In-situ density measurement for plastic injection molding via ultrasonic technology

Zhengyang DONG, Peng ZHAO, Kaipeng JI, Yuhong CHEN, Shiquan GAO, Jianzhong FU

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Front. Mech. Eng. ›› 2022, Vol. 17 ›› Issue (4) : 58. DOI: 10.1007/s11465-022-0714-2
RESEARCH ARTICLE
RESEARCH ARTICLE

In-situ density measurement for plastic injection molding via ultrasonic technology

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Abstract

Density variation during the injection molding process directly reflects the state of plastic melt and contains valuable information for process monitoring and optimization. Therefore, in-situ density measurement is of great interest and has significant application value. The existing methods, such as pressure−volume−temperature (PVT) method, have the shortages of time-delay and high cost of sensors. This study is the first to propose an in-situ density measurement method using ultrasonic technology. The analyses of the time-domain and frequency-domain signals are combined in the proposed method. The ultrasonic velocity is obtained from the time-domain signals, and the acoustic impedance is computed through a full-spectral analysis of the frequency-domain signals. Experiments with different process conditions are conducted, including different melt temperature, injection speed, material, and mold structure. Results show that the proposed method has good agreement with the PVT method. The proposed method has the advantages of in-situ measurement, non-destructive, high accuracy, low cost, and is of great application value for the injection molding industry.

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Keywords

ultrasonic measurement / melt density / in-situ measurement / injection molding

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Zhengyang DONG, Peng ZHAO, Kaipeng JI, Yuhong CHEN, Shiquan GAO, Jianzhong FU. In-situ density measurement for plastic injection molding via ultrasonic technology. Front. Mech. Eng., 2022, 17(4): 58 https://doi.org/10.1007/s11465-022-0714-2

