Fill-front and cure progress monitoring for VARTM with auto-calibrating dielectric sensors
Fill-front and cure progress monitoring for VARTM with auto-calibrating dielectric sensors
复制标题
使用自动校准介电传感器对 VARTM 进行填充前和固化进度监控
DOI：
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
B. Minaie
中科院分区：
文献类型：
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作者：
G. Rowe;Jun;Kevin Chiu;Jason Tan;A. Mamishev;B. Minaie
填充前沿和固化进度监控对于真空辅助树脂传递模塑(VARTM)制造过程至关重要。本文介绍的多通道实验系统包括传感器、信号调理、数据采集软件和信号后处理部分。该传感器是机械柔性和光学透明的边缘电场电极系统。已报道的研究阶段的重点是自动校准方法。具体地说，通过使用复杂的传感器几何结构提高了系统的测量精度。在填充和固化过程中，树脂中的介电常数和温度变化的影响也通过自动校准算法得到缓解。该算法使用传感器的非线性部分来准确地确定树脂在灌装过程中前进了多远。这些传感器段充当检查点，通过计算信号随时间的一阶和二阶导数并对这些曲线进行平滑以消除噪声影响来检测。此外，在进入模具之前加入额外的传感器来估计介电常数，可能会进一步改进监控算法。一旦树脂完全填充模具，使用相同的传感器进行介电光谱分析以监测固化进程。选择透明传感器，以便在VARTM过程中实现对填充前沿的可视监控。
Fill-front and cure progress monitoring is critical for vacuum-assisted resin transfer molding (VARTM) manufacturing processes. The experimental multi-channel system presented in this paper includes sensors, signal conditioning, data acquisition software, and signal post-processing components. The sensors are mechanically flexible and optically transparent fringing electric field electrode systems. The emphasis of the reported stage of research is on auto-calibration methods. Specifically, measurement accuracy of the system is increased by using complex sensor geometries. Effects of dielectric permittivity and temperature variations in the resin during filling and curing are also mitigated with an auto-calibration algorithm. The algorithm uses non-linear portions of the sensor to determine accurately how far the resin has progressed during filling. These sensor segments act as checkpoints and are detected by calculating first and second derivatives of the signal over time and smoothing of these curves to eliminate noise effects. Furthermore, the inclusion of additional sensors to estimate dielectric permittivity before entering the mold may provide further improvements in the monitoring algorithm. Once the resin has completely filled the mold, dielectric spectroscopy is performed to monitor cure progression using the same sensors. The transparent sensors are chosen to enable visual monitoring of the fill-front during the VARTM process.