Intelligent leakage tracking method and system for airtightness detection equipment

Abstract

The embodiment of the present invention discloses an intelligent leakage tracking method and device for airtightness detection equipment. Before the detection begins, infrared imaging is used to obtain a first detection infrared image of a part to be detected at a first position. Subsequently, the part contour features in the image are extracted to generate a part contour feature image. During the actual detection process, a second detection infrared image of the first position is obtained again. Using the generated part contour feature image, feature extraction is performed on the second detection infrared image to obtain an extracted feature image. From the extracted feature image, the maximum and minimum temperature values ​​are screened out, and a first temperature difference is calculated. The first temperature difference is compared with a first temperature threshold range. If the first temperature difference exceeds the first threshold range, the system generates first leakage risk data. The reliance on manual operation is reduced, the consistency and efficiency of detection are improved, and damage to internal components of the part caused by the use of liquid detection methods is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of air tightness detection, and in particular to an intelligent leakage tracking method and system for air tightness detection equipment. Background Art

[0002] For some parts or components that need to maintain airtightness, airtightness testing is often required after production to obtain the airtightness index of the parts or components.

[0003] One of the existing detection methods is to use manual detection, that is, by injecting gas into the parts to be tested, and then placing the parts underwater or applying leak detection liquid to the gaps and holes on the surface of the parts, and then the inspector conducts a comprehensive visual inspection of the parts to determine whether the parts are leaking. The efficiency of detection using this method is very low, and since there is no unified standard for each inspector to judge the airtightness, the airtightness of the parts is inconsistent, affecting the subsequent use of the product.

[0004] A Chinese patent application number: CN115638928A discloses an air tightness detection device and detection equipment that uses liquid to detect parts in order to obtain the number of bubbles to determine whether there is a leaking area. This judgment method requires the entire part to be placed in the liquid. If there is a leak, water will seep into the part, causing the components inside the part to be damaged, so that it can only be scrapped and cannot be used. Secondly, due to the tension of the liquid, if the pores on the surface of the part are very small, the liquid tension will affect the pores in this part, making it impossible to detect them, resulting in inaccurate test results. Summary of the invention

[0005] Based on this, it is necessary to propose an intelligent leakage tracking method and system for airtightness detection equipment to solve the above technical problems.

[0006] An intelligent leakage tracing method for airtightness detection equipment, the intelligent leakage tracing method for airtightness detection equipment comprising:

[0007] Acquire a first detection infrared image of the part corresponding to the first position before detection, and generate a part contour feature image based on the first detection infrared image;

[0008] During detection, a second detection infrared image of the part corresponding to the first position within a first threshold range time is obtained, and features of the second detection infrared image are extracted based on the part contour feature image to obtain an extracted feature image;

[0009] Screening the extracted characteristic image to screen out a maximum temperature and a minimum temperature, and calculating a first temperature difference according to the maximum temperature and the minimum temperature;

[0010] The first temperature difference is compared with a first temperature threshold range, and if the first temperature difference is greater than the first temperature threshold range, first leakage risk data is generated.

[0011] In at least one embodiment of the present application, the method further includes:

[0012] The first leakage risk data includes: a minimum temperature value and a minimum value characteristic position image corresponding to the minimum temperature value.

[0013] In at least one embodiment of the present application, the method further includes:

[0014] Mapping the minimum feature position image to the part contour feature image to obtain a mapped position image;

[0015] Acquire temperature information of other area images of the mapped position image in the first range of the part contour feature image and temperature information corresponding to the mapped position image;

[0016] The temperature information of the other area images and the temperature information corresponding to the mapped position image are difference calculated one by one to obtain a second temperature difference. If the second temperature difference is greater than a second temperature threshold range, it is determined that the detection area is waiting for a reconfirmation signal.

[0017] In at least one embodiment of the present application, the method further includes:

[0018] During the detection, a third detection infrared image of the part at a second position within a first threshold range is acquired, wherein the second position is arranged in a mirror-symmetrical manner with the first position;

[0019] Mapping the minimum feature position image to the third detection infrared image, obtaining a third detection temperature of the minimum feature in the third detection infrared image, and performing a difference calculation between the third detection temperature and the minimum value of the temperature to obtain a third temperature difference;

[0020] If the third temperature difference is greater than the third temperature threshold range, the detection area to-be-reconfirmed signal is modified into a final leakage signal, and final leakage data is generated.

