Development And Application Of In-line Ultrasonic Monitoring System For Mixing Quality Of Polymer Blending Extrusion

Blending and extrusion is the most commonly used plastic modification method in the industry,and ensuring the blending quality is a necessary requirement for plastic processing enterprises to improve production efficiency and sustainable development.The quality testing of these products currently relies on off-line testing of random sampling of products.This method is time consuming and laborious,feedback lags,and can not fully guarantee the quality consistency and stability of the entire batch of products.Real-time monitoring and quality control of the continuous extrusion process is a prominent technical difficulty,which has become a bottleneck restricting the production precision of modified plastics.To this end,in this paper,a quality monitoring system based on ultrasonic on-line measurement technology is developed,and a quality assessment method for the determination of polymer blend production is proposed.In this paper,modular measurement hardware and human interface are designed.The hardware part is composed of three modules,including an extrusion die and an electric control device,an ultrasonic transmitting and receiving device,and an ultrasonic guided wave device with adjustable measurement gap.The modular design allows the system to be connected to different types of extrusion processing equipment.The measurement gap adjustable design enables ultrasonic measurement to be applied to a variety of polymer blends with widely varying acoustic attenuation.The human interface is written in Labview,and the software framework is built in the producer-consumer mode.Python is used to write data processing methods and algorithm models to achieve various functions,which consists of processing information acquisition,ultrasonic signal acquisition and processing,measurement parameter settings,interface display,and blending quality assessment.The reliability of the developed online ultrasonic monitoring system is tested.The test results show that:(1)The system works smoothly in the process range of 260°C and 10 MPa,and ensures good signal transmission performance.(2)The pitch error of the system guided wave device is less than 0.1mm,and the error of melt sound velocity test(polyethylene material)is less than 1%.(3)The system has been used and tested for more than 600 hours without obvious failure.Based on the relationship between ultrasonic signal and polymer blend material properties,two sets of quality assessment schemes based on acoustic characteristic parameter process statistics and acoustic signal data model classification are proposed.The qualified materials and the unqualified polypropylene-based calcium carbonate-filled composite materials provided by the manufacturer were used as the research object,the acoustic characteristic parameters coMParing experiments,standard sample data acquisition experiments and blending process simulation experiments were designed.The feasibility of the quality assessment methods were analyzed and verified.Research shows as follows:(1)In the experiment of mixed qualified samples and unqualified samples,the correlation between ultrasonic melt echo amplitude as well as its Fourier transform amplitude spectrum and qualified sample mass ratio is higher,and the linear model determining coefficient is 0.96.Therefore,these two parameters can be used as process characteristic parameters for statistical process analysis.The characteristic parameters were calculated using the ultrasonic signals of the standard qualified samples and the normality test was performed.The control parameters of the??~?control chart for univariate and the T~2 control chart for Multivariate were calculated.The two control charts can accurately identify the unqualified samples randomly appearing in the simulation experiment of the blending process,which is consistent with the sample number of the experimental design.(2)After the PCA dimension reduction and K-means clustering,the ultrasonic echo signals collected by the two types of standard samples showed a recurrence rate of 84.4%,showing strong signal separability.Then,the SVM model based on time domain feature and the CNN model based on wavelet packet decomposition coefficient matrix are established.The classification accuracy rate of the two models on the verification set is 96.35%and 99.58%,and therate on the test set is 99.69%and 99.17%.On the basis of the model classification,the batch count chart can be used to locate the unqualified sample batch,which is consistent with the sample number of the experimental design.(3)Acoustic parameter process statistical method requires experimental design based on control variables to find characteristic parameters,and range calibration of qualified samples.Acoustic signal model classification requires data modeling and parameter tuning for samples of different quality levels.When the relationship between the material properties affecting product quality and the characterization of ultrasonic signals is relatively simple,the former scheme is explanatory,simply implementing and strongly anti-interference.On the contrary,in the case that the process formula is complicated and the quality influence factors are still unknown,the latter scheme has higher operability and accuracy.The two quality evaluation schemes performed well in the processing of qualified products of Polyp-based calcium carbonate filled composites,and the feasibility of engineering application of ultrasonic quality monitoring system was preliminarily verified.The research results in this paper can be developed into a new online quality monitoring standard for polymer blend extrusion processing products,which will promote the improvement of production efficiency.