Method for detecting internal defects of fabricated building components

Abstract

The application relates to the technical field of defect detection, and particularly discloses a detection method for internal defects of fabricated building components, which comprises the following steps: collecting ultrasonic feedback parameters in the process of defect detection of the fabricated building components by an ultrasonic detection method through a data acquisition module; preliminarily analyzing the defect degrees of different defect types of the fabricated building components by combining the ultrasonic feedback parameters in the process of defect detection of the fabricated building components; and when the defect degree of any defect type is determined to be suspicious, introducing an infrared thermal imaging detection method for secondary detection to secondarily judge whether defects exist in the defect type with suspected defects in the fabricated building components, so that the defect detection can be optimized based on secondary verification, and the accuracy of the defect detection result of the fabricated building components is improved.

Description

Technical Field

[0001] This invention relates to the field of defect detection technology, specifically a method for detecting internal defects in prefabricated building components. Background Technology

[0002] During the production, transportation, and installation of prefabricated building components, various internal defects can easily arise due to uneven material distribution, insufficient vibration, improper curing, or external forces. If these internal defects are not detected and addressed in a timely manner, they will seriously affect the structural load-bearing capacity and durability of the components. Therefore, it is necessary to conduct internal defect detection on prefabricated building components.

[0003] In existing technologies, the detection of internal defects in prefabricated building components is generally based on ultrasonic testing, which relies on its sensitivity to changes in acoustic impedance to effectively detect volumetric defects inside the components. In this process, when using ultrasonic testing, the ultrasonic testing method analyzes the possible defects inside the prefabricated building components based on the ultrasonic data obtained from feedback, thereby realizing the detection of internal defects in prefabricated building components.

[0004] Traditional internal defect detection methods typically employ a single detection method to determine internal defects in components, lacking a mechanism for collaborative judgment using multiple methods. When the detection result is in a critical region, i.e., a "suspected defect" state, there is a lack of a systematic secondary verification scheme, which leads to a decrease in the accuracy of defect detection results. Summary of the Invention

[0005] The purpose of this invention is to provide a method for detecting internal defects in prefabricated building components, thereby solving the following technical problems: How to improve the accuracy of defect detection results for prefabricated building components.

[0006] The objective of this invention can be achieved through the following technical solutions: A method for detecting internal defects in prefabricated building components, the method comprising: S1: The ultrasonic feedback parameters during the defect detection process of prefabricated building components are collected through the data acquisition module; S2: The data calculation module couples the feedback parameters during the defect detection process of prefabricated building components to obtain the defect risk index of the prefabricated building components. S3: By combining the defect risk index of prefabricated building components with the preset defect risk index threshold range, the degree of defect of different defect types of prefabricated building components is analyzed, including no defects, suspected defects, and obvious defects. S4: When it is determined that there is doubt about any type of defect in the prefabricated building component, the infrared thermal imaging detection method is introduced for secondary detection, and the infrared feedback data during the detection process is collected through the data acquisition module. S5: By combining the judgment data in the detection process of infrared thermal imaging, a secondary judgment is made on whether there are defects in the suspected defect types of prefabricated building components.

[0007] Furthermore, the data collected by the data acquisition module includes: Ultrasonic feedback data from ultrasonic testing and infrared feedback data from infrared thermal imaging testing; The ultrasonic feedback data of the ultrasonic detection method includes sound velocity, amplitude, frequency, and amplitude attenuation coefficient. The infrared feedback data of the infrared thermal imaging detection method includes surface temperature difference, thermal diffusion rate, phase delay, and area of ​​abnormal temperature zone.

[0008] Furthermore, the processing procedure of the data calculation module in S2 includes: Through formula The defect risk index obtained by ultrasonic testing of the a-th prefabricated building component was calculated. ; Where 'a' represents any prefabricated building component. Let be the velocity of sound when the a-th prefabricated building component is tested using ultrasonic testing. The preset speed of sound, Let be the amplitude of the ultrasonic testing method used to test the a-th prefabricated building component. For the preset amplitude, Let be the frequency offset when using ultrasonic testing to inspect the a-th prefabricated building component. for The standard value, denoted as the amplitude attenuation coefficient when using ultrasonic testing to inspect the a-th prefabricated building component.

