Air tightness detection method and system for doors and windows

Abstract

The invention relates to an air tightness detection method and system for doors and windows, and relates to the field of door and window detection technologies, and the method comprises the steps: obtaining a detection operation state; when the detection operation state is consistent with a preset detection starting state, a preset smoke spraying assembly is controlled to work so as to spray out gas with a preset detection color, and a shooting device preset at the position right facing the door and window is controlled to obtain a door and window detection image in real time; performing color feature recognition in the door and window detection image to determine an image feature color set; judging whether a detection color exists in the image feature color set or not; if the detection color does not exist in the image feature color set, maintaining the original state; and if the detection color exists in the image feature color set, determining a position point containing the detection color in the door and window detection image as a penetration point. According to the invention, the overall detection effect of door and window air tightness detection is improved.

Description

Technical Field

[0001] The present application relates to the field of door and window detection technology, and in particular to an air tightness detection method and system for doors and windows. Background Art

[0002] The air tightness test of doors and windows is of great significance for ensuring the energy efficiency of buildings, indoor environmental quality, health of residents, structural safety, etc. Therefore, before doors and windows leave the factory, they need to be tested for air tightness to ensure that the doors and windows can be used normally afterwards.

[0003] In the related art, when testing the air tightness of doors and windows, a special testing device is used, including an air pressure control system, an air flow measurement device and a data recording device. First, ensure that the door to be tested is installed firmly and has no leaks. Then, the door and window are sealed in a pre-set environment. A certain air pressure difference is applied through the control device to make the air try to penetrate through the gaps of the door and window. The air flow measurement device will record the amount of air passing through the door, thereby calculating the air tightness performance index.

[0004] In the above-mentioned related technologies, when conducting air tightness testing of doors and windows, only the overall infiltration amount of the doors and windows can be known, but it is impossible to know from which point of the doors and windows the air infiltrates. When the air tightness indicators of the doors and windows cannot meet the requirements, the subsequent rectification of the doors and windows still requires the search for the infiltration points, which results in poor air tightness testing results for the doors and windows, and there is still room for improvement. Summary of the invention

[0005] In order to improve the overall detection effect of air tightness detection of doors and windows, the present application provides an air tightness detection method and system for doors and windows.

[0006] In a first aspect, the present application provides an air tightness detection method for doors and windows, which adopts the following technical solution:

[0007] A method for detecting air tightness of doors and windows, comprising:

[0008] Get the status of the detection job;

[0009] When the detection operation state is consistent with the preset detection start state, the preset smoke spraying assembly is controlled to spray gas with a preset detection color, and the shooting device preset at a position facing the door and window is controlled to obtain the door and window detection image in real time;

[0010] Performing color feature recognition in the door and window detection image to determine the image feature color set;

[0011] Determine whether the detection color exists in the image feature color set;

[0012] If the detection color does not exist in the image feature color set, the original state is maintained;

[0013] If the detection color exists in the image feature color set, the position point containing the detection color in the door and window detection image is determined as the penetration point.

[0014] Optionally, if the detection color exists in the image feature color set, the air tightness detection method for doors and windows further includes:

[0015] Get the current existence time point;

[0016] Determine a previous time point on a preset time axis according to an existing time point and a preset unit time length, and define the door and window detection image corresponding to the previous time point as the previous detection image;

[0017] In the previous detection image, an area containing the detection color is determined as a gas existence area, and a diffusion possible area is delineated according to the gas existence area and a preset allowable diffusion distance;

[0018] Compare the door and window detection image at the current time point with the previous detection image to determine the difference area;

[0019] In the difference area, the position points in the possible diffusion area are determined as diffusion points, and the position points in the difference area that are not in the possible diffusion area are determined as penetration points.

[0020] Optionally, the step of defining a possible diffusion area according to the gas existing area and a preset allowable diffusion distance includes:

[0021] In the gas existing area, all the door and window detection images on the time axis are analyzed to determine the starting time point of each position point;

[0022] According to a preset time sorting rule, the starting time points are sorted from front to back, and the position point corresponding to the starting time point at the front is defined as the starting point;

[0023] A contour point is randomly selected on the contour line of the gas existing area, and the diffusion direction is determined according to the starting point and the contour point, and the corresponding contour point is moved by the allowed diffusion distance according to the diffusion direction to determine the diffusion post-order point;

[0024] The point association is determined according to each contour point, and all the diffusion post-order points are connected according to the point association to generate a possible diffusion area.