References

[1]
Yang C, Su L J, Huang C N, Huang H X, Castro J M, Yi A Y. Effect of packing pressure on refractive index variation in injection molding of precision plastic optical lens. Advances in Polymer Technology, 2011, 30(1): 51–61
CrossRef Google scholar
[2]
Zhao P, Yang W M, Wang X M, Li J G, Yan B, Fu J Z. A novel method for predicting degrees of crystallinity in injection molding during packing stage. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 2019, 233(1): 204–214
CrossRef Google scholar
[3]
Hayu R, Sutanto H, Ismail Z. Accurate density measurement of stainless steel weights by hydrostatic weighing system. Measurement, 2019, 131: 120–124
CrossRef Google scholar
[4]
Nemiroski A, Kumar A A, Soh S, Harburg D V, Yu H D, Whitesides G M. High-sensitivity measurement of density by magnetic levitation. Analytical Chemistry, 2016, 88(5): 2666–2674
CrossRef Google scholar
[5]
Davidson S, Perkin M. An investigation of density determination methods for porous materials, small samples and particulates. Measurement, 2013, 46(5): 1766–1770
CrossRef Google scholar
[6]
Zhou X D, Zhang Y, Mao T, Zhou H M. Monitoring and dynamic control of quality stability for injection molding process. Journal of Materials Processing Technology, 2017, 249: 358–366
CrossRef Google scholar
[7]
Xu H, Wu D M, Zhu Q X, Zhang Y J. Research of precision injection control system based on the on-line measurement of polymer melt density. Advanced Materials Research, 2012, 383: 5136–5141
CrossRef Google scholar
[8]
Gao R X, Tang X Y, Gordon G, Kazmer D O. Online product quality monitoring through in-process measurement. CIRP Annals, 2014, 63(1): 493–496
CrossRef Google scholar
[9]
Chen J Y, Yang K J, Huang M S. Online quality monitoring of molten resin in injection molding. International Journal of Heat and Mass Transfer, 2018, 122: 681–693
CrossRef Google scholar
[10]
Wang J, Hopmann C, Kahve C, Hohlweck T, Alms J. Measurement of specific volume of polymers under simulated injection molding processes. Materials & Design, 2020, 196: 109136
CrossRef Google scholar
[11]
Zhao P, Zhang J F, Dong Z Y, Huang J Y, Zhou H W, Fu J Z, Turng L S. Intelligent injection molding on sensing, optimization, and control. Advances in Polymer Technology, 2020, 2020: 7023616
CrossRef Google scholar
[12]
Zhou X W, Zhang Y, Yu W J, Li M Y, Chen Y H, Zhou H M. An imaging performance analysis method correlated with geometrical deviation for the injection molded high-precision aspheric negative plastic lens. Journal of Manufacturing Processes, 2020, 58: 1115–1125
CrossRef Google scholar
[13]
Abeykoon C. A novel soft sensor for real-time monitoring of the die melt temperature profile in polymer extrusion. IEEE Transactions on Industrial Electronics, 2014, 61(12): 7113–7123
CrossRef Google scholar
[14]
Suñol F, Ochoa D A, Garcia J E. High-precision time-of-flight determination algorithm for ultrasonic flow measurement. IEEE Transactions on Instrumentation and Measurement, 2019, 68(8): 2724–2732
CrossRef Google scholar
[15]
Zhao G L, Liu S Z, Zhang C, Jin L, Yang Q X. Quantitative testing of residual deformation in plate with varying thickness based on nonlinear ultrasound. Materials & Design, 2022, 214: 110402
CrossRef Google scholar
[16]
Zheng J Y, Zhang Y, Hou D S, Qin Y K, Guo W C, Zhang C, Shi J F. A review of nondestructive examination technology for polyethylene pipe in nuclear power plant. Frontiers of Mechanical Engineering, 2018, 13(4): 535–545
CrossRef Google scholar
[17]
Kariminejad M, Tormey D, Huq S, Morrison J, McAfee M. Ultrasound sensors for process monitoring in injection moulding. Sensors, 2021, 21(15): 5193
CrossRef Google scholar
[18]
Ageyeva T, Horváth S, Kovács J G. In-mold sensors for injection molding: on the way to Industry 4.0. Sensors, 2019, 19(16): 3551
CrossRef Google scholar
[19]
Zhao P, Zhao Y, Kharbas H, Zhang J F, Wu T, Yang W M, Fu J Z, Turng L S. In-situ ultrasonic characterization of microcellular injection molding. Journal of Materials Processing Technology, 2019, 270: 254–264
CrossRef Google scholar
[20]
Brown E C, Mulvaney-Johnson L, Coates P D. Ultrasonic measurement of residual wall thickness during gas assisted injection molding. Polymer Engineering and Science, 2007, 47(11): 1730–1739
CrossRef Google scholar
[21]
Zhao P, Ji K P, Zhang J F, Chen Y H, Dong Z Y, Zheng J G, Fu J Z. In-situ ultrasonic measurement of molten polymers during injection molding. Journal of Materials Processing Technology, 2021, 293: 117081
CrossRef Google scholar
[22]
Zhao L J, Lai Y, Pei C, Jen C K, Wu K D. Real-time diagnosing polymer processing in injection molding using ultrasound. Journal of Applied Polymer Science, 2012, 126(6): 2059–2066
CrossRef Google scholar
[23]
Shepard C L, Burghard B J, Friesel M A, Hildebrand B P, Moua X, Diaz A A, Enderlin C W. Measurements of density and viscosity of one- and two-phase fluids with torsional waveguides. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 1999, 46(3): 536–548
CrossRef Google scholar
[24]
Abu-Zahra N H. Measuring melt density in polymer extrusion processes using shear ultrasound waves. The International Journal of Advanced Manufacturing Technology, 2004, 24(9): 661–666
CrossRef Google scholar
[25]
van Deventer J, Delsing J. Thermostatic and dynamic performance of an ultrasonic density probe. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2001, 48(3): 675–682
CrossRef Google scholar
[26]
Raišutis R, Kažys R, Mažeika L. Application of the ultrasonic pulse-echo technique for quality control of the multi-layered plastic materials. NDT & E International, 2008, 41(4): 300–311
CrossRef Google scholar
[27]
Knapp C, Carter G. The generalized correlation method for estimation of time delay. IEEE Transactions on Acoustics, Speech, and Signal Processing, 1976, 24(4): 320–327
CrossRef Google scholar
[28]
Yu T M, Jiang F C, Wang J H, Wang Z Q, Chang Y P, Guo C H. Acoustic insulation and absorption mechanism of metallic hollow spheres composites with different polymer matrix. Composite Structures, 2020, 248: 112566
CrossRef Google scholar
[29]
Hayward A T J. Compressibility equations for liquids: a comparative study. British Journal of Applied Physics, 1967, 18(7): 965–977
CrossRef Google scholar
[30]
Wang J, Hopmann C, Schmitz M, Hohlweck T, Wipperfürth J. Modeling of PVT behavior of semi-crystalline polymer based on the two-domain Tait equation of state for injection molding. Materials & Design, 2019, 183: 108149
CrossRef Google scholar
[31]
Ma Z G, Wei W, Zu Y Q, Huang M, Zhou P J, Shi X Z, Liu C T. A novel and simple method to improve thermal imbalance and sink mark of gate region in injection molding. International Communications in Heat and Mass Transfer, 2021, 127: 105498
CrossRef Google scholar
[32]
Michaeli W, Starke C. Ultrasonic investigations of the thermoplastics injection moulding process. Polymer Testing, 2005, 24(2): 205–209
CrossRef Google scholar
[33]
Hoseini M R, Zuo M J, Wang X D. Denoising ultrasonic pulse-echo signal using two-dimensional analytic wavelet thresholding. Measurement, 2012, 45(3): 255–267
CrossRef Google scholar
[34]
SmithS. Digital Signal Processing: A Practical Guide for Engineers and Scientists. Amsterdam: Elsevier, 2013
[35]
Zhao P, Xia N, Zhang J F, Xie J, Zhang C Q, Fu J Z. Measurement of molecular orientation using longitudinal ultrasound and its first application in in-situ characterization. Polymer, 2020, 187: 122092
CrossRef Google scholar

