Real-time monitoring method for melt index of modified engineering plastic

Abstract

The invention provides a modified engineering plastic melt index real-time monitoring method which comprises the following steps: determining a melt index difference value of adjacent monitoring points by acquiring a melt index value of each section of an extrusion production line; obtaining the number of shearing cycles of the extrusion production line, identifying the fiber shearing damage degree of each section according to the melt index difference and the number of shearing cycles to obtain fiber damage distribution, and determining the fiber fracture position according to the fiber damage distribution; the melt index difference value corresponding to the fiber fracture position is analyzed by obtaining the melt index of the fiber fracture position, and the monitoring point interval is dynamically adjusted through the melt index difference value; and obtaining the melt index value and the fiber shortening amplitude after the interval adjustment of the monitoring points, and comparing the melt index change and the fiber length loss of each monitoring point to obtain the corresponding distribution of the fiber shortening amplitude and the melt index value.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of information technology, and in particular to a modified engineering plastic melt index real-time monitoring method. BACKGROUND

[0002] In modern manufacturing, the research and application of carbon fiber modified engineering plastics occupy an important position. This material is widely used in the fields of automobiles, aerospace, etc. due to its high strength and lightweight characteristics, and has become a key support for promoting industrial technology progress. However, despite its great potential, how to ensure the stability of the material's performance during processing is still a challenge that needs to be solved, especially in the monitoring and control of melt index, a core indicator. At present, although many methods try to obtain data during material processing by fixing monitoring points, these methods often ignore the dynamic influence of internal structure changes of the material during processing. Especially in extrusion processing, the shear action on the material will continuously change its physical properties. The arrangement of fixed interval monitoring points can uniformly collect data, but when considering the fiber shortening caused by screw shearing, the melt index increases monotonically along the extrusion direction and the change rate is different. Fiber length attenuation is caused by the shearing action of the device screw, and the strength and frequency of this shearing action are not consistent at different stages and positions of processing, resulting in an irregular change trend of the melt index in the extrusion direction. Due to the failure to effectively capture the phased characteristics of this change, it is difficult for technical personnel to accurately determine the specific distribution position of fiber breakage and predict the performance of the final product in advance. Specifically, in a extrusion production line, the material from entering the screw to the final molding process, the fiber may be rapidly broken in some areas due to high-intensity shearing, while in other areas it remains relatively stable. If the specific location and degree of these breakage cannot be identified in time, it is difficult to make targeted adjustments to the processing parameters. For example, in the area close to the front end of the screw, the fiber may be greatly shortened due to initial shearing, resulting in a rapid rise in melt index, while in the rear area, the shearing action is weakened, and the change trend becomes flat. This inconsistency makes the overall monitoring extremely complex. Therefore, how to dynamically capture the influence of fiber length attenuation on melt index during processing and accurately identify the phased distribution characteristics of fiber breakage has become a key problem to improve the prediction accuracy of the quality of the final product. SUMMARY

[0003] The present application provides a modified engineering plastic melt index real-time monitoring method, the method comprising: Obtaining the melt index value of each section of the extrusion production line, and determining the melt index difference value of adjacent monitoring points; obtaining the number of shear cycles of the extrusion production line, identifying the fiber shear damage degree of each section according to the melt index difference and the number of shear cycles, obtaining the fiber damage distribution, and determining the fiber fracture position according to the fiber damage distribution; obtaining the melt index of the fiber fracture position, analyzing the melt index difference corresponding to the fiber fracture position, and dynamically adjusting the monitoring point interval according to the melt index difference; obtaining the melt index value and the fiber shortening amplitude after the monitoring point interval is adjusted, comparing the melt index change and the fiber length loss of each monitoring point, and obtaining the corresponding distribution of the fiber shortening amplitude and the melt index value; extracting the melt index change trend of each section according to the corresponding distribution of the fiber shortening amplitude and the melt index value, obtaining the melt index prediction curve along the extrusion direction, and predicting the melt index change amount of the downstream monitoring point according to the melt index prediction curve; combining the predicted melt index change amount with the fiber fracture position, identifying the fiber fracture type, determining the production line temperature adjustment amount and the screw speed adjustment amount according to the temperature sensitivity and the shear sensitivity corresponding to the fiber fracture type.

[0004] Further, the obtaining of the melt index value of each section of the extrusion production line and the determination of the melt index difference of adjacent monitoring points comprises: obtaining the temperature sensing reading of a preset position in the barrel of the extrusion production line, determining the viscosity value of each position according to the inverse proportional relationship between the temperature value and the melt viscosity, calculating the initial melt index value of each monitoring point according to the corresponding formula of the viscosity value and the melt index, collecting the initial melt index value of adjacent monitoring points, calculating the numerical difference between the front and rear monitoring points, and taking the numerical difference as the melt index difference of adjacent monitoring points.

[0005] Further, the obtaining of the number of shear cycles of the extrusion production line, the identification of the fiber shear damage degree of each section according to the melt index difference and the number of shear cycles, the obtaining of the fiber damage distribution, and the determination of the fiber fracture position according to the fiber damage distribution comprise: obtaining the screw speed and the barrel length of the extrusion production line, calculating the number of shear cycles according to the residence time of the material in the barrel, taking the product of the number of shear cycles and the melt index difference as the damage coefficient of each monitoring section, determining the fiber shear damage degree of each section according to the ratio of the damage coefficient to the damage threshold, constructing the fiber damage distribution curve along the extrusion direction according to the damage coefficient value of each section, calculating the gradient change rate by using the differential method to calculate the slope change of adjacent points of the fiber damage distribution curve, and determining the fiber fracture position according to the gradient change rate.

[0006] Further, the obtaining of the melt index of the fiber fracture position, the analysis of the melt index difference corresponding to the fiber fracture position, and the dynamic adjustment of the monitoring point interval according to the melt index difference comprise: Obtaining the melt index measured value at the fiber fracture position, calculating the melt index difference value of the adjacent monitoring points before and after the fiber fracture position, dividing the melt index difference value by the original monitoring point interval to obtain the change rate coefficient, multiplying the change rate coefficient by the reference monitoring interval to calculate the adjusted monitoring point interval value, and re-determining the position of each monitoring point according to the adjusted monitoring point interval value.

