Heating building outer wall outer surface thermal defect diagnosis method and device, computer equipment and readable storage medium

Abstract

The invention provides a heat supply building outer wall outer surface thermal defect diagnosis method and device, computer equipment and a readable storage medium, and belongs to the technical field of heat supply building energy saving. The problems that an existing building outer wall defect detection method is not high in automation degree and low in calculation efficiency are solved. The method comprises the following steps: step 1, building an outdoor temperature data set by collecting historical meteorological data of a building location; 2, the building outer wall structure is investigated and researched; 3, calculating the outdoor comprehensive temperature and the delay time of the wall body under the action of periodic heat; 4, determining the acquisition time of the infrared thermogram of the outer surface of the outer wall; 5, infrared image feature two-stage classification identification is carried out; 6, judging the thermal defect degree of the outer wall; and 7, calling the model and outputting a thermotechnical defect diagnosis result. The method is mainly used for heat supply building outer wall outer surface thermotechnical defect diagnosis.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy-saving heating buildings, and in particular relates to a method, device, computer equipment and readable storage medium for diagnosing thermal defects on the outer surface of an exterior wall of a heating building. Background Art

[0002] The exterior wall area of ​​a building accounts for approximately two-thirds of the total area of ​​its external envelope. Thermal defects in the exterior walls are one of the factors that affect a building's energy-saving performance and the comfort of its indoor thermal environment. Currently, a large number of heated buildings use external wall insulation, which places the insulation layer outside the structural layer. This approach has many advantages. However, this type of wall structure often suffers from thermal defects such as missing insulation, cracking, hollowing, and thermal bridges that affect the building's energy-saving performance. This is due to aging, degradation, or damage caused by outdoor climate factors, or it may be caused by poor construction quality during new construction or renovation. Moreover, thermal defects are generally difficult to detect with the naked eye, as the insulation layer is covered by a finishing layer, making them difficult to quickly and accurately identify.

[0003] To ensure building energy efficiency and indoor thermal environment quality, the "Residential Building Energy Efficiency Testing Standard" (JGJ / T132-2009) provides methods for detecting thermal defects in exterior envelope structures and recommends the use of infrared thermal imaging cameras. However, manually implementing the testing process outlined in this standard presents weaknesses such as long lead times, high labor and material costs, and difficulty ensuring accuracy. The standard does not provide specific calculation or identification methods for exterior wall defect areas and main body areas in infrared images, nor does it provide methods for identifying and segmenting non-exterior wall areas (doors, windows, etc.). Furthermore, thermal defects on the exterior surfaces of heated building exterior walls vary in types and characteristics, necessitating different repair or treatment measures. Methods should be developed to classify defect types and quantify their severity to facilitate the rapid development of repair or renovation plans.

[0004] The existing Chinese invention patent with publication number CN115144434A discloses "A method for detecting defects in building exterior walls using infrared thermal imaging technology." The recommended sampling test time is the period when the outdoor air temperature rises. However, this conclusion is too macro and does not target the specific conditions of the test building (such as: geographical location, exterior wall orientation, and exterior wall structure, etc.). The journal article "Rapid Identification Method for Thermal Defects of Building Exterior Walls Based on Infrared Image Features" (Building Science, 2023.06) proposes the use of machine learning methods to identify thermal defects in building exterior walls, but there are still problems such as low degree of automation and need to improve computational efficiency. Summary of the Invention

[0005] In view of this, the present invention aims to propose a method, device, computer equipment and readable storage medium for diagnosing thermal defects on the outer surface of the exterior wall of a heating building, so as to solve the problems of low automation and low computational efficiency of existing building exterior wall defect detection methods.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building comprises the following steps:

[0008] Step 1: Build an outdoor temperature data set by collecting historical meteorological data of the building location;

[0009] Step 2: Conduct research on the building's exterior wall structure;

[0010] Step 3: Calculate the outdoor comprehensive temperature and the delay time of the wall under periodic thermal action;

[0011] Step 4: Determine the acquisition time of the infrared thermal image of the exterior wall surface;

[0012] Step 5: Perform two-level classification and recognition of infrared image features;

[0013] Step 6: Determine the degree of thermal defects of the exterior wall;

[0014] Step 7: Call the model and output the thermal defect diagnosis results.