[0009] Furthermore, the analysis process in S3 also includes: By using ultrasonic testing to assess the defect risk index of the a-th prefabricated building component Threshold ranges of ultrasonic testing defect risk index corresponding to different defect types Perform a comparison; like The defect severity of the i-th defect type of the a-th prefabricated building component is determined to be obvious. like The defect level of the i-th defect type of the a-th prefabricated building component is determined to be questionable. like The defect level of the i-th defect type of the a-th prefabricated building component is determined to be no defect.

[0010] Furthermore, the analysis process in S3 also includes: If the a-th prefabricated building component has a defect of any type and the degree of defect is obvious, then the a-th prefabricated building component is judged to have a defect and is marked. If the a-th prefabricated building component does not have any type of defect and its defect level is obvious, but has any type of defect and its defect level is questionable, then infrared thermal imaging detection method is introduced for secondary detection. If the defect level of all defect types of the a-th prefabricated building component is no defect, then the a-th prefabricated building component is determined to have no defects.

[0011] Furthermore, the secondary judgment process in S5 includes: Through formula The defect risk index obtained by infrared thermal imaging detection method for the a-th prefabricated building component was calculated. ; in, The surface temperature difference is measured using infrared thermal imaging to detect the a-th prefabricated building component. For the preset surface temperature difference, Let be the thermal diffusion rate when detecting the a-th prefabricated building component using infrared thermal imaging. The preset thermal diffusion rate, The phase delay is used when using infrared thermal imaging to detect the a-th prefabricated building component. for The standard value, Let be the area of ​​the abnormal region detected by infrared thermal imaging method for the a-th prefabricated building component. for The standard value.

[0012] Furthermore, the secondary judgment process in S5 also includes: The defect risk index obtained by detecting the a-th prefabricated building component using infrared thermal imaging. The infrared thermal imaging defect risk index thresholds corresponding to the defect types judged as potentially defective are respectively... Compare: like The defect level of the prefabricated building component that is judged to be of questionable defect type is considered to be obvious. like The defect level of the a-th prefabricated building component that is judged as having questionable defects is determined to be "not obvious".

[0013] Furthermore, the different defect types in S3 include: Internal defects in prefabricated building components include, but are not limited to, isolated pores, inclusions, honeycombing, voids, delamination, and closed cracks.

[0014] The beneficial effects of this invention are: (1) This invention uses ultrasonic feedback parameters in the defect detection process of prefabricated building components to conduct a preliminary analysis of the defect degree of different defect types of prefabricated building components. When it is determined that the defect degree of any defect type is suspected, infrared thermal imaging detection method is introduced for secondary detection to make a secondary judgment on whether the suspected defect type in the prefabricated building components has defects. This can realize the optimization of defect detection based on secondary verification, thereby improving the accuracy of defect detection results of prefabricated building components.

[0015] (2) This invention uses ultrasonic testing to determine the defect risk index of the a-th prefabricated building component. Threshold ranges of ultrasonic testing defect risk index corresponding to different defect types A comparison is performed by introducing a doubtful interval. By designating the "high-risk zone" close to the threshold boundary as the questionable zone, it is equivalent to adding a safety net to the detection system. This filters out most extreme cases that may be caused by measurement errors or environmental interference and puts them into the secondary verification process, thereby greatly reducing the risk of direct misjudgment and improving the accuracy of defect detection results for prefabricated building components.

[0016] (3) In this invention, the defect risk index of the a-th prefabricated building component is determined by combining ultrasonic testing. Threshold ranges of ultrasonic testing defect risk index corresponding to different defect types The comparison results can directly output the two high-confidence results of obvious defects and no defects, and perform secondary detection on the low-confidence results of doubtful defects to achieve in-depth analysis, thereby greatly reducing the risk of direct misjudgment, and thus optimizing the defect detection method of prefabricated building components and improving the rationality of the detection results.

[0017] (4) The present invention obtains the defect risk index by detecting the a-th prefabricated building component using infrared thermal imaging detection method. The infrared thermal imaging defect risk index thresholds corresponding to the defect types judged as potentially defective are respectively... By comparing the results, the degree of defects that are suspected can be verified a second time. The "suspected" status of the initial ultrasonic screening can be upgraded to "obvious" or confirmed as "not obvious". This solves the uncertainty in the detection and improves the accuracy of the defect detection results of prefabricated building components. Attached Figure Description

[0018] The invention will now be further described with reference to the accompanying drawings.