Nomenclature

2s + 1 Filter window size
b Intercept of the linear fitting
c Ultrasonic velocity
f Frequency
fc Central frequency of the transducer
h Thickness of plastic melt
H(f) Transfer function of the echo signals
j Imaginary unit
k Slope of the linear fitting
K Proportionality propagation coefficient
m Coefficient that convert the unit of damping coefficient from Np/cm to dB/cm
P Melt pressure
R u1u2 Correlation function of u1 and u2
R0, R1 Reflection coefficients of the Material 1/Material 2 surface and Material 2/Material 3 surface, respectively
Δt Time delay between u1(t) and u2(t)
T0, T0 Transmission coefficients of the ultrasonic waves passing forward and backward through the Material 1/Material 2 surface, respectively
T Melt temperature
u(t): Time-domain signals
U0 Original ultrasonic signal generated ultrasonic transducer
U1, U2 First and second echo signals reflected from the two surfaces of Material 2, respectively
U(f) Amplitude spectrum of signals
U1(f), U2(f) Amplitude spectrum of U1 and U2, respectively
V Specific volume
Z0, Z1, Z2 Acoustic impedances of Materials 1, 2, and 3, respectively
α Damping coefficient
ρ Density

Acknowledgements

This work was supported by the “Pioneer” and “Leading Goose” R&D Program of Zhejiang, China (Grant No. 2022C01069), the National Natural Science Foundation of China (Grant No. 51875519), the Key Project of Science and Technology Innovation 2025 of Ningbo City, China (Grant No. 2021Z044), and the Project of Innovation Enterprises Union of Ningbo City, China (Grant No. 2021H002). The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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