A thermal insulation performance detection system for thermal insulation concrete composite material

Abstract

The application discloses a kind of thermal insulation concrete composite material heat preservation performance detection system, it is related to building material thermal detection technical field, including sample boundary construction module, to thermal insulation concrete composite material sample executes clamping positioning processing, thickness reading processing, contour reading processing and sensing position identification processing, generates sample boundary basic data;Stage thermal excitation module, to sample boundary basic data executes heat face boundary construction processing, cold face boundary construction processing, constant temperature difference excitation processing, step temperature rise excitation processing, step temperature drop excitation processing and recovery stage excitation processing, generates boundary temperature control data.In the application, the detection boundary corresponding to the heating direction and the cooling direction is formed for the thermal insulation concrete composite material sample, and then the sample is implemented in stages thermal excitation according to the detection order of constant temperature difference, step temperature rise, step temperature drop and recovery stage, so as to improve the correspondence and comparability of thermal response results between each detection stage.

Description

Technical Field

[0001] This invention relates to the field of thermal testing technology for building materials, and in particular to a testing system for the thermal insulation performance of thermally insulated concrete composite materials. Background Technology

[0002] The thermal insulation performance of thermally insulated concrete composite materials is usually tested based on the thermal response of the sample under the action of hot and cold boundaries. Existing technologies mostly evaluate the thermal insulation capacity of materials by temperature acquisition, heat flow acquisition, surface thermal field observation, and calculation of overall thermal resistance or equivalent thermal conductivity. As the internal structure of materials develops towards multi-region and multi-interface composite structures, the testing process also needs to take into account the correspondence between thermal responses at different testing stages in order to improve the accuracy of characterizing changes in thermal insulation performance.

[0003] Existing detection technologies still have shortcomings: there is a lack of unified sampling time, sensing location and thermal field region correspondence for thermal responses from different sources, making it difficult to form continuous and consistent alignment results; the detection results focus on overall thermal resistance or overall equivalent thermal conductivity, making it difficult to identify changes in thermal pathways, changes in interfacial thermal resistance and the location of local thermal bridges; there is a lack of continuous correlation and stage difference identification between different detection stages, affecting the accuracy of stage insulation attenuation determination and final detection conclusions. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a thermal insulation performance testing system for thermally insulated concrete composite materials.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a thermal insulation performance testing system for thermally insulated concrete composite materials, comprising: a sample boundary construction module, which performs clamping and positioning processing, thickness reading processing, contour reading processing, and sensor position marking processing on the thermally insulated concrete composite material sample to generate basic sample boundary data; a staged thermal excitation module, which performs hot surface boundary construction processing, cold surface boundary construction processing, constant temperature difference excitation processing, step heating excitation processing, step cooling excitation processing, and recovery stage excitation processing on the basic sample boundary data to generate boundary temperature control data; a multi-source thermal response acquisition module, which performs hot surface temperature acquisition processing, cold surface temperature acquisition processing, surface thermal field image acquisition processing, penetration heat flow acquisition processing, internal temperature distribution acquisition processing, and stage mass change acquisition processing on the basic sample boundary data and boundary temperature control data to generate a time-series thermal response dataset; and a thermal response alignment and processing module, which performs sampling time alignment processing, sensor position alignment processing, thermal field region correspondence processing, and detection stage slicing processing on the time-series thermal response dataset and the basic sample boundary data to generate... The system comprises the following modules: a thermal response alignment module and a thermal path reconstruction module. The thermal response alignment data undergoes surface thermal field discrete identification, penetration heat flow correlation, internal temperature gradient correlation, and Landweber iterative internal heat conduction inversion algorithm processing to generate regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data. A damp heat correction and evaluation module performs damp heat state correlation processing, Pettitt abrupt change point stage attenuation identification algorithm processing, and insulation attenuation correction processing on the stage quality change acquisition results, regional thermal path data, and interface thermal resistance distribution data to generate damp heat coupling correction data and stage insulation attenuation data. A comprehensive judgment and output module performs overall equivalent thermal conductivity calculation, overall thermal resistance calculation, regional insulation consistency judgment, interface anomaly level judgment, and insulation performance test conclusion generation on the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, damp heat coupling correction data, and stage insulation attenuation data to generate overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, interface anomaly level results, and insulation performance test conclusions.

[0006] As a further description of the above technical solution: The sample boundary construction module receives the thermally insulated concrete composite sample, places it in the clamping position, and ensures that the sample remains stable in the corresponding heating and cooling directions while in the clamping state. It performs multi-position thickness reading processing along the thickness direction of the sample and writes the corresponding thickness readings for each position into the same data record in positional order. It performs contour reading processing along the outer edge of the sample and writes the contour readings into the thickness readings in the corresponding contour extension order. Based on the hot surface temperature acquisition position, cold surface temperature acquisition position, through-heat flow acquisition position, and internal temperature distribution acquisition position, it performs sensor position identification processing and integrates the sensor position identifications with the thickness and contour readings to generate the basic sample boundary data.

[0007] As a further description of the above technical solution: The phased thermal excitation module receives the basic boundary data of the sample and performs hot and cold boundary construction processing based on the thickness, contour, and sensor position identification information in the basic boundary data. This ensures that the hot and cold boundaries correspond to the two detection areas on either side of the thermally insulated concrete composite sample. After completing the hot and cold boundary construction processing, a constant temperature difference excitation process is performed according to the detection sequence to establish a constant temperature difference between the hot and cold boundaries. Following the constant temperature difference excitation process, a step-increase excitation process is performed, causing the hot boundary temperature to change step by step according to the phase sequence, while maintaining the cold boundary temperature in the boundary state corresponding to the current detection phase. After the step-increase excitation process, a step-decrease excitation process is performed, causing the hot boundary temperature to gradually decrease according to the phase sequence corresponding to the step-increase excitation process. Finally, after the step-decrease excitation process, a recovery phase excitation process is performed, causing the hot and cold boundaries to enter the boundary state corresponding to the recovery phase, generating boundary temperature control data.

[0008] As a further description of the above technical solution: The multi-source thermal response acquisition module receives basic sample boundary data and boundary temperature control data. Based on the detection stage sequence and sampling time in the boundary temperature control data, it performs hot surface temperature acquisition processing, cold surface temperature acquisition processing, surface thermal field image acquisition processing, penetration heat flow acquisition processing, internal temperature distribution acquisition processing, and stage mass change acquisition processing, respectively. The hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, penetration heat flow acquisition content, internal temperature distribution acquisition content, and stage mass change acquisition content are organized according to the same sampling time. The acquisition content of each type at the same sampling time is written to correspond with the sensor position identification content in the basic sample boundary data and arranged continuously according to the detection stage sequence to generate a time-series thermal response dataset.

[0009] As a further description of the above technical solution: The thermal response alignment and processing module receives the time-series thermal response dataset and the basic data of the sample boundary. It performs sampling time alignment processing on the hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, through-thermal flow acquisition content, internal temperature distribution acquisition content, and stage mass change acquisition content in the time-series thermal response dataset, ensuring that the various acquisition contents at the same sampling time maintain a corresponding relationship. Based on the sensor position identifiers in the basic data of the sample boundary, it performs sensor position alignment processing on the various acquisition contents after sampling time alignment, ensuring that the hot surface temperature acquisition content, cold surface temperature acquisition content, through-thermal flow acquisition content, and internal temperature distribution acquisition content correspond to their respective acquisition positions. Based on the contour reading content in the basic data of the sample boundary, it performs thermal field region correspondence processing on the surface thermal field image acquisition content after sensor position alignment, ensuring that each thermal field region in the surface thermal field image acquisition content corresponds to the contour range of the thermally insulated concrete composite sample. Finally, it performs detection stage slicing processing on the various acquisition contents after sampling time alignment, sensor position alignment, and thermal field region correspondence processing to generate thermal response aligned data.

[0010] As a further description of the above technical solution: The thermal path reconstruction module receives thermal response alignment data and performs surface thermal field discrete recognition processing on the surface thermal field image acquisition content in the thermal response alignment data according to the thermal field region, so that the surface thermal field changes corresponding to different thermal field regions form a discrete correspondence. After the surface thermal field discrete recognition processing is completed, the content of each thermal field region is correlated with the through heat flow acquisition content corresponding to the same sampling time and the same region. After the through heat flow correlation processing is completed, the content of each region is correlated with the internal temperature distribution acquisition content corresponding to the same sampling time and the same location. Finally, the Landweber iterative internal heat conduction inversion algorithm is applied to the content of each region after the surface thermal field discrete recognition processing, through heat flow correlation processing, and internal temperature gradient correlation processing to generate regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data.

[0011] As a further description of the above technical solution: The steps of the Landweber iterative internal heat conduction inversion algorithm include: reading the content of each region after surface thermal field discrete identification, penetration heat flow correlation, and internal temperature gradient correlation, and arranging them in order according to the correspondence between thermal field region, sampling time, and location, so that the content of each region remains consistent before entering the iterative process; performing regional heat conduction estimation based on the penetration heat flow and internal temperature distribution data in each region, and performing a correspondence comparison between the estimated regional heat conduction and surface thermal field changes; performing reverse iterative correction processing on each region based on the comparison results, and re-performing regional heat conduction estimation and correspondence comparison processing on the corrected regional content; using the corrected regional content from the current round of reverse iterative correction as the input for the next round of reverse iterative correction, and continuously performing multiple rounds of reverse iterative correction processing according to the thermal field region and sampling time; and performing heat path aggregation, interface thermal resistance correspondence processing, and local thermal bridge location processing on the regional content after multiple rounds of reverse iterative correction processing to generate regional heat path data, interface thermal resistance distribution data, and local thermal bridge indication data.

[0012] As a further description of the above technical solution: The damp heat correction assessment module receives the phase mass change acquisition results, regional thermal path data, and interface thermal resistance distribution data. It reads these data according to the detection phase sequence, maintaining a correspondence between the phase mass change acquisition results, regional thermal path data, and interface thermal resistance distribution data within the same detection phase. For the phase mass change acquisition results, regional thermal path data, and interface thermal resistance distribution data that maintain a correspondence within the same detection phase, damp heat state correlation processing is performed to establish a correspondence between the mass change content and heat conduction change content corresponding to each detection phase. The Pettitt mutation point phase attenuation identification algorithm is applied to the damp heat state correlation results corresponding to adjacent detection phases to establish a phase difference relationship between the thermal path change content and interface thermal resistance change content between adjacent detection phases. Based on the phase difference relationship, insulation attenuation correction processing is performed to generate damp heat coupling correction data and phase insulation attenuation data.