[0021] In at least one embodiment of the present application, the method further includes:

[0022] The three-dimensional coordinate information of the leakage point is generated according to the minimum temperature value, the second detection infrared image and the third detection infrared image, and the final leakage signal is recorded and generated according to the three-dimensional coordinate information of the leakage point.

[0023] In at least one embodiment of the present application, the method further includes:

[0024] If the first temperature difference is not greater than the first temperature threshold range, a normal signal is generated.

[0025] In at least one embodiment of the present application, the step of performing difference calculation on the temperature information of the other area image and the temperature information corresponding to the mapped position image to obtain a second temperature difference, and if the second temperature difference is greater than a second temperature threshold range, determining that the detection area is to be reconfirmed as a signal further comprises:

[0026] If the second temperature difference is not greater than the second temperature threshold range, generating a first leakage signal and generating first leakage data;

[0027] The part position information is acquired, and a first leakage position is calculated according to the minimum feature position image, the first position, the part contour feature image and the part position information to generate the first leakage position.

[0028] In at least one embodiment of the present application, if the third temperature difference is greater than a third temperature threshold range, the step of modifying the detection area to-be-reconfirmed signal to a final leakage signal and generating final leakage data further includes:

[0029] The part position information is acquired, and a second leakage position is calculated according to the first position, the second position, the part position information, the part contour feature image and the minimum feature position image to generate the second leakage position.

[0030] In at least one embodiment of the present application, if the third temperature difference is greater than a third temperature threshold range, the step of modifying the detection area to-be-reconfirmed signal to a final leakage signal and generating final leakage data further includes:

[0031] If the third temperature difference is not greater than the third temperature threshold range, a normal signal is generated.

[0032] An intelligent leakage tracking system for airtightness detection equipment is applied to the intelligent leakage tracking method for airtightness detection equipment described above, and the system comprises:

[0033] An image acquisition module, used to acquire a first detection infrared image and a second detection infrared image of a part at a first position;

[0034] A contour extraction module extracts the first detection infrared image to obtain a part contour feature image;

[0035] A feature extraction module extracts features from the second detection infrared image according to the part contour feature image to obtain an extracted feature image;

[0036] A screening module, screening out the maximum temperature and the minimum temperature from the extracted feature image;

[0037] A difference calculation module calculates the difference according to the maximum temperature and the minimum temperature selected to obtain a first temperature difference;

[0038] The judgment module judges the first temperature difference and the first temperature threshold range, and generates first leakage risk data if the first temperature difference is greater than the first temperature threshold range.

[0039] The intelligent leakage tracking method and device for airtightness detection equipment implementing the present invention shall have at least the following features:

[0040] Beneficial effects:

[0041] The present invention discloses an intelligent leakage tracking method and device for airtightness detection equipment. Before the detection begins, an infrared image of a part to be detected at a first position (i.e., a first detection infrared image) is obtained by using infrared imaging technology. Subsequently, the contour features of the part in the image are extracted by image processing technology to generate a part contour feature image.

[0042] In the actual detection process, the infrared image of the part at the first position (ie, the second detection infrared image) is acquired again. The feature image of the part contour generated previously is used to extract features from the second detection infrared image to obtain an extracted feature image.

[0043] From the extracted feature image, the extreme values ​​of temperature (maximum value and minimum value) are screened out, and the temperature difference between them (first temperature difference) is calculated.

[0044] The calculated first temperature difference is compared with a preset first temperature threshold range. If the first temperature difference exceeds the first threshold range, the system generates a leakage risk alarm signal (first leakage risk data).

[0045] The reliance on manual operation is reduced, the consistency and efficiency of detection are improved, and tiny leaks can be detected through accurate calculation of the first temperature difference and comparison with the first threshold range, which is not easy to miss.

[0046] This avoids damage to internal components of parts caused by using liquid detection methods and improves the safety of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0048] in:

[0049] Figure 1 A flowchart of an intelligent leakage tracking method for an airtightness detection device in one embodiment;

[0050] Figure 2 A flowchart of an intelligent leakage tracking method for airtightness detection equipment in another embodiment;

[0051] Figure 3 A structural block diagram of an intelligent leakage tracking system of an airtightness detection device in one embodiment;

[0052] Figure 4 It is an application environment diagram of an intelligent leakage tracking method of an airtightness detection device according to an embodiment;

[0053] Figure 5 for Figure 4 A reference schematic diagram of a first detection infrared image acquired at a first position (before detection);

[0054] Figure 6 for Figure 4 A reference schematic diagram of a second detection infrared image obtained at a second position (during detection, the circle in the figure indicates the minimum temperature).