[0025] Optionally, the method further includes a step of determining a permissible diffusion distance, the step comprising:

[0026] Determine the overall diffusion duration based on the earliest starting time point and the preceding time point in the sorting;

[0027] Determine the historical diffusion distance based on the starting point and the selected contour points;

[0028] The unit diffusion distance is determined by calculation based on the historical diffusion distance and the overall diffusion time;

[0029] The permissible diffusion distance is determined by calculation based on the unit diffusion distance and unit duration.

[0030] Optionally, after the unit diffusion distance is determined, the air tightness detection method for doors and windows also includes:

[0031] The unit diffusion distances of the contour points are combined to construct a unit distance set;

[0032] A historical interval with a width of a preset historical duration is established on the time axis with the existing time point as the rear end point, and the obtained unit distance set is defined as a historical distance set in the historical interval;

[0033] The elements in the current unit distance set are randomly bound to the elements in the historical distance set one by one, and the monomer distance deviation is determined by calculation based on the two mutually bound elements, and the set distance deviation is determined by calculation based on all the monomer distance deviations;

[0034] Determine the set distance deviation with the smallest value according to the sorting rule, and define the set distance deviation as the representative distance deviation of the historical distance set;

[0035] Determine the representative distance deviation with the smallest value according to the sorting rule, and define the historical distance set corresponding to the representative distance deviation as a similar distance set;

[0036] Determine the subsequent diffusion distance corresponding to each position point based on the similar distance set on the time axis;

[0037] The difference calculation is performed based on the subsequent diffusion distance and the permitted diffusion distance to determine the diffusion difference;

[0038] Determine whether the diffusion difference is less than a preset error allowable value;

[0039] If the diffusion difference is not less than the allowable error value, the currently determined allowable diffusion distance is maintained;

[0040] If the diffusion difference is less than the allowable error value, the mean value of the current allowable diffusion distance and the subsequent diffusion distance is calculated to update and determine the new allowable diffusion distance.

[0041] Optionally, after the representative distance deviation is determined, the air tightness detection method for doors and windows further includes:

[0042] Determine whether there are at least two historical distance sets with the same minimum representative distance deviation;

[0043] If there are not at least two historical distance sets with the smallest representative distance deviation and the same historical distance set, the historical distance set corresponding to the smallest representative distance deviation is defined as the similar distance set;

[0044] If there are at least two historical distance sets with the smallest representative distance deviation and the same historical distance set, the historical distance set corresponding to the smallest representative distance deviation is defined as the candidate distance set;

[0045] In the candidate distance set, the corresponding historical diffusion distance is defined as the candidate diffusion distance, and the overall diffusion difference is determined by calculation based on all the candidate diffusion distances and the current corresponding historical diffusion distance;

[0046] The overall diffusion difference with the smallest value is determined according to the sorting rule, and the candidate distance set corresponding to the overall diffusion difference is defined as a similar distance set.

[0047] In a second aspect, the present application provides an air tightness detection system for doors and windows, which adopts the following technical solution:

[0048] An air tightness detection system for doors and windows, comprising:

[0049] The acquisition module is used to obtain the detection job status;

[0050] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0051] A judgment module, connected with the acquisition module and the processing module, for judging the information;

[0052] When the judging module judges that the detection operation state is consistent with the preset detection start state, the processing module controls the preset smoke spraying component to spray gas with a preset detection color, and controls the shooting device preset at a position facing the door and window to obtain the door and window detection image in real time;

[0053] The processing module performs color feature recognition in the door and window detection image to determine the image feature color set;

[0054] The judging module judges whether the detection color exists in the image feature color set;

[0055] If the judgment module determines that the detection color does not exist in the image feature color set, the original state is maintained;

[0056] If the judgment module determines that the detection color exists in the image feature color set, the processing module determines the position point containing the detection color in the door and window detection image as the penetration point.

[0057] In a third aspect, the present application provides a computer storage medium capable of storing corresponding programs, which has the characteristics of improving the overall detection effect of air tightness detection of doors and windows, and adopts the following technical solutions:

[0058] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned air tightness detection methods for doors and windows.