[0007] Further, the melt index value obtained after adjusting the monitoring point interval and the fiber shortening amplitude are compared with the melt index change and the fiber length loss of each monitoring point to obtain the corresponding distribution of the fiber shortening amplitude and the melt index value, including: According to the adjusted monitoring point distribution scheme, the melt index measured value of each point is collected, the average length of the fiber is measured, the ratio of the average length of the fiber to the length of the raw material before extrusion is taken as the fiber shortening amplitude, the difference between the melt index measured value of each monitoring point and the initial melt index before extrusion is taken as the melt index increment, and the corresponding relationship curve is fitted by using the linear regression method according to the fiber shortening amplitude and the melt index increment.

[0008] Further, the melt index change trend of each section is extracted according to the corresponding distribution of the fiber shortening amplitude and the melt index value to obtain a melt index prediction curve along the extrusion direction, and the melt index change amount of the downstream monitoring point is predicted according to the melt index prediction curve, including: The average value of three consecutive data points in each monitoring section is calculated by using the moving average method, the difference between the adjacent average values is divided by the monitoring point interval to obtain the melt index change slope of each section, the melt index prediction curve equation is constructed by using the cubic polynomial fitting method according to the melt index change slope data, and the melt index prediction value of the target monitoring point downstream is calculated according to the melt index prediction curve equation, and the difference between the prediction value and the measured value of the current monitoring point is taken as the melt index change amount.

[0009] Further, the predicted melt index change amount is combined with the fiber fracture position to identify the fiber fracture type, the temperature adjustment amount and the screw speed adjustment amount are determined according to the temperature sensitivity and the shear sensitivity corresponding to the fiber fracture type, including: According to the predicted melt index change amount and the corresponding relationship between the fiber fracture position, the temperature-induced fracture or the shear-induced fracture is determined, the corresponding temperature sensitivity coefficient and the shear sensitivity coefficient are obtained through the fracture type, the parameter adjustment reference value is determined by multiplying the sensitivity coefficient by the deviation of the melt index measured value and the standard value, the production line temperature adjustment amplitude and the screw speed adjustment amplitude are determined according to the parameter adjustment reference value, the temperature adjustment amount of each heating section is calculated according to the temperature adjustment amplitude and the heat conduction characteristic, and the screw speed adjustment amount is determined according to the screw speed adjustment amplitude.

[0010] Further, the predicted melt index change amount is combined with the fiber breakage position to identify the fiber breakage type, including: According to the melt index change amount, the change rate between adjacent monitoring points is calculated to determine a sharp fluctuation mode or a gentle fluctuation mode, a breakage sample is collected from the fiber breakage position to measure the breakage cross-section surface roughness and the fiber end necking zone length, the roughness texture feature is determined according to the breakage cross-section surface roughness to judge brittle breakage, the stretching trace is determined according to the necking zone length to judge ductile breakage, and the temperature sensitivity coefficient corresponding to the brittle breakage and the shear sensitivity coefficient corresponding to the ductile breakage are obtained.

[0011] The technical scheme provided by the embodiment of the present application can include the following beneficial effects: The present application discloses a modified engineering plastic melt index real-time monitoring method, which is aimed at the business scene problems of fiber shear damage and breakage position identification, melt index change prediction and dynamic adjustment of process parameters in the extrusion production process. The difference value is calculated by obtaining the melt index value of each section, the fiber damage degree is evaluated by combining the shear cycle number, the breakage position is determined, and the monitoring point interval is dynamically adjusted according to the melt index difference value. Then, the corresponding relationship between the melt index change and the fiber length loss is analyzed, the change trend is extracted, the downstream melt index change amount is predicted, and finally the production line temperature and screw speed adjustment amount are determined by combining the breakage type, temperature and shear sensitivity. Through the comprehensive analysis of melt index prediction and fiber damage distribution, the present application realizes the accurate identification of fiber breakage type and the intelligent optimization of process parameters, effectively reduces the fiber damage, and improves the production efficiency and product quality. BRIEF DESCRIPTION OF DRAWINGS

[0012] Fig. 1 The flowchart of the modified engineering plastic melt index real-time monitoring method of the present application.

[0013] Fig. 2 The schematic diagram of the modified engineering plastic melt index real-time monitoring method of the present application.

[0014] Fig. 3 The schematic diagram of the modified engineering plastic melt index real-time monitoring method of the present application. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be described in detail below in combination with the drawings and specific embodiments.

[0016] As Figs. 1-3 , the modified engineering plastic melt index real-time monitoring method of the present embodiment can specifically include: Step S101, by acquiring the melt index value of each section of the extrusion production line, the melt index difference value of adjacent monitoring points is determined.

[0017] The temperature sensor readings of the preset positions in the barrel of the extrusion production line are obtained, the viscosity values of each position are determined according to the inverse proportional relationship between the temperature value and the melt viscosity, and the initial melt index values of each monitoring point are calculated through the corresponding formula of the viscosity value and the melt index. The initial melt index values of adjacent monitoring points are collected, the numerical difference between the front and rear monitoring points is calculated, and if the difference exceeds the preset threshold, it is judged that there is a shear effect in this section. The numerical difference is taken as the melt index difference value of adjacent monitoring points.

[0018] Specifically, in an embodiment, the melt flow index (MFI) is an important parameter to characterize the flowability of thermoplastic melt, which is defined as the mass of melt extruded in 10 minutes under specified temperature and load, with the unit of g / 10min. The larger the melt flow index, the better the material flowability. In an embodiment, a plurality of temperature sensors are uniformly arranged in the barrel of the extrusion production line along the axial direction, and a monitoring point is set every 200 millimeters. The temperature value collected by the temperature sensor is converted into the corresponding melt viscosity value through the Arrhenius equation, and for every 10 degrees Celsius increase in temperature, the viscosity value of the carbon fiber modified plastic decreases by about 30%.

[0019] Specifically, there is a power law relationship between the viscosity value and the melt index, and the melt index is equal to a constant divided by the 0.8 power of the viscosity value. Through the corresponding formula, the viscosity value of each monitoring point is converted into the initial melt index value, forming a melt index distribution sequence along the extrusion direction.

