CN-122016930-A - Conversion method of thermal imaging data, modulation signal reconstruction method and computer device

CN122016930ACN 122016930 ACN122016930 ACN 122016930ACN-122016930-A

Abstract

The invention belongs to the technical field of active infrared thermal imaging nondestructive detection, and particularly relates to a conversion method for modulating thermal imaging data and flash thermal imaging data, a signal reconstruction method and a computer device. The method for converting modulated thermal imaging data and flash thermal imaging data comprises S1, obtaining a temperature time sequence T of average temperature of a sample changing with time under modulated thermal excitation ω (T) step S2 of time-series T of temperature ω (T) performing a nonlinear fit to obtain an initial phase shift of the modulated thermal excitation Step S3, initial phase shift by modulating thermal excitation Calculating parameters And Step S4, for temperature time series Obtaining temperature time data under flash-like thermal excitation ( ). The invention provides a theoretical basis for the combination of two technologies by establishing a conversion model between modulation thermal imaging and flash thermal imaging data.

Inventors

TAO NING
SUN JIANGANG
CHANG YUXIN
YU JING
LI XIANG
LI JIACHENG
HE YI
WANG GUAN

Assignees

首都师范大学
北京维泰凯信新技术有限公司

Dates

Publication Date: 20260512
Application Date: 20251212

Claims (10)

1. A method of converting modulated thermal imaging data and flash thermal imaging data, comprising: Step S1, obtaining a temperature time sequence T of the average temperature change of the sample along with time under the modulation thermal excitation ω (T) wherein, A modulation angular frequency for modulating the thermal stimulus; step S2, the temperature time sequence T is carried out ω (T) as a temperature time series Nonlinear fitting is performed by using the following formula to obtain initial phase shift of modulated thermal excitation ; Wherein, the And Respectively are And the non-oscillating and oscillating components of (c), k being the thermal conductivity of the sample, The thermal diffusion coefficient of the sample is L, the thickness of the sample is L, F is the heating constant for modulating thermal excitation; ; step S3, initial phase shift by modulating thermal excitation Calculating parameters And ; , (14) Step S4, for the temperature time sequence of a single pixel point of the sample under the modulation thermal excitation method Temperature time data under flash-like thermal excitation is obtained using the following formula ( ); (13)。
2. The method of converting modulated thermal imaging data and flash thermal imaging data according to claim 1, wherein said step S1 comprises: Step S1a, obtaining a temperature time sequence T ω (T) of temperature change of each pixel point of the sample along with time under modulation thermal excitation; step S1b, averaging the temperatures of all pixel points at the determined time points to obtain a temperature time sequence T of the average temperature of the sample changing along with time ω (t)。
3. The method of converting modulated thermal imaging data to flash thermal imaging data according to claim 2, wherein in the substep S1a, the modulated thermal excitation is in one of two forms: Cosine modulation excitation, which modulates the heating intensity: ; A generally cosine modulated excitation comprising a steady state component and an oscillating component of any phase angle, which modulates the heating intensity as: 。
4. The method of converting modulated thermal imaging data and flash thermal imaging data according to claim 2, wherein the step S1 is preceded by: Step S0, a sample is subjected to periodic heating for a preset period T and a preset duration T0 by using a modulation thermal excitation method, a heat map sequence is acquired on the surface of the sample according to a preset acquisition frequency in the periodic heating process, and a temperature time sequence T ω (T) of the temperature change of each pixel point along with time is extracted, wherein the method comprises at least one of the following steps: ① Cleaning the surface of the sample; ② Covering the surface of the sample with a water-soluble black paint; ③ Using a halogen lamp as a thermal excitation source, and periodically heating the surface of the sample by using a silicon controlled rectifier dimmer to drive and generate cosine or sine modulated light and heat; ④ Recording the change of the surface temperature of the sample along with time by using a thermal infrared imager; ⑤ An infrared filter device is disposed between the heat source and the sample.
5. The method of converting modulated thermal imaging data to flash thermal imaging data according to any one of claims 1 to 4, wherein the sample is a flat plate sample or a tubular sample.
6. A method for reconstructing a modulated signal of thermal imaging data, comprising: performing steps S1-S4 of the method for converting modulated thermal imaging data and flash thermal imaging data according to any one of claims 1-5 to obtain temperature time data under flash-like thermal excitation ( ); Step S5, using the temperature data under the flash-like thermal excitation ( ) Reconstructing the target modulation frequency using Modulated temperature signal ; 。
7. The method for reconstructing a modulated signal of thermal imaging data according to claim 6, wherein said step S3 further comprises: For N different target modulation frequencies And (3) respectively executing the steps S4-S5 to generate complete multi-frequency modulation temperature signals, wherein N is more than or equal to 2.
8. The method for reconstructing a modulated signal of thermal imaging data according to claim 7, wherein said step S5 further comprises: Step S6, for the reconstructed modulation temperature signal Fitting parameters are continuously adjusted by a cyclic iteration method, so that a fitting function is realized Corresponding theoretical value and modulation temperature signal The deviation between the two is gradually reduced to obtain the best fitting coefficient And And then calculate the phase of the thermal wave response signal Amplitude and amplitude of ; (19) , 。
9. The method for reconstructing a modulated signal of thermal imaging data according to claim 8, And (4) executing steps S4-S6 on all pixel points on the sample, obtaining a frequency domain characteristic display phase diagram and/or amplitude diagram, and further obtaining defect information in the sample.
10. A computer apparatus, comprising: Memory and processor, and A computer program stored in the memory; Wherein the processor executes the computer program to implement a method of converting modulated thermal imaging and data flash thermal imaging data as claimed in any one of claims 1 to 5 or a method of reconstructing modulated signals of thermal imaging data as claimed in any one of claims 6 to 9.