[0019] Figure 1 This is a flowchart of the method for detecting internal defects in prefabricated building components in this invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figure 1 As shown, in one embodiment, this application provides a method for detecting internal defects in prefabricated building components, the method comprising: S1: The ultrasonic feedback parameters during the defect detection process of prefabricated building components are collected through the data acquisition module; S2: The data calculation module couples the feedback parameters during the defect detection process of prefabricated building components to obtain the defect risk index of the prefabricated building components. S3: By combining the defect risk index of prefabricated building components with the preset defect risk index threshold range, the degree of defect of different defect types of prefabricated building components is analyzed, including no defects, suspected defects, and obvious defects. S4: When it is determined that there is doubt about any type of defect in the prefabricated building component, the infrared thermal imaging detection method is introduced for secondary detection, and the infrared feedback data during the detection process is collected through the data acquisition module. S5: By combining the judgment data in the detection process of infrared thermal imaging, a secondary judgment is made on whether there are defects in the suspected defect types of prefabricated building components. Through the above technical solution, this embodiment provides a method for detecting internal defects in prefabricated building components. First, the ultrasonic feedback parameters during the defect detection process of the prefabricated building components are collected by the data acquisition module. Then, the feedback parameters during the defect detection process of the prefabricated building components are coupled and processed by the data calculation module to obtain the defect risk index of the prefabricated building components. Combining the defect risk index of the prefabricated building components with a preset defect risk index threshold range, the degree of defects of different defect types of the prefabricated building components is analyzed, including no defects, suspected defects, and obvious defects. Subsequently, when it is determined that any defect type of the prefabricated building components is suspected of being defective, infrared thermal imaging detection is introduced for secondary detection. On this basis, the infrared feedback data during the detection process of infrared thermal imaging detection is collected by the data acquisition module, and by combining the judgment data during the detection process of infrared thermal imaging detection, a secondary judgment is made on whether the suspected defect type in the prefabricated building components is defective. The above technical solution combines ultrasonic feedback parameters during the defect detection process of prefabricated building components to conduct a preliminary analysis of the defect severity of different defect types in the prefabricated building components. When it is determined that the defect severity of any defect type is questionable, infrared thermal imaging detection is introduced for secondary detection to make a secondary judgment on whether the questionable defect type in the prefabricated building component actually exists. This allows for optimization of defect detection based on secondary verification, thereby improving the accuracy of defect detection results for prefabricated building components.

[0022] The data collected by the data acquisition module includes: Ultrasonic feedback data from ultrasonic testing and infrared feedback data from infrared thermal imaging testing; The ultrasonic feedback data of the ultrasonic detection method includes sound velocity, amplitude, frequency, and amplitude attenuation coefficient. The infrared feedback data of the infrared thermal imaging detection method includes surface temperature difference, thermal diffusion rate, phase delay, and area of ​​abnormal temperature region; Through the above technical solution, this example provides data collected by the data acquisition module, including ultrasonic feedback data from ultrasonic testing and infrared feedback data from infrared thermal imaging. The ultrasonic feedback data from ultrasonic testing includes sound velocity, amplitude, frequency, and amplitude attenuation coefficient. Based on this, the ultrasonic feedback data from ultrasonic testing can reflect the degree of defects within prefabricated building components. Specifically, when ultrasonic waves propagate in concrete, if they encounter defects such as voids, cracks, or loose areas, the sound waves will detour or propagate through the edge of the defect, resulting in a longer propagation path and a significant decrease in sound velocity. When defects (such as porosity or cavities) occur, some energy is reflected, scattered, or absorbed, leading to a significant decrease in the amplitude of the received signal. Furthermore, because defects (such as looseness or cavities) absorb high-frequency sound waves more strongly, the high-frequency components in the received signal attenuate faster, and the dominant frequency shifts to lower frequencies. Therefore, a decrease in frequency also indicates the presence of defects in the prefabricated building components. Finally, the amplitude attenuation coefficient reflects the rate of energy loss during sound wave propagation. When defects are present, amplitude scattering and absorption are enhanced, resulting in a significantly increased attenuation coefficient. With this setup, the presence of defects in prefabricated building components can be analyzed based on ultrasonic feedback data. Specifically, the infrared feedback data of infrared thermal imaging detection includes surface temperature difference, thermal diffusion rate, phase delay, and area of ​​abnormal temperature zone. It should be noted that when there are defects inside the component (such as voids, debonding, cracks), the thermophysical properties (thermal conductivity, heat capacity) of the defect area are different from the surrounding material, which leads to the obstruction or acceleration of heat transfer, thereby increasing the surface temperature difference. When there are defects in prefabricated building components, the discontinuity of the material will lead to a decrease in the thermal diffusion rate. The phase delay has a linear relationship with the defect depth; the higher the phase delay, the more likely a defect is to be present. Finally, since the material inside prefabricated building components is uniform, an increase in the area of ​​abnormal temperature zone indicates that there is material inhomogeneity in some areas, directly reflecting the presence of defects inside the prefabricated building components. With this setup, the above data can also be used to analyze whether there are defects in prefabricated building components. Furthermore, due to the different detection methods, secondary verification can be achieved, thereby optimizing the defect detection method for prefabricated building components and improving the rationality of the detection results.

