House external window detection method and system, terminal and storage medium

Abstract

The invention provides a house external window detection method and device, a terminal and a storage medium, and the method comprises the steps: obtaining an external window thermal image generated by scanning an external window of a current house through thermal imaging equipment, and extracting corresponding temperature distribution information from the external window thermal image; acquiring an outer window image generated by shooting the outer window of the current house by a camera device, and identifying the outer window image to determine outer window structural features and outer window potential safety hazards; constructing an outer window three-dimensional model based on the outer window thermal image and the outer window image; and detecting and evaluating the outer window based on the outer window three-dimensional model, the temperature distribution information, the outer window structure characteristics and the outer window potential safety hazard to obtain a detection and evaluation result reflecting the outer window thermal performance and the outer window safety performance. Through combined detection of thermal imaging and machine vision, comprehensive evaluation of the thermal performance and the safety performance of the outer window is realized, automatic detection of the outer window of the house is realized, and the detection efficiency and the accuracy of a detection result are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of building detection, and in particular to a method, system, terminal and storage medium for detecting exterior windows of a house. Background Art

[0002] At present, the inspection of exterior windows of houses mostly relies on manual operation. This method is not only inefficient, but also easily affected by human factors, making it difficult to ensure the accuracy and comprehensiveness of the inspection results. In particular, in the inspection of thermal and safety performance, there is a lack of efficient automated means, making it difficult to meet the high standards of modern buildings for safety and energy conservation. Summary of the invention

[0003] The technical problem to be solved by the present invention is that, in view of the above-mentioned defects of the prior art, a method, system, terminal and storage medium for detecting exterior windows of a house are provided, aiming to solve the problems in the prior art that the detection of exterior windows of a house relies on manual detection, resulting in low efficiency, low detection accuracy, and inability to achieve automated detection.

[0004] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0005] A method for detecting exterior windows of a house, wherein the method comprises:

[0006] Obtaining an external window thermal image generated by scanning an external window of a current house with a thermal imaging device, and extracting corresponding temperature distribution information from the external window thermal image;

[0007] Acquire an exterior window image generated by photographing an exterior window of a current house by a camera device, and identify the exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house;

[0008] Constructing a three-dimensional model of the exterior window corresponding to the current house based on the exterior window thermal image and the exterior window image;

[0009] The exterior windows of the current house are inspected and evaluated based on the exterior window three-dimensional model, the temperature distribution information, the exterior window structural characteristics and the exterior window safety hazards, to obtain inspection and evaluation results reflecting the exterior window thermal performance and exterior window safety performance of the current house.

[0010] In one implementation, the step of obtaining a thermal image of an exterior window generated by scanning an exterior window of a current house with a thermal imaging device includes:

[0011] Obtain an external window thermal image generated by scanning the external windows of the current house with an infrared thermal imager.

[0012] In one implementation, the extracting corresponding temperature distribution information from the exterior window thermal image includes:

[0013] The exterior window thermal image is analyzed using a preset thermal image processing algorithm to extract corresponding temperature gradient information and hot spot information.

[0014] In one implementation, before identifying the exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house, the method further includes:

[0015] Preprocessing the exterior window image according to a preset RGB image processing method to obtain a corresponding target exterior window image;

[0016] The identifying of the exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house includes:

[0017] The target exterior window image is identified using a preset image recognition algorithm to determine the exterior window structural features and exterior window safety hazards of the current house.

[0018] In one implementation, preprocessing the external window image according to a preset RGB image processing method to obtain a corresponding target external window image includes:

[0019] The external window image is subjected to noise removal and contrast enhancement processing according to a preset RGB image processing method to obtain a corresponding target external window image.

[0020] In one implementation, the housing exterior window detection method further includes:

[0021] Monitor the state changes of the external windows of the current house in real time, and determine whether there is an abnormality in the external windows of the current house based on the state changes of the external windows;

[0022] If there is an abnormality in the external window of the current house, an alarm is triggered and corresponding alarm information is pushed to the user.