[0013] As a further description of the above technical solution: The steps of the Pettitt mutation point stage decay identification algorithm include: reading the correlation results of the wet and heat state corresponding to the adjacent detection stages according to the detection stage order, and performing sequential arrangement processing on the quality change content, thermal path change content, and interface thermal resistance change content corresponding to each detection stage to maintain the stage correspondence between adjacent detection stages; performing stage position correspondence processing on the content of each detection stage after the stage order arrangement processing, so that the quality change content, thermal path change content, and interface thermal resistance change content corresponding to the current detection stage are respectively compared with the quality change content, thermal path change content, and interface thermal resistance change content corresponding to the previous detection stage to form a stage comparison sequence; performing stage difference accumulation processing on the content of each detection stage that forms the stage comparison sequence, so that each detection stage forms a corresponding stage difference change amount during the detection sequence; performing mutation point identification processing on the content of each detection stage after the stage difference accumulation processing, determining the detection stage position where the stage difference change amount changes in concentration, and forming a mutation point correspondence relationship between the detection stage position and the corresponding thermal path change content and interface thermal resistance change content; and performing stage decay localization processing based on the mutation point correspondence relationship to generate the stage difference relationship.

[0014] As a further description of the above technical solution: The comprehensive judgment output module receives regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-thermal coupling correction data, and stage insulation attenuation data. Based on the regional thermal path data and interface thermal resistance distribution data, it performs overall equivalent thermal conductivity calculation and overall thermal resistance calculation. Based on the regional thermal path data and local thermal bridge indication data, it performs regional insulation consistency judgment processing to ensure that insulation differences between different thermal field regions result in regional insulation consistency. Based on the interface thermal resistance distribution data, humid-thermal coupling correction data, and stage insulation attenuation data, it performs interface anomaly level judgment processing to determine the degree of thermal resistance change at different interface locations. Interface anomaly level results; the overall equivalent thermal conductivity and overall thermal resistance are respectively mapped to the detection stages corresponding to constant temperature difference excitation treatment, step heating excitation treatment, step cooling excitation treatment and recovery stage excitation treatment, and arranged in the order of detection stages; the regional insulation consistency results and interface anomaly level results are respectively mapped to the same thermal field area and the same interface position in each detection stage, and stage association processing is performed with the overall equivalent thermal conductivity and overall thermal resistance corresponding to each detection stage; the results of each detection stage after the completion of stage association processing are compared before and after the stage, and the insulation performance test conclusion is generated based on the change relationship between each detection stage.

[0015] The present invention has the following beneficial effects: 1. In this invention, a detection boundary corresponding to the heating and cooling directions is first formed on the thermal insulation concrete composite material sample. Then, the sample is subjected to staged thermal excitation according to the detection sequence of constant temperature difference, step heating, step cooling and recovery stage. At each detection stage, the hot surface temperature, cold surface temperature, surface thermal field image, penetrating heat flow, internal temperature distribution and stage mass change are collected simultaneously. With the help of sampling time alignment processing, sensor position alignment processing, thermal field area correspondence processing and detection stage slice processing, the thermal response content from different sources can remain continuous and consistent on the same detection basis, thereby improving the correspondence and comparability of thermal response results between each detection stage, and providing a stable data foundation for subsequent thermal insulation performance analysis.

[0016] 2. In this invention, after completing thermal response alignment, surface thermal field discrete identification, penetration heat flow correlation, internal temperature gradient correlation, and Landweber iterative internal heat conduction inversion algorithm processing are performed on different thermal field regions to identify differences in thermal pathways, interface thermal resistance changes, and local thermal bridge locations in different regions of the material. Simultaneously, combining the stage mass change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data, the system performs damp heat state correlation, Pettitt mutation point stage attenuation identification algorithm processing, and insulation attenuation correction processing to continuously identify and locate changes in heat conduction and interface thermal resistance between different detection stages. Based on this processing chain, the system can not only complete the calculation of the overall equivalent thermal conductivity and overall thermal resistance, but also generate regional insulation consistency results, interface anomaly level results, and insulation performance test conclusions, thereby improving the completeness, relevance, and accuracy of the thermal insulation performance test of thermally insulated concrete composite materials. Attached Figure Description

[0017] Figure 1 This is a system architecture diagram of the present invention. Detailed Implementation

[0018] 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.

[0019] Reference Figure 1This invention provides an embodiment of a thermal insulation performance testing system for thermally insulated concrete composite materials, comprising: a sample boundary construction module, which performs clamping and positioning processing, thickness reading processing, contour reading processing, and sensor position marking processing on the thermally insulated concrete composite material sample to generate basic sample boundary data; a staged thermal excitation module, which performs hot surface boundary construction processing, cold surface boundary construction processing, constant temperature difference excitation processing, step heating excitation processing, step cooling excitation processing, and recovery stage excitation processing on the basic sample boundary data to generate boundary temperature control data; a multi-source thermal response acquisition module, which performs hot surface temperature acquisition processing, cold surface temperature acquisition processing, surface thermal field image acquisition processing, penetration heat flow acquisition processing, internal temperature distribution acquisition processing, and stage mass change acquisition processing on the basic sample boundary data and boundary temperature control data to generate a time-series thermal response dataset; and a thermal response alignment and processing module, which performs sampling time alignment processing, sensor position alignment processing, thermal field region correspondence processing, and detection stage slicing processing on the time-series thermal response dataset and the basic sample boundary data to generate thermal response pairs. The system comprises the following modules: A thermal path reconstruction module, which performs surface thermal field discrete identification, penetration heat flow correlation, internal temperature gradient correlation, and Landweber iterative internal heat conduction inversion algorithm processing on the thermal response aligned data to generate regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data; a damp heat correction and evaluation module, which performs damp heat state correlation processing, Pettitt mutation point stage attenuation identification algorithm processing, and insulation attenuation correction processing on the stage quality change acquisition results, regional thermal path data, and interface thermal resistance distribution data to generate damp heat coupling correction data and stage insulation attenuation data; and a comprehensive judgment and output module, which performs overall equivalent thermal conductivity calculation, overall thermal resistance calculation, regional insulation consistency judgment, interface anomaly level judgment, and insulation performance test conclusion generation processing on the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, damp heat coupling correction data, and stage insulation attenuation data to generate overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, interface anomaly level results, and insulation performance test conclusions.

[0020] In this embodiment, after receiving the thermally insulated concrete composite material sample, the sample boundary construction module first moves the sample into the clamping position. During the clamping process, the heating direction of the thermally insulated concrete composite material sample is kept consistent with the direction corresponding to the subsequent hot surface, and the cooling direction of the sample is kept consistent with the direction corresponding to the subsequent cold surface. After the sample is moved in, the current clamping state is maintained without any directional change, so that the thermally insulated concrete composite material sample always maintains the same heating direction and the same cooling direction during the subsequent thickness reading, contour reading, and sensing position marking processes.

[0021] After the clamping and positioning process is completed, the thickness readings of multiple positions along the thickness direction of the thermally insulated concrete composite material sample are read sequentially. For each position read, the thickness readings of that position are written into the same data record, with the content of the position read earlier arranged first and the content of the position read later arranged last. After all positions along the thickness direction are read, the thickness readings of each position are arranged continuously in the same data record according to the position order.

[0022] After completing the thickness reading process, the contour reading process is continuously performed along the outer edge of the thermal insulation concrete composite material sample. During the contour reading process, the corresponding contour reading content is read segment by segment according to the contour extension direction, and the contour reading content of the current segment is written in correspondence with the data record already written near the corresponding position of the current segment. After all the contour reading content is written, the contour reading content is arranged continuously in the data record according to the contour extension order and maintains a corresponding relationship with the thickness reading content.

[0023] After completing the contour reading process, sensor position marking is performed one by one according to the hot surface temperature acquisition position, cold surface temperature acquisition position, penetration heat flow acquisition position, and internal temperature distribution acquisition position. After marking each acquisition position, the corresponding sensor position marking content is written into the data record, and the sensor position marking content is kept in positional correspondence with the thickness reading content and contour reading content of the corresponding position. After all acquisition positions have completed the sensor position marking process, the sensor position marking content, thickness reading content, and contour reading content are integrated to generate the basic data of the sample boundary.

[0024] After receiving the basic data of the sample boundary, the phased thermal excitation module first reads the thickness reading content, contour reading content, and sensor position identification content in the basic data of the sample boundary. During the reading process, the thickness reading content is mapped to the thickness direction position of the thermal insulation concrete composite sample, the contour reading content is mapped to the outer edge range of the thermal insulation concrete composite sample, and the sensor position identification content is mapped to the hot surface temperature acquisition position, cold surface temperature acquisition position, penetration heat flow acquisition position, and internal temperature distribution acquisition position.

[0025] After completing the above reading, first perform the hot surface boundary construction process to ensure that the hot surface boundary corresponds to one side of the test area of ​​the thermal insulation concrete composite sample; then perform the cold surface boundary construction process to ensure that the cold surface boundary corresponds to the other side of the test area of ​​the thermal insulation concrete composite sample; after the hot surface boundary and cold surface boundary are both constructed, make the hot surface boundary and cold surface boundary correspond to the two sides of the test area of ​​the thermal insulation concrete composite sample respectively.

[0026] After completing the hot and cold surface boundary construction processes, constant temperature difference excitation processing is performed according to the detection sequence; this brings the hot and cold surface boundaries into a constant temperature difference state and maintains the continuous and stable boundary state under the current detection sequence; after the current detection sequence is completed, the corresponding boundary state is retained for subsequent detection sequences.

[0027] After the constant temperature difference excitation process is completed, the step temperature rise excitation process is continued to be performed according to the detection sequence; the hot surface boundary temperature changes step by step according to the stage sequence, and the corresponding hot surface boundary temperature state is maintained under each stage sequence; at the same time, the cold surface boundary temperature is maintained to the boundary state corresponding to the current detection stage, so that the change of the hot surface boundary and the current state of the cold surface boundary remain corresponding in the same detection stage.

[0028] After the step heating excitation process is completed, the step cooling excitation process continues; the hot surface boundary temperature is gradually reduced according to the stage sequence corresponding to the step heating excitation process, and the boundary state corresponding to the current detection stage is maintained after each reduction; at the same time, the cold surface boundary continues to maintain the boundary state corresponding to the current detection stage, so that the hot surface boundary reduction process and the current state of the cold surface boundary maintain the detection stage correspondence.

[0029] After the step cooling excitation process is completed, the recovery stage excitation process is executed; the hot and cold surface boundaries enter the boundary states corresponding to the recovery stage, and the boundary states corresponding to the recovery stage form a complete detection sequence with the previous constant temperature difference excitation process, step heating excitation process, and step cooling excitation process; after the recovery stage excitation process is completed, boundary temperature control data is generated.

[0030] After receiving the basic data of the sample boundary and the boundary temperature control data, the multi-source thermal response acquisition module first reads the detection stage sequence and sampling time in the boundary temperature control data, and determines the acquisition order of various acquisition contents based on the detection stage sequence and sampling time; at the same time, it reads the sensor position identification content in the basic data of the sample boundary so that the subsequent acquisition contents can be consistent with the corresponding acquisition position.

