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사출성형기 배럴의 사출 압력 손실에 관한 연구

2월 18, 2023

머리말

Injection molding process parameter setting is a field of strong experience and weak theory, and it is difficult to establish [1] for its accurate mathematical model, while data analysis technology is a method to finding knowledge from historical data, which does not need complex theoretical construction, so it is more and more widely used in this field. 예를 들어, Zhang Lingli et al. [2] used multiple regression analysis to establish a regression model for the relationship between the injection pressure and mold temperature and the geometric size of the moldingXie Peiping et al [3] discussed the relationship between the residual stress of the product by studying the type cavity pressure curve of different parts; SHEN C Y et al [4] optimized the injection process parameters to reduce the volume shrinkage of the molding product, 그리고 [5] proposed a injection process monitoring method through the network model, so as to realize fault monitoring and quality prediction.

In the previous production practice, engineers can only obtain the injection pressure data in the barrel of the injection molding machine, so the injection pressure in the barrel is often equivalent to the injection pressure in the mold cavity, while the injection pressure loss in the barrel is ignored. With the development of injection molding technology, more and moreMore and more practitioners realized that the key index affecting the quality of injection molding products was the mold cavity injection pressure rather than the injection pressure feedback by the injection molding machine, and began to pay attention to the study of injection pressure loss in the injection molding machine, but few systematic research data and conclusions were reported.

According to the technology development trend in the field of plastic injection molding, combined with the industry status, now in the injection pressure loss research, through a series of tests to obtain data, and using the data analysis technology to explore the injection pressure loss pattern, improve the injection pressure loss prediction accuracy.

Equipment and mold for study

The injection molding test is carried out on a 1 200 kN electric injection molding machine, which adopts full motor drive and PLC, frequency conversion and servo control technology, and can achieve high precision control. Control of the injection molding machine for stability

Performance can ensure the reliability and stability of the test results. The mold used for research is a two plate mold of ordinary flow channel installed with pressure sensor at the pair of gate. The cavity size is 301 mm 57 mm 2.5 mm. The formed product has uniform thickness and simple structure, which can realize the low cost and high efficiency injection test process.

To facilitate data acquisition and analysis, the ComoDataCen was utilizedThe te (central storage system for r injection process data), centralized collection and processingThe injection pressure and the sensor pressure at the mold gate, the injection test model is shown in Figure 1.

experimental method

Since the study trial was designed to explore the factors affecting the pressure during injection, the pressure

사출 속도, melt temperature, and material type as 3 objects

Study variables, with a single point of reference viscosity index (VI) between 51.6~

327.2 (single point reference viscosity index is at the specified temperature and shear rate of 1 000 / 에스) using Cross-WLFThe viscosity calculated by the viscosity model can reflect the fluidity of the material to a certain extent, perform injection tests under different melt temperature conditions at screw speeds of 20 ~ 180 mm/s, and collect injection pressure and injection sensor pressure under various injection tests. The list of research test materials is shown in Table 1.

Test data collection

Through a series of injection molding tests, the injection pressure of injection machine and mold sensor pressure curve under different process conditions of various materials are obtained, and the injection pressure curve V / P is switched

The time pressure value PF 1 and the die sensor pressure curve V / P switch

The differential pressure value of PF 2 obtains Δ PF and characterizes the injection pressure loss in the barrel of the injection molding machine in the filling stage. As shown in Figure 2, the fill phaseInjection pressure loss in the barrel of the injection machine Δ PF = 1 649-946=703bar.

For the calculation of the injection pressure loss in the barrel stage, after the pressure loss, the difference between the pressure value PP2 Δ P is the pressure loss in the pressure value in the barrel and the barrel is the pressure loss in the barrel and the injection pressure loss Δ PP=999-732=267 bar.

Analysis of trial data

Test data collation

Through the above methods, the test data of each group was sorted out and the test data table was constructed. A total of 132 groups of injection tests were conducted for 6 재료. Due to the limited space, 테이블 2 only lists some test data.

Linear regression analysis of the trial data

According to the test data, Δ PF and PF 1, Δ PF and Δ PF V, Δ PF, 각기, and melt temperature T, 그림과 같이 3 의 모양을 나타내 다 5.