[0023] In one implementation, determining whether the external window of the current house is abnormal based on the change in the state of the external window includes:

[0024] When the change in the state of the external window indicates that the thermal performance of the external window drops to a preset threshold, it is determined that there is an abnormality in the external window of the current house;

[0025] Alternatively, when the change in the state of the exterior window indicates that the structural damage of the exterior window has reached a preset degree, it is determined that there is an abnormality with the exterior window of the current house.

[0026] The present invention also discloses a house exterior window detection system, wherein the system comprises:

[0027] A thermal imaging detection module, used to obtain a thermal image of an external window generated by scanning an external window of a current house by a thermal imaging device, and to extract corresponding temperature distribution information from the thermal image of the external window;

[0028] A machine vision detection module is used to obtain an external window image generated by a camera device shooting an external window of a current house, and identify the external window image to determine the structural features of the external window of the current house and the safety hazards of the external window;

[0029] The data processing and analysis module is used to construct a three-dimensional model of the exterior windows corresponding to the current house based on the exterior window thermal image and the exterior window image, and to detect and evaluate the exterior windows of the current house based on the exterior window three-dimensional model, the temperature distribution information, the exterior window structural characteristics and the exterior window safety hazards, so as to obtain a detection and evaluation result reflecting the thermal performance and safety performance of the exterior windows of the current house.

[0030] The present invention also discloses a terminal, which includes: a memory, a processor, and a house exterior window detection program stored in the memory and executable on the processor, wherein the house exterior window detection program implements the steps of the house exterior window detection method described above when executed by the processor.

[0031] The present invention also discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program can be executed to implement the steps of the house exterior window detection method as described above.

[0032] The present invention provides a method, system, terminal and storage medium for detecting exterior windows of a house, wherein the method comprises: obtaining an exterior window thermal image generated by scanning the exterior windows of the current house by a thermal imaging device, and extracting corresponding temperature distribution information from the exterior window thermal image; obtaining an exterior window image generated by photographing the exterior windows of the current house by a camera device, and identifying the exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house; constructing an exterior window three-dimensional model corresponding to the current house based on the exterior window thermal image and the exterior window image; and detecting and evaluating the exterior windows of the current house based on the exterior window three-dimensional model, the temperature distribution information, the exterior window structural features and the exterior window safety hazards, and obtaining a detection and evaluation result reflecting the thermal performance and safety performance of the exterior windows of the current house. It can be seen that the present invention realizes automatic detection of the exterior windows of the house by performing corresponding data processing on the exterior window thermal image generated by the thermal imaging device and the exterior window image generated by the camera device, significantly improving the detection efficiency and reducing the labor cost, that is, the comprehensive evaluation of the thermal performance and safety performance of the exterior windows is realized through the combined detection of thermal imaging and machine vision, and the accuracy of the detection results is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a flow chart of a preferred embodiment of the housing exterior window detection method of the present invention;

[0034] Figure 2 It is a thermal imaging image of the exterior windows of a house in winter and summer in the present invention;

[0035] Figure 3 It is a thermal imaging image of a single-layer glass observed indoors in the present invention;

[0036] Figure 4 It is a schematic diagram of heat transfer of an external window in the present invention;

[0037] Figure 5 It is a flow chart of a preferred embodiment of a specific housing exterior window detection method of the present invention;

[0038] Figure 6 It is a schematic diagram of a framework of an external window thermal performance evaluation process in the present invention;

[0039] Figure 7 It is a schematic diagram of a quad-rotor drone and a six-rotor drone in the present invention;

[0040] Figure 8 It is a schematic diagram of a thermal defect of an exterior window detected by a thermal imaging diagram in the present invention;

[0041] Fig. 9 It is a schematic diagram of a thermal defect recognition algorithm in the present invention;

[0042] Fig.10 It is a basic network structure schematic diagram of a convolutional neural network in the present invention;