[0031] After the reading is completed, hot surface temperature acquisition processing, cold surface temperature acquisition processing, surface thermal field image acquisition processing, penetration heat flow acquisition processing, internal temperature distribution acquisition processing, and stage quality change acquisition processing are performed respectively. At the same sampling time, the hot surface temperature acquisition content is obtained first, followed by the cold surface temperature acquisition content, then the surface thermal field image acquisition content, then the penetration heat flow acquisition content, then the internal temperature distribution acquisition content, and finally the stage quality change acquisition content, so that the various acquisition contents at the same sampling time are synchronized in time.

[0032] After acquiring various types of data at the same sampling time, the hot surface temperature data, cold surface temperature data, surface thermal field image data, penetration heat flow data, internal temperature distribution data, and stage quality change data are organized according to the same sampling time. During the organization process, the various types of data at the same sampling time are grouped into the corresponding records of the same sampling time, and the various types of data corresponding to different sampling times are arranged separately.

[0033] After completing the collation of the corresponding sampling time, the various acquisition contents at the current sampling time are written into the sensor position identifier contents in the basic data of the sample boundary item by item. During the writing process, the hot surface temperature acquisition contents are made to correspond to the hot surface temperature acquisition position, the cold surface temperature acquisition contents are made to correspond to the cold surface temperature acquisition position, the through heat flow acquisition contents are made to correspond to the through heat flow acquisition position, and the internal temperature distribution acquisition contents are made to correspond to the internal temperature distribution acquisition position. The surface thermal field image acquisition contents and the stage mass change acquisition contents are kept consistent with the current sampling time. After all the sampling times are written, they are arranged continuously in the order of detection stages to generate a time-series thermal response dataset.

[0034] After receiving the time-series thermal response dataset and the basic sample boundary data, the thermal response alignment and processing module first reads the hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, penetration heat flow acquisition content, internal temperature distribution acquisition content, and stage mass change acquisition content from the time-series thermal response dataset, and retrieves them one by one in the corresponding order of each sampling time. At the same time, it reads the sensor position identification content and contour reading content from the basic sample boundary data, providing the corresponding basis for subsequent sensor position alignment processing and thermal field region correspondence processing.

[0035] After completing the above readings, the sampling time alignment process is first performed on the hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, penetration heat flow acquisition content, internal temperature distribution acquisition content, and stage quality change acquisition content. The various types of acquisition content at the same sampling time are then merged back to the corresponding positions at the same sampling time to prevent the various types of acquisition content at different sampling times from being mixed together. After all sampling times have been processed, the various types of acquisition content at the same sampling time are kept in correspondence.

[0036] After completing the sampling time alignment process, based on the sensor position identification content in the sample boundary basic data, the sensor position alignment process is further performed on various types of acquisition content; the hot surface temperature acquisition content is aligned with the corresponding hot surface temperature acquisition position, the cold surface temperature acquisition content is aligned with the corresponding cold surface temperature acquisition position, the through heat flow acquisition content is aligned with the corresponding through heat flow acquisition position, and the internal temperature distribution acquisition content is aligned with the corresponding internal temperature distribution acquisition position; after all positions are processed, each type of acquisition content corresponds to its respective acquisition position.

[0037] After completing the sensor position alignment process, based on the contour reading content in the sample boundary basic data, the surface thermal field image acquisition content is processed to correspond the thermal field regions. Each thermal field region in the surface thermal field image acquisition content is mapped to the contour range of the thermal insulation concrete composite sample, and the thermal field region located within the contour range is kept consistent with the corresponding contour position. After all thermal field regions are processed, the correspondence between each thermal field region in the surface thermal field image acquisition content and the contour range of the thermal insulation concrete composite sample is maintained.

[0038] After completing the sampling time alignment, sensor position alignment, and thermal field region correspondence processing, the detection stage slicing process is performed on all acquired content. The various types of acquired content, which have been continuously arranged according to the detection stage order, are sequentially assigned to the corresponding detection stages, so that the hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, penetration heat flow acquisition content, internal temperature distribution acquisition content, and stage quality change acquisition content in the same detection stage maintain continuous correspondence within the stage. After slicing is completed for all detection stages, thermal response aligned data is generated.

[0039] In this embodiment, after receiving the thermal response alignment data, the thermal path reconstruction module first reads the surface thermal field image acquisition content, the through heat flow acquisition content, and the internal temperature distribution acquisition content in the thermal response alignment data item by item according to the sampling time sequence. Then, it maintains the synchronous retrieval relationship between the surface thermal field image acquisition content at the same sampling time and the through heat flow acquisition content and the internal temperature distribution acquisition content corresponding to that sampling time, and continuously expands the content corresponding to the previous sampling time and the content corresponding to the next sampling time in the original arrangement order. After completing the reading according to the sampling time sequence, it reads the content of each region in the surface thermal field image acquisition content segment by segment along the thermal field region in each sampling time, so that the content of the previous thermal field region at the same sampling time and the content of the next thermal field region are arranged in sequence according to the position of the thermal field region, and the content of each thermal field region is kept consistent with the current sampling time. After completing the above reading, the surface thermal field image acquisition content is processed by performing discrete surface thermal field recognition processing according to thermal field regions. Each thermal field region in the acquired surface thermal field image content is separated one by one, so that each thermal field region retains only the surface thermal field change content corresponding to the current region, and the surface thermal field change content corresponding to adjacent thermal field regions is separated from each other in terms of arrangement position. After processing all thermal field regions at the same sampling time, the same processing is performed on all thermal field regions at the next sampling time, so that the surface thermal field change content corresponding to different thermal field regions forms a discrete correspondence at each sampling time, and the surface thermal field change content of the same thermal field region remains continuous between sampling times. Surface thermal field discrete recognition processing formula: ; Sampling time Lower heating zone The corresponding changes in the surface thermal field, Sampling time The surface thermal field image acquisition content is as follows: : Hot zone The region indicator function, : The lateral position in the surface thermal field image : The longitudinal position in the surface thermal field image : Hot zone number, : Sampling time number. When it is necessary to form a representative value for the current thermal field region: ; Sampling time Lower heating zone Contents of average surface thermal field change : Hot zone The corresponding set of locations : Hot zone The number of positions in the text.

[0040] After completing the discrete identification of the surface thermal field, the content of each thermal field region that has formed a discrete correspondence is correlated with the penetration heat flow acquisition content corresponding to the same region at the same sampling time. First, the surface thermal field change content corresponding to the current thermal field region at the current sampling time is retrieved. Then, the penetration heat flow acquisition content at the same sampling time that is at the same position as the current thermal field region is retrieved, ensuring that the surface thermal field change content and the penetration heat flow acquisition content of the current thermal field region are in the same corresponding unit. After the current thermal field region is correlated, the penetration heat flow acquisition content corresponding to the next thermal field region is retrieved sequentially and the same correlation process is performed, ensuring that the content of each thermal field region at the same sampling time carries penetration heat flow acquisition content consistent with its region position. After all thermal field regions at the current sampling time are processed, the same process is performed on each thermal field region at the next sampling time in the order of sampling time, ensuring that the content of each thermal field region maintains a continuous and consistent correlation with the penetration heat flow acquisition content corresponding to the same region at the same sampling time. Penetration heat flow correlation processing formula: ; Sampling time Lower heating zone The content of the region after completing the penetration heat flow correlation processing. Sampling time Lower heating zone Contents of average surface thermal field change Sampling time Lower heating zone The corresponding penetration heat flux acquisition content, : Hot zone number, : Sampling time number.

[0041] After completing the through-thermal flux correlation processing, the content of each region is correlated with the internal temperature distribution data collected at the same sampling time and location using internal temperature gradient correlation processing. First, the surface thermal field changes and through-thermal flux data collected at the current sampling time are read from the current region's content, which are already correlated. Then, the internal temperature distribution data collected at the same location is read, ensuring that the surface thermal field changes, through-thermal flux data collected, and internal temperature distribution data collected in the current region remain synchronously correlated under the same sampling time and location conditions. After the current region completes the correlation, the same processing is performed on the remaining regions at the same sampling time, ensuring that each region's content carries internal temperature distribution data collected at its corresponding location. After all regions at the current sampling time have completed the processing, the same processing is performed on the content of each region at the next sampling time, ensuring that each region's content maintains the correspondence between surface thermal field changes, through-thermal flux data collected, and internal temperature distribution data collected before entering the subsequent Landweber iterative internal heat conduction inversion algorithm. Internal temperature gradient correlation processing formula: ; Sampling time Lower heating zone At the thickness position The internal temperature gradient content at that location, Sampling time Lower heating zone At the thickness position Data collected on the internal temperature distribution of the location. The interval between adjacent positions in the thickness direction. Position in the thickness direction : Hot zone number, : Sampling time number. When it is necessary to generate representative values ​​of the internal temperature gradient at the regional level: ; Sampling time Lower heating zone The average internal temperature gradient content, Number of locations involved in the calculation along the thickness direction. : No. The thickness position is determined. After completing the surface thermal field discrete identification, penetration heat flow correlation, and internal temperature gradient correlation processing, the Landweber iterative internal heat conduction inversion algorithm is executed. First, all region contents are read, and the sequential arrangement is performed according to the correspondence between thermal field region, sampling time, and position. This ensures that the region contents of the same thermal field region at different sampling times are arranged continuously in the order of the sampling time, and the region contents of different thermal field regions at the same sampling time are arranged continuously in the order of their region positions. Furthermore, each region content maintains a consistent correspondence with its current position throughout the arrangement process. After all region contents have been sequentially arranged, each region content has a clear correspondence between its thermal field region position, sampling time position, and current position before entering the iterative processing.

[0042] After sequential processing, regional heat conduction estimation is performed based on the penetration heat flow and internal temperature distribution data collected in each region. First, the penetration heat flow data is read from the current region, followed by the internal temperature distribution data, which is positioned within the same region, ensuring they revolve around the same current region. After reading the current region, regional heat conduction estimation is performed based on the penetration heat flow and internal temperature distribution data, generating the corresponding regional heat conduction estimate. After generating the regional heat conduction estimate, it is compared with the corresponding surface thermal field change data, maintaining a comparison at the same sampling time and location. After the comparison is completed for the current region, the same process is applied to the remaining regions, ensuring all regions generate corresponding regional heat conduction estimates and comparison results consistent with the surface thermal field change data. Landweber Iterative Internal Heat Conduction Inversion Algorithm Formula: ; : No. Wheel sampling time Corresponding thermal field area The content of regional heat conduction estimation, : No. Wheel sampling time Corresponding thermal field area The content of regional heat conduction estimation, Iteration step size, : A region conduction mapping matrix established from the data collected through heat flow and the data collected on the internal temperature distribution. : Region Transmission Mapping Matrix The transpose of the matrix, Sampling time Lower heating zone The corresponding observation vector, Iteration round number, : Hot zone number, : Sampling time number. The observation vector can be written as: ; Sampling time Lower heating zone The observation vector, Sampling time Lower heating zone The content of the penetrating heat flow acquisition, Sampling time Lower heating zone The average internal temperature gradient content, Sampling time Lower heating zone The average surface thermal field variation. Formula for estimating regional heat conduction: ; Sampling time Lower heating zone The content of regional heat conduction estimation, Sampling time Lower heating zone The corresponding penetration heat flux acquisition content, Sampling time Lower heating zone The average internal temperature gradient content, : Hot zone number, : Sampling time number. Corresponding comparison processing formula: ; Sampling time Lower heating zone The corresponding comparison processing results Sampling time Lower heating zone Contents of average surface thermal field change Sampling time Lower heating zone The content of regional heat conduction estimation, The proportionality coefficient between the changes in the surface thermal field and the estimated regional heat conduction. : Hot zone number, : Sampling time number.