[0020] Exemplarily, the initial melt index values of adjacent monitoring points are obtained by difference operation to obtain the change amount. The preset threshold is set to 0.5 g / 10min according to the characteristics of the carbon fiber modified material, and when the melt index difference value of adjacent monitoring points exceeds the threshold, it is determined that there is obvious shear effect in the barrel of this section, and the fiber is broken in this section. The melt index difference value directly reflects the damage degree of the fiber in different sections.

[0021] Step S102, the number of shear cycles of the extrusion production line is obtained, the fiber shear damage degree of each section is identified according to the melt index difference value and the number of shear cycles, the fiber damage distribution is obtained, and the fiber breakage position is determined according to the fiber damage distribution.

[0022] The screw rotation speed of the extrusion production line and the barrel length are obtained, the shear cycle number is calculated according to the residence time of the material in the barrel, and the product of the shear cycle number and the melt index difference value is taken as the damage coefficient of each monitoring section. By comparing the damage coefficient with the damage threshold value set based on the material characteristics, if the damage coefficient exceeds the threshold value, it is determined that the fiber shear damage degree of this section is serious, and the fiber damage distribution curve along the extrusion direction is constructed according to the damage coefficient values of each section. The slope change of adjacent points of the fiber damage distribution curve is calculated by using the difference method, the gradient change rate is obtained, the peak point of the gradient change rate is identified, and when the peak value exceeds the preset threshold value, the position of the monitoring point is determined as the fiber fracture position.

[0023] Specifically, in one embodiment, the screw rotation speed of the extrusion production line is obtained in real time by a frequency converter, and the barrel length is a fixed value of 1200 mm. The residence time of the material in the barrel is calculated according to the feeding rate and the barrel volume, wherein the feeding rate is obtained in real time by a feeding port weighing sensor. When the screw rotation speed is 60 revolutions per minute, the average residence time of the carbon fiber modified plastic is about 3 minutes, and the corresponding shear cycle number is 180 times.

[0024] Specifically, the damage coefficient is determined by the product of the shear cycle number and the melt index difference value. The calculation formula of the damage coefficient is: D=N x AMI, wherein D is the damage coefficient, N is the shear cycle number, and AMI is the melt index difference value (g / 10min). The coefficient comprehensively reflects the cumulative effect of shear number and strength on fiber damage. For example, when the shear cycle number N=150 times and the melt index difference value AMI=0.8 g / 10min, the damage coefficient D=150 x 0.8=120. The damage threshold value D_threshold is set according to the fracture toughness of the material, and when D>D_threshold, it is determined as serious damage.

[0025] It should be noted that the fiber damage distribution curve is constructed by using a cubic spline interpolation method. The damage coefficients of the monitoring points are taken as discrete data points, and a continuous and smooth distribution curve is generated by using an interpolation algorithm. The distribution curve can intuitively reflect the change rule of the fiber damage along the extrusion direction, and the curve slope mutation place often corresponds to the fiber fracture area.

[0026] In one possible implementation, the process of calculating the gradient change rate by using the difference method includes: calculating the difference between the damage coefficients of adjacent two monitoring points, and dividing the monitoring point interval to obtain the local slope; the difference between the adjacent two local slopes is the gradient change rate. When the gradient change rate exceeds the preset peak value 5.0, it indicates that the fiber fracture degree at this position increases sharply.

[0027] Preferably, the determination of the fiber breakage position is also combined with the material flow state. In the compression section of the screw, due to strong shearing effect, the peak of the gradient change rate usually appears in the middle and rear part of the section; in the metering section, the shearing effect is weakened, and the gradient change rate tends to be flat. By identifying multiple gradient peak points, the main position and the secondary position of the fiber breakage can be determined, which provides a basis for subsequent monitoring point optimization adjustment.

[0028] In step S103, the melt index difference corresponding to the fiber breakage position is analyzed by obtaining the melt index of the fiber breakage position, and the monitoring point interval is dynamically adjusted by the melt index difference.

[0029] The melt index measured value at the fiber breakage position is obtained, the melt index difference of the adjacent monitoring points before and after the breakage position is calculated, and the change rate coefficient of the section is obtained by dividing the original monitoring point interval. The change rate coefficient is multiplied by the initial set reference monitoring interval of the production line to calculate the adjusted monitoring point interval value, and if the change rate coefficient is greater than the preset threshold value, the monitoring point interval is reduced. The positions of the monitoring points are re-determined according to the adjusted monitoring point interval value, the number of monitoring points is increased according to the reduced interval in the fiber breakage intensive area, and a dynamically optimized monitoring point distribution scheme is obtained.

[0030] Specifically, in one embodiment, the melt index measured value of the fiber breakage position is obtained by a high-precision melt index instrument, and the measurement accuracy reaches 0.01 g / 10 min. The melt index difference of adjacent monitoring points reflects the severity of fiber damage in the section, and the larger the difference, the more serious the fiber breakage. The change rate coefficient is calculated by dividing the melt index difference by the original monitoring point interval, and the unit is g / 10 min / mm.

[0031] Specifically, when the carbon fiber modified plastic experiences strong shearing in the compression section of the screw, the melt index difference usually reaches 1.2 g / 10 min, the original monitoring point interval is 200 mm, and the calculated change rate coefficient is 0.006. This coefficient directly reflects the change intensity of the melt index per unit length, providing a quantitative basis for subsequent interval adjustment.

[0032] It should be noted that the reference monitoring interval is initially set to 200 mm according to the total length of the extrusion production line and the cost constraint. The adjusted monitoring point interval is determined by the product of the change rate coefficient and the reference interval. The preset threshold value is set to 0.005, and when the change rate coefficient exceeds the threshold value, it indicates that the fiber damage in the section is serious, and the monitoring point interval is adjusted to 0.5 times the reference interval, i.e. 100 mm. This dynamic adjustment mechanism realizes the reasonable allocation of monitoring resources.

[0033] In one possible implementation, the monitoring point rearrangement adopts a piecewise optimization method. The extrusion production line is divided into three regions: a feeding section, a compression section, and a metering section. The monitoring point positions are rearranged according to the adjusted interval values of the sections. In the compression section where fiber breakage is concentrated, the number of monitoring points is increased from the original three to six, and the interval is reduced to 100 mm. In the feeding section where damage is relatively light, the original interval of 200 mm is maintained.