[0043] Fig.11 It is a schematic diagram of the DeepLabV3+ network structure in the present invention;

[0044] Fig.12 It is a schematic diagram of a UAV-IRT system framework in the present invention;

[0045] Fig.13 This is a schematic diagram of the flight distance of a drone in the present invention;

[0046] Fig.14 It is a schematic diagram of a flight path of a UAV in the present invention;

[0047] Fig.15 It is a functional principle block diagram of a preferred embodiment of the house exterior window detection system of the present invention;

[0048] Fig.16 It is a schematic diagram of a specific house exterior window detection system in the present invention;

[0049] Fig.17It is a functional principle block diagram of a preferred embodiment of the terminal in the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0051] See also Figure 1 , Figure 1 Flow chart of the housing exterior window detection method of the present invention. Figure 1 As shown, the housing exterior window detection method described in the embodiment of the present invention includes:

[0052] Step S11, obtaining an exterior window thermal image generated by scanning an exterior window of a current house with a thermal imaging device, and extracting corresponding temperature distribution information from the exterior window thermal image.

[0053] In this embodiment, a thermal imaging device, such as a thermal imaging camera, which can be an infrared thermal imager, is deployed in the current house to perform contactless scanning on the external window to generate a corresponding external window thermal image, and then obtain the external window thermal image generated by the thermal imaging device, and extract the corresponding temperature distribution information from the external window thermal image. Specifically, the external window thermal image is analyzed using a preset thermal image processing algorithm to extract the corresponding temperature gradient information and hot spot information. It can be understood that the thermal image of the external window is collected, analyzed, and the temperature distribution information therein is determined, so that the thermal performance of the external window can be evaluated based on the temperature distribution information, such as evaluating the thermal insulation performance of the external window, and determining whether there are problems such as thermal bridges.

[0054] Among them, thermal bridge describes a situation in a building where the outside and the inside are directly connected through one or more elements with a higher thermal conductivity than the rest of the building envelope. Specifically, it refers to reinforced concrete or metal beams, columns, ribs and other parts in the envelope structure such as exterior walls and roofs. These parts have strong heat transfer capacity, dense heat flow, and low inner surface temperature, so they are called thermal bridges.

[0055] It should be noted that thermal images are a special type of image that records the heat or temperature of the object itself or radiated outward. In thermal images, temperature distribution information such as temperature gradients and hot spots can be determined. The temperature gradient is a physical quantity that describes the direction and rate of the fastest temperature changes in a specific area. Hot spots refer to areas with higher temperatures in thermal images. In thermal images, hot spots are usually displayed in red or pink, representing higher temperatures. Conversely, blue and green represent lower temperatures.

[0056] For example, see Figure 2As shown in Figure 1, there are temperature differences on the surface of the exterior window glass in different seasons, and this difference can be clearly reflected in the thermal imaging diagram. For example, in summer and winter, a single-layer glass curtain wall is scanned by a thermal imaging device to generate thermal imaging diagrams. From these thermal imaging diagrams, we can see the heat loss of the single-layer glass in winter and the heat gain in summer. Figure 3 As shown in the figure, when observing the thermal image of a single layer of glass from indoors, part of the glass is shaded internally. The high temperature of the unshaded part shows the radiation heat gain and glare problems. Therefore, when performing infrared thermal imaging measurement, corresponding temperature compensation can be performed to improve the imaging quality. Among them, the commonly used temperature compensation methods include the least squares method and machine learning algorithms. The least squares method performs correction by establishing the relationship between the factors affecting temperature measurement and the temperature value.

[0057] Step S12: acquiring an exterior window image generated by photographing an exterior window of the current house with a camera device, and identifying the exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house.

[0058] In this embodiment, the external windows of the current house are photographed by a camera device, such as a high-definition camera, deployed in the current house to generate a corresponding RGB image of the external window, and then the image of the external window photographed by the camera device is obtained, and then the image of the external window is recognized to determine the structural characteristics of the external window of the current house and the safety hazards of the external window. It can be understood that the high-definition image of the external window is collected by a high-definition camera, and then the image is recognized and processed to identify the structural characteristics of the external window and the safety hazards such as cracks and damage.