[0043] After completing the correspondence comparison process, a reverse iterative correction process is performed on the content of each region based on the correspondence comparison results. First, the correspondence comparison result corresponding to the current region is read, and then the reverse iterative correction process is performed on the content of the current region based on the current correspondence comparison result, so that the content of the current region is consistent with the current sampling time, the current thermal field region, and the current position after correction. After the reverse iterative correction process is completed in the current region, the content of the current region after reverse iterative correction is read again, the regional heat conduction estimation process is re-executed, and the newly formed regional heat conduction estimation content is compared with the surface thermal field change content of the current region again, so that the current region completes the continuous processing of "regional heat conduction estimation process - correspondence comparison process - reverse iterative correction process - regional heat conduction estimation process again - correspondence comparison process again" in the same round. After the current region completes the processing of the current round, the same processing is performed on the next thermal field region until all the content of the current region has completed one reverse iterative correction process.

[0044] After all regions in the current round have completed the reverse iterative correction process, the regions corrected by the reverse iterative correction in the current round are used as the input for the next round of reverse iterative correction. Multiple rounds of reverse iterative correction are then executed continuously according to the thermal field region and sampling time sequence. First, the regions corrected by the reverse iterative correction in the previous round are retrieved item by item according to the thermal field region sequence at the current sampling time, ensuring that the corresponding content of the previous thermal field region is in a continuous sequence with the corresponding content of the next thermal field region. After all regions at the current sampling time have been processed, the next sampling time is entered according to the sampling time sequence, and the same processing is performed on the regions at the next sampling time. In each round of processing, the regional heat conduction estimation processing, the corresponding comparison processing, and the reverse iterative correction processing are repeated, so that the content of each region is continuously updated as the round progresses. After multiple rounds of reverse iterative correction are continuously performed, the regional content of the same thermal field region at different sampling times is continuously corrected round by round, and the regional content of different thermal field regions at the same sampling time is corrected separately round by round.

[0045] After completing multiple rounds of reverse iterative correction, thermal path aggregation processing is performed based on the content of each region formed in the final round. First, the regional heat conduction estimation content and corresponding surface thermal field changes, penetration heat flow acquisition content, and internal temperature distribution acquisition content are read from each region in the final round according to the thermal field region order. Then, the relevant content of the same thermal field region at different sampling times is merged into the corresponding range of the same thermal field region according to the sampling time order, ensuring continuous connection of heat conduction changes in the current thermal field region between sampling times. After merging the same thermal field region, the same merging process is performed on the remaining thermal field regions in sequence, so that each thermal field region forms a continuous thermal path aggregation relationship. After all thermal field regions are aggregated, regional thermal path data is generated. Thermal path aggregation processing formula: ; : Hot zone Regional thermal pathway data, Sampling time Lower heating zone The content of the regional heat conduction estimation after the final round is completed. The number of sampling moments involved in the data collection. : Hot zone number, : Sampling time number.

[0046] After completing the thermal path aggregation process, interface thermal resistance correspondence processing is performed based on the content of each region formed in the final round. First, the content of adjacent regions is read according to their positional relationship. Then, the estimated heat conduction, penetration heat flow, and internal temperature distribution data of adjacent regions at the same sampling time are kept adjacent and correspondent, forming a correspondence at the interface position between adjacent regions. After the current adjacent region is corresponded, the same processing is performed on the next adjacent region in the order of the thermal regions, forming a continuous correspondence at the interface position between each adjacent thermal region. After all adjacent regions are processed at previous and subsequent sampling times, the interface positions are kept continuously corresponding at different sampling times, generating interface thermal resistance distribution data. Interface thermal resistance correspondence processing formula: ; Sampling time Bottom of the screen Interfacial thermal resistance distribution data, Sampling time Thermal field area on one side of the lower interface The average internal temperature distribution data collected. Sampling time The other side of the lower interface has a thermal field area. The average internal temperature distribution data collected. Sampling time bottom interface location The corresponding penetration heat flux acquisition content, Interface location number, : Sampling time number. When it is necessary to obtain the stage comprehensive result of the interface location: ; Interface location Interfacial thermal resistance distribution data, The number of sampling moments involved in the data collection. Sampling time bottom interface location The interface thermal resistance distribution data is obtained. After completing the interface thermal resistance correspondence processing, the local thermal bridge location processing is performed. First, the estimated heat conduction content of each thermal field region after multiple rounds of reverse iterative correction processing and the corresponding surface thermal field change content are read. Then, the corresponding content of the current thermal field region and the adjacent thermal field regions are compared item by item along the thermal field region position direction, so that the change position between the current thermal field region and the adjacent thermal field region remains continuously corresponding at the same sampling time. After the comparison of all thermal field regions at the current sampling time is completed, the same comparison is performed on the next sampling time, so that the change at the same position remains continuous between the previous and next sampling times. After the comparison of all sampling times is completed, the positions with concentrated and continuously corresponding change positions are retained within the corresponding range of the current position, generating local thermal bridge indication data. Local thermal bridge location processing formula: ; Sampling time Lower heating zone Local thermal bridge indication data corresponding to the location, Sampling time Lower heating zone The content of the regional heat conduction estimation after the final round is completed. Sampling time The next adjacent thermal field region The content of the regional heat conduction estimation after the final round is completed. Sampling time Lower heating zone Contents of average surface thermal field change Sampling time The next adjacent thermal field region Contents of average surface thermal field change : Weighting coefficient for the difference in surface thermal field change : Hot zone number, : Sampling time number. When it is necessary to generate location-level local thermal bridge indication results: ; : Hot zone Local thermal bridge indication data corresponding to the location, The number of sampling moments involved in the data collection. Sampling time Lower heating zone Local thermal bridge indication data corresponding to the location.

[0047] After completing the thermal path aggregation, interface thermal resistance correspondence processing, and local thermal bridge location processing, the existing regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data are continuously output in the order of thermal field region and sampling time, while maintaining the original correspondence between the regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data, so that subsequent processing can directly call the current three types of data. Output arrangement formula: ; Sampling time The output arrangement results are as follows: Sampling time Lower heating zone Corresponding regional thermal pathway data, Sampling time bottom interface location The corresponding interface thermal resistance distribution data, Sampling time Lower heating zone The corresponding local thermal bridge indication data, Number of thermal zones Number of interface positions : Sampling time number.

[0048] In this embodiment, after receiving the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data, the damp heat correction assessment module first reads the phase quality change acquisition results corresponding to each detection phase in the order of detection phases. Then, it reads the regional thermal pathway data and interface thermal resistance distribution data corresponding to each detection phase in the same order of detection phases. When reading the content of the current detection phase, the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data corresponding to the current detection phase are placed in the corresponding positions of the same detection phase. When reading the content of the next detection phase, the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data corresponding to the next detection phase are placed in the corresponding positions of the next detection phase, and the previous detection phase and the next detection phase are continuously connected in the detection phase order. After all detection phases are read, the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data under the same detection phase are kept in correspondence.

[0049] After completing the sequential reading according to the detection stages, the corresponding stage quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data within the same detection stage are subjected to damp-heat state correlation processing. First, the stage quality change acquisition results corresponding to the current detection stage are read, followed by the regional thermal pathway data, ensuring that the stage quality change acquisition results and the regional thermal pathway data are consistent within the same detection stage. Then, the interface thermal resistance distribution data corresponding to the current detection stage is read, ensuring that the interface thermal resistance distribution data, the stage quality change acquisition results, and the regional thermal pathway data are consistent within the same detection stage. After completing the above correspondence in the current detection stage, the quality change content and the heat conduction change content corresponding to the current detection stage are maintained in correlation within the same detection stage. After the processing of the current detection stage is completed, the same processing is performed on the next detection stage according to the detection stage sequence, ensuring that the quality change content and heat conduction change content corresponding to each detection stage form a correspondence. After processing is completed for all detection stages, the damp-heat state correlation result is formed. Damp-heat state correlation processing formula: ; : No. Correlation results of damp heat status corresponding to each detection stage : No. The quality changes corresponding to each testing stage : No. Changes in the thermal pathway corresponding to each detection stage : No. Contents of interface thermal resistance changes corresponding to each detection stage. The correlation coefficient of the content of phase quality changes. Correlation coefficients of changes in thermal pathways. Correlation coefficients of the content related to changes in interfacial thermal resistance. : Detection stage number. When it needs to be written in a consecutive arrangement of detection stages: ; : The sequence of correlation results of damp and heat states corresponding to all detection stages. Total number of testing phases : Correlation results of damp heat status corresponding to each detection stage. After completing the humidity and heat state correlation processing, the Pettitt mutation point stage attenuation identification algorithm is applied to the humidity and heat state correlation results corresponding to adjacent detection stages. First, the humidity and heat state correlation results corresponding to adjacent detection stages are read in the order of detection stages. When reading the humidity and heat state correlation results corresponding to the current detection stage, the corresponding mass change, thermal path change, and interface thermal resistance change are read simultaneously. When reading the humidity and heat state correlation results corresponding to the previous detection stage, the corresponding mass change, thermal path change, and interface thermal resistance change are read simultaneously. After both the current and previous detection stages are read, the mass change, thermal path change, and interface thermal resistance change content corresponding to the current and previous detection stages are sequentially arranged according to the detection stage order, maintaining a stage correspondence between adjacent detection stages. After the sequential arrangement of the current set of adjacent detection stages is completed, the humidity and heat state correlation results corresponding to the next set of adjacent detection stages are read and arranged in the same way, ensuring a continuous arrangement relationship between all adjacent detection stages. Sequential arrangement processing formula: ; : No. The stage content vector corresponding to each detection stage. : No. The quality changes corresponding to each testing stage : No. Changes in the thermal pathway corresponding to each detection stage : No. Contents of interface thermal resistance changes corresponding to each detection stage. : Testing stage number. All testing stages, arranged sequentially, can be written as: ; : The sequential arrangement of results corresponding to all detection stages : A vector of stage content arranged in the order of detection stages.