[0055] 100. Intelligent leakage tracking system of airtightness detection equipment; 110. Image acquisition module; 120. Contour extraction module; 130. Feature extraction module; 140. Screening module; 150. Difference calculation module; 160. Judgment module. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] The present invention provides an intelligent leakage tracing method for airtightness detection equipment, and the intelligent leakage tracing method for airtightness detection equipment comprises:

[0058] S101, acquiring a first detection infrared image of a part corresponding to a first position before detection, and generating a part contour feature image based on the first detection infrared image;

[0059] S102, during detection, obtaining a second detection infrared image of the part corresponding to the first position within a first threshold range time, and performing feature extraction on the second detection infrared image according to the part contour feature image to obtain an extracted feature image;

[0060] S103, screening the extracted characteristic image to screen out the maximum temperature and the minimum temperature, and calculating a first temperature difference according to the maximum temperature and the minimum temperature;

[0061] S104, comparing the first temperature difference with a first temperature threshold range;

[0062] S105: If the first temperature difference is greater than the first temperature threshold range, generate first leakage risk data.

[0063] Please refer to Figure 1-Figure 4 In this embodiment, before the detection begins, the system uses infrared imaging technology to obtain an infrared image of the part to be detected at the first position (i.e., the first detection infrared image). Subsequently, the system extracts the part contour features in the image through image processing technology to generate a part contour feature image.

[0064] In the actual detection process, the system acquires the infrared image of the part at the first position again (i.e., the second detection infrared image) within a certain period of time (e.g., 15 minutes, 20 minutes, 25 minutes) after the gas is injected. The system uses the previously generated part contour feature image to extract features from the second detection infrared image to obtain an extracted feature image. The extracted feature image is an image with the same features as the part contour, that is, the part contour feature image is mapped to the second detection infrared image to obtain an extracted feature image (an infrared temperature image) of the part contour in the second detection infrared image corresponding to the part contour feature image.

[0065] The system selects the extreme values ​​(maximum value and minimum value) of temperature from the extracted feature image, and calculates the temperature difference between them (first temperature difference).

[0066] The system compares the calculated first temperature difference with a preset first temperature threshold range. If the first temperature difference exceeds the first threshold range, the system generates a leakage risk alarm signal (first leakage risk data).

[0067] The reliance on manual operation is reduced, the consistency and efficiency of detection are improved, and tiny leaks can be detected through accurate calculation of the first temperature difference and comparison with the first threshold range, which is not easy to miss.

[0068] This avoids damage to internal components of parts caused by using liquid detection methods and improves the safety of detection.

[0069] It should be noted that the infrared thermal imaging camera is fixed on a stable bracket to ensure that it can capture the complete image of the part.

[0070] In the initial state of the part (ie, before gas is injected), an infrared image of the part is collected and recorded as a first detection infrared image.

[0071] The first detected infrared image is converted into a grayscale image or a pseudo-color image through image processing software to facilitate identification of temperature distribution characteristics.

[0072] The Canny edge detection algorithm is used to process the grayscale image and extract the edge features of the parts.

[0073] Use contour tracking algorithms such as Sobel or Laplacian to further pinpoint the outer contour of the part.

[0074] Generate a contour feature image of the part, which saves the shape and outer boundary information of the part.

[0075] During the air tightness test (ie after the gas is injected), the infrared thermal imaging camera is used again to capture the thermal imaging image of the part to obtain a second test infrared image.

[0076] The second detection infrared image is registered and compared using the previously generated part contour feature image.

[0077] The corresponding characteristic image part is extracted from the second detection infrared image by methods such as template matching or feature point alignment to ensure that the characteristics are consistent with those of the first detection infrared image.

[0078] Parse the temperature data in the infrared image and obtain the temperature value of each pixel.

[0079] By traversing the entire feature image area, find the point with the highest temperature (maximum value) and the point with the lowest temperature (minimum value).