[0059] Step S13: constructing a three-dimensional model of the exterior windows corresponding to the current house based on the exterior window thermal image and the exterior window image.

[0060] In this embodiment, after obtaining the external window thermal image generated by the thermal imaging device and the external window image taken by the high-definition camera, a three-dimensional model of the external window corresponding to the current house is constructed based on the external window thermal image and the external window image. It can be understood that the thermal imaging and machine vision data are fused to construct a three-dimensional model of the external window, wherein the three-dimensional model of the external window can be used to perform performance analysis in terms of heat energy, light, ventilation, etc., thereby helping to optimize the design of the window to improve the energy efficiency and comfort of the building.

[0061] Step S14: Based on the exterior window three-dimensional model, the temperature distribution information, the exterior window structural characteristics and the exterior window safety hazards, the exterior windows of the current house are inspected and evaluated to obtain inspection and evaluation results reflecting the exterior window thermal performance and exterior window safety performance of the current house.

[0062] In this embodiment, the thermal image of the external window collected by the thermal imaging device and the image of the external window taken by the camera device are obtained, and then the thermal image of the external window is analyzed to determine the corresponding temperature distribution information, and the external window image is identified to determine the structural characteristics of the external window and the safety hazards of the external window, and then the external window of the current house is tested and evaluated based on the three-dimensional model of the external window, the temperature distribution information, the structural characteristics of the external window and the safety hazards of the external window, and the test and evaluation results reflecting the thermal performance and safety performance of the external window of the current house are obtained. It can be understood that by integrating thermal imaging data and machine vision data, constructing a three-dimensional model of the external window, using a data analysis algorithm to comprehensively consider the temperature distribution information, the structural characteristics of the external window and the safety hazards of the external window, and generating a corresponding evaluation report, a comprehensive evaluation of the thermal performance and safety performance of the external window is achieved, and the accuracy of the test results is improved. Then, according to the evaluation report, the thermal performance of the external window can be optimized, which helps to improve the energy-saving effect of the house, reduce energy consumption, and thus promote energy conservation and environmental protection.

[0063] For example, the performance of window systems can be evaluated using the WINDOW software and THERM software, see Figure 4 As shown, the thermal performance of the window system is calculated, so that thermal characteristics such as U factor, shading coefficient, solar heat gain coefficient and other glass center optical parameters can be calculated, the window system is presented as a one-dimensional steady-state model, and then an iterative method is used to perform accurate temperature distribution information analysis, so that any performance index can be derived from the temperature distribution information.

[0064] For example, see the above Figure 4 As shown, by calculating the total product area-weighted properties, WINDOW software can check window products composed of various partitions, gaskets, gas layers, frames and glass layers in any climate conditions and at any angle. After determining the U-factor of the glass frame and edge, WINDOW software can determine the area-weighted total product value, where the U-factor is calculated by multiplying the properties of each component by the respective component area to calculate the area-weighted sum of the properties of each component, and then dividing this total by the total projected area of ​​the product, that is:

[0065]

[0066] Among them, U is the U factor of the edge, A is the area, cg is the center of the glass, such as the edge of the glass, f is the frame, and pf is the size of the window product in the rough opening of the wall or roof.

[0067] THERM software complements WINDOW by solving the two-dimensional energy equation using the finite element method. It should be noted that THERM software integrates the frame and glass components of WINDOW, and boundary conditions can be applied to create a more detailed door and window system model, or boundary conditions can be assigned to each boundary surface to define the numerical model.