[0023] The processing procedure of the data calculation module in S2 includes: Through formula The defect risk index obtained by ultrasonic testing of the a-th prefabricated building component was calculated. ; Where 'a' represents any prefabricated building component. Let be the velocity of sound when the a-th prefabricated building component is tested using ultrasonic testing. The preset speed of sound, Let be the amplitude of the ultrasonic testing method used to test the a-th prefabricated building component. For the preset amplitude, Let be the frequency offset when using ultrasonic testing to inspect the a-th prefabricated building component. for The standard value mentioned above can be selected and set based on the allowable error in empirical data. The amplitude attenuation coefficient is used when ultrasonic testing is applied to the a-th prefabricated building component. Through the above technical solution, this example provides the defect risk index obtained from the inspection of the a-th prefabricated building component. It can be done through the formula Calculations show that, obviously, the lower the sound velocity and amplitude when using ultrasonic testing on the a-th prefabricated building component, and the greater the frequency shift and amplitude attenuation coefficient when using ultrasonic testing on the a-th prefabricated building component, the higher the defect risk index obtained from the inspection of the a-th prefabricated building component. The larger the value, the greater the likelihood of defects in the a-th prefabricated building component. Conversely, the higher the sound velocity and amplitude during ultrasonic testing of the a-th prefabricated building component, and the smaller the frequency shift and amplitude attenuation coefficient, the lower the defect risk index obtained from the ultrasonic testing of the a-th prefabricated building component. The smaller the value, the less likely there is a defect in the a-th prefabricated building component; This calculation method allows for a rapid initial screening of prefabricated building components for defects based on ultrasonic feedback data.

[0024] The analysis process in S3 also includes: By using ultrasonic testing to assess the defect risk index of the a-th prefabricated building component Threshold ranges of ultrasonic testing defect risk index corresponding to different defect types Perform a comparison; like The defect severity of the i-th defect type of the a-th prefabricated building component is determined to be obvious. like The defect level of the i-th defect type of the a-th prefabricated building component is determined to be questionable. like Determine the degree of defect of the i-th defect type of the a-th prefabricated building component as no defect; Using the above technical solution, this example demonstrates the defect risk index of the a-th prefabricated building component using ultrasonic testing. Threshold ranges of ultrasonic testing defect risk index corresponding to different defect types A comparison is performed by introducing a doubtful interval. By designating the "high-risk zone" close to the threshold boundary as the questionable zone, it is equivalent to adding a safety net to the detection system. This filters out most of the extreme cases that may be caused by measurement errors or environmental interference and puts them into the secondary verification process, thereby greatly reducing the risk of direct misjudgment and improving the accuracy of defect detection results for prefabricated building components. Furthermore, by setting a doubt interval, high-confidence results (obvious defects or no defects) can be output directly, while low-confidence results (doubtful) enter in-depth analysis, achieving the best balance between cost and accuracy; It should be noted that the threshold ranges for the ultrasonic testing defect risk index for the different defect types mentioned above are... The settings can be fitted based on experience.