[0050] After completing the sequential arrangement process, the content of each detection stage, arranged according to the detection stage order, undergoes a corresponding process to ensure the positions of the preceding and following stages are aligned. First, the quality change content corresponding to the current detection stage is aligned with the quality change content corresponding to the previous detection stage. Then, the thermal path change content corresponding to the current detection stage is aligned with the thermal path change content corresponding to the previous detection stage. Next, the interface thermal resistance change content corresponding to the current detection stage is aligned with the interface thermal resistance change content corresponding to the previous detection stage. After the current detection stage is aligned, the quality change content, thermal path change content, and interface thermal resistance change content corresponding to the current detection stage are compared with the corresponding content of the previous detection stage to form a stage comparison sequence. After the current detection stage is processed, the same process is performed on the next detection stage according to the detection stage order, so that all detection stage content forms a continuous stage comparison sequence. The formula for the corresponding position of the preceding and following stages is as follows: ; : No. The results correspond to the positions of the preceding and following stages in each detection stage. : No. The stage content vector corresponding to each detection stage. : The content vector corresponding to the previous detection stage : No. The difference in quality between each testing stage and the previous testing stage : No. The difference in thermal pathway changes between each detection stage and the previous detection stage : No. The difference in interfacial thermal resistance between each detection stage and the previous detection stage : Testing stage number.

[0051] After forming the stage comparison sequence, stage difference accumulation processing is performed on the content of each detection stage. First, the stage comparison sequence corresponding to the current detection stage is read. Then, the quality change content, thermal path change content, and interface thermal resistance change content corresponding to the current detection stage are continuously compared between the current detection stage position and the previous detection stage position. After the comparison is completed in the current detection stage, the comparison result corresponding to the current detection stage is continuously retained during the detection sequence progression, ensuring that the comparison result of the current detection stage is seamlessly connected with the comparison result formed in the previous detection stage. When the same processing is performed in the next detection stage, the comparison result corresponding to the next detection stage is seamlessly connected with the comparison result corresponding to the current detection stage. After all detection stages are processed, each detection stage forms its corresponding stage difference change amount during the detection sequence progression. Stage difference accumulation processing formula: ; : No. The single-stage difference value corresponding to each detection stage. Weighting coefficient for poor quality variation. Weighting coefficient for the difference in thermal pathway variation. Weighting coefficient for the difference in interfacial thermal resistance. : No. The difference in quality between each testing stage and the previous testing stage : No. The difference in thermal pathway changes between each detection stage and the previous detection stage : No. The difference in interfacial thermal resistance between each detection stage and the previous detection stage : Testing stage number. Accumulated processing of stage differences: ; : No. The change in stage difference corresponding to each detection stage : No. The single-stage difference value corresponding to each detection stage. : The detection stage number in the cumulative summation process, : Testing stage number.

[0052] After generating the stage difference change amount, abrupt change point identification processing is performed on the content of each detection stage after the stage difference accumulation processing is completed. First, the stage difference change amount corresponding to each detection stage is read sequentially along the detection stage order, ensuring that the stage difference change amount corresponding to the current detection stage corresponds to the stage difference change amount corresponding to the previous detection stage. After the current detection stage is read, the stage difference change amount corresponding to the current detection stage is aligned with the corresponding thermal path change content and interface thermal resistance change content at the same detection stage position. Then, the stage difference change amount corresponding to the next detection stage is read, ensuring that the stage difference change amount corresponding to the next detection stage corresponds to the corresponding thermal path change content and interface thermal resistance change content at the same detection stage position. After all detection stages are read, the detection stage position where the stage difference change amount is concentrated is determined, and this detection stage position is aligned with the corresponding thermal path change content and interface thermal resistance change content to form an abrupt change point correspondence. Pettitt abrupt change point identification formula: ; : No. The Pettitt statistic for each detection stage : No. The rank of the change in stage difference corresponding to each detection stage in all detection stages. Total number of testing phases : The detection stage number in the rank statistics process. : Detection stage number. The mutation point location can be written as: ; The location of the detection stage where the changes in the amount of variation in the stage are concentrated. Take the position corresponding to the statistic with the largest absolute value. : No. The Pettitt statistic for each detection stage Total number of testing phases : Detection stage number. Establishes a correspondence between mutation points: ; Mutation point correspondence The location of the mutation point in the detection stage. The changes in the thermal pathway corresponding to the location of the mutation point in the detection stage. The change in interfacial thermal resistance corresponding to the location of the mutation point in the detection stage.

[0053] After establishing the correspondence between abrupt change points, stage attenuation localization processing is performed based on this correspondence. First, the correspondence between abrupt change points corresponding to the current detection stage position is read. Then, the changes in thermal pathways and interface thermal resistance corresponding to the current detection stage position are maintained continuously within the current detection stage position. Subsequently, the current detection stage position is maintained in a sequential relationship with the previous and subsequent detection stages, ensuring a clear stage transition between the current and previous detection stages. After all detection stage positions with established abrupt change point correspondence have been processed, a stage difference relationship is generated. Stage attenuation localization processing formula: ; : No. The relationship between the differences between the detection stages. : Testing stage number, The location of the mutation point during the detection phase. This reflects the distance between the change in phase variation and the location of the mutation point. ; : No. The amplitude of the stage difference relationship corresponding to each detection stage : No. The change in stage difference corresponding to each detection stage The amount of change in stage difference corresponding to the detection stage where the mutation point is located. : Testing stage number, The location of the mutation point in the detection stage.

[0054] After generating the stage difference relationship, insulation attenuation correction processing is performed based on the stage difference relationship. First, the stage difference relationship corresponding to the current detection stage is read. Then, the stage mass change acquisition results, regional thermal path data, and interface thermal resistance distribution data corresponding to this detection stage are read simultaneously, ensuring that the stage difference relationship corresponding to the current detection stage corresponds to the same detection stage position as the stage mass change acquisition results, regional thermal path data, and interface thermal resistance distribution data. Subsequently, within the current detection stage position, the continuous correlation between mass change content, heat conduction change content, and interface thermal resistance change content is maintained, and the processing results of the current detection stage position are retained within the corresponding range of the current detection stage. After the processing of the current detection stage is completed, the same processing is performed on the next detection stage according to the detection stage sequence, ensuring that the processing results corresponding to each detection stage are connected sequentially. After completing the insulation attenuation correction processing for all detection stages, humid-thermal coupling correction data and stage insulation attenuation data are generated. Insulation attenuation correction processing formula: ; : No. Humidity and heat coupling correction data corresponding to each detection stage : No. Correlation results of damp heat status corresponding to each detection stage : No. The relationship between the differences between the detection stages. : No. The single-stage difference value corresponding to each detection stage. : Correction coefficient for stage difference relationship : Detection stage number. Difference between correction results from adjacent detection stages: ; : No. The insulation attenuation data corresponding to each testing stage : No. Humidity and heat coupling correction data corresponding to each detection stage : The humidity and heat coupling correction data corresponding to the previous detection stage, : Testing stage number, Total number of testing phases.

[0055] After generating the humidity-heat coupling correction data and the stage insulation attenuation data, the humidity-heat coupling correction data and the stage insulation attenuation data corresponding to the current detection stage are arranged consecutively according to the detection stage order. The content corresponding to the previous detection stage is kept continuous with the content corresponding to the next detection stage, allowing subsequent processing to directly call upon the humidity-heat coupling correction data and the stage insulation attenuation data. The formula for the consecutively arranged detection stages is as follows: ; : The consecutive output results corresponding to all detection stages : Humidity and heat coupling correction data corresponding to each detection stage : Thermal insulation attenuation data corresponding to each testing stage Total number of testing phases.

[0056] In this embodiment, after the comprehensive judgment output module receives regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-heat coupling correction data, and stage insulation attenuation data, it first reads the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-heat coupling correction data, and stage insulation attenuation data corresponding to the constant temperature difference excitation processing in the same detection stage order. Then, it reads the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-heat coupling correction data, and stage insulation attenuation data corresponding to the step heating excitation processing in the same detection stage order. Next, it reads the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-heat coupling correction data, and stage insulation attenuation data corresponding to the step cooling excitation processing in the same detection stage order. Finally, it reads the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-heat coupling correction data, and stage insulation attenuation data corresponding to the recovery stage excitation processing in the same detection stage order. This ensures that the data content corresponding to each detection stage is arranged continuously in the detection stage order and that the previous detection stage is connected to the next detection stage.

[0057] After reading the data in the order of the detection stages, the overall equivalent thermal conductivity is calculated based on the regional thermal path data and the interface thermal resistance distribution data. First, the regional thermal path data corresponding to the current detection stage is read, ensuring that the regional thermal path data for different thermal field regions within the current detection stage are arranged continuously within the same detection stage. Then, the interface thermal resistance distribution data corresponding to the current detection stage is read, ensuring that the interface thermal resistance distribution data for different interface locations within the current detection stage are arranged continuously within the same detection stage. After both the regional thermal path data and the interface thermal resistance distribution data for the current detection stage are read, the regional thermal path data for all thermal field regions within the current detection stage are matched with the interface thermal resistance distribution data for all interface locations within the current detection stage, ensuring that the corresponding overall equivalent thermal conductivity is formed for the current detection stage. After the current detection stage is processed, the same process is performed on the next detection stage in the order of the detection stages, ensuring that each detection stage forms its corresponding overall equivalent thermal conductivity.

[0058] After completing the overall equivalent thermal conductivity calculation, the overall thermal resistance calculation is performed based on the regional thermal path data and interface thermal resistance distribution data. First, the regional thermal path data corresponding to the current detection stage is read, and then the interface thermal resistance distribution data corresponding to the current detection stage is read, ensuring that the regional thermal path data and the interface thermal resistance distribution data corresponding to the current detection stage maintain a continuous correspondence within the same detection stage range. After the corresponding data for the current detection stage are matched, the overall thermal resistance calculation is performed around the regional thermal path data corresponding to each thermal field region and the interface thermal resistance distribution data corresponding to each interface position within the current detection stage, so that the current detection stage forms the corresponding overall thermal resistance. After the current detection stage is processed, the same process is performed on the next detection stage according to the detection stage sequence, so that each detection stage forms the corresponding overall thermal resistance.

[0059] After completing the calculation of the overall equivalent thermal conductivity and overall thermal resistance, the process continues to determine the consistency of regional insulation based on the regional thermal path data and local thermal bridge indicator data. First, the regional thermal path data corresponding to the current testing stage is read, and the data is arranged sequentially according to the order of the thermal field regions. Then, the local thermal bridge indicator data corresponding to the current testing stage is read, and arranged sequentially according to the order of the thermal field regions. The regional thermal path data and local thermal bridge indicator data corresponding to each thermal field region in the current testing stage are then used to determine the consistency of regional insulation. After the data is arranged, the regional thermal pathway data and the local thermal bridge indication data corresponding to the same thermal field area are kept in the same position. Then, the insulation difference between the previous and subsequent thermal field areas is continuously judged along the thermal field area sequence, so that the insulation difference between different thermal field areas forms a continuous arrangement result in the current detection stage. After the processing of the current detection stage is completed, the regional insulation consistency result corresponding to the current detection stage is generated. After the current detection stage is generated, the same processing is performed on the next detection stage according to the detection stage sequence, so that each detection stage forms the corresponding regional insulation consistency result.