[0068] In this embodiment, the state change of the external window of the current house can also be monitored in real time, and based on the state change of the external window, it is determined whether the external window of the current house has an abnormality; if the external window of the current house has an abnormality, an alarm is triggered, and the corresponding alarm information is pushed to the user. It can be understood that when the state change of the external window indicates that the thermal performance of the external window has dropped to a preset threshold, it is determined that the external window of the current house has an abnormality; or when the state change of the external window indicates that the structural damage of the external window has reached a preset degree, it is determined that the external window of the current house has an abnormality. That is to say, by monitoring the changes in the temperature distribution information of the external window and the changes in the safety of the external window in real time, the real-time monitoring of the state change of the external window is realized. Once an abnormality is found, such as a decrease in thermal insulation performance, aggravated structural damage, etc., an alarm is triggered to remind the user to take timely measures to repair or maintain the external window, so that potential safety hazards can be discovered and warned in time.

[0069] It can be seen that in the embodiments of the present invention, by performing corresponding data processing on the external window thermal images generated by the thermal imaging device and the external window images generated by the camera device, automatic detection of the external windows of the house is achieved, which significantly improves the detection efficiency and reduces the labor cost. That is, through the combined detection of thermal imaging and machine vision, a comprehensive evaluation of the thermal performance and safety performance of the external windows is achieved, thereby improving the accuracy of the detection results.

[0070] See also Figure 5 As shown, the embodiment of the present invention discloses a specific method for detecting exterior windows of a house. Compared with the previous embodiment, this embodiment further illustrates and optimizes the technical solution.

[0071] Step S21, obtaining an exterior window thermal image generated by scanning an exterior window of a current house with a thermal imaging device, and extracting corresponding temperature distribution information from the exterior window thermal image.

[0072] Step S22, obtaining an exterior window image generated by photographing an exterior window of the current house by a camera device;

[0073] Step S23, pre-processing the exterior window image according to a preset RGB image processing method to obtain a corresponding target exterior window image, and using a preset image recognition algorithm to recognize the target exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house.

[0074] In this embodiment, an external window image taken by a camera device is obtained, and the external window image is preprocessed according to a preset RGB image processing method to obtain a corresponding target external window image. Specifically, noise removal and contrast enhancement are performed on the external window image according to the preset RGB image processing method to obtain a corresponding target external window image, and then a preset image recognition algorithm is used to perform recognition processing on the preprocessed target external window image to identify safety hazards such as structural features, cracks, and damages of the external window.

[0075] Step S24: constructing a three-dimensional model of the exterior windows corresponding to the current house based on the exterior window thermal image and the exterior window image.

[0076] Step S25, based on the external window three-dimensional model, the temperature distribution information, the external window structural characteristics and the external window safety hazards, the external windows of the current house are inspected and evaluated to obtain inspection and evaluation results reflecting the external window thermal performance and external window safety performance of the current house.

[0077] For the specific contents of the above steps S21 to S22 and steps S24 to S25, reference may be made to the corresponding contents disclosed in the above embodiments, which will not be repeated here.

[0078] It can be seen that in the embodiments of the present invention, by performing corresponding data processing on the external window thermal images generated by the thermal imaging device and the external window images generated by the camera device, automatic detection of the external windows of the house is achieved, which significantly improves the detection efficiency and reduces the labor cost. That is, through the combined detection of thermal imaging and machine vision, a comprehensive evaluation of the thermal performance and safety performance of the external windows is achieved, thereby improving the accuracy of the detection results.