[0025] The analysis process in S3 also includes: If the a-th prefabricated building component has a defect of any type and the degree of defect is obvious, then the a-th prefabricated building component is judged to have a defect and is marked. If the a-th prefabricated building component does not have any type of defect and its defect level is obvious, but has any type of defect and its defect level is questionable, then infrared thermal imaging detection method is introduced for secondary detection. If the defect level of all defect types of the a-th prefabricated building component is no defect, it is determined that the a-th prefabricated building component has no defects. Using the above technical solution, this example combines ultrasonic testing to assess the defect risk index of the a-th prefabricated building component. Threshold ranges of ultrasonic testing defect risk index corresponding to different defect types The comparison results can directly output the two high-confidence results of obvious defects and no defects, and perform secondary detection on the low-confidence results of doubtful defects to achieve in-depth analysis, thereby greatly reducing the risk of direct misjudgment, and thus optimizing the defect detection method of prefabricated building components and improving the rationality of the detection results.

[0026] The secondary judgment process in S5 includes: Through formula The defect risk index obtained by infrared thermal imaging detection method for the a-th prefabricated building component was calculated. ; in, The surface temperature difference is measured using infrared thermal imaging to detect the a-th prefabricated building component. For the preset surface temperature difference, Let be the thermal diffusion rate when detecting the a-th prefabricated building component using infrared thermal imaging. The preset thermal diffusion rate, The phase delay is used when using infrared thermal imaging to detect the a-th prefabricated building component. for The standard value mentioned above can be selected and set based on the allowable error in empirical data. Let be the area of ​​the abnormal region detected by infrared thermal imaging method for the a-th prefabricated building component. for The standard value mentioned above can be selected and set based on the allowable error in empirical data; Through the above technical solution, this example provides a defect risk index obtained by infrared thermal imaging detection method for the a-th prefabricated building component. It can be done through the formula Calculations show that the larger the surface temperature difference, phase delay, and abnormal area of ​​the a-th prefabricated building component detected by infrared thermal imaging, and the lower the thermal diffusion rate of the a-th prefabricated building component detected by infrared thermal imaging, the higher the defect risk index obtained by infrared thermal imaging detection of the a-th prefabricated building component. The higher the value of the defect risk index, the more likely a defect exists in the a-th prefabricated building component. Conversely, the smaller the surface temperature difference, phase delay, and abnormal area of ​​the a-th prefabricated building component detected by infrared thermal imaging, and the higher the thermal diffusion rate of the a-th prefabricated building component detected by infrared thermal imaging, the higher the defect risk index obtained by infrared thermal imaging detection of the a-th prefabricated building component. The lower the value, the less likely there is to be any obvious defects in the a-th prefabricated building component. Based on this, this calculation method can provide data support for subsequent analysis of whether there are defects in the defect types within the doubtful interval, thereby enabling secondary verification of the defect severity of the defect types within the doubtful interval and reducing detection errors.

[0027] The secondary judgment process in S5 also includes: The defect risk index obtained by detecting the a-th prefabricated building component using infrared thermal imaging. The infrared thermal imaging defect risk index thresholds corresponding to the defect types judged as potentially defective are respectively... Compare: like The defect level of the prefabricated building component that is judged to be of questionable defect type is considered to be obvious. like The defect level of the prefabricated building component that is judged to be of questionable defect type is deemed to be "not obvious". Using the above technical solution, this example obtains the defect risk index by detecting the a-th prefabricated building component using infrared thermal imaging detection. The infrared thermal imaging defect risk index thresholds corresponding to the defect types judged as potentially defective are respectively... By comparing the results, the degree of defects that are suspected can be verified a second time. The "suspected" status of the initial ultrasonic screening can be upgraded to "obvious" or confirmed as "not obvious". This solves the uncertainty in the detection and improves the accuracy of the defect detection results of prefabricated building components. It should be noted that the infrared thermal imaging detection method defect risk index threshold corresponds to the defect type judged as having questionable defects. The settings can be fitted based on experience.

[0028] The different defect types in S3 include: Internal defects in prefabricated building components include, but are not limited to, isolated pores, inclusions, honeycombing, voids, delamination, and closed cracks; Through the above technical solutions, this example provides different defect types, including but not limited to isolated pores, inclusions, honeycombing, voids, delamination, and closed cracks. These defects are common problems in prefabricated building components. Clarifying the defect types upgrades the detection conclusion from "whether there is a problem" to "what the problem is and how to deal with it," thereby further improving the rationality of the detection.

