Infrared phase-locked thermal imaging defect identification method for honeycomb sandwich structure

Abstract

The invention provides an infrared phase-locked thermal imaging defect identification method for a honeycomb sandwich structure, the method comprises the following steps: S1, constructing an analytical model of temperature change and distribution of a test piece by adopting an infrared phase-locked thermal imaging detection method; s2, extracting amplitude and phase information of a steady-state or quasi-steady-state process in the temperature signal by adopting a digital phase locking method, and obtaining defect characteristics by utilizing the influence of defects on the phase information; s3, constructing a finite difference model of a heat conduction process, and deducing the heating surface temperature of the test piece considering radiation and convection effects; and S4, establishing a heat and electricity equivalent model in the heat conduction process, and confirming existence of defects. According to the method, constant heat flow, alternating heat flow and transverse heat diffusion influence in the honeycomb sandwich structure are fully considered, and the method is effective for detection process ranges of defects of different types and different depths and detection of different defects.

Description

technical field [0001] The invention belongs to the technical field of non-destructive testing, in particular to an infrared lock-in thermal imaging defect identification method for a honeycomb sandwich structure. Background technique [0002] The honeycomb sandwich structure came out and has been widely used in various fields. Compared with traditional materials and structures, it is much lighter and more rigid, and has a very obvious effect on product weight reduction. Due to the difficulty of precise control of various process parameters in the manufacturing process, the honeycomb sandwich structure is likely to cause unstable quality, large dispersion, and various types of defects such as debonding, delamination, poor bonding, pores, inclusions, and deformation of the honeycomb core. However, the detection effect and efficiency of traditional ray, ultrasonic and other detection methods are not good and need to be improved urgently. In this context, the infrared thermal ...

AI Technical Summary

Problems solved by technology

According to the analysis of infrared lock-in thermal imaging detection principle, the process parameters in the detection process include band range, integration time, thermal sensitivity, loading amplitude, loading frequency, loading cycle, phase-locking frequency, phase value, environmental impact and loading distance, etc. Influencing factors, it is difficult to effectively determine the detection process of products with different structures, thicknesses and sizes by using traditional process test methods

Images