[0079] For example, the thermal performance of building envelopes (such as exterior windows) can be evaluated by installing an infrared thermal imaging system on a drone. Figure 6 As shown in FIG, the main stages of using an infrared thermal imaging system built on a drone to evaluate the thermal performance of building exterior windows include: instrument selection and on-site survey, flight parameter configuration, and data analysis. In the instrument selection and on-site survey stage, a thermal imaging device can be selected and built on a drone, such as a thermal infrared camera (infrared thermal imager) can be installed on the drone to observe the surrounding weather environment of the unmanned aerial vehicle. The drone can be a quad-rotor drone or a six-rotor drone, see Figure 7As shown, rotary wing drones have certain advantages in stable image transmission and operational flexibility; in the flight parameter configuration stage, that is, the parameter selection stage, on-site testing can be performed to test locations such as windows, roofs, and walls; test focus positions, flight paths, etc., and at the same time test the appropriate flight speed, flight altitude, and flight path. In the data analysis stage, the data analysis method can be qualitative or quantitative, and the image formats involved in the thermal performance and safety performance evaluation of external windows are mainly thermal infrared images generated by thermal imaging equipment and RGB images generated by camera equipment. The relevant image processing methods can be semantic segmentation or machine learning. For example, by combining traditional image processing and machine learning techniques, thermal defects of building exterior windows can be identified and located through steps such as image segmentation, feature extraction, and classification.

[0080] For example, see Figure 8 As shown in the figure, the thermal defects of building exterior windows that can be detected by the infrared thermal imaging system mainly include cracks in the insulation layer, delamination of the insulation layer, holes, quality defects of the adhesive in the insulation layer, thermal bridges and air leakage, etc., which helps to identify and evaluate problems such as thermal bridges and voids.

[0081] Specifically, the thermal image obtained by infrared thermal imaging can be used to detect thermal defects through a defect recognition algorithm, wherein see Fig. 9 As shown in the figure, the thermal defect recognition algorithm mainly involves image classification, target detection (edge ​​detection), semantic segmentation (threshold segmentation) algorithm and deep learning algorithm, such as convolutional neural network (CNN), which can better realize the automatic extraction and classification of image features. The basic network structure of convolutional neural network can be seen in Fig.10 As shown, the DeepLabV3+ model can be used specifically. The DeepLabV3+ network structure can be found in Fig.11 As shown, it has a high recognition accuracy in building wall thermal defect detection.

[0082] Among them, in the quantitative analysis of thermal performance evaluation, the temperature data (temperature distribution information) obtained by infrared thermal imaging can be used to calculate the heat loss and thermal conductivity of the building's exterior windows. After post-processing and correction, these data can be used to determine whether the building's exterior windows meet energy efficiency standards. For example, when evaluating the thermal performance of building exterior windows, the steady-state heat conduction theory can be used to calculate the thermal conductivity (U value), where the basic heat conduction equation is:

[0083]

[0084] Where K represents the thermal conductivity of the wall (unit: W / (m 2 ·K)), q represents the heat flow through the wall (unit: W / m2 ), in and Τ ext Respectively represents the air temperature inside and outside (unit: ℃)

[0085] Taking into account factors such as the internal and external surface temperature of the wall, the radiation temperature and the radiation heat transfer coefficient, the overall thermal conductivity of the wall is calculated as follows:

[0086]

[0087] Where ε represents the surface emissivity of the wall, T refl represents the radiation temperature, T s,in represents the inner surface temperature of the wall, T s,out represents the outer surface temperature of the wall, and σ represents the radiation heat transfer coefficient.

[0088] In addition, the wall surface emissivity ε has a significant impact on the accuracy of infrared temperature measurement, that is, accurate measurement of emissivity is crucial for thermal performance testing. The emissivity is calculated as follows:

[0089]

[0090] Where ε represents the emissivity, T0 is the actual surface temperature, T0' is the radiation temperature measured by the infrared thermal imager, and T u is the ambient temperature.

[0091] Specifically, the emissivity of the wall surface is calculated using known temperature measurements, namely:

[0092]

[0093] Also, see Fig.12 As shown in the figure, the UAV-IRT (Infrared Reflow Technology) system is mainly composed of a UAV platform, a thermal infrared camera (thermal imaging equipment), an optical camera (camera equipment), a control terminal and the like. Specifically, the UAV pilot controls the UAV equipped with an infrared thermal imager through a remote command terminal to fly to a predetermined position around the building to scan and photograph the exterior windows. A corresponding ground control station can also be built on the ground to control the UAV through the ground control station. The image data can then be transmitted through a satellite and processed by a computer to evaluate the thermal performance and safety performance of the building's exterior windows.