[0060] After completing the regional insulation consistency determination process, the interface anomaly level determination process continues based on the interface thermal resistance distribution data, the humid-heat coupling correction data, and the stage insulation attenuation data. First, the interface thermal resistance distribution data corresponding to the current testing stage is read, and the interface thermal resistance distribution data corresponding to each interface position within the current testing stage are arranged sequentially according to the interface position. Then, the humid-heat coupling correction data corresponding to the current testing stage is read, maintaining synchronization with the interface thermal resistance distribution data according to the current testing stage position. Next, the stage insulation attenuation data corresponding to the current testing stage is read, ensuring that the stage insulation attenuation data corresponds to the interface thermal resistance distribution data and the humid-heat coupling correction data corresponding to the current testing stage at the same testing stage position. After all three types of data for the current testing stage are aligned, the interface anomaly level determination process is sequentially performed around each interface position within the current testing stage, so that the degree of thermal resistance change corresponding to each interface position forms an interface anomaly level result within the current testing stage. After the current testing stage is processed, the same process is performed on the next testing stage according to the testing stage order, so that each testing stage forms a corresponding interface anomaly level result.

[0061] After forming the overall equivalent thermal conductivity and overall thermal resistance, the overall equivalent thermal conductivity and overall thermal resistance are respectively mapped to the detection stages corresponding to the constant temperature difference excitation treatment, the step heating excitation treatment, the step cooling excitation treatment, and the recovery stage excitation treatment, and arranged in the order of the detection stages. First, the overall equivalent thermal conductivity and overall thermal resistance formed in each detection stage corresponding to the constant temperature difference excitation treatment are arranged in the order of the detection stages. Then, the overall equivalent thermal conductivity and overall thermal resistance formed in each detection stage corresponding to the step heating excitation treatment are arranged in the order of the detection stages. Next, the overall equivalent thermal conductivity and overall thermal resistance formed in each detection stage corresponding to the step cooling excitation treatment are arranged in the order of the detection stages. Finally, the overall equivalent thermal conductivity and overall thermal resistance formed in each detection stage corresponding to the recovery stage excitation treatment are arranged in the order of the detection stages, so that the overall equivalent thermal conductivity and overall thermal resistance formed in each detection stage of the recovery stage excitation treatment are arranged in the order of the detection stages, so that the overall equivalent thermal conductivity and overall thermal resistance formed in each detection stage of the entire detection stage are continuously arranged.

[0062] After generating the regional insulation consistency results and interface anomaly level results, these results are mapped to the same thermal field region and the same interface location in each testing stage, respectively. They are then associated with the overall equivalent thermal conductivity and overall thermal resistance of each testing stage. First, the regional insulation consistency results for the current testing stage are read, and the results for each thermal field region within the current testing stage are arranged in order of thermal field region. Next, the interface anomaly level results for the current testing stage are read, and the results for each interface location within the current testing stage are arranged in order of interface location. After the regional insulation consistency results and interface anomaly level results for the current testing stage are arranged, the overall equivalent thermal conductivity and overall thermal resistance of the current testing stage are read. Thermal resistance is used to ensure that the overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, and interface anomaly level results corresponding to the current testing stage correspond to the same testing stage position. Subsequently, for the same thermal field area in the current testing stage, stage correlation processing is performed between the regional insulation consistency results and the overall equivalent thermal conductivity and overall thermal resistance. Similarly, for the same interface position in the current testing stage, stage correlation processing is performed between the interface anomaly level results and the overall equivalent thermal conductivity and overall thermal resistance. This ensures that the regional insulation consistency results and interface anomaly level results corresponding to the current testing stage are respectively correlated with the overall equivalent thermal conductivity and overall thermal resistance corresponding to the current testing stage. After the processing of the current testing stage is completed, the same processing is performed on the next testing stage according to the testing stage sequence, so that each testing stage forms a corresponding stage correlation result.

[0063] After completing the stage association processing, the results of each detection stage are compared with those of the previous stage. First, the stage association results corresponding to the current detection stage are read, and then the stage association results corresponding to the previous detection stage are read. The overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, and interface anomaly level results corresponding to the current detection stage are kept in line with the overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, and interface anomaly level results corresponding to the previous detection stage. After the current detection stage is aligned with the previous detection stage, the changes in overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, and interface anomaly level results between the current and previous detection stages are compared with those of the previous stage. After the comparison of the current detection stage is completed, the same comparison process is performed between the next detection stage and the current detection stage in the order of the detection stages, so that a continuous comparison relationship between the previous and subsequent stages is formed among all detection stages.

[0064] After completing the comparison processing before and after the testing stages, the thermal insulation performance test conclusion is generated based on the change relationship between each testing stage. First, the change relationship formed between each testing stage corresponding to the constant temperature difference excitation treatment is read, then the change relationship formed between each testing stage corresponding to the step temperature rise excitation treatment is read, then the change relationship formed between each testing stage corresponding to the step temperature fall excitation treatment is read, and finally the change relationship formed between each testing stage corresponding to the recovery stage excitation treatment is read. After all the change relationships of all testing stages are read, the overall equivalent thermal conductivity change relationship, overall thermal resistance change relationship, regional thermal insulation consistency result change relationship, and interface anomaly level result change relationship between each testing stage are arranged continuously in the testing order. After the continuous arrangement is completed, the thermal insulation performance test conclusion generation processing is performed around the change relationship between all testing stages, so that the overall equivalent thermal conductivity, overall thermal resistance, regional thermal insulation consistency result, and interface anomaly level result remain continuously corresponding within the same test conclusion range, and the thermal insulation performance test conclusion is generated.

[0065] After completing the generation and processing of the thermal insulation performance test results, the overall equivalent thermal conductivity, overall thermal resistance, regional thermal insulation consistency results, interface anomaly level results, and thermal insulation performance test results are continuously output in the order of the test stages, while maintaining the original correspondence between the corresponding contents in the same test stage without changing, so that subsequent calls can directly obtain the overall equivalent thermal conductivity, overall thermal resistance, regional thermal insulation consistency results, interface anomaly level results, and thermal insulation performance test results.

[0066] Specific Implementation Example 1: In this embodiment, after receiving the thermally insulated concrete composite material sample, the sample boundary construction module moves the sample into the clamping position and keeps the heating direction consistent with the direction corresponding to the hot surface and the cooling direction consistent with the direction corresponding to the cold surface during the clamping process. Under the condition that the clamping state remains unchanged, the thickness reading content corresponding to multiple positions is read sequentially along the thickness direction, and then the contour reading content is read continuously along the outer edge. Based on the hot surface temperature acquisition position, cold surface temperature acquisition position, penetration heat flow acquisition position and internal temperature distribution acquisition position, the sensing position marking process is performed one by one, so that the thickness reading content, contour reading content and sensing position marking content keep the position corresponding in the same data record, and the sample boundary basic data is generated.

[0067] After the basic data of the sample boundary is generated, the phased thermal excitation module reads the thickness reading, contour reading, and sensor position identification. The thickness reading is mapped to the thickness direction of the thermally insulated concrete composite sample, the contour reading is mapped to the outer edge range, and the sensor position identification is mapped to each acquisition position. Then, the hot surface boundary construction process and the cold surface boundary construction process are executed sequentially, so that the hot surface boundary and the cold surface boundary correspond to the detection areas on both sides of the thermally insulated concrete composite sample, respectively. After the boundary construction is completed, the constant temperature difference excitation process, the step heating excitation process, the step cooling excitation process, and the recovery stage excitation process are executed sequentially according to the detection order, so that all detection stages are continuous in the detection order, and boundary temperature control data are generated.

[0068] After the boundary temperature control data is generated, the multi-source thermal response acquisition module continuously performs hot surface temperature acquisition processing, cold surface temperature acquisition processing, surface thermal field image acquisition processing, penetration heat flow acquisition processing, internal temperature distribution acquisition processing, and stage mass change acquisition processing according to the detection stage sequence and sampling time in the boundary temperature control data. At the same sampling time, the hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, penetration heat flow acquisition content, internal temperature distribution acquisition content, and stage mass change acquisition content are kept synchronously corresponding and written into the sensor position identification content in the sample boundary basic data item by item. After all sampling times are completed, the various acquisition contents are continuously arranged according to the detection stage sequence to generate a time-series thermal response dataset.

[0069] After the time-series thermal response dataset is generated, the thermal response alignment and processing module first performs sampling time alignment processing on the hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, penetration heat flow acquisition content, internal temperature distribution acquisition content, and stage quality change acquisition content, so that the various acquisition contents at the same sampling time are re-merged into the corresponding positions of the same sampling time; then, it performs sensor position alignment processing based on the sensor position identifier content, so that the hot surface temperature acquisition content, cold surface temperature acquisition content, penetration heat flow acquisition content, and internal temperature distribution acquisition content correspond to their respective acquisition positions; then, it performs thermal field region correspondence processing based on the contour reading content, so that each thermal field region in the surface thermal field image acquisition content corresponds to the contour range of the thermal insulation concrete composite material sample; after completing the above processing, it performs detection stage slicing processing on all acquisition contents to generate thermal response aligned data.

[0070] After the thermal response alignment data is generated, the thermal path reconstruction module first performs surface thermal field discrete recognition processing on the surface thermal field image acquisition content according to the thermal field region, so that the surface thermal field change content corresponding to different thermal field regions forms a discrete correspondence. Then, it performs penetration heat flow association processing on the content of each thermal field region with the penetration heat flow acquisition content corresponding to the same region at the same sampling time, and then performs internal temperature gradient association processing on the content of internal temperature distribution acquisition content corresponding to the same location at the same sampling time, so that the content of each thermal field region simultaneously maintains the correspondence between the surface thermal field change content, the penetration heat flow acquisition content, and the internal temperature distribution acquisition content. On this basis, the Landweber iterative internal heat conduction inversion algorithm is executed, and after the processing is completed, thermal path aggregation processing, interface thermal resistance correspondence processing, and local thermal bridge location processing are continued to be executed to generate regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data.

[0071] After the regional thermal pathway data, interface thermal resistance distribution data, and local thermal bridge indication data are generated, the damp heat correction and evaluation module reads the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data according to the detection phase sequence, and keeps the three types of content corresponding within the same detection phase. Then, damp heat state association processing is performed to establish a correspondence between the quality change content and the heat conduction change content corresponding to each detection phase. On this basis, the Pettitt mutation point phase attenuation identification algorithm is executed to establish a phase difference relationship between the thermal pathway change content and the interface thermal resistance change content of adjacent detection phases. Then, based on the phase difference relationship, heat preservation attenuation correction processing is performed to generate damp heat coupling correction data and phase heat preservation attenuation data.