[0015] Furthermore, in step 1, the time intervals of sunny or cloudy weather conditions are selected to construct a temperature data set formed by the air temperature at each hour.

[0016] Furthermore, the outdoor integrated temperature calculated in step 3 is used to express the combined effect of outdoor air temperature and solar radiation.

[0017] Furthermore, step 3 calculates the delay time of the wall under periodic heat action based on the thermal inertia index of the exterior wall, the heat transfer coefficients of the inner and outer surfaces of the exterior wall, and the heat storage coefficients of the inner and outer surfaces of the exterior wall.

[0018] Furthermore, the selection of the collection time in step 4 needs to satisfy the conditions that the derivative of the outdoor comprehensive temperature sine function is in the interval -0. to 0.5 and the time after the heating transfer delay time when the outdoor comprehensive temperature reaches the peak.

[0019] Furthermore, infrared thermal image acquisition is to capture infrared thermal image information of the inspected surfaces of the exterior walls of the inspected building in all directions, and infrared thermal images of the same part of the inspected surface.

[0020] Furthermore, in step 5, the two-level classification and recognition of infrared image features completes the elimination of inherent high-temperature areas and the analysis and evaluation of thermal defects through image calling, preprocessing and standardization, and the establishment of a machine learning diagnosis model based on the combination of mechanism analysis and data-driven.

[0021] Furthermore, a device for diagnosing thermal defects on the outer surface of an exterior wall of a heating building is provided, the device comprising:

[0022] The collection module is used to build an outdoor temperature data set by collecting historical meteorological data of the building location;

[0023] Analysis module, used to investigate the building exterior wall structure;

[0024] Calculation module, used to calculate the outdoor comprehensive temperature and the delay time of the wall under periodic thermal action;

[0025] A time determination module is used to determine the acquisition time of the infrared thermal image of the outer surface of the exterior wall;

[0026] Feature recognition module, used for two-level classification and recognition of infrared image features;

[0027] Defect judgment module, used to judge the degree of thermal defects of exterior walls;

[0028] The result diagnosis module is used to call the model and output the thermal defect diagnosis results.

[0029] Furthermore, a computer device includes a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes the method for diagnosing thermal defects on the exterior surface of the exterior wall of a heating building as described in any one of claims 1 to 9.

[0030] Furthermore, a computer-readable storage medium is provided, wherein the computer-readable storage medium is used to store a computer program, wherein the computer program executes the method for diagnosing thermal defects on the outer surface of the exterior wall of a heating building according to any one of claims 1-9.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. The present invention combines statistical analysis of meteorological data, heat transfer characteristics under the action of harmonics, the least squares principle, building thermal characteristics and machine learning methods. From physical mechanism to model construction, and then to practical application, it has the characteristics of easy understanding, convenient implementation, strong theoretical interpretability and strong robustness, which can meet the needs of thermal defect detection and analysis of the exterior surface of building exterior walls.

[0033] 2. The present invention calculates the outdoor comprehensive temperature as a periodic thermal effect over a period of time, and considers the delay effect of typical building exterior wall structures on harmonic thermal effects. The above factors are combined to determine the recommended acquisition time of infrared thermal images of exterior walls of buildings in different regions and directions. This can effectively avoid interference caused by too small temperature differences or too large temperature fluctuations, and help improve the accuracy of the training process and the accuracy of thermal defect classification prediction results.

[0034] 3. This invention features ease of use, simple operation, universal applicability, rapidity, and efficiency. It can accurately, efficiently, and automatically detect thermal defects on the exterior surfaces of building exterior walls. This method can be used to identify thermal defects on building exterior walls, providing technical guidance for repairing and improving the performance of exterior wall insulation. This method is beneficial for promoting energy conservation and emission reduction in the construction industry while improving the quality of the indoor thermal environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which constitute part of the present invention, are provided to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are provided to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0036] Figure 1 The present invention provides a flow chart of a method for diagnosing thermal defects on the exterior surface of an exterior wall of a heating building. DETAILED DESCRIPTION

[0037] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely explain the technical solutions in the embodiments of the present invention. It should be noted that the embodiments of the present invention and the features therein can be combined with each other in the absence of conflict, and the embodiments described are only part of the embodiments of the present invention, not all of the embodiments.

