comparison method. The response speed and control accuracy of the test method are higher than those of the two comparison methods. At the same time, the test method has better disturbance suppression ability. The operation of the whole capping process is more safely and stably guaranteed. At the same time, the pressure is fast and stable, and the control performance is remarkable.