Scatter plot is one of the most effective graphical methods [6] to determine whether there are connections, patterns, or trends between 2 numerical variables. 그러므로, a comparison of the scatter distribution in Figure 3 의 모양을 나타내 다 5 shows that there is a strong correlation between Δ PF and PF 1 (the pattern of plotted points leans from bottom left to topright

Obkew, meaning that the PF 1 value increases with Δ PF values, implying a positive correlation [5]), while the injection velocity V and melt temperature T are barely correlated.

The Pearson’s correlation coefficient in natural science is widely used to measure the degree of correlation between two variables, with values between-1 and 1. Peare

The inferior correlation coefficient is usually represented by the letter R, whose value is negative indicates a negative correlation between variables, and being regular indicates a positive correlation, and the greater the absolute value of R, the higher the correlation of the 2 sets of data. 그러므로, the Pearson correlation coefficient between the Δ PF and PF 1, V, 티, 그리고 3 data sets,

Fang, used to measure the degree of correlation between Δ PF and the 3 variables. R2=0.981, Δ PF and V number for 1 data sets for Δ PF and PF 1

According to R2=0.282 in the set and R2=0.534 in the T data set, the highest correlation was determined between Δ PF and PF 1, and then the number was found by minimizing the sum of squares of the error

Pressure loss coefficient of the segment. Based on the regression analysis method, for a large number of statistics

Data mathematical processing, determine the correlation between dependent variables and some independent variables, establish good correlation regression equation (function expression) [8], constructed the injection machine barrel injection pressure loss prediction mode, can optimize the injection pressure setting in the trial process, to assist technicians quickly find more reasonable injection pressure and pressure. Due to the limited test conditions, the injection pressure loss coefficient of the barrel injection between different injection molding machines is not studied and analyzed, and it is not clear between the pressure loss coefficient of the injection barrel and the equipment parameters of the injection molding machine. With the deepening of the research, more and more are in the barrel

According to the mathematical optimization technique of the best function matching [(7]

least square method),

The influencing factors related to the injection pressure loss will be mined for perfection

Fit the best matching function of Δ PF and PF 1 dataset to obtain the Δ PF about PF 1 expression:

ΔPF =0.410 1×PF1 （1）

Formula (1) can be used as a prediction model for the injection pressure loss in the barrel of the injection machine in the filling stage. In actual production, the injection pressure value in the barrel of the injection machine is easily obtained, so this model has wide applicability.

비슷하게, according to the study test data, draw the scatter plot of the pressure holding stage, 그림과 같이 6, and fit the best matching function of the pressure loss Δ PP in the barrel and the pressure injection pressure PP1 data set in the pressure holding stage:

ΔPP =0.258 9×PP1

The above studies show that the loss of injection pressure is not correlated with the injection speed and melt temperature, but is strongly associated with the injection pressure in the barrel, and can be determined by constructing (fx) =kx functionShooting pressure loss, x is the barrel injection pressure of the injection molding machine, and k is the pressureloss efficiency. Furthermore, equations (1) 그리고 (2) reveal the basic phenomenon of different injection pressure loss coefficient in the barrel during different injection stages (filling and pressure retention).

tag

For a long time, engineers have no research on the injection pressure loss in the barrel of the injection molding machine. 일반적으로, the flow simulation analysis generally only considers the pressure transfer in the mold, so that the estimation of the injection pressure deviates. A new pattern of injection pressure loss is revealed: Δ P =k P, Δ P =k P; where k k is the filling and pressure preservation stepPressure loss coefficient of the segment. Based on the regression analysis method, for a large number of statistics

Data mathematical processing, determine the correlation between dependent variables and some independent variables, establish good correlation of regression equation (function expression) [8], the construction of barrel injection pressure loss prediction mode, can optimize the injection pressure setting in the trial process, to assist technicians quickly find more reasonable injection pressure and pressure. Due to the limited test conditions, the injection pressure loss coefficient of the barrel injection between different injection molding machines is not studied and analyzed, and it is not clear between the pressure loss coefficient of the injection barrel and the equipment parameters of the injection molding machine. With the deepening of the research, more and more are in the barrelThe influencing factors related to the injection pressure loss will be mined for perfectionAnd improve the prediction model of injection pressure loss in the barrel of injection molding machine, and promote the improvement of the pressure solver of flow simulation analysis software, and promote the automation and intelligent development of injection process optimization method.