Description

Conversion method of thermal imaging data, modulation signal reconstruction method and computer device Technical Field The invention belongs to the technical field of active infrared thermal imaging nondestructive detection, and particularly relates to a conversion method and a signal reconstruction method for modulating thermal imaging data and flash thermal imaging data, a computer device, which are suitable for bidirectional conversion and modulation response reconstruction of the modulating thermal imaging data and the flash thermal imaging data and are used for quantitative detection and imaging of internal defects of materials. Background Active infrared thermal imaging is a nondestructive testing technology which utilizes external thermal excitation and records the change rule of a measured object surface temperature field along with time, and deduces the different structures such as internal defects and damage of materials through inversion. The method has the characteristics of non-contact, rapid imaging, large coverage and the like, and is widely applied to the fields of aerospace, rail transit, energy equipment, composite material manufacturing, structural health monitoring and the like. The commonly used active excitation modes mainly comprise flash thermal imaging and modulation thermal imaging, and the two modes have different characteristics in the aspects of excitation modes, signal characteristics and applicable depths. Flash thermal imaging provides a rapid rise in surface temperature followed by a decay trend by a short pulse heat source applying energy instantaneously to the material surface. Because the diffusion speed of heat flow in the material is faster, the flash temperature field is sensitive to shallow defects in early stages, but the deep defect signal is obviously weakened with the passage of time, so that flash thermal imaging is more suitable for the rapid detection of surface and near-surface defects. The main advantages of flash excitation are that a complete time attenuation curve can be obtained through a single experiment, function analysis is relatively simple, and the method for processing time-frequency domain data of a thermal image sequence is more, so that the method is suitable for carrying out transient reconstruction analysis such as thermal chromatography. However, the detection depth is limited by the thermal diffusion coefficient of the material, the duration of the thermal excitation pulse and the excitation energy, and the detection of the deep defects, particularly the material with lower thermal diffusion coefficient, has weaker thermal response signal of the deep defects, is easy to be annihilated by surface noise and has limited depth detection range. The modulation thermal imaging is used for exciting thermal wave signals in the material by applying periodic thermal excitation to the material, if defects such as layering and debonding are encountered, thermal wave phase delay or amplitude attenuation is caused by thermal diffusivity difference, the surface temperature response sequence signals are processed to extract amplitude and phase images, defect characterization is realized based on phase difference or amplitude difference between the defects and a matrix, particularly a phase diagram, the defect characterization is more sensitive to internal characteristics of the material than the amplitude diagram, and the defect characterization is not easily interfered by factors such as uneven heating, surface conditions of the material and the like. Modulated thermal imaging can compensate the defect of the flash mode in deep detection to a certain extent, but still has some problems in practical application. The diffusion depth of the modulated heat wave is closely related to the modulation frequency, the low-frequency heat wave has stronger penetrating power and can increase the detection depth, but the low-frequency heat wave often causes serious blurring of shallow characteristic signals, and the increase of the modulation frequency can enhance the resolution of shallow defects but can limit the detection depth. In addition, modulation thermal imaging has a problem of "blind frequency" in practical application, that is, at a specific modulation frequency, the phase difference or amplitude difference between the defect and the background tends to be weakened, so that defects in certain depth ranges are difficult to detect. Because of these limitations, multiple experiments at different modulation frequencies are typically required on the same sample to achieve both depth of detection and resolution. However, the multi-frequency experimental method not only increases the experimental complexity, but also increases the detection time, and seriously reduces the detection efficiency. Therefore, how to reduce the blind frequency influence, reduce the modulation thermal imaging test times and time and improve the depth detection capability and the data utili