[0038] See also Figure 1 This embodiment describes a method for diagnosing thermal defects on the exterior surface of an exterior wall of a heating building, comprising the following steps:

[0039] Step 1: Build an outdoor temperature data set by collecting historical meteorological data of the building location;

[0040] A time interval without special meteorological conditions (usually 3-4 days) is selected to construct a temperature data set formed by the air temperature at each hour.

[0041] Step 2: Conduct research on the building's exterior wall structure;

[0042] By investigating the exterior wall structure of the building, we can understand its typical structural layers and the geometric dimensions and important parameters of the thermophysical properties of the materials at each layer (thermal conductivity, density, specific heat capacity, etc.).

[0043] Step 3: Calculate the outdoor comprehensive temperature and the delay time of the wall under periodic thermal action;

[0044] The hourly value of the outdoor comprehensive temperature is calculated based on the outdoor air temperature, the absorption coefficient of the outer surface of the typical building exterior wall to solar radiation heat, the solar radiation intensity, the external surface heat transfer coefficient and the effective long-wave radiation temperature of the exterior wall. Using data analysis software, a sinusoidal function with a period of 24 hours is obtained based on the least squares principle to express the daily outdoor comprehensive temperature fluctuations in different directions.

[0045] The delay time of the wall under periodic (daily) heat action is calculated based on the thermal inertia index of the exterior wall, the heat transfer coefficient of the inner and outer surfaces of the exterior wall, and the heat storage coefficient of the inner and outer surfaces of the exterior wall.

[0046] Step 4: Determine the acquisition time of the infrared thermal image of the exterior wall surface;

[0047] Infrared thermal imaging equipment is used to collect images of building exterior walls from different regions, eras, and types. The inspection time must be determined according to a process calculation, taking into account the dual effects of the outdoor integrated temperature and the heat transfer delay characteristics of the exterior wall. The time period T corresponding to the derivative of the hourly outdoor integrated temperature function lies in the interval (-0.5, 0.5) is selected. The time when the outdoor integrated temperature at a certain location of the test building reaches its peak is t1, and the delay time of the wall under periodic thermal effects is t2. The acquisition time must be both included in T and later than t1 + t2.

[0048] Step 5: Perform two-level classification and recognition of infrared image features;

[0049] Dynamic numerical simulations were used to study the infrared image characteristics of building exterior surfaces. Considering that not all areas with abnormal surface temperatures are thermal defects, the study used a hierarchical classification process to improve recognition efficiency and accuracy. The first level classified areas based on inherently high temperatures and thermal defects, while the second level categorized and diagnosed thermal defects.

[0050] Step 6: Determine the degree of thermal defects of the exterior wall;

[0051] The process of image retrieval, preprocessing, standardization, and the construction of a machine learning diagnostic model for thermal defects on exterior wall surfaces follows. For areas with thermal defects, a quadtree segmentation method is used to determine the defect area ratio.

[0052] Step 7: Call the model and output the thermal defect diagnosis results.

[0053] Furthermore, the outdoor comprehensive temperature calculated in step 3 is used to express the combined effect of outdoor air temperature and solar radiation.

[0054] The calculated outdoor comprehensive temperature is used to express the combined effect of outdoor air temperature and solar radiation, and is calculated according to formula (1).

[0055] t sa =t e +ρ s I / α e -t 1r (1)

[0056] Among them, t sa is the outdoor comprehensive temperature; t e is the outdoor air temperature; ρ s is the absorption coefficient of solar radiation heat on the exterior surface of the exterior wall; I is the solar radiation intensity; α e is the external surface heat transfer coefficient; t 1r is the effective long-wave radiation temperature of the exterior wall. Based on the least squares principle, the daytime outdoor comprehensive temperature curves of different orientations in the form of sine (or cosine) are generated.