[0080] Record the temperature values ​​of the point with the highest temperature (maximum value) and the point with the lowest temperature (minimum value) and their position coordinates in the image.

[0081] The difference between the maximum temperature and the minimum temperature, ie, the first temperature difference, is calculated.

[0082] According to the screened maximum temperature value (T_max) and minimum temperature value (T_min), a first temperature difference ΔT1 = T_max-T_min is calculated.

[0083] Set a safe temperature difference range ΔT_threshold, for example 3°C.

[0084] It is determined whether ΔT1 is greater than ΔT_threshold.

[0085] If ΔT1 exceeds the first temperature threshold range, the system generates first leakage risk data and marks it as a potential leakage point.

[0086] For example:

[0087] In the absence of gas injection into the part, the initial temperature distribution of the shell is obtained by an infrared camera. The initial image shows that the temperature of the entire shell is evenly distributed at around 30°C.

[0088] The boundary and shape of the shell are extracted through image processing, a contour feature image is generated, and the geometric features of the shell are recorded.

[0089] Gas was injected into the enclosure, and after waiting for 10 minutes, another infrared image was taken. The second image showed that the temperature of some areas of the enclosure increased to 35°C, while other areas remained at 30°C.

[0090] The second infrared image is compared with the initial image, the temperature increase area is identified from the shell, the characteristic image part is extracted, and the points with the highest temperature (35°C) and the lowest temperature (30°C) are found.

[0091] The calculated ΔT1 = 35°C - 30°C = 5°C.

[0092] Comparing ΔT1 with the set 3°C ​​threshold, it is found that ΔT1 exceeds the threshold. The system determines that there is a potential leakage risk and generates the first leakage risk data.

[0093] It can accurately locate the leakage area of ​​the shell and mark the parts that need further inspection or repair, avoiding the subjective judgment and misjudgment problems in traditional methods.

[0094] Automated temperature detection and analysis improves detection efficiency and reduces errors caused by human operation.

[0095] It should be further explained that the temperature of the injected gas should be higher or lower than the overall temperature of the part. In this embodiment, the method of injecting hot air is used for detection. It should be noted that the temperature of the hot air is higher than the temperature of the part, and the hot air is higher than the ambient temperature. In other embodiments, the method of introducing low-temperature air can be used. However, it should be noted that in the case of parts made of materials that expand with heat and contract with cold, the method of introducing hot air can make the pores leak better.

[0096] The first threshold time is an artificially set time, such as within 5 minutes of ventilation, in order to differentiate the temperature of the gas from the temperature of the component.

[0097] In at least one embodiment of the present application, the method further includes:

[0098] The first leakage risk data includes: a minimum temperature value and a minimum value characteristic position image corresponding to the minimum temperature value.

[0099] Please refer to Figure 1-Figure 4 In this embodiment, during the detection process, the system records the temperature value of the lowest temperature point detected on the surface or inside of the part, that is, the minimum temperature value.

[0100] The system uses infrared imaging to obtain a temperature distribution image of the part, and then selects the lowest value point in the temperature distribution. This may be due to a gas leak in the area causing cold air to enter or the temperature not reaching the normal level, causing an abnormal drop in temperature.

[0101] Recording the minimum temperature value helps to further analyze and confirm potential leak areas, because the minimum temperature value may indicate areas with poor air tightness, and areas with abnormally low temperatures are usually important signs of leak points.

[0102] After the minimum temperature is detected, the system captures the specific location of the point and generates a feature image, marking the spatial location of the minimum temperature, which helps to visualize the location of the temperature anomaly and provide engineers with a clear visual reference.

[0103] In at least one embodiment of the present application, the method further includes:

[0104] S201, mapping the minimum feature position image into the part contour feature image to obtain a mapped position image;

[0105] S202, obtaining temperature information of other regions of the mapped position image in the first range of the part contour feature image and temperature information corresponding to the mapped position image;

[0106] S203, performing difference calculation on the temperature information of the other area images and the temperature information corresponding to the mapped position image one by one to obtain a second temperature difference;

[0107] S204: If the second temperature difference is greater than a second temperature threshold range, it is determined as a detection area waiting for reconfirmation signal.