[0059] In summary, the present application includes at least one of the following beneficial technical effects:

[0060] 1. When testing the air tightness of doors and windows, the colored gas is sprayed to enable the test personnel to intuitively determine the air flow situation, so as to know the penetration points with poor air tightness on the doors and windows, so as to facilitate the subsequent rectification of the doors and windows, thereby improving the overall detection effect of the air tightness detection of doors and windows;

[0061] 2. When detecting the penetration point, fully analyze the diffusion of the color gas, so that the determined penetration point is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a flow chart of the air tightness testing method for doors and windows.

[0063] Figure 2 It is a module flow chart of the air tightness detection method for doors and windows. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 2 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0065] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0066] The present application embodiment discloses a method for detecting air tightness of doors and windows, referring to Figure 1 The method flow of the air tightness detection method for doors and windows includes the following steps:

[0067] Step S100: Obtain the detection operation status.

[0068] The detection operation status is the status of whether the door and window air tightness detection is required, that is, whether the detection operation needs to be started, which can be obtained by identifying the status of the start button.

[0069] Step S101: When the detection operation state is consistent with the preset detection start state, the preset smoke spray component is controlled to spray gas with a preset detection color, and the shooting device preset at the position facing the door and window is controlled to obtain the door and window detection image in real time.

[0070] The detection start-up state is the detection operation state when the air tightness detection of doors and windows is required. The smoke spray component is a component that can spray gas with a detection color, wherein the gas of the detection color can be stored in the storage bin of the smoke spray component. When the smoke spray component is operating, the nozzle valve of the smoke spray component opens to spray the gas, wherein the detection color is a prominent color that does not appear on the doors and windows, and the specific setting is made by the staff according to the actual situation; the shooting device is a device with an image shooting function, wherein the smoke spray component and the shooting device are respectively arranged on both sides of the doors and windows to be inspected, and the nozzle of the smoke spray component and the shooting head of the shooting device are both facing the location of the doors and windows; the door and window detection image is an image of the entire door and window obtained by the shooting device.

[0071] Step S102: performing color feature recognition in the door and window detection image to determine an image feature color set.

[0072] The image feature color set is a set of pixel colors of each feature point detected in the door and window detection image. By performing a three-color analysis on each pixel to determine the color range of each pixel, the color set of the entire image can be known.

[0073] Step S103: Determine whether the detection color exists in the image feature color set.

[0074] The purpose of the judgment is to find out whether smoke has penetrated through the gaps in doors and windows.

[0075] Step S1031: If the detection color does not exist in the image feature color set, the original state is maintained.

[0076] When the detection color does not exist in the image feature color set, it means that there is no gas penetration at this time, and the detection can be continued in the original state.

[0077] Step S1032: If the detection color exists in the image feature color set, the position point containing the detection color in the door and window detection image is determined as the penetration point.

[0078] When there is a detection color in the image feature color set, it means that there is gas penetration. At this time, the position point with the detection color is the point where gas penetration occurs. It is defined as the penetration point to determine the position point on the doors and windows with poor air tightness, so as to facilitate subsequent rectification.

[0079] If the detection color exists in the image feature color set, the air tightness detection method for doors and windows also includes:

[0080] Step S200: Obtain the current existence time point.

[0081] The existence time point is the time point when the detection color is detected.

[0082] Step S201: determining a previous time point on a preset time axis according to existing time points and a preset unit time length, and defining a door and window detection image corresponding to the previous time point as a previous detection image.

[0083] The time axis is a coordinate axis formed by the combination of various time points, which points from the time points that have passed to the time points that have not yet arrived, that is, the time points that have passed are on the left side of the time axis, and the time points that have not yet arrived are on the right side of the time axis; the unit time length is the interval shooting time length when the shooting device performs the shooting operation, which is specifically set by the staff according to the actual situation. The previous time point is the time point obtained by moving the existing time point along the left side of the time axis by the unit time length, that is, the time point of the last image capture; define the previous detection image to distinguish different door and window detection images for subsequent analysis.

[0084] Step S202: determining the area containing the detection color in the previous detection image as the gas existence area, and defining the possible diffusion area according to the gas existence area and the preset allowable diffusion distance.