[0057] Furthermore, step 3 calculates the delay time of the wall under periodic heat action based on the thermal inertia index of the exterior wall, the heat transfer coefficients of the inner and outer surfaces of the exterior wall, and the heat storage coefficients of the inner and outer surfaces of the exterior wall.

[0058] The heat transfer delay characteristics analysis of the exterior wall is to first calculate the heat transfer delay time of the building exterior wall under periodic thermal action according to formula (2).

[0059]

[0060] Where ξ0 is the delay time of the outdoor comprehensive temperature wave, D is the thermal inertia index of the exterior wall, which is related to the thermal resistance and heat storage coefficient of each material layer of the exterior wall; α i and α e are the heat transfer coefficients of the inner and outer surfaces of the exterior wall, respectively; Yi and Ye are the surface heat storage coefficients of the inner and outer surfaces of the exterior wall, respectively. According to formula (2), the heat transfer delay time is estimated according to the design working conditions.

[0061] Furthermore, the selection of the collection time in step 4 needs to satisfy the conditions that the derivative of the outdoor comprehensive temperature sine function is in the interval -0. to 0.5 and the time after the heating transfer delay time when the outdoor comprehensive temperature reaches the peak.

[0062] Furthermore, infrared thermal image acquisition is to capture infrared thermal image information of the inspected surfaces of the exterior walls of the tested building in all directions. There should be no less than 2 infrared thermal images of the same part of the inspected surface, and the measurement values ​​of the key points for two consecutive times should not be greater than 0.5℃. The infrared thermal imager used in the test should be designed to have an applicable wavelength range of (8.0~14.0)μm and no less than 76,800 pixels.

[0063] The two-level classification and recognition of infrared image features primarily identifies and eliminates inherently high-temperature areas, such as exterior windows and walls beneath them. Furthermore, thermal defects, including common types such as cracks, leaks, hollows, and thermal bridges, are identified. Specifically, based on infrared imagery of exterior walls in different climate zones, ages, types (residential, public, industrial), and orientations, a dynamic numerical simulation method is used to analyze and extract the infrared thermal image features of each type. Inherently high-temperature areas are then preemptively eliminated to facilitate classification and diagnosis of thermal defects.

[0064] Furthermore, in step 5, the two-level classification and recognition of infrared image features completes the elimination of inherent high-temperature areas and the analysis and evaluation of thermal defects through image calling, preprocessing and standardization, and the establishment of a machine learning diagnosis model based on the combination of mechanism analysis and data-driven.

[0065] Furthermore, the exterior wall thermal defect determination refers to inputting qualified infrared thermal image information of the inspected surface, calling the above-mentioned machine learning diagnostic model, excluding inherent high-temperature areas, completing automatic identification of the main area of ​​the inspected surface and the thermal defect area, automatically classifying the thermal defect area, and automatically realizing the calculation of the relative area ratio ψ in the "Residential Building Energy Saving Test Standard" JGJ / T132-2009, and making determinations based on the indicators specified in "5.2 Qualified Indicators and Determination Methods" of the standard. The following formula (3) is the calculation of the relative area ratio ψ.

[0066]

[0067] Where: ψ: the ratio of the inspected surface defect area to the main area; A 1,i : The area of ​​the main area of ​​the i-th thermal image (m 2 );A 2,i : The area of ​​the defective area in the i-th thermal image refers to the area composed of points whose average temperature difference with the main area of ​​the inspected surface (excluding the defective area) is greater than or equal to 1°C (m 2 ).

[0068] Furthermore, a device for diagnosing thermal defects on the outer surface of an exterior wall of a heating building is provided, the device comprising:

[0069] The collection module is used to build an outdoor temperature data set by collecting historical meteorological data of the building location;

[0070] Analysis module, used to investigate the building exterior wall structure;

[0071] Calculation module, used to calculate the outdoor comprehensive temperature and the delay time of the wall under periodic thermal action;

[0072] A time determination module is used to determine the acquisition time of the infrared thermal image of the outer surface of the exterior wall;

[0073] Feature recognition module, used for two-level classification and recognition of infrared image features;

[0074] Defect judgment module, used to judge the degree of thermal defects of exterior walls;

[0075] The result diagnosis module is used to call the model and output the thermal defect diagnosis results.