[0108] In at least one embodiment of the present application, the method further includes:

[0109] S301, during detection, obtaining a third detection infrared image of a part at a second position within a first threshold range, wherein the second position is arranged in a mirror-symmetrical manner to the first position;

[0110] S302, mapping the minimum feature position image to the third detection infrared image, obtaining a third detection temperature of the minimum feature in the third detection infrared image, and performing a difference calculation between the third detection temperature and the minimum value of the temperature to obtain a third temperature difference;

[0111] S303: If the third temperature difference is greater than a third temperature threshold range, modifying the detection area reconfirmation signal to be a final leakage signal, and generating final leakage data.

[0112] In at least one embodiment of the present application, the method further includes:

[0113] The three-dimensional coordinate information of the leakage point is generated according to the minimum temperature value, the second detection infrared image and the third detection infrared image, and the final leakage signal is recorded and generated according to the three-dimensional coordinate information of the leakage point.

[0114] Please refer to Figure 1-Figure 6 In this embodiment, an image registration algorithm is used to map the minimum feature position image to the contour feature image of the part. Common algorithms include SIFT (Scale Invariant Feature Transform), SURF (Speeded Up Robust Features), and the like.

[0115] In the previous steps, the specific location of the temperature minimum is determined and the corresponding minimum feature location image is generated.

[0116] By first detecting the infrared image, a complete part contour feature image is generated to show the overall shape and position of the part.

[0117] Using algorithms such as SIFT or SURF, identify common feature points between two images.

[0118] According to these feature points, the image registration algorithm is applied to accurately align the minimum feature position image to the part contour feature image to obtain the mapped position image.

[0119] Extract temperature data from part profile feature images and use infrared temperature measurement software or custom algorithms to interpret the temperature information of image pixels.

[0120] In the mapped position image, a neighborhood range including the position is defined, such as a circular area with a minimum feature position as the center and a radius of a certain number of pixels (eg, 5 mm-2 cm).

[0121] The temperature data of all pixels within the first range are extracted to form a temperature information data set.

[0122] The temperature data of the minimum feature point in the mapped position image is extracted as the reference temperature information.

[0123] Calculate the second temperature difference, use a simple difference formula to calculate the temperature difference between the reference temperature information (the temperature value of the minimum feature point in the mapped position image) and the temperature information data set, calculate the temperature difference between each point and the minimum feature point, and form a data set of the second temperature difference.

[0124] A second temperature threshold range is set, and whether an abnormality exists is determined by comparing the second temperature difference with the second temperature threshold range.

[0125] According to experimental data or industry standards, the second temperature threshold range is set, for example, 5°C.

[0126] Each value in the second temperature difference value set is compared with the second temperature threshold range to determine whether any value exceeds the second temperature threshold range.

[0127] If exceeded, a detection zone waiting for reconfirmation signal is generated.

[0128] By using the symmetry of the part, an infrared image (third detected infrared image) of another symmetrical position (second position) is acquired for comparison.

[0129] Within the first threshold range time, a third detected infrared image of the second position (symmetrical position) is acquired.

[0130] The minimum feature position image is mapped to the third detection infrared image to extract the temperature information of the symmetrical position.

[0131] Calculate the third temperature difference, that is, the difference between the temperature at the symmetrical position and the minimum value.

[0132] The third temperature difference is compared with a set third temperature threshold range, and if it exceeds, leakage is confirmed.

[0133] Generate final leakage data, record the specific leakage point and temperature information.

[0134] Combine the multi-angle detection images and the 3D model of the parts to calculate the 3D coordinates of the leakage point.

[0135] Use multiple infrared images and camera viewing information, combined with the 3D model of the part, to perform 3D reconstruction.

[0136] Determine the specific location of the leakage point in space and generate three-dimensional coordinate data.

[0137] Through multiple temperature data analysis and comparison, the leak point can be accurately located. Symmetry detection ensures that all parts of the parts are covered, which improves the comprehensiveness and accuracy of the detection. The whole process is automated to reduce manual errors and improve detection efficiency.

[0138] It should be further explained that by comparing the temperature data of symmetrical positions, the accuracy of the test results can be verified. Assuming that the part design and manufacturing process are symmetrical, the temperature distribution of symmetrical positions should be consistent under normal circumstances. If the detected temperature difference is significant, especially in symmetrical parts, this may indicate an abnormal situation, such as a leakage problem.