[0085] The gas existence area is the location point area with colored gas. The allowable diffusion distance is the distance set by the staff for the gas to diffuse outward within a unit time. It can be a fixed value or set according to actual conditions, which will not be elaborated here. The possible diffusion area is the area that the gas can cover after diffusion.

[0086] Step S203: Compare the door and window detection image at the current existence time point with the previous detection image to determine the difference area.

[0087] The difference area is the location area of ​​the newly added gas with the detection color, which is determined by comparing the door and window detection image at the current existence time point with the previous detection image one by one.

[0088] Step S204: in the difference area, determining the position points in the possible diffusion area as diffusion points, and determining the position points in the difference area that are not in the possible diffusion area as penetration points.

[0089] When the difference area is within the possible diffusion area, it means that the location point is more likely to be obtained by smoke diffusion, that is, it is not the location where the gas actually penetrates. At this time, it can be defined as a diffusion point, and the remaining location points can be defined as penetration points to achieve accurate determination of the penetration point, which is convenient for subsequent analysis.

[0090] The steps to define the possible diffusion area based on the gas presence area and the preset allowable diffusion distance include:

[0091] Step S300: Analyze all door and window detection images on the time axis in the gas existing area to determine the starting time point of each position point.

[0092] The starting time point is the time point when the gas of the detection color is detected for the first time at each position point in the determined gas existence area.

[0093] Step S301: sorting the starting time points from front to back according to a preset time sorting rule, and defining the position point corresponding to the starting time point at the front as the starting point.

[0094] The time sorting rule is a method that can sort the time sequence in sequence. The time sorting rule can be used to determine the earliest starting time point, which is also the time point corresponding to the penetration point. At this time, the position point is defined as the starting point for subsequent analysis.

[0095] Step S302: randomly selecting a contour point on the area contour line of the gas existing area, and determining a diffusion direction according to the starting point and the contour point, and moving the corresponding contour point by an allowed diffusion distance according to the diffusion direction to determine a diffusion post-order point.

[0096] The diffusion direction is the direction from the starting point to the contour point. The movement of the gas can be simulated by moving the corresponding contour point according to the corresponding diffusion direction by the allowed diffusion distance, so as to obtain the post-diffusion point to which the gas can diffuse under theoretical conditions, which is convenient for subsequent analysis.

[0097] Step S303: determining the point association status according to each contour point, and connecting all the diffusion post-order points according to the point association status to generate a possible diffusion area.

[0098] The point association situation refers to the connection situation of each contour point, that is, the specific connection situation of the adjacent contour points connected to each contour point. Connecting the subsequent points of diffusion according to the point association situation of the corresponding contour points can form a new area, which is the possible diffusion area.

[0099] The method also includes a step of determining the permissible diffusion distance, the step comprising:

[0100] Step S400: determining the overall diffusion duration according to the first start time point and the preceding time point in the sorting.

[0101] The overall diffusion time is the time interval from the determination of the first penetration point to the time point when the last image is acquired.

[0102] Step S401: determining the historical diffusion distance according to the starting point and the selected contour point.

[0103] The historical diffusion distance is the distance value of the gas diffusion from the starting point to the selected contour point, that is, the straight-line distance value of the two points.

[0104] Step S402: Calculate the unit diffusion distance based on the historical diffusion distance and the overall diffusion duration.

[0105] The unit diffusion distance is the distance that the gas can diffuse per unit time, which is determined by dividing the historical diffusion distance by the overall diffusion time.

[0106] Step S403: Calculate the permitted diffusion distance according to the unit diffusion distance and the unit duration.

[0107] By multiplying the unit diffusion distance by the unit time, a more accurate permissible diffusion distance can be obtained, which facilitates the analysis of the diffusion of the gas.

[0108] After the unit diffusion distance is determined, the air tightness detection method for doors and windows also includes:

[0109] Step S500: Combining the unit diffusion distances of the contour points to construct a unit distance set.

[0110] The unit distance set is a set consisting of determined unit diffusion distances.

[0111] Step S501: establishing a history interval with a width of a preset history time length on the time axis with the existing time point as the rear end point, and defining the obtained unit distance set as a history distance set in the history interval.