[0034] Preferably, the dynamically optimized monitoring point distribution scheme also takes into account the influence of the temperature field. Fibers in high-temperature regions are more prone to thermal degradation and breakage, so additional monitoring points are added in sections where the temperature exceeds 280°C. Through this arrangement strategy that comprehensively considers the effects of shear damage and temperature, accurate monitoring of the fiber state is achieved, and the accuracy of product quality prediction is improved.

[0035] In step S104, the melt index values and the fiber shortening amplitude after adjustment of the monitoring point intervals are obtained. The melt index changes and the fiber length loss of each monitoring point are compared to obtain the corresponding distribution of the fiber shortening amplitude and the melt index value.

[0036] According to the adjusted monitoring point distribution scheme, the melt index measured values of each point are collected. The fiber morphology at the sampling points is observed under a microscope, and the average fiber length is measured. The ratio of the average fiber length to the fiber length of the raw material before extrusion is taken as the fiber shortening amplitude. The difference between the melt index measured value of each monitoring point and the initial melt index before extrusion is calculated as the melt index increment. The numerical relationship between the fiber shortening amplitude and the melt index increment is compared, and the correlation between the two is fitted using a linear regression method to obtain a fitting coefficient. According to the fitting coefficient and the measured data of each monitoring point, a corresponding relationship curve of the fiber shortening amplitude and the melt index value is constructed, and the fiber shortening amplitude and the melt index value of each monitoring point are marked in the coordinate system to form a corresponding distribution graph.

[0037] Specifically, in one embodiment, the melt index measured values of the monitoring points are obtained by an online melt index instrument equipped with a precision sensor, with a real-time collection frequency of once per minute. At the same time, sampling devices are set at each monitoring point to extract a small amount of melt sample from the barrel, which is rapidly cooled and solidified to prepare a thin sample for microscope observation.

[0038] Specifically, the fiber length measurement is performed using a polarized light microscope in combination with image analysis software. The prepared thin sample is placed on a glass slide, and 50 fibers are randomly selected for length measurement under a magnification of 200 times. The arithmetic mean of the lengths is calculated as the average fiber length at the monitoring point. The initial length of the fibers in the raw material before extrusion is measured by the same method, which is typically 6 mm. The fiber shortening amplitude is defined as the fiber damage ratio, and the calculation formula is: shortening amplitude = (initial length - current length) / initial length.

[0039] It should be noted that the calculation of the melt index increment is based on the initial melt index value of the raw material before extrusion. The initial melt index of the carbon fiber modified plastic raw material is usually 10 g / 10 min, and the measured value of each monitoring point will gradually increase after screw shearing. When the melt index measured at a certain monitoring point is 15 g / 10 min, the melt index increment is 5 g / 10 min. This increment directly reflects the degree of influence of fiber breakage on material fluidity.

[0040] In one possible implementation, the linear regression analysis is implemented by least squares method. A linear regression equation is established with the fiber shortening amplitude as the independent variable and the melt index increment as the dependent variable. The shortening amplitude is defined as the damage ratio, i.e. 1 minus the remaining length ratio. The fitting coefficient represents the change amount of the melt index caused by the fiber shortening by a unit length. When the fitting coefficient is 8.5, it means that the melt index increment increases by about 0.85 g / 10 min for every 0.1 increase in the fiber shortening amplitude.

[0041] Preferably, the corresponding relationship curve is presented in the form of a scatter plot superimposed with a fitting straight line. The horizontal axis is the fiber shortening amplitude, the vertical axis is the melt index value, and the measured data of each monitoring point is marked in the form of a scatter plot, and the fitting straight line shows the overall trend. The corresponding distribution diagram directly reflects the quantitative relationship between the fiber damage degree and the material fluidity change along the extrusion direction, and provides a data basis for subsequent melt index prediction.

[0042] In step S105, according to the corresponding distribution of the fiber shortening amplitude and the melt index value, the melt index change trend of each section is extracted to obtain a melt index prediction curve along the extrusion direction, and the melt index change amount of the downstream monitoring point is predicted through the melt index prediction curve.

[0043] According to the corresponding distribution of the fiber shortening amplitude and the melt index value, the moving average method is used to calculate the average value of the three consecutive data points in each monitoring section, and the difference between the adjacent average values is divided by the distance between the monitoring points to obtain the melt index change slope of each section. Through the melt index change slope data of each section, a continuous function along the extrusion direction is constructed by using a cubic polynomial fitting method to obtain a melt index prediction curve equation. According to the melt index prediction curve equation, the length value of the target monitoring point from the extrusion starting point is input to calculate the predicted melt index value at this position, and the difference between the predicted value and the measured value of the current monitoring point is used as the melt index change amount. The error correction is performed by using the melt index change amount and the measured deviation of the adjacent monitoring point, and if the deviation exceeds the preset threshold, the order of the fitting polynomial is increased to re-fit to obtain the corrected melt index change amount prediction result of the downstream monitoring point.

[0044] Specifically, in one embodiment, the moving average method is implemented by taking the arithmetic average of the melt index values of the three adjacent monitoring points to smooth the data fluctuations. In particular, from the second monitoring point, the melt index values of the second monitoring point and the monitoring points before and after the second monitoring point are taken, and the average of the three is calculated as the representative value of the monitoring segment. When the melt index of the second monitoring point is 12 g / 10 min, and the melt indexes of the first and third monitoring points are 11 g / 10 min and 13.5 g / 10 min, respectively, the average value of this segment is 12.17 g / 10 min.

[0045] Specifically, the calculation of the melt index change slope is based on the difference between the average values of adjacent monitoring segments. The average value of the latter monitoring segment is subtracted from the average value of the former monitoring segment, and then divided by the actual physical distance between the monitoring points. If the average values of two adjacent monitoring segments are 12.17 g / 10 min and 13.25 g / 10 min, respectively, and the distance between the monitoring points is 100 mm, then the slope of this interval is 0.0108 g / 10 min / mm. This slope value intuitively reflects the rate of change of the melt index along the extrusion direction, and the larger the slope, the more severe the fiber breakage.