[0139] Suppose when testing the air tightness of an electronic device casing, the inspector finds that a specific area on the left side of the device shows an abnormally low temperature. If the right side of the device is completely symmetrical, then according to the symmetry detection method, the system will automatically compare the temperature of the corresponding position on the right side. If the temperature on the right side is normal, but the temperature on the left side is abnormally low, this is a clear indication that there may be a leak or insulation problem on the left side, rather than a temperature deviation caused by external environmental factors.

[0140] Secondly, the third temperature threshold range is set so that it can also be applied when detecting asymmetric parts, so as to avoid the problem of being unable to detect due to asymmetry.

[0141] Symmetric detection provides a double verification mechanism to enhance the reliability and credibility of the detection results. Even if the detection on one side is abnormal, it can still be confirmed or eliminated through the detection on the symmetrical side. This double verification mechanism helps reduce the false alarm rate and missed detection rate, ensuring the accuracy of the detection results.

[0142] In at least one embodiment of the present application, the method further includes:

[0143] S106: If the first temperature difference is not greater than the first temperature threshold range, a normal signal is generated.

[0144] Please refer to Figure 1-Figure 4In this embodiment, the first temperature difference value (i.e., the difference between the maximum and minimum temperature values) calculated during the detection process is compared with the preset first temperature threshold range. If the difference value does not exceed the set threshold range, it is considered to be within the normal range.

[0145] In air tightness testing, the temperature difference is one of the key indicators to determine whether there is a leak. A smaller temperature difference usually means that the temperature distribution of the parts is more uniform, which means that the air tightness is good and there is no obvious leak point.

[0146] When the system determines that the first temperature difference is within the first temperature threshold range, a normal signal is generated, which indicates that no abnormality is found in the detection process and the airtightness of the part meets the expected standard.

[0147] Through accurate temperature difference calculation and standardized threshold judgment, the system can reduce the possibility of misjudgment and false alarm, and reduce additional inspections or unnecessary rework caused by false alarms.

[0148] It improves detection efficiency and accuracy, reduces human errors, and optimizes the quality control process by generating normal signals, making the manufacturing process more efficient and reliable.

[0149] In at least one embodiment of the present application, the step of performing difference calculation on the temperature information of the other area image and the temperature information corresponding to the mapped position image to obtain a second temperature difference, and if the second temperature difference is greater than a second temperature threshold range, determining that the detection area is to be reconfirmed as a signal further comprises:

[0150] S205: if the second temperature difference is not greater than the second temperature threshold range, generating a first leakage signal and generating first leakage data;

[0151] The part position information is acquired, and a first leakage position is calculated according to the minimum feature position image, the first position, the part contour feature image and the part position information to generate the first leakage position.

[0152] Please refer to Figure 1-Figure 4 In this embodiment, if the second temperature difference does not exceed the second temperature threshold range, the system will generate first leakage data and record relevant data, indicating that a possible leakage point is found during the detection process.

[0153] The system calculates the precise leak location and generates leak location data using the minimum feature location image, the first location, the part contour feature image and the part location information.

[0154] By comparing and calculating the temperature information of multiple areas one by one, potential leakage points can be identified more accurately, improving detection accuracy.

[0155] Through multiple confirmation and signal generation mechanisms, the possibility of missed detection and false alarm is reduced, ensuring the reliability of detection results.

[0156] The process of calculating the leak location enables the system to provide accurate leak point data, facilitating subsequent repair and treatment and improving maintenance efficiency.

[0157] In at least one embodiment of the present application, if the third temperature difference is greater than a third temperature threshold range, the step of modifying the detection area to-be-reconfirmed signal to a final leakage signal and generating final leakage data further includes:

[0158] The part position information is acquired, and a second leakage position is calculated according to the first position, the second position, the part position information, the part contour feature image and the minimum feature position image to generate the second leakage position.

[0159] Please refer to Figure 1-Figure 4 In this embodiment, the system obtains the specific position information (part position information) of the inspected part in the inspection device, including the positioning and posture data of the part, to facilitate subsequent precise positioning and processing.

[0160] Using the first position, the second position, the part position information, the part contour feature image and the minimum feature position image, the system comprehensively calculates the second leakage position and generates accurate leakage point data.

