软质泡沫夹层复合材料结构胶接质量红外热像检测研究

Infrared Thermography Detection for Bonding Quality of Soft Foam Sandwich Composite Structures

  • 摘要: 针对软质泡沫复合材料结构胶接质量无损检测需求,开展激励模式研究,确定了脉冲红外热像模式,并采用一阶导数处理方法形成了特征图像,提高了图像信噪比和缺陷的分辨率,通过构建的神经网络识别软件能够有效识别试件内的脱粘缺陷。研究结果实现缺陷智能检测评判,降低人为评判误检漏检风险,提高检测效率,满足航天器软质泡沫复合材料结构研制快速检测需求。

     

    Abstract: Because of the demand for nondestructive testing of the bonding quality of soft foam composite structures, excitation mode research was conducted, and the pulsed infrared thermal image mode was determined suitable. A first-derivative processing method was used to form a featured image, which improved the image signal-to-noise ratio and defect resolution. Debonding defects in the specimens were effectively identified using the constructed neural network recognition software. The results revealed that the risk of false and missing detections in manual evaluation can be reduced by intelligent detection, and that the detection efficiency can be improved. The above research meets the requirements for the rapid detection of soft foam composite structures in spacecrafts.

     

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