[0046] It should be noted that the selection of the cubic polynomial fitting method is based on the nonlinear characteristics of the change of the melt index of the carbon fiber modified plastic. The fitting equation takes the form of y=ax³+bx²+cx+d, where y represents the predicted value of the melt index, x represents the length from the start of the extrusion, and a, b, c, and d are the fitting coefficients. The fitting process uses the least squares method to determine the coefficients by minimizing the sum of the squared differences between the measured values and the fitted values of each monitoring point. The cubic polynomial equation obtained by fitting the monitoring point data can describe the change law of the melt index along the entire production line. The fitting coefficient a reflects the degree of curvature of the curve, the coefficient b affects the overall slope of the curve, the coefficient c determines the linear growth part, and the coefficient d is equal to the initial melt index value of the raw material. The specific values of the coefficients are determined according to the material properties, the length of the production line, and the number of monitoring points.

[0047] In one possible implementation, the position of the downstream monitoring point is determined by the actual length value from the start of the extrusion. The start of the extrusion production line is defined as the position where the material enters the screw, denoted as 0 mm. Each monitoring point has a unique position identifier, such as the fifth monitoring point located at 500 mm. When the melt index at the position of 600 mm needs to be predicted, x=600 is substituted into the established cubic polynomial equation to calculate the predicted value at that position. If the equation is y=0.00002x³+0.005x²+0.2x+10, then the predicted melt index at 600 mm is 16.92 g / 10 min.

[0048] Preferably, the melt index variation is determined by comparing the difference between adjacent monitoring points. Taking the measured value at the current monitoring point 500 mm, 15.8 g / 10 min, as a reference, the predicted melt index at 600 mm is 16.92 g / 10 min, and the melt index variation is 1.12 g / 10 min. This variation reflects the performance change of the material within a 100 mm extrusion distance. Further, the triggering of the error correction mechanism is based on the degree of deviation between the predicted value and the measured value. When there is measured data at the downstream monitoring point, the relative deviation between the predicted value and the measured value is calculated. If the measured value at 600 mm is 17.5 g / 10 min and the predicted value is 16.92 g / 10 min, the relative deviation is 3.3%. The preset threshold is usually set to 5%, and the correction program is triggered when the deviation exceeds this threshold.

[0049] Exemplarily, error correction is achieved by adjusting the order of the polynomial. Initially, a cubic polynomial is used, and when the error exceeds the threshold, a quartic polynomial y = ex 4 + ax 3 + bx 2 + cx + d is used to refit. The introduction of the quartic term coefficient e can better capture the local characteristics of the melt index variation, especially in the region where the fiber breaks sharply. After refitting, the new predicted value is calculated and the relative deviation is verified to see if it is reduced below the threshold. If the quartic polynomial still does not meet the accuracy requirements, a quintic polynomial can be tried, but the order of the polynomial should not exceed six to avoid overfitting. The order selection also needs to consider the number of monitoring points, which is generally required to be at least twice the order of the polynomial.

[0050] It can be understood that the corrected predicted result provides a reliable basis for production process control. When the prediction shows that the melt index at a certain position downstream will exceed the upper limit of the product specification, the screw speed or temperature parameters can be adjusted in advance to avoid product quality problems. Through this prediction and correction mechanism, accurate control of the extrusion process of carbon fiber modified plastics is achieved.

[0051] Step S106, combining the predicted melt index variation with the fiber breakage position to identify the fiber breakage type, and determining the production line temperature adjustment amount and the screw speed adjustment amount according to the temperature sensitivity and shear sensitivity corresponding to the fiber breakage type.

[0052] According to the corresponding relationship between the predicted melt index change amount and the fiber breakage position, if the change amount exceeds the preset threshold value and the breakage position is concentrated in the high temperature zone, it is determined as temperature-induced breakage, and if the breakage position is in the high shear zone, it is determined as shear-induced breakage. The corresponding sensitivity parameters are obtained through the breakage type, the temperature sensitivity coefficient of the temperature-induced breakage is extracted from the pre-established material database, and the shear sensitivity coefficient of the shear-induced breakage is calculated according to the screw geometric parameters. The deviation between the sensitivity coefficient and the measured value and the standard value of the melt index is multiplied to determine the parameter adjustment reference value, and the temperature adjustment range and the screw speed adjustment range of the production line are determined according to the parameter adjustment reference value. According to the temperature adjustment range and the heat conduction characteristics of the material, the temperature adjustment amount of each heating section is calculated, and the screw speed adjustment amount is determined by the ratio of the screw speed adjustment range to the current screw speed.

[0053] Specifically, in one embodiment, the determination of the fiber breakage type is based on the comprehensive analysis of the melt index change amount and the breakage position. The preset threshold value is set to 1.5 g / 10 min, and when the melt index change amount exceeds this value, the breakage type identification program is triggered. The extrusion production line is divided into three main regions along the axial direction: the feeding section temperature is 160-180℃, the compression section temperature is 200-240℃, and the metering section temperature is 250-280℃. The high temperature zone is defined as the region where the temperature exceeds 260℃, and the high shear zone is defined as the region where the screw compression ratio is greater than 3.5.

[0054] Specifically, the determination condition of the temperature-induced breakage includes two aspects: the melt index change amount exceeds the preset threshold value and the breakage position is concentrated in the high temperature region of the rear section of the barrel. In this breakage mode, the fiber undergoes thermal degradation in a high temperature environment, and the molecular chain breakage causes the fiber length to be sharply shortened. When the temperature of the fiber surface increases by 10℃, the decomposition rate of the coupling agent on the surface of the carbon fiber doubles, resulting in a decrease in the interfacial bonding force between the fiber and the matrix. When the temperature distribution data of the breakage position shows that more than 70% of the breakage points are located in the region above 265℃, it is determined as temperature-induced breakage.

[0055] It should be noted that the identification of shear-induced breakage is based on the screw geometric parameters and the shear rate distribution. The high shear zone mainly appears in the compression section and the mixing section of the screw, and the screw channel depth of these regions gradually decreases, and the compression and shear effect on the material is enhanced. When the breakage position is concentrated in the middle of the screw compression section, and the shear rate of this region exceeds 500 s -1 When, it is determined as shear-induced breakage. In this breakage mode, the fiber undergoes brittle breakage under strong mechanical shear, and the fracture surface presents an irregular tear-like morphology.