[0112] The historical duration is the duration set by the staff for data acquisition and analysis of airtightness detection tests conducted under historical circumstances. A historical interval is established to facilitate the acquisition of data under the historical duration; a historical distance set is defined to distinguish the unit distance sets obtained in the historical interval to facilitate subsequent analysis.

[0113] Step S502: randomly bind the elements in the current unit distance set to the elements in the historical distance set one by one, and calculate based on the two mutually bound elements to determine the monomer distance deviation, and calculate based on all the monomer distance deviations to determine the set distance deviation.

[0114] The element binding method is as follows: for example, there are two sets {A, B, C} and {X, Y, Z}, then the following binding results can be obtained: ①AX, BY, CZ; ②AY, BZ, CX; ③AZ, BX, CY; ④AX, BZ, CY; ⑤AY, BX, CZ; ⑥AZ, BY, CX; the monomer distance deviation is the difference between the two bound elements, and the set distance deviation is the sum of all monomer distance deviations.

[0115] Step S503: determining a set distance deviation with a minimum value according to the sorting rule, and defining the set distance deviation as a representative distance deviation of the historical distance set.

[0116] The set distance deviation with the smallest value can be determined through the sorting rule, that is, the binding situation between the two sets at this time makes the two sets closest, which can be determined as the representative distance deviation.

[0117] Step S504: determining a representative distance deviation with a minimum value according to the sorting rule, and defining a historical distance set corresponding to the representative distance deviation as a similar distance set.

[0118] The sorting rules can be used to determine the representative distance deviation with the smallest value. That is, the historical distance set corresponding to the representative distance deviation is closest to the current unit distance set, that is, the two diffusion situations are most similar. At this time, it is defined as a similar distance set to distinguish different historical distance sets, which is convenient for subsequent analysis.

[0119] Step S505: Determine the subsequent diffusion distance corresponding to each position point according to the similar distance set on the time axis.

[0120] The subsequent diffusion distance is the distance value diffused after a unit time length of the location point corresponding to the similar distance set in the historical situation, and can be obtained by searching the historical data.

[0121] Step S506: performing a difference calculation based on the subsequent diffusion distance and the permitted diffusion distance to determine a diffusion difference.

[0122] The diffusion difference is the difference between the distances that would be diffused in theory under the two conditions, that is, the difference between the subsequent diffusion distance and the permitted diffusion distance, and the difference is an absolute value.

[0123] Step S507: Determine whether the diffusion difference is less than a preset error tolerance value.

[0124] The allowable error value is the maximum diffusion difference allowed when the subsequent diffusion distance and the permitted diffusion distance are close, as set by the staff. The purpose of the judgment is to know whether the two values ​​are close.

[0125] Step S5071: If the diffusion difference is not less than the allowable error value, the currently determined allowable diffusion distance is maintained.

[0126] When the diffusion difference is not less than the allowable error value, it means that the reference value under historical circumstances is not very meaningful. At this time, the currently determined allowable diffusion distance can be maintained.

[0127] Step S5072: If the diffusion difference is less than the allowable error value, a mean value is calculated based on the current allowable diffusion distance and the subsequent diffusion distance to update and determine a new allowable diffusion distance.

[0128] When the diffusion difference is less than the allowable error value, it means that the data obtained under historical circumstances has a certain reference value. At this time, the mean of the current allowable diffusion distance and the subsequent diffusion distance is calculated to obtain a more accurate allowable diffusion distance.

[0129] After the representative distance deviation is determined, the air tightness detection method for doors and windows also includes:

[0130] Step S600: Determine whether there are at least two historical distance sets with the same representative distance deviation and the smallest deviation.

[0131] The purpose of the judgment is to find out whether there are multiple historical distance sets that meet the requirements, so as to determine the only similar distance set.

[0132] Step S6001: If there are not at least two historical distance sets with the smallest representative distance deviation and the same historical distance set, the historical distance set corresponding to the smallest representative distance deviation is defined as the similar distance set.

[0133] When there are not at least two historical distance sets with the smallest representative distance deviation and the same historical distance set, it means that there is only one historical distance set that meets the requirements, and it can be defined as a similar distance set.

[0134] Step S6002: If there are at least two historical distance sets with the same minimum representative distance deviation, the historical distance set corresponding to the minimum representative distance deviation is defined as the candidate distance set.