[0161] The first position includes coordinate data of the first position relative to the part, the second position includes coordinate data of the second position relative to the part, and the part position information includes the coordinates of the part and the reference coordinates located at the first position and the second position. A three-dimensional coordinate system is established based on the first position, the second position, and the part position information. The first position and the second position are mapped in the three-dimensional coordinate system with the part position as the origin. Then, the coordinate point in the three-dimensional coordinate system is calculated based on the minimum value of the temperature corresponding to the minimum feature position image and the part contour feature image, so as to obtain the precise leakage position, that is, the second leakage position, and send the second leakage position to the outside so that external inspectors can perform refined processing on the leakage position.

[0162] Through strict temperature difference judgment and signal confirmation mechanism, the system can effectively reduce repeated detection and false alarms and improve detection efficiency.

[0163] The leakage data generated by the system includes detailed information such as leakage location and temperature difference, providing sufficient basis for subsequent quality control and problem troubleshooting.

[0164] By making comprehensive use of various location information and feature images, the system can accurately locate the leak point and generate detailed leak location data, which is helpful for subsequent repair and treatment work.

[0165] Through multiple temperature difference calculations and strict threshold comparisons, the system can more accurately identify leak points, improve detection accuracy and reliability, and reduce the possibility of misjudgment and missed judgment.

[0166] In at least one embodiment of the present application, if the third temperature difference is greater than a third temperature threshold range, the step of modifying the detection area to-be-reconfirmed signal to a final leakage signal and generating final leakage data further includes:

[0167] S304: If the third temperature difference is not greater than a third temperature threshold range, a normal signal is generated.

[0168] Please refer to Figure 1-Figure 4 In this embodiment, if the third temperature difference is not greater than a preset threshold, the system generates a "normal signal", indicating that there is no leakage problem in the area.

[0169] The system automatically generates corresponding signals (normal or leakage) based on the comparison results of the temperature difference, improving detection efficiency and reducing manual intervention.

[0170] Through precise temperature difference calculation and automated signal processing, the accuracy and efficiency of detection are improved. The automatically generated detailed leakage data provides a reliable basis for subsequent repair work, while ensuring that each detection area is carefully inspected to ensure the overall quality of the product.

[0171] An intelligent leakage tracing system 100 for airtightness detection equipment is applied to the intelligent leakage tracing method for airtightness detection equipment described above, and the system comprises:

[0172] 110 An image acquisition module is used to acquire a first detection infrared image and a second detection infrared image of a part at a first position;

[0173] 120, a contour extraction module extracts the first detection infrared image to obtain a part contour feature image;

[0174] 130 a feature extraction module, extracting features from the second detection infrared image according to the part contour feature image to obtain an extracted feature image;

[0175] 140 screening module, screening out the maximum temperature and the minimum temperature from the extracted feature image;

[0176] 150 a difference calculation module, calculating a difference according to the maximum temperature and the minimum temperature selected, to obtain a first temperature difference;

[0177] 160 judgment module, judges the first temperature difference and the first temperature threshold range, and generates first leakage risk data if the first temperature difference is greater than the first temperature threshold range.

[0178] Please refer to Figure 1-Figure 4 In this embodiment, the image acquisition module 110 collects the first detection infrared image and the second detection infrared image of the part at the first position, the contour extraction module 120 processes the first detection infrared image to extract the contour feature image of the part, the feature extraction module 130 extracts the feature image from the second detection infrared image according to the contour feature image of the part, the screening module 140 screens out the maximum and minimum values ​​of the temperature from the extracted feature image, the difference calculation module 150 calculates the difference between the maximum and minimum values ​​of the temperature to obtain a first temperature difference, and the judgment module 160 compares the first temperature difference with a preset first temperature threshold range. If the first temperature difference is greater than the first temperature threshold range, first leakage risk data is generated.

[0179] The system realizes accurate detection of the airtightness of parts through multi-module collaboration. Infrared image acquisition, feature extraction, temperature screening and difference calculation steps all improve the detection accuracy.

[0180] Each module runs automatically, and the entire process from image acquisition to risk assessment is highly automated, reducing human intervention and errors.

[0181] By comparing the temperature difference with the threshold, the system can promptly detect potential leakage risks and generate leakage risk data for subsequent processing.

[0182] The system is based on infrared imaging detection of temperature changes, which avoids the problem of liquid detection possibly damaging parts and improves the reliability of detection.