[0056] In one possible implementation, the construction of the material database is based on the accumulation of a large amount of experimental data. The database contains the thermal stability parameters, degradation kinetic constants and fiber fracture critical stress values of different grades of carbon fiber modified plastics at various temperatures. The temperature sensitivity coefficient is defined as the rate of change of melt index per unit temperature change, which is obtained through thermogravimetric analysis and rheological tests. For commonly used short carbon fiber reinforced polypropylene materials, the temperature sensitivity coefficient is usually in the range of 0.08-0.12 g / 10 min / °C. When temperature-induced fracture is detected, the temperature sensitivity coefficient of the corresponding material at the current temperature is extracted from the database, such as 0.10 g / 10 min / °C at 270°C. Preferably, the calculation of the shear sensitivity coefficient takes into account the geometric parameters of the screw. The screw diameter, pitch, compression ratio and channel depth jointly determine the shear strength distribution. The shear sensitivity coefficient is calculated by the formula K=kxDxC / H, where D is the screw diameter (mm), N is the screw speed (rpm), C is the compression ratio (dimensionless), H is the channel depth (mm), and k is the empirical coefficient (determined according to the material properties). This formula reflects the influence of geometric parameters and operating parameters on shear strength. For example, for a screw with a diameter of 65 mm, a compression ratio of 3.8, and a channel depth of 8 mm, at a speed of 80 rpm, the empirical coefficient is 0.0024, and the calculated shear sensitivity coefficient is about 0.15 min / rpm. This coefficient represents the degree of influence of unit speed change on the melt index. Further, the determination of the parameter adjustment reference value involves deviation calculation and the application of the sensitivity coefficient. The melt index standard value is set according to the product specification, usually 12±2 g / 10 min. When the measured value of a certain monitoring point is 15 g / 10 min, the deviation is 3 g / 10 min. Multiply the deviation value by the corresponding sensitivity coefficient to obtain the parameter adjustment reference value. For temperature-induced fracture, the adjustment reference value = 3x0.10 = 0.3, indicating that the temperature needs to be reduced by 30°C; for shear-induced fracture, the adjustment reference value = 3x0.15 = 0.45, indicating that the speed needs to be reduced by 45 rpm.

[0057] Exemplarily, the determination of the temperature adjustment range and the screw speed adjustment range also takes into account the production stability constraints. The temperature adjustment range cannot exceed ±40°C to avoid insufficient material plasticization or excessive degradation. The screw speed adjustment range is limited to ±60 rpm to prevent excessive yield fluctuations. When the calculated adjustment reference value exceeds these limits, a step-by-step adjustment strategy is adopted, with an adjustment range of 50% of the limit value, gradually reaching the target value through multiple iterations.

[0058] It can be understood that the calculation of the temperature adjustment amount of each heating section needs to consider the heat conduction characteristics. The thermal conductivity of carbon fiber modified plastic is about 0.3 W / m·K, which is 20% higher than that of pure resin material. The barrel heating system is divided into six independent temperature control sections, each with a length of 200 mm. According to the heat conduction equation, the temperature difference between adjacent heating sections should not exceed 20°C. When the temperature of the fourth heating section needs to be reduced by 30°C, the third section is reduced by 20°C, and the fifth section is reduced by 25°C, forming a smooth temperature gradient transition.

[0059] For example, the final determination of the screw rotation speed adjustment amount is realized by the ratio method. The current screw rotation speed is 80 rpm, and the calculated rotation speed adjustment amplitude is -45 rpm, and the adjustment ratio is -45 / 80 = -0.56. Considering the production continuity, the actual adjustment amount is set to 40% of the current speed, that is, 32 rpm, and the screw rotation speed is reduced from 80 rpm to 48 rpm. This gradual adjustment method avoids the impact of parameter mutation on product quality, and at the same time provides a buffer time for observing the adjustment effect. Through the coordinated adjustment of temperature and speed, effective control of fiber breakage is realized, and the melt index of the final product is ensured to be stable within the specification range.

[0060] According to the melt index change amount, the index fluctuation mode of each monitoring point is determined, the roughness of the broken section and the morphological state of the fiber end are collected from the fiber breakage position, the rough texture of the broken section corresponding to the index fluctuation mode is analyzed, the fiber end stretch marks corresponding to the index gentle change are evaluated, it is determined that the rough broken section belongs to the brittle fracture type and the fiber end stretch marks belong to the ductile fracture type, the temperature sensitivity of the brittle fracture type and the shear sensitivity of the ductile fracture type are identified.

[0061] According to the melt index change amount, the difference between adjacent monitoring points and the monitoring interval time is calculated as a change rate, if the change rate exceeds a preset threshold, it is marked as a sharp fluctuation mode, if the change rate is less than the threshold, it is marked as a gentle fluctuation mode, and the index fluctuation mode distribution of each monitoring point is obtained. Collect the broken sample from the fiber breakage position in the index fluctuation mode distribution, measure the surface roughness Ra value of the broken section by scanning electron microscope to obtain the roughness value, and measure the necking zone length of the fiber end by microscope to obtain the morphological state parameter. The roughness value is corresponding to the sharp fluctuation mode, when the roughness Ra value exceeds the preset roughness threshold, it is determined as a rough texture feature, and the morphological state parameter is corresponding to the gentle fluctuation mode, when the necking zone length exceeds the preset length threshold, it is determined that there is a stretch mark. According to the rough texture feature, it is determined that the fracture type is brittle fracture, the temperature sensitivity coefficient corresponding to the brittle fracture is obtained from the material database, and according to the stretch mark, it is determined that the fracture type is ductile fracture, and the shear sensitivity coefficient corresponding to the ductile fracture is obtained from the material database.

[0062] Specifically, in one embodiment, the calculation of the melt index change rate is based on a dynamic analysis of the real-time monitoring data. Each monitoring point is equipped with an online melt index tester, and the sampling interval is set to 5 minutes. The melt index difference between adjacent monitoring points divided by the time interval gives the change rate, with units of g / 10min / min. The preset threshold is set to 0.3 g / 10min / min according to the material properties of the carbon fiber modified plastic. When the change rate of a certain monitoring point reaches 0.5 g / 10min / min, it is marked as a sharp fluctuation mode, indicating that the fiber fracture is severe at this location; when the change rate is 0.1 g / 10min / min, it is marked as a gentle fluctuation mode, indicating that the fiber is gradually damaged.