[0029] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A method for detecting internal defects in prefabricated building components, characterized in that, The method includes: S1: The ultrasonic feedback parameters during the defect detection process of prefabricated building components are collected through the data acquisition module; S2: The data calculation module couples the feedback parameters during the defect detection process of prefabricated building components to obtain the defect risk index of the prefabricated building components. S3: By combining the defect risk index of prefabricated building components with the preset defect risk index threshold range, the degree of defect of different defect types of prefabricated building components is analyzed, including no defects, suspected defects, and obvious defects. S4: When it is determined that there is doubt about any type of defect in the prefabricated building component, the infrared thermal imaging detection method is introduced for secondary detection, and the infrared feedback data during the detection process is collected through the data acquisition module. S5: By combining the judgment data in the detection process of infrared thermal imaging, a secondary judgment is made on whether there are defects in the suspected defect types of prefabricated building components.

2. The method for detecting internal defects in prefabricated building components according to claim 1, characterized in that, The data collected by the data acquisition module includes: Ultrasonic feedback data from ultrasonic testing and infrared feedback data from infrared thermal imaging testing; The ultrasonic feedback data of the ultrasonic detection method includes sound velocity, amplitude, frequency, and amplitude attenuation coefficient. The infrared feedback data of the infrared thermal imaging detection method includes surface temperature difference, thermal diffusion rate, phase delay, and area of ​​abnormal temperature zone.

3. The method for detecting internal defects in prefabricated building components according to claim 1, characterized in that, The processing procedure of the data calculation module in S2 includes: Through formula The defect risk index obtained by ultrasonic testing of the a-th prefabricated building component was calculated. ; Where 'a' represents any prefabricated building component. Let be the velocity of sound when the a-th prefabricated building component is tested using ultrasonic testing. The preset speed of sound, Let be the amplitude of the ultrasonic testing method used to test the a-th prefabricated building component. For the preset amplitude, Let be the frequency offset when using ultrasonic testing to inspect the a-th prefabricated building component. for The standard value, denoted as the amplitude attenuation coefficient when using ultrasonic testing to inspect the a-th prefabricated building component.

4. The method for detecting internal defects in prefabricated building components according to claim 3, characterized in that, The analysis process in S3 also includes: By using ultrasonic testing to assess the defect risk index of the a-th prefabricated building component Threshold ranges of ultrasonic testing defect risk index corresponding to different defect types Perform a comparison; like The defect severity of the i-th defect type of the a-th prefabricated building component is determined to be obvious. like The defect level of the i-th defect type of the a-th prefabricated building component is determined to be questionable. like The defect level of the i-th defect type of the a-th prefabricated building component is determined to be no defect.

5. The method for detecting internal defects in prefabricated building components according to claim 4, characterized in that, The analysis process in S3 also includes: If the a-th prefabricated building component has a defect of any type and the degree of defect is obvious, then the a-th prefabricated building component is judged to have a defect and is marked. If the a-th prefabricated building component does not have any type of defect and its defect level is obvious, but has any type of defect and its defect level is questionable, then infrared thermal imaging detection method is introduced for secondary detection. If the defect level of all defect types of the a-th prefabricated building component is no defect, then the a-th prefabricated building component is determined to have no defects.

6. The method for detecting internal defects in prefabricated building components according to claim 5, characterized in that, The secondary judgment process in S5 includes: Through formula The defect risk index obtained by infrared thermal imaging detection method for the a-th prefabricated building component was calculated. ; in, The surface temperature difference is measured using infrared thermal imaging to detect the a-th prefabricated building component. For the preset surface temperature difference, Let be the thermal diffusion rate when detecting the a-th prefabricated building component using infrared thermal imaging. The preset thermal diffusion rate, The phase delay is used when using infrared thermal imaging to detect the a-th prefabricated building component. for The standard value, Let be the area of ​​the abnormal region detected by infrared thermal imaging method for the a-th prefabricated building component. for The standard value.

7. The method for detecting internal defects in prefabricated building components according to claim 6, characterized in that, The secondary judgment process in S5 also includes: The defect risk index obtained by detecting the a-th prefabricated building component using infrared thermal imaging. The infrared thermal imaging defect risk index thresholds corresponding to the defect types judged as potentially defective are respectively... Compare: like The defect level of the prefabricated building component that is judged to be of questionable defect type is considered to be obvious. like The defect level of the a-th prefabricated building component that is judged as having questionable defects is determined to be "not obvious".

8. The method for detecting internal defects in prefabricated building components according to claim 1, characterized in that, The different defect types in S3 include: Internal defects in prefabricated building components include, but are not limited to, isolated pores, inclusions, honeycombing, voids, delamination, and closed cracks.

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