[0135] When there are at least two historical distance sets with the smallest representative distance deviation and the same historical distance set, it means that there are multiple historical distance sets that meet the requirements. At this time, they are defined as alternative distance sets to distinguish different historical distance sets, which is convenient for subsequent analysis.

[0136] Step S601: defining the corresponding historical diffusion distance in the candidate distance set as a candidate diffusion distance, and performing calculations based on all the candidate diffusion distances and the current corresponding historical diffusion distance to determine the overall diffusion difference.

[0137] The overall diffusion difference reflects the degree of diffusion similarity between two gas diffusion situations. The larger the value, the more dissimilar the two diffusion situations are. Conversely, the more similar the diffusion situations are. The overall diffusion difference is obtained by subtracting the current corresponding historical diffusion distance from all alternative diffusion distances, calculating the absolute value, and then summing them up.

[0138] Step S602: determining the overall diffusion difference with the smallest value according to the sorting rule, and defining the candidate distance set corresponding to the overall diffusion difference as the similarity distance set.

[0139] The overall diffusion difference with the smallest value can be determined by the sorting rule, that is, the two diffusion conditions are most similar at this time, and the corresponding candidate distance set can be defined as the similar distance set.

[0140] Reference Figure 2 Based on the same inventive concept, an embodiment of the present invention provides an air tightness detection system for doors and windows, comprising:

[0141] The acquisition module is used to obtain the detection job status;

[0142] A processing module, connected to the acquisition module and the judgment module, for storing and processing information;

[0143] A judgment module, connected with the acquisition module and the processing module, for judging the information;

[0144] When the judging module judges that the detection operation state is consistent with the preset detection start state, the processing module controls the preset smoke spraying component to spray gas with a preset detection color, and controls the shooting device preset at a position facing the door and window to obtain the door and window detection image in real time;

[0145] The processing module performs color feature recognition in the door and window detection image to determine the image feature color set;

[0146] The judging module judges whether the detection color exists in the image feature color set;

[0147] If the judgment module determines that the detection color does not exist in the image feature color set, the original state is maintained;

[0148] If the judging module judges that the detection color exists in the image feature color set, the processing module determines the position point containing the detection color in the door and window detection image as the penetration point;

[0149] Diffusion analysis module, used to analyze the diffusion of colored gases to determine the more accurate penetration point;

[0150] A module for determining a possible diffusion area is used to determine a relatively accurate possible diffusion area;

[0151] The permitted diffusion distance determination module is used to determine a more appropriate permitted diffusion distance;

[0152] The permitted diffusion distance update module refers to the smoke diffusion situation in historical situations to update the permitted diffusion distance;

[0153] The historical distance set screening module is used to screen multiple historical distance sets that meet the requirements to determine the only similar distance set that meets the requirements for use.

[0154] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0155] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded and executed by a processor and is used for an air tightness detection method for doors and windows.

[0156] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

Claims

1. A method for detecting air tightness of doors and windows, characterized in that: include: Get the status of the detection job; When the detection operation state is consistent with the preset detection start state, the preset smoke spraying assembly is controlled to spray gas with a preset detection color, and the shooting device preset at a position facing the door and window is controlled to obtain the door and window detection image in real time; Performing color feature recognition in the door and window detection image to determine the image feature color set; Determine whether the detection color exists in the image feature color set; If the detection color does not exist in the image feature color set, the original state is maintained; If the detection color exists in the image feature color set, the position point containing the detection color in the door and window detection image is determined as the penetration point.

2. The air tightness detection method for doors and windows according to claim 1, characterized in that: If the detection color exists in the image feature color set, the air tightness detection method for doors and windows also includes: Get the current existence time point; Determine a previous time point on a preset time axis according to an existing time point and a preset unit time length, and define the door and window detection image corresponding to the previous time point as the previous detection image; In the previous detection image, an area containing the detection color is determined as a gas existence area, and a diffusion possible area is delineated according to the gas existence area and a preset allowable diffusion distance; Compare the door and window detection image at the current time point with the previous detection image to determine the difference area; In the difference area, the position points in the possible diffusion area are determined as diffusion points, and the position points in the difference area that are not in the possible diffusion area are determined as penetration points.