[0063] Specifically, the collection of the fractured samples needs to be carried out after the production line is stable. At the monitoring point position marked as different fluctuation modes, a small amount of melt is extracted through the lateral sampling port and quickly cooled and solidified. The solidified sample is brittle fractured in liquid nitrogen to obtain a fresh fracture surface. The low-temperature fracture method is used to avoid damage to the original fracture morphology caused by secondary processing. Three parallel samples are collected at each monitoring point to ensure the repeatability of the measurement results. The sample size is controlled to be 5mm x 5mm x 2mm to facilitate scanning electron microscope observation.

[0064] It should be noted that the measurement of the surface roughness Ra value is realized by using a scanning electron microscope combined with three-dimensional morphology analysis software. The working parameters of the scanning electron microscope are set as follows: acceleration voltage 15 kV, working distance 10 mm, and magnification 2000 times. A measurement area of 100μm x 100μm is selected on the fracture cross section, and a gray-scale image of the surface morphology is obtained by electron beam scanning. The three-dimensional morphology analysis software reconstructs the height distribution of the surface according to the gray value difference and calculates the arithmetic average roughness Ra value. The Ra value is defined as the arithmetic average of the absolute value of the profile deviation, which reflects the average fluctuation degree of the cross section. The preset roughness threshold is set to 1.5μm, which is based on statistical analysis of a large number of carbon fiber modified plastic fracture samples. When the Ra value exceeds this threshold, it indicates that the cross section roughness is high, showing typical brittle fracture characteristics. The cross section of brittle fracture shows characteristic morphologies such as river pattern and cleavage steps. These microstructures result in a higher surface roughness, with an Ra value usually above 2μm.

[0065] In one possible implementation, the observation of fiber end morphology is performed using a polarized light microscope coupled with an image analysis system. The sample containing broken fibers is prepared into 10 μιη thick sections and mounted on glass slides. In polarized light mode, the interface between fiber and matrix is clearly visible. The necking zone appears as a tapered region where the fiber end gradually tapers, which is the result of plastic deformation of the fiber under tensile stress. The length of the necking zone is measured by image analysis software, defined as the axial distance from the location where the fiber starts to taper (diameter reduces to 95% of the original diameter) to the breaking point. The original diameter of carbon fiber is usually 7 μιη, when the length of the necking zone exceeds 15 μιη (about 2 times of the diameter), it is determined that there is a clear stretch mark, indicating that the fiber has undergone significant plastic deformation process. The preset length threshold is 10 μιη, when the measured value exceeds the threshold, it is confirmed as ductile fracture.

[0066] Preferably, the correspondence between the rough texture feature and the sharp fluctuation pattern is based on the principles of fracture mechanics. Sharp fluctuation indicates that the melt index changes rapidly in a short time, corresponding to the instantaneous brittle fracture of the fiber. During the brittle fracture process, the crack propagation speed is fast, and the fracture energy is mainly consumed in the formation of new surface, resulting in a rough and uneven fracture surface. Under scanning electron microscope, radial stripes can be observed extending outward from the fracture initiation point, with a height difference of 3-5 μιη between the stripes, forming a rough fracture morphology. Further, the association of stretch mark with the flat fluctuation pattern reflects the gradual characteristics of ductile fracture. Flat fluctuation means that the melt index rises slowly, corresponding to the plastic deformation process of the fiber under continuous shearing action. Before ductile fracture, the fiber first necks, and then breaks at the thinnest part of the necking zone. The preset length threshold is 10 μιη, when the measured length of the necking zone is 18 μιη, it is confirmed that there is a stretch mark, and it is determined as a ductile fracture type.

[0067] Illustratively, the construction of the material database includes the sensitive coefficient information of different fracture types. The temperature sensitive coefficient of brittle fracture is obtained by thermal mechanical analysis, reflecting the influence of temperature change on the brittleness of the material. When the temperature increases from 260 °C to 280 °C, the probability of brittle fracture increases by 30%, and the corresponding temperature sensitive coefficient is 0.015 / °C. The shear sensitive coefficient of ductile fracture is determined by rheological test, which characterizes the promoting effect of shearing action on the plastic deformation of the fiber. When the screw speed increases from 60 rpm to 100 rpm, the proportion of ductile fracture increases by 40%, and the corresponding shear sensitive coefficient is 0.01 / rpm.

[0068] It can be understood that the sensitivity coefficient obtained by identifying the fracture type provides a quantitative basis for the optimization of production parameters. Brittle fracture is mainly controlled by temperature, and reducing the processing temperature can reduce the thermal degradation and embrittlement of the fiber. Ductile fracture is mainly affected by shearing action, and adjusting the screw speed can control the degree of plastic deformation of the fiber. This fracture type identification method based on micro-morphology analysis realizes the precise control of the processing of carbon fiber modified plastics.

[0069] For example, in actual production, when it is detected that the value of a certain section Ra is 2.3 μm and corresponds to a sharp fluctuation pattern, it is determined that the brittle fracture dominant region. The temperature sensitivity coefficient 0.015 / ℃ is extracted from the database, and the temperature adjustment amount is calculated in combination with the melt index deviation. By this quantitative parameter adjustment method, the product melt index is controlled within the target range, and the quality stability of the carbon fiber modified plastic is improved.

[0070] The above description is only the preferred embodiment of the present application and the explanation of the technical principles applied. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the concept of the present application. For example, the above features are replaced with the technical features disclosed in the present application (but not limited to) having similar functions to form a technical solution.