[0076] Furthermore, a computer device includes a memory and a processor, wherein the memory stores a computer program. When the processor runs the computer program stored in the memory, the processor executes a method for diagnosing thermal defects on the outer surface of the exterior wall of a heating building.

[0077] Furthermore, a computer-readable storage medium is provided, wherein the computer-readable storage medium is used to store a computer program, wherein the computer program executes a method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building.

[0078] Those skilled in the art will appreciate that the features described in the various embodiments and / or claims of this disclosure may be combined or coupled in various ways, even if such combinations or couplings are not explicitly described in this disclosure. In particular, the various embodiments of this disclosure may be combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations are intended to fall within the scope of this disclosure.

[0079] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the invention. Thus, the present invention is intended to include such changes and modifications as fall within the scope of the claims and their equivalents.

Claims

1. A method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building, characterized by: It includes the following steps: Step 1: Build an outdoor temperature data set by collecting historical meteorological data of the building location; Step 2: Conduct research on the building's exterior wall structure; Step 3: Calculate the outdoor comprehensive temperature and the delay time of the wall under periodic thermal action; Step 4: Determine the acquisition time of the infrared thermal image of the exterior wall surface; Step 5: Perform two-level classification and recognition of infrared image features; Step 6: Determine the degree of thermal defects of the exterior wall; Step 7: Call the model and output the thermal defect diagnosis results.

2. A method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building according to claim 1, characterized in that: In step 1, the time intervals of sunny or cloudy weather conditions are selected to construct a temperature data set formed by the air temperature at each hour.

3. The method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building according to claim 1, characterized in that: The combined effect of outdoor air temperature and solar radiation is expressed according to the outdoor composite temperature calculated in step 3.

4. The method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building according to claim 1, characterized in that: Step 3 calculates the delay time of the wall under periodic heat action based on the thermal inertia index of the exterior wall, the heat transfer coefficients of the inner and outer surfaces of the exterior wall, and the heat storage coefficients of the inner and outer surfaces of the exterior wall.

5. The method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building according to claim 1, characterized in that: The selection of the collection time in step 4 needs to satisfy the conditions that the derivative of the outdoor comprehensive temperature sine function is in the interval -0. to 0.5 and the time after the heating transfer delay time when the outdoor comprehensive temperature reaches the peak.

6. The method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building according to claim 1, characterized in that: Infrared thermal image acquisition is to capture the infrared thermal image information of the inspected surfaces of the exterior walls of the tested building in all directions, and the infrared thermal image of the same part of the inspected surface.

7. The method for diagnosing thermal defects on the outer surface of an exterior wall of a heating building according to claim 1, characterized in that: In step 5, the two-level classification and recognition of infrared image features is carried out through image calling, preprocessing and standardization, and a machine learning diagnosis model based on the combination of mechanism analysis and data-driven is established to complete the elimination of inherent high-temperature areas and the analysis and evaluation of thermal defects.

8. A device for diagnosing thermal defects on the outer surface of an exterior wall of a heating building, characterized in that: The device comprises: The collection module is used to collect historical meteorological data of the building's location and construct an outdoor temperature data set; the analysis module is used to conduct research on the building's exterior wall structure; The calculation module is used to calculate the outdoor comprehensive temperature and the delay time of the wall under periodic thermal action; the time determination module is used to determine the acquisition time of the infrared thermal image of the outer surface of the exterior wall; Feature recognition module, used for two-level classification and recognition of infrared image features; Defect judgment module, used to judge the degree of thermal defects of exterior walls; The result diagnosis module is used to call the model and output the thermal defect diagnosis results.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein a computer program is stored in the memory. When the processor runs the computer program stored in the memory, the processor executes the method for diagnosing thermal defects on the outer surface of the exterior wall of a heating building according to any one of claims 1 to 9.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store a computer program, and the computer program executes the method for diagnosing thermal defects on the outer surface of the exterior wall of a heating building according to any one of claims 1 to 9.

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