3. The air tightness detection method for doors and windows according to claim 2, characterized in that: The steps to define the possible diffusion area based on the gas presence area and the preset allowable diffusion distance include: In the gas existing area, all the door and window detection images on the time axis are analyzed to determine the starting time point of each position point; According to a preset time sorting rule, the starting time points are sorted from front to back, and the position point corresponding to the starting time point at the front is defined as the starting point; A contour point is randomly selected on the contour line of the gas existing area, and the diffusion direction is determined according to the starting point and the contour point, and the corresponding contour point is moved by the allowed diffusion distance according to the diffusion direction to determine the diffusion post-order point; The point association is determined according to each contour point, and all the diffusion post-order points are connected according to the point association to generate a possible diffusion area.

4. The air tightness detection method for doors and windows according to claim 3, characterized in that: The method further comprises a step of determining the permissible diffusion distance, the step comprising: Determine the overall diffusion duration based on the earliest starting time point and the preceding time point in the sorting; Determine the historical diffusion distance based on the starting point and the selected contour points; The unit diffusion distance is determined by calculation based on the historical diffusion distance and the overall diffusion time; The permissible diffusion distance is determined by calculation based on the unit diffusion distance and unit duration.

5. The air tightness detection method for doors and windows according to claim 4, characterized in that: After the unit diffusion distance is determined, the air tightness detection method for doors and windows also includes: The unit diffusion distances of the contour points are combined to construct a unit distance set; A historical interval with a width of a preset historical duration is established on the time axis with the existing time point as the rear end point, and the obtained unit distance set is defined as a historical distance set in the historical interval; The elements in the current unit distance set are randomly bound to the elements in the historical distance set one by one, and the monomer distance deviation is determined by calculation based on the two mutually bound elements, and the set distance deviation is determined by calculation based on all the monomer distance deviations; Determine the set distance deviation with the smallest value according to the sorting rule, and define the set distance deviation as the representative distance deviation of the historical distance set; Determine the representative distance deviation with the smallest value according to the sorting rule, and define the historical distance set corresponding to the representative distance deviation as a similar distance set; Determine the subsequent diffusion distance corresponding to each position point based on the similar distance set on the time axis; The difference calculation is performed based on the subsequent diffusion distance and the permitted diffusion distance to determine the diffusion difference; Determine whether the diffusion difference is less than a preset error allowable value; If the diffusion difference is not less than the allowable error value, the currently determined allowable diffusion distance is maintained; If the diffusion difference is less than the allowable error value, the mean value of the current allowable diffusion distance and the subsequent diffusion distance is calculated to update and determine the new allowable diffusion distance.

6. The air tightness detection method for doors and windows according to claim 5, characterized in that: After the representative distance deviation is determined, the air tightness detection method for doors and windows also includes: Determine whether there are at least two historical distance sets with the same minimum representative distance deviation; If there are not at least two historical distance sets with the smallest representative distance deviation and the same historical distance set, the historical distance set corresponding to the smallest representative distance deviation is defined as the similar distance set; If there are at least two historical distance sets with the smallest representative distance deviation and the same historical distance set, the historical distance set corresponding to the smallest representative distance deviation is defined as the candidate distance set; In the candidate distance set, the corresponding historical diffusion distance is defined as the candidate diffusion distance, and the overall diffusion difference is determined by calculation based on all the candidate diffusion distances and the current corresponding historical diffusion distance; The overall diffusion difference with the smallest value is determined according to the sorting rule, and the candidate distance set corresponding to the overall diffusion difference is defined as a similar distance set.

7. An air tightness detection system for doors and windows, characterized in that: include: The acquisition module is used to obtain the detection job status; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; When the judging module judges that the detection operation state is consistent with the preset detection start state, the processing module controls the preset smoke spraying component to spray gas with a preset detection color, and controls the shooting device preset at a position facing the door and window to obtain the door and window detection image in real time; The processing module performs color feature recognition in the door and window detection image to determine the image feature color set; The judging module judges whether the detection color exists in the image feature color set; If the judgment module determines that the detection color does not exist in the image feature color set, the original state is maintained; If the judgment module determines that the detection color exists in the image feature color set, the processing module determines the position point containing the detection color in the door and window detection image as the penetration point.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 6.

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