[0094] It should be noted that the flight distance of different drones from the building exterior wall has an impact on the quality of thermal imaging images, so during the field test phase, see Fig.13As shown, the appropriate flight distance of the drone can be determined by testing different flight distances to ensure the quality of thermal imaging images, and see Fig.14 As shown in the figure, the commonly used flight paths of drones in the thermal performance evaluation of building exterior windows may include but are not limited to the horizontal strip method, the vertical strip method, the grid method, the circular method, the spiral flight method, and the field angle method.

[0095] In one embodiment, if Fig.15 As shown, based on the above-mentioned house exterior window detection method, the present invention also provides a house exterior window detection system, including:

[0096] The thermal imaging detection module 100 is used to obtain an external window thermal image generated by scanning an external window of the current house by a thermal imaging device, and to extract corresponding temperature distribution information from the external window thermal image;

[0097] The machine vision detection module 200 is used to obtain an external window image generated by photographing the external window of the current house by a camera device, and to identify the external window image to determine the structural features of the external window of the current house and the safety hazards of the external window;

[0098] The data processing and analysis module 300 is used to construct a three-dimensional model of the exterior windows corresponding to the current house based on the exterior window thermal image and the exterior window image, and to detect and evaluate the exterior windows of the current house based on the exterior window three-dimensional model, the temperature distribution information, the exterior window structural characteristics and the exterior window safety hazards, so as to obtain a detection and evaluation result reflecting the thermal performance and safety performance of the exterior windows of the current house.

[0099] For example, see Fig.16As shown in the figure, the house exterior window detection system is composed of a thermal imaging detection module, a machine vision detection module, and a data processing and analysis module, wherein the thermal imaging detection module generates a corresponding exterior window thermal image by performing non-contact scanning of the exterior window through a thermal imaging camera deployed in the current house, obtains the exterior window thermal image generated by the thermal imaging camera, and analyzes the temperature gradient information and hot spot information in the exterior window thermal image, so as to evaluate the thermal insulation performance of the exterior window according to the temperature gradient information and hot spot information; the machine vision detection module uses a high-definition camera to collect a high-definition image of the exterior window, and then removes noise and enhances contrast of the exterior window image, and then uses an image recognition algorithm to identify the processed exterior window image to identify the structural characteristics and safety hazards of the exterior window; the data processing and analysis module The block mainly integrates thermal imaging data and machine vision data to construct a three-dimensional model of the exterior window, that is, based on the exterior window thermal image and the exterior window image, a three-dimensional model of the exterior window corresponding to the current house is constructed, and the thermal performance and safety performance of the exterior window are further comprehensively evaluated, and a detailed evaluation report is generated. In addition, an intelligent monitoring and early warning module can also be constructed in the exterior window detection system of the house. The intelligent monitoring and early warning module realizes real-time monitoring of the state changes of the exterior windows by real-time monitoring of the changes in the temperature distribution information of the exterior windows and the changes in the safety conditions of the exterior windows. Once an abnormal situation is found, such as a decrease in thermal insulation performance and increased structural damage, the intelligent monitoring and early warning module can automatically issue an alarm to remind users to take timely measures to repair or maintain the exterior windows, so as to timely discover and warn of potential safety hazards.

[0100] Fig.17 A schematic diagram of the structure of a terminal provided in an embodiment of the present application. The terminal may include:

[0101] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0102] When the processor 502 executes the program, the housing exterior window detection method provided in the above embodiment is implemented.

[0103] Furthermore, the terminal further includes:

[0104] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0105] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0106] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0107] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0108] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0109] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0110] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the above-mentioned housing exterior window detection method is implemented.

[0111] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0112] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0113] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes additional implementations, in which the order shown or discussed may not be followed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0114] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can read instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary and then storing it in a computer memory.