[0072] After the generation of the humid-heat coupling correction data and the stage insulation attenuation data, the comprehensive judgment output module reads the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-heat coupling correction data, and stage insulation attenuation data. First, it performs overall equivalent thermal conductivity calculation and overall thermal resistance calculation, and then performs regional insulation consistency judgment and interface anomaly level judgment. Subsequently, the regional insulation consistency results and interface anomaly level results are mapped to the same thermal field area and the same interface position in each detection stage, and stage association processing is performed with the overall equivalent thermal conductivity and overall thermal resistance corresponding to each detection stage. After the stage association processing is completed, the comparison processing between the previous and subsequent stages is performed, and the insulation performance test conclusion is generated based on the change relationship between each detection stage. Finally, the overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, interface anomaly level results, and insulation performance test conclusion are continuously arranged and output in the order of the detection stages.

[0073] Specific Implementation Example 2: In this embodiment, after receiving the thermal response alignment data, the thermal path reconstruction module first reads the surface thermal field image acquisition content, the penetration heat flow acquisition content, and the internal temperature distribution acquisition content item by item according to the sampling time sequence. Then, it maintains a synchronous retrieval relationship between the surface thermal field image acquisition content at the same sampling time and the penetration heat flow acquisition content and the internal temperature distribution acquisition content corresponding to that sampling time. After completing the reading according to the sampling time sequence, it reads the content of each region in the surface thermal field image acquisition content segment by segment along the thermal field region in each sampling time, so that the content of the previous thermal field region at the same sampling time and the content of the next thermal field region are arranged sequentially according to the position of the thermal field region, and the content of each thermal field region is kept consistent with the current sampling time.

[0074] After completing the above reading, the thermal path reconstruction module performs surface thermal field discrete recognition processing on the surface thermal field image acquisition content according to the thermal field region, splitting each thermal field region one by one, so that each thermal field region retains only the surface thermal field change content corresponding to the current region, and the surface thermal field change content corresponding to adjacent thermal field regions is separated from each other in the arrangement position; after all thermal field regions are processed at the same sampling time, the same processing is performed on all thermal field regions at the next sampling time, so that the surface thermal field change content corresponding to different thermal field regions forms a discrete correspondence at each sampling time, and the surface thermal field change content of the same thermal field region remains continuous between the sampling times.

[0075] After completing the discrete identification of the surface thermal field, the thermal path reconstruction module performs a penetration heat flow association process on the content of each thermal field region that has formed a discrete correspondence with the penetration heat flow acquisition content corresponding to the same region at the same sampling time. First, it retrieves the surface thermal field change content corresponding to the current thermal field region at the current sampling time, and then retrieves the penetration heat flow acquisition content that is consistent with the current thermal field region at the same sampling time, so that the surface thermal field change content of the current thermal field region and the penetration heat flow acquisition content of the current thermal field region are in the same corresponding unit. After the current thermal field region is matched, the penetration heat flow acquisition content corresponding to the next thermal field region is retrieved in sequence and the same matching process is performed, so that the content of each thermal field region at the same sampling time has penetration heat flow acquisition content consistent with its region position. After all thermal field regions at the current sampling time are processed, the same process is performed on each thermal field region at the next sampling time in the order of sampling time, so that the content of each thermal field region and the penetration heat flow acquisition content corresponding to the same region at the same sampling time maintain a continuous and consistent association relationship.

[0076] After completing the through-thermal flow correlation processing, the thermal path reconstruction module performs internal temperature gradient correlation processing on the content of each region and the internal temperature distribution acquisition content corresponding to the same sampling time and location. First, it reads the surface thermal field change content and through-thermal flow acquisition content that are already correlated in the current region content at the current sampling time, and then reads the internal temperature distribution acquisition content that is consistent with the current region location, so that the surface thermal field change content, through-thermal flow acquisition content and internal temperature distribution acquisition content in the current region content remain synchronously corresponding under the same sampling time and location conditions. After the current region completes the correspondence, the same processing is performed on the remaining regions at the same sampling time in sequence. After all regions at the current sampling time have completed the processing, the same processing is performed on the content of each region at the next sampling time in the order of sampling time, so that the content of each region simultaneously maintains the correspondence between the surface thermal field change content, through-thermal flow acquisition content and internal temperature distribution acquisition content before entering the Landweber iterative internal heat conduction inversion algorithm processing.

[0077] After completing the surface thermal field discrete identification, through-thermal flow correlation, and internal temperature gradient correlation processing, the thermal path reconstruction module continues to execute the Landweber iterative internal heat conduction inversion algorithm. First, it reads all region content and performs sequential arrangement processing according to the correspondence between thermal field region, sampling time, and location. This ensures that the region content of the same thermal field region at different sampling times is arranged continuously in the order of the sampling time, and that the region content of different thermal field regions at the same sampling time is arranged continuously in the order of their region locations. After the sequential arrangement processing is completed, it executes the processing based on the through-thermal flow acquisition content and internal temperature distribution acquisition content of each region. The process involves performing regional heat conduction estimation and comparing the estimated regional heat conduction with the corresponding surface thermal field changes in the current region. After the comparison is completed, a reverse iterative correction is performed on each region based on the comparison results. The revised regional heat conduction estimation and comparison are then performed again. After all regions have completed the reverse iterative correction in the current round, the revised regional content is used as the input for the next round. Multiple rounds of reverse iterative correction are then performed sequentially according to the thermal field region and sampling time.

[0078] After completing multiple rounds of reverse iterative correction, the thermal path reconstruction module performs thermal path aggregation, interface thermal resistance correspondence processing, and local thermal bridge location processing based on the content of each region formed in the final round. In the thermal path aggregation processing, relevant content of the same thermal field region at different sampling times is merged into the corresponding range of the same thermal field region according to the sampling time sequence to generate regional thermal path data. In the interface thermal resistance correspondence processing, the regional heat conduction estimation content, penetration heat flow acquisition content, and internal temperature distribution acquisition content of adjacent thermal field regions at the same sampling time are kept adjacent and correspondent to generate interface thermal resistance distribution data. In the local thermal bridge location processing, the corresponding content of the current thermal field region and the adjacent thermal field regions are compared item by item along the thermal field region position direction, and after the comparison of all sampling times is completed, the positions with concentrated and continuous corresponding changes are retained to generate local thermal bridge indication data.

[0079] After the regional thermal pathway data, interface thermal resistance distribution data, and local thermal bridge indication data are generated, the damp heat correction assessment module receives the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data. First, it reads the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data corresponding to each detection phase in the order of detection phases, so that the three types of content under the same detection phase are placed in the corresponding positions of the same detection phase. After completing the reading in the order of detection phases, it performs damp heat state association processing on the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data that maintain the corresponding relationship under the same detection phase, so that the quality change content and heat conduction change content corresponding to each detection phase are respectively linked.

[0080] After completing the damp heat state correlation processing, the damp heat correction and evaluation module performs Pettitt mutation point stage attenuation identification algorithm processing on the damp heat state correlation results corresponding to adjacent detection stages. First, it reads the damp heat state correlation results corresponding to adjacent detection stages in the order of detection stages, and simultaneously reads the quality change content, thermal path change content, and interface thermal resistance change content corresponding to the current detection stage and the previous detection stage. Then, it arranges the quality change content, thermal path change content, and interface thermal resistance change content corresponding to adjacent detection stages in the order of detection stages. After completing the sequential arrangement processing, it continues to perform the corresponding processing of the preceding and following stages, so that the current detection... The quality changes, thermal path changes, and interface thermal resistance changes corresponding to each stage are compared with the corresponding content of the previous detection stage to form a stage comparison sequence. After forming the stage comparison sequence, stage difference accumulation processing is performed to ensure that each detection stage generates a corresponding stage difference change amount as the detection sequence progresses. After generating the stage difference change amount, abrupt change point identification processing is performed to determine the location of the detection stage where the stage difference change amount is concentrated, and to establish an abrupt change point correspondence between this detection stage location and the corresponding thermal path changes and interface thermal resistance changes. After establishing the abrupt change point correspondence, stage attenuation localization processing is performed to generate the stage difference relationship.

[0081] After the stage difference relationship is generated, the damp heat correction assessment module performs insulation attenuation correction processing based on the stage difference relationship. First, it reads the stage difference relationship corresponding to the current detection stage, and then simultaneously reads the stage quality change acquisition results, regional thermal path data, and interface thermal resistance distribution data corresponding to the current detection stage. It ensures that the stage difference relationship corresponding to the current detection stage corresponds to the stage quality change acquisition results, regional thermal path data, and interface thermal resistance distribution data corresponding to the current detection stage at the same detection stage position. Subsequently, it maintains the continuous correlation between the quality change content, heat conduction change content, and interface thermal resistance change content within the current detection stage position, and retains the processing results of the current detection stage position within the corresponding range of the current detection stage. After completing the insulation attenuation correction processing for all detection stages, it generates damp heat coupling correction data and stage insulation attenuation data.

[0082] After the generation of the humid-heat coupling correction data and the stage insulation attenuation data, the comprehensive judgment output module receives the regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-heat coupling correction data, and stage insulation attenuation data, and reads the data corresponding to the constant temperature difference excitation processing, step heating excitation processing, step cooling excitation processing, and recovery stage excitation processing in the order of the detection stages. After completing the reading in the order of the detection stages, it first performs overall equivalent thermal conductivity calculation processing and overall thermal resistance calculation processing based on the regional thermal path data and interface thermal resistance distribution data, then performs regional insulation consistency judgment processing based on the regional thermal path data and local thermal bridge indication data, and finally performs... The process involves determining the interface anomaly level; after generating the overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, and interface anomaly level results, the regional insulation consistency results and interface anomaly level results are mapped to the same thermal field region and the same interface position in each testing stage, and stage association processing is performed with the overall equivalent thermal conductivity and overall thermal resistance corresponding to each testing stage; after the stage association processing is completed, the results of each testing stage after the stage association processing are compared before and after the stage, and the insulation performance test conclusion is generated based on the change relationship between each testing stage; finally, the overall equivalent thermal conductivity, overall thermal resistance, regional insulation consistency results, interface anomaly level results, and insulation performance test conclusion are continuously arranged and output in the order of the testing stages.