Claims

1. A method for real-time monitoring of the melt flow index of modified engineering plastics, characterized in that, The method includes: Obtain the melt index values ​​for each section of the extrusion production line and determine the melt index difference between adjacent monitoring points; The number of shearing cycles in the extrusion production line is obtained. The degree of shear damage to each fiber segment is identified based on the melt index difference and the number of shearing cycles to obtain the fiber damage distribution. The fiber breakage location is determined based on the fiber damage distribution. Obtain the melt index at the fiber breakage location, analyze the melt index difference corresponding to the fiber breakage location, and dynamically adjust the monitoring point interval based on the melt index difference; The melt index value and fiber shortening range after the monitoring point interval was adjusted were obtained. The changes in melt index and fiber length loss at each monitoring point were compared to obtain the corresponding distribution of fiber shortening range and melt index value. Based on the corresponding distribution of fiber shortening amplitude and melt index value, the melt index change trend of each segment is extracted to obtain the melt index prediction curve along the extrusion direction. Based on the melt index prediction curve, the melt index change at downstream monitoring points is predicted. By combining the predicted melt flow index change with the fiber breakage location, the fiber breakage type is identified. Based on the temperature sensitivity and shear sensitivity corresponding to the fiber breakage type, the production line temperature adjustment amount and screw speed adjustment amount are determined.

2. The method for real-time monitoring of melt flow index of modified engineering plastics according to claim 1, characterized in that, The process of obtaining the melt index values ​​of each section of the extrusion production line and determining the melt index difference between adjacent monitoring points includes: The temperature sensor readings at preset positions inside the barrel of the extrusion production line are obtained. The viscosity values ​​at each position are determined according to the inverse relationship between temperature and melt viscosity. The initial melt index value of each monitoring point is calculated according to the formula corresponding to the viscosity value and melt index. The initial melt index values ​​of adjacent monitoring points are collected. The numerical difference between the monitoring points is calculated. The numerical difference is used as the melt index difference between adjacent monitoring points.

3. The method for real-time monitoring of melt flow index of modified engineering plastics according to claim 1, characterized in that, The process of obtaining the shearing cycle number of the extrusion production line, identifying the degree of fiber shear damage in each segment based on the melt index difference and the shearing cycle number, obtaining the fiber damage distribution, and determining the fiber breakage location based on the fiber damage distribution includes: The screw speed and barrel length of the extrusion production line are obtained. The number of shearing cycles is calculated based on the residence time of the material in the barrel. The product of the number of shearing cycles and the difference in melt flow index is used as the damage coefficient of each monitoring section. The degree of fiber shear damage in each section is determined by comparing the damage coefficient with the damage threshold. A fiber damage distribution curve along the extrusion direction is constructed based on the damage coefficient values ​​of each section. The gradient change rate is obtained by calculating the slope change of adjacent points of the fiber damage distribution curve using the difference method. The fiber breakage location is determined based on the gradient change rate.

4. The method for real-time monitoring of melt flow index of modified engineering plastics according to claim 1, characterized in that, Obtain the melt index at the fiber breakage location, analyze the melt index difference corresponding to the fiber breakage location, and dynamically adjust the monitoring point interval based on the melt index difference, including: Obtain the measured melt index value at the fiber breakage location, calculate the melt index difference between adjacent monitoring points before and after the fiber breakage location, divide the melt index difference by the original monitoring point spacing to obtain the rate of change coefficient, calculate the adjusted monitoring point spacing value by multiplying the rate of change coefficient by the benchmark monitoring interval, and redetermine the position of each monitoring point based on the adjusted monitoring point spacing value.

5. The method for real-time monitoring of melt flow index of modified engineering plastics according to claim 1, characterized in that, The process of obtaining the melt index value and fiber shortening amplitude after adjusting the monitoring point interval, comparing the melt index change and fiber length loss at each monitoring point, and obtaining the corresponding distribution of fiber shortening amplitude and melt index value includes: According to the adjusted monitoring point distribution scheme, the measured melt index values ​​of each point are collected, the average fiber length is measured, and the ratio of the average fiber length to the raw material fiber length before extrusion is taken as the fiber shortening range. The difference between the measured melt index value of each monitoring point and the initial melt index before extrusion is calculated as the melt index increment. The corresponding relationship curve is obtained by fitting the fiber shortening range and the melt index increment using a linear regression method.

6. The method for real-time monitoring of melt flow index of modified engineering plastics according to claim 1, characterized in that, Based on the corresponding distribution of fiber shortening and melt index values, the melt index variation trend of each segment is extracted to obtain a melt index prediction curve along the extrusion direction. The melt index variation at downstream monitoring points is then predicted based on this prediction curve, including: The moving average method is used to calculate the average value of three consecutive data points in each monitoring segment. The difference between adjacent average values ​​is divided by the distance between monitoring points to obtain the slope of the melt index change in each segment. Based on the melt index change slope data, the melt index prediction curve equation is constructed using a cubic polynomial fitting method. The melt index prediction value of the downstream target monitoring point is calculated based on the melt index prediction curve equation. The difference between the prediction value and the measured value of the current monitoring point is taken as the melt index change.

7. The method for real-time monitoring of melt flow index of modified engineering plastics according to claim 1, characterized in that, By combining the predicted melt flow index change with the fiber breakage location, the fiber breakage type is identified. Based on the temperature and shear sensitivity corresponding to the fiber breakage type, the production line temperature adjustment and screw speed adjustment are determined, including: Based on the predicted change in melt index and the corresponding relationship between the fiber fracture location, temperature-induced fracture or shear-induced fracture is determined. The corresponding temperature sensitivity coefficient and shear sensitivity coefficient are obtained through the fracture type. The sensitivity coefficient is multiplied by the deviation between the measured melt index value and the standard value to determine the parameter adjustment benchmark value. The temperature adjustment range and screw speed adjustment range of the production line are determined based on the parameter adjustment benchmark value. The temperature adjustment amount of each heating section is calculated based on the temperature adjustment range and the heat conduction characteristics. The screw speed adjustment amount is determined based on the screw speed adjustment range.

8. The method for real-time monitoring of melt flow index of modified engineering plastics according to claim 7, characterized in that, By combining the predicted melt flow index change with the fiber fracture location, the fiber fracture type is identified, including: The rate of change between adjacent monitoring points is calculated based on the change in melt index to determine whether the fluctuation pattern is rapid or gradual. Fracture samples are collected from the fiber fracture location to measure the surface roughness of the fracture section and the length of the necking zone at the fiber end. The surface roughness of the fracture section is used to determine the rough texture characteristics to identify brittle fracture. The length of the necking zone is used to determine the tensile marks to identify ductile fracture. The temperature sensitivity coefficient corresponding to the brittle fracture and the shear sensitivity coefficient corresponding to the ductile fracture are obtained.

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