[0115] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0116] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0117] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0118] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

[0119] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for detecting exterior windows of a house, characterized in that: The method comprises: Obtaining an external window thermal image generated by scanning an external window of a current house with a thermal imaging device, and extracting corresponding temperature distribution information from the external window thermal image; Acquire an exterior window image generated by photographing an exterior window of a current house by a camera device, and identify the exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house; Constructing a three-dimensional model of the exterior window corresponding to the current house based on the exterior window thermal image and the exterior window image; The exterior windows of the current house are inspected and evaluated based on the exterior window three-dimensional model, the temperature distribution information, the exterior window structural characteristics and the exterior window safety hazards, to obtain inspection and evaluation results reflecting the exterior window thermal performance and exterior window safety performance of the current house.

2. The housing exterior window detection method according to claim 1, characterized in that: The step of obtaining a thermal image of an exterior window generated by scanning an exterior window of a current house with a thermal imaging device includes: Obtain an external window thermal image generated by scanning the external windows of the current house with an infrared thermal imager.

3. The housing exterior window detection method according to claim 1, characterized in that: The step of extracting corresponding temperature distribution information from the exterior window thermal image comprises: The exterior window thermal image is analyzed using a preset thermal image processing algorithm to extract corresponding temperature gradient information and hot spot information.

4. The housing exterior window detection method according to claim 1, characterized in that: Before the external window image is recognized to determine the external window structural features and external window safety hazards of the current house, the method further includes: Preprocessing the exterior window image according to a preset RGB image processing method to obtain a corresponding target exterior window image; The identifying of the exterior window image to determine the exterior window structural features and exterior window safety hazards of the current house includes: The target exterior window image is identified using a preset image recognition algorithm to determine the exterior window structural features and exterior window safety hazards of the current house.

5. The housing exterior window detection method according to claim 4, characterized in that: The preprocessing of the external window image according to the preset RGB image processing method to obtain the corresponding target external window image includes: The external window image is subjected to noise removal and contrast enhancement processing according to a preset RGB image processing method to obtain a corresponding target external window image.

6. The housing exterior window detection method according to any one of claims 1 to 5, characterized in that: Also includes: Monitor the state changes of the external windows of the current house in real time, and determine whether there is an abnormality in the external windows of the current house based on the state changes of the external windows; If there is an abnormality in the external window of the current house, an alarm is triggered and corresponding alarm information is pushed to the user.

7. The housing exterior window detection method according to claim 6, characterized in that: The determining whether the external window of the current house is abnormal based on the change in the external window state includes: When the change in the state of the external window indicates that the thermal performance of the external window drops to a preset threshold, it is determined that there is an abnormality in the external window of the current house; Alternatively, when the change in the state of the exterior window indicates that the structural damage of the exterior window has reached a preset degree, it is determined that there is an abnormality with the exterior window of the current house.

8. A house exterior window detection system, characterized in that: The system comprises: A thermal imaging detection module, used to obtain a thermal image of an exterior window generated by scanning an exterior window of a current house by a thermal imaging device, and to extract corresponding temperature distribution information from the thermal image of the exterior window; A machine vision detection module is used to obtain an external window image generated by a camera device shooting an external window of a current house, and identify the external window image to determine the structural features of the external window of the current house and the safety hazards of the external window; The data processing and analysis module is used to construct a three-dimensional model of the exterior windows corresponding to the current house based on the exterior window thermal image and the exterior window image, and to detect and evaluate the exterior windows of the current house based on the exterior window three-dimensional model, the temperature distribution information, the exterior window structural characteristics and the exterior window safety hazards, so as to obtain a detection and evaluation result reflecting the thermal performance and safety performance of the exterior windows of the current house.

9. A terminal, characterized in that: include: A memory, a processor, and a house exterior window detection program stored in the memory and executable on the processor, wherein the house exterior window detection program, when executed by the processor, implements the steps of the house exterior window detection method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program can be executed to implement the steps of the house exterior window detection method according to any one of claims 1 to 7.

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