[0083] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A system for testing the thermal insulation performance of thermally insulated concrete composite materials, characterized in that: include: The specimen boundary construction module performs clamping and positioning processing, thickness reading processing, contour reading processing, and sensor position marking processing on the thermal insulation concrete composite specimen to generate basic data of the specimen boundary. The phased thermal excitation module performs hot surface boundary construction processing, cold surface boundary construction processing, constant temperature difference excitation processing, step heating excitation processing, step cooling excitation processing, and recovery stage excitation processing on the basic boundary data of the sample to generate boundary temperature control data. The multi-source thermal response acquisition module performs hot surface temperature acquisition processing, cold surface temperature acquisition processing, surface thermal field image acquisition processing, penetration heat flow acquisition processing, internal temperature distribution acquisition processing, and stage mass change acquisition processing on the basic data and boundary temperature control data of the sample boundary, generating a time-series thermal response dataset. The thermal response alignment and processing module performs sampling time alignment processing, sensor position alignment processing, thermal field region correspondence processing, and detection stage slicing processing on the time-series thermal response dataset and sample boundary basic data to generate thermal response aligned data. The thermal path reconstruction module performs surface thermal field discrete identification processing, penetration heat flow correlation processing, internal temperature gradient correlation processing, and Landweber iterative internal heat conduction inversion algorithm processing on thermal response alignment data to generate regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data. The damp heat correction assessment module performs damp heat state correlation processing, Pettitt mutation point stage attenuation identification algorithm processing, and insulation attenuation correction processing on the phase quality change acquisition results, regional thermal pathway data, and interface thermal resistance distribution data to generate damp heat coupling correction data and phase insulation attenuation data. The comprehensive judgment output module performs overall equivalent thermal conductivity calculation, overall thermal resistance calculation, regional insulation consistency judgment, interface anomaly level judgment, and insulation performance test conclusion generation on regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid-thermal coupling correction data, and stage insulation attenuation data.

2. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The sample boundary construction module receives the thermal insulation concrete composite material sample, places the thermal insulation concrete composite material sample into the clamping position, and keeps the thermal insulation concrete composite material sample in the clamping state with the heating direction and cooling direction corresponding and stable. Multi-location thickness readings were performed along the thickness direction of the thermally insulating concrete composite material sample, and the thickness readings corresponding to each location were written into the same data record in the order of location. Perform contour reading processing along the outer edge of the thermal insulation concrete composite material specimen, and write the contour reading content into the corresponding thickness reading content according to the contour extension order; Based on the hot surface temperature acquisition location, cold surface temperature acquisition location, penetration heat flow acquisition location, and internal temperature distribution acquisition location, sensor location identification processing is performed, and the sensor location identification content is integrated with the thickness reading content and contour reading content to generate basic sample boundary data.

3. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The phased thermal excitation module receives the basic data of the sample boundary and performs hot surface boundary construction processing and cold surface boundary construction processing based on the thickness reading content, contour reading content and sensor position identification content in the basic data of the sample boundary, so that the hot surface boundary and the cold surface boundary correspond to the two sides of the detection area of ​​the thermal insulation concrete composite sample respectively. After completing the hot surface boundary construction process and the cold surface boundary construction process, constant temperature difference excitation process is performed according to the detection sequence to form a constant temperature difference state between the hot surface boundary and the cold surface boundary. After constant temperature difference excitation, step temperature rise excitation is performed to make the hot surface boundary temperature change step by step in a stage sequence, and to keep the cold surface boundary temperature in the boundary state corresponding to the current detection stage. After the step heating excitation process, a step cooling excitation process is performed to cause the hot surface boundary temperature to gradually decrease in the order of stages corresponding to the step heating excitation process. After the step cooling excitation process, the recovery stage excitation process is performed to bring the hot and cold surface boundaries into the boundary states corresponding to the recovery stage, generating boundary temperature control data.

4. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The multi-source thermal response acquisition module receives basic boundary data and boundary temperature control data of the sample. Based on the detection stage sequence and sampling time in the boundary temperature control data, it performs hot surface temperature acquisition processing, cold surface temperature acquisition processing, surface thermal field image acquisition processing, penetration heat flow acquisition processing, internal temperature distribution acquisition processing, and stage mass change acquisition processing respectively. The data collected on the hot surface temperature, cold surface temperature, surface thermal field image, penetrating heat flow, internal temperature distribution, and stage quality change are organized according to the same sampling time. The various types of data collected at the same sampling time are written into the corresponding sensor position identifiers in the basic data of the sample boundary, and then arranged continuously according to the detection stage order to generate a time-series thermal response dataset.

5. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The thermal response alignment and sorting module receives the time-series thermal response dataset and the basic data of the sample boundary. It performs sampling time alignment processing on the hot surface temperature acquisition content, cold surface temperature acquisition content, surface thermal field image acquisition content, penetration heat flow acquisition content, internal temperature distribution acquisition content and stage mass change acquisition content in the time-series thermal response dataset, so that the various acquisition contents at the same sampling time maintain the corresponding relationship. Based on the sensor position identification information in the basic data of the sample boundary, sensor position alignment processing is performed on various types of acquisition content after the sampling time alignment processing is completed, so that the hot surface temperature acquisition content, cold surface temperature acquisition content, penetration heat flow acquisition content and internal temperature distribution acquisition content correspond to their respective acquisition positions. Based on the contour reading content in the basic data of the sample boundary, the surface thermal field image acquisition content after the sensing position alignment process is completed is processed to correspond the thermal field regions, so that each thermal field region in the surface thermal field image acquisition content corresponds to the contour range of the thermal insulation concrete composite sample. After completing the sampling time alignment processing, sensor position alignment processing, and thermal field region correspondence processing, the detection stage slicing processing is performed on various types of acquired content to generate thermal response aligned data.

6. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The thermal path reconstruction module receives thermal response alignment data and performs surface thermal field discrete recognition processing on the surface thermal field image acquisition content in the thermal response alignment data according to the thermal field region, so that the surface thermal field change content corresponding to different thermal field regions forms a discrete correspondence. After the surface thermal field discrete identification processing is completed, the contents of each thermal field region are correlated with the corresponding penetration heat flow acquisition contents of the same region at the same sampling time. After completing the penetration heat flow correlation processing, the content of each region will be correlated with the internal temperature distribution data collected at the same sampling time and location by performing internal temperature gradient correlation processing. After the surface thermal field discrete identification, penetration heat flow correlation, and internal temperature gradient correlation processing are completed, the Landweber iterative internal heat conduction inversion algorithm is applied to each region to generate regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data.

7. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The steps of the Landweber iterative internal heat conduction inversion algorithm include: reading the contents of each region after the surface thermal field discrete identification processing, penetration heat flow correlation processing and internal temperature gradient correlation processing are completed, and performing sequential processing according to the correspondence between thermal field region, sampling time and location, so that the contents of each region remain consistent before entering the iterative processing; Based on the penetration heat flow and internal temperature distribution data collected in each region, regional heat conduction estimation is performed, and the estimated regional heat conduction data is compared with the surface thermal field change data. Based on the corresponding comparison processing results, reverse iterative correction processing is performed on the content of each region, and the region heat conduction estimation processing and corresponding comparison processing are re-performed on the content of each region after reverse iterative correction. The content of each region after the current round of reverse iteration correction is used as the input content for the next round of reverse iteration correction. Multiple rounds of reverse iteration correction are executed continuously in the order of thermal field region and sampling time. Based on the content of each region after multiple rounds of reverse iterative correction, thermal path aggregation processing, interface thermal resistance correspondence processing, and local thermal bridge location processing are performed to generate regional thermal path data, interface thermal resistance distribution data, and local thermal bridge indication data.

8. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The damp heat correction assessment module receives the phase quality change acquisition results, regional thermal path data and interface thermal resistance distribution data, reads the phase quality change acquisition results, regional thermal path data and interface thermal resistance distribution data in the order of detection phase, and maintains the corresponding relationship between the phase quality change acquisition results, regional thermal path data and interface thermal resistance distribution data under the same detection phase. Perform damp heat state correlation processing on the phase quality change acquisition results, regional thermal path data and interface thermal resistance distribution data that maintain the corresponding relationship under the same detection stage, so that the quality change content corresponding to each detection stage is in correspondence with the heat conduction change content. The Pettitt mutation point stage attenuation identification algorithm is applied to the correlation results of the humid heat state corresponding to the adjacent detection stages to form a stage difference relationship between the thermal path changes and interface thermal resistance changes between adjacent detection stages. Based on the stage difference relationship, thermal insulation attenuation correction processing is performed to generate moisture-heat coupling correction data and stage thermal insulation attenuation data.

9. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The steps of the Pettitt mutation point stage decay identification algorithm include: reading the correlation results of the wet and heat state corresponding to the adjacent detection stages in the order of detection stages, and performing sequential processing on the mass change content, thermal path change content and interface thermal resistance change content corresponding to each detection stage to maintain the stage correspondence between adjacent detection stages. After the contents of each detection stage are arranged in the order of detection stages, the corresponding positions of the previous and next stages are processed so that the contents of quality change, thermal path change and interface thermal resistance change corresponding to the current detection stage are compared with the contents of quality change, thermal path change and interface thermal resistance change corresponding to the previous detection stage to form a stage comparison sequence. The content of each detection stage in the formation of the phase alignment sequence is processed by the phase difference accumulation process, so that each detection stage forms a corresponding phase difference change during the progress of the detection sequence; After the cumulative processing of stage differences is completed, mutation point identification processing is performed on the content of each detection stage to determine the location of the detection stage where the change in stage difference is concentrated, and to establish a mutation point correspondence between the location of the detection stage and the corresponding thermal path change content and interface thermal resistance change content. Based on the correspondence of mutation points, stage attenuation localization processing is performed to generate stage difference relationships.

10. The thermal insulation performance testing system for thermally insulated concrete composite materials according to claim 1, characterized in that: The comprehensive judgment output module receives regional thermal path data, interface thermal resistance distribution data, local thermal bridge indication data, humid heat coupling correction data, and stage insulation attenuation data. Based on the regional thermal path data and interface thermal resistance distribution data, it performs overall equivalent thermal conductivity calculation and overall thermal resistance calculation. Based on regional thermal pathway data and local thermal bridge indication data, regional insulation consistency determination processing is performed to make the insulation differences between different thermal field areas form a regional insulation consistency result. Based on the interface thermal resistance distribution data, the humid heat coupling correction data and the stage insulation attenuation data, the interface anomaly level determination process is performed to form the interface anomaly level result by the degree of thermal resistance change corresponding to different interface locations. The overall equivalent thermal conductivity and overall thermal resistance are respectively mapped to the detection stages corresponding to constant temperature difference excitation treatment, step heating excitation treatment, step cooling excitation treatment and recovery stage excitation treatment, and arranged in the order of detection stages; The results of regional thermal insulation consistency and interface anomaly level are respectively mapped to the same thermal field area and the same interface position in each detection stage, and are associated with the overall equivalent thermal conductivity and overall thermal resistance of each detection stage for stage processing. After the completion of the stage correlation processing, the results of each detection stage are compared before and after the stage, and the thermal insulation performance test conclusion is generated based on the change relationship between each detection stage.

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