journal article·2003-04

Flow monitoring in liquid composite molding based on linear direct current sensing technique

Thierry Luthy, Paolo Ermanni

Polymer Composites· Volume 24· Issue 2
Publisher page

Abstract

Abstract On‐line monitoring of the Liquid Composite Molding (LCM) process is a key element to improve part quality and to reduce manufacturing cost. In this context, direct current (DC) resistance measurement is a promising sensing technique allowing to track both flow front position and degree of curing of the resin during injection. An original measurement technique called Linear Direct Current (LDC) based on the same physical principle as DC was developed to record the flow front position continuously and not only at discrete nodes location. Preliminary measurements in a 1D‐flow channel have shown the large influence of the hardware configuration on the accuracy of the LDC system. Further experiments were conducted with the support of an embedded print plate in the flow channel as LDC sensor. These 2D measurements have demonstrated the relatively good spatial accuracy and stability of the LDC system. Permeability characterization in the 1D‐flow channel based on flow front position delivered by LDC, ultrasound monitoring techniques and visual recording is also presented in this paper. The flow front position determined by conventional methods based on video capture is taken as reference. Comparison of the permeability values (Kvisual, KLDC and KUS) shows a maximum deviation of 6.93% given by the LDC‐system. The ultrasound interface change measurement principle allows very accurate and reproducible punctual flow front tracking and shows a maximum deviation compared to the reference permeability (Kvisual) of 3.32%. This study shows the potential of the investigated techniques for flow front monitoring of LCM injection processes.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Epoxy Resin Curing Processes · Injection Molding Process and Properties · Material Properties and Processing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (19)

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