[0183] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0184] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. An intelligent leakage tracking method for airtightness detection equipment, characterized in that: The intelligent leakage tracking method of the airtightness detection equipment comprises: Acquire a first detection infrared image of the part corresponding to the first position before detection, and generate a part contour feature image based on the first detection infrared image; During detection, a second detection infrared image of the part corresponding to the first position within a first threshold range time is obtained, and features of the second detection infrared image are extracted based on the part contour feature image to obtain an extracted feature image; Screening the extracted characteristic image to screen out a maximum temperature and a minimum temperature, and calculating a first temperature difference according to the maximum temperature and the minimum temperature; comparing the first temperature difference with a first temperature threshold range, and generating first leakage risk data if the first temperature difference is greater than the first temperature threshold range; The first leakage risk data includes: a minimum temperature value and a minimum characteristic position image corresponding to the minimum temperature value; Mapping the minimum feature position image to the part contour feature image to obtain a mapped position image; Acquire temperature information of other area images of the mapped position image in the first range of the part contour feature image and temperature information corresponding to the mapped position image; Calculate the difference between the temperature information of the other area images and the temperature information corresponding to the mapped position image one by one to obtain a second temperature difference; if the second temperature difference is greater than a second temperature threshold range, determine that the detection area is to be reconfirmed. During the detection, a third detection infrared image of the part at a second position within a first threshold range is acquired, wherein the second position is arranged in a mirror-symmetrical manner with the first position; Mapping the minimum feature position image to the third detection infrared image, obtaining a third detection temperature of the minimum feature in the third detection infrared image, and performing a difference calculation between the third detection temperature and the minimum value of the temperature to obtain a third temperature difference; If the third temperature difference is greater than the third temperature threshold range, the detection area to-be-reconfirmed signal is modified into a final leakage signal, and final leakage data is generated.

2. The intelligent leakage tracking method of airtightness detection equipment according to claim 1, characterized in that: The method further comprises: The three-dimensional coordinate information of the leakage point is generated according to the minimum temperature value, the second detection infrared image and the third detection infrared image, and the final leakage signal is recorded and generated according to the three-dimensional coordinate information of the leakage point.

3. The intelligent leakage tracking method of airtightness detection equipment according to claim 1, characterized in that: The method further comprises: If the first temperature difference is not greater than the first temperature threshold range, a normal signal is generated.

4. The intelligent leakage tracking method of airtightness detection equipment according to claim 1, characterized in that: The step of performing difference calculation on the temperature information of the other area images and the temperature information corresponding to the mapped position image to obtain a second temperature difference, and if the second temperature difference is greater than a second temperature threshold range, determining that the detection area is to be reconfirmed, further includes: If the second temperature difference is not greater than the second temperature threshold range, generating a first leakage signal and generating first leakage data; The part position information is acquired, and a first leakage position is calculated according to the minimum feature position image, the first position, the part contour feature image and the part position information to generate the first leakage position.

5. The intelligent leakage tracking method of airtightness detection equipment according to claim 1, characterized in that: If the third temperature difference is greater than the third temperature threshold range, the step of modifying the detection area to-be-confirmed signal to a final leakage signal and generating final leakage data also includes: The part position information is acquired, and a second leakage position is calculated according to the first position, the second position, the part position information, the part contour feature image and the minimum feature position image to generate the second leakage position.

6. The intelligent leakage tracking method of airtightness detection equipment according to claim 1, characterized in that: If the third temperature difference is greater than the third temperature threshold range, the step of modifying the detection area to-be-confirmed signal to a final leakage signal and generating final leakage data also includes: If the third temperature difference is not greater than the third temperature threshold range, a normal signal is generated.

7. An intelligent leakage tracing system for airtightness detection equipment, applied to the intelligent leakage tracing method for airtightness detection equipment according to any one of claims 1 to 6, characterized in that: The system comprises: An image acquisition module, used to acquire a first detection infrared image and a second detection infrared image of a part at a first position; A contour extraction module extracts the first detection infrared image to obtain a part contour feature image; A feature extraction module extracts features from the second detection infrared image according to the part contour feature image to obtain an extracted feature image; A screening module, screening out the maximum temperature and the minimum temperature from the extracted feature image; A difference calculation module calculates the difference according to the maximum temperature and the minimum temperature selected to obtain a first temperature difference; The judgment module judges the first temperature difference and the first temperature threshold range, and generates first leakage risk data if the first temperature difference is greater than the first temperature threshold range.

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