Quality detection method and system based on thermal insulation integrated pipe, terminal equipment and medium

Abstract

The invention is suitable for the technical field of production data processing, and provides a quality detection method and system based on a heat preservation integrated pipe, terminal equipment and a medium, and the method comprises the steps: firstly obtaining real-time image information of a target heat preservation pipe based on an industrial camera, and then obtaining real-time image information of the target heat preservation pipe according to a gray level conversion algorithm; according to the method, the excessive adhesion area information in the real-time image information is quickly determined, and finally, the quality detection result information is effectively generated according to the excessive adhesion area information. The production process of the thermal insulation integrated pipe can be comprehensively monitored in real time, unqualified products can be recognized and eliminated in time, the production reliability is greatly improved, important data support is provided, and follow-up quality analysis and improvement are facilitated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of production data processing, in particular to a quality detection method and system based on a heat preservation integrated pipe, a terminal device and a medium. BACKGROUND

[0002] The PP-R heat preservation integrated pipe generally comprises a heat preservation layer, an outer protective layer and a PP-R inner pipe, is not easy to be eroded by chemical substances, has good corrosion resistance, can effectively reduce heat loss and is suitable for a wide range of applications.

[0003] At present, in the production process of the PP-R heat preservation integrated pipe, there is a lack of effective real-time monitoring mechanism, which makes it difficult to find unqualified products in time, and the production reliability is low, which needs to be further improved. SUMMARY

[0004] Therefore, the embodiments of the present application provide a quality detection method and system based on a heat preservation integrated pipe, a terminal device and a medium to solve the problem of low production reliability in the prior art.

[0005] In a first aspect, the embodiments of the present application provide a quality detection method based on a heat preservation integrated pipe, which comprises the following steps: acquiring real-time image information of a target heat preservation pipe based on a preset industrial camera; determining over-adhesion area information in the real-time image information according to a preset gray scale conversion algorithm; generating quality detection result information according to the over-adhesion area information.

[0006] Compared with the prior art, the quality detection method based on a heat preservation integrated pipe provided by the embodiments of the present application has the beneficial effects that the terminal device can first acquire real-time image information of a target heat preservation pipe based on an industrial camera, then quickly determine over-adhesion area information in the real-time image information according to a gray scale conversion algorithm, and finally effectively generate quality detection result information according to the over-adhesion area information, so as to monitor unqualified heat preservation integrated pipes in real time in mass production, effectively improve the production reliability and solve the problem of low production reliability to a certain extent.

[0007] In a second aspect, the embodiments of the present application provide a quality detection system based on a heat preservation integrated pipe, which comprises the following modules: a real-time image information acquisition module configured to acquire real-time image information of a target heat preservation pipe based on a preset industrial camera; an over-adhesion area information determination module configured to determine over-adhesion area information in the real-time image information according to a preset gray scale conversion algorithm; The quality detection result information generation module is configured to generate quality detection result information according to the excessive adhesion area information.

[0008] In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method in the first aspect when executing the computer program.

[0009] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the steps of the method in the first aspect.

[0010] It can be understood that the beneficial effects of the second aspect to the fourth aspect can be referred to the related description in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced.

[0012] Figure 1 is a flowchart of a quality detection method provided by an embodiment of the present application; Figure 2 is a flowchart of step S200 in the quality detection method provided by an embodiment of the present application; Figure 3 is a flowchart of step S300 in the quality detection method provided by an embodiment of the present application; Figure 4 is a first flowchart after step S300 in the quality detection method provided by an embodiment of the present application; Figure 5 is a flowchart after step S430 in the quality detection method provided by an embodiment of the present application; Figure 6 is a second flowchart after step S300 in the quality detection method provided by an embodiment of the present application; Figure 7 is a third flowchart after step S300 in the quality detection method provided by an embodiment of the present application; Figure 8 is a flowchart of step S700 in the quality detection method provided by an embodiment of the present application; Figure 9 is a flowchart of step S710 in the quality detection method provided by an embodiment of the present application; Figure 10is a module block diagram of a quality detection system provided by an embodiment of the present application. Figure 11 is a schematic diagram of a terminal device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0013] In the following description, specific details are set forth in order to provide a thorough understanding of embodiments of the present application. However, persons having ordinary skill in the art will appreciate that embodiments of the present application can be practiced without the specific details, other embodiments can implement the present application with or without these specific details. In other instances, well-known structures and devices are not shown in order to avoid obscuring the application.

[0014] In the description of the present application and the appended claims, the terms "first", "second", "third", etc. are used only to distinguish descriptions, and cannot be understood as indicating or implying relative importance.

[0015] In the present application, the reference "one embodiment" or "some embodiments" means that the specific features, structures or characteristics described in connection with the embodiment are included in one or more embodiments of the present application. Therefore, the statements "in one embodiment", "in some embodiments", "in other some embodiments", "in other some embodiments" and the like appearing in different places in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized. The terms "include", "contain", "have" and their variants mean "include but not limited to", unless otherwise specifically emphasized.

[0016] In order to illustrate the technical solutions described in the present application, the following will be described by specific embodiments.

[0017] Please refer to Figure 1 , Figure 1 is a flowchart of a quality detection method based on a heat preservation integrated pipe provided by an embodiment of the present application. In the present embodiment, the execution subject of the quality detection method is a terminal device. It can be understood that the types of the terminal device include but are not limited to mobile phones, tablet computers, notebook computers, ultra-mobile personal computers (UMPC), netbooks, personal digital assistants (PDA) and the like, and the specific type of the terminal device is not limited by the present embodiment.

[0018] Please refer to Figure 1 , the quality detection method provided by the present embodiment includes but is not limited to the following steps: In S100, real-time image information of the target heat preservation pipe is acquired based on a preset industrial camera.

[0019] Specifically, the terminal device can acquire real-time image information of the target heat preservation pipe based on a preset industrial camera, where the real-time image information is used to describe an image obtained by real-time shooting of the target heat preservation pipe by the industrial camera.

[0020] It should be noted that for the PP-R heat preservation integrated pipe that does not meet the quality requirements, the PP-R inner pipe will be attached with a large amount of heat preservation layer after the heat preservation layer in the connection area is peeled off, which seriously affects the subsequent hot melt connection of the PP-R.

[0021] In S200, over-attached area information in the real-time image information is determined according to a preset gray scale conversion algorithm.

[0022] Specifically, after the terminal device acquires the real-time image information, the terminal device can effectively determine the over-attached area information in the real-time image information according to a preset gray scale conversion algorithm, where the over-attached area information is used to describe an area on the target heat preservation pipe where the foaming material is over-attached.

[0023] In some possible implementation manners, in order to effectively determine the over-attached area information, please refer to Figure 2 , step S200 includes but is not limited to the following steps: In S210, the real-time image information is subjected to gray scale conversion processing based on a preset gray scale conversion algorithm to generate gray scale image information.

[0024] Specifically, the terminal device can subject the real-time image information to gray scale conversion processing based on a preset gray scale conversion algorithm to generate gray scale image information, where the gray scale image information is used to describe the real-time image information subjected to the gray scale conversion processing.

[0025] In S220, the gray scale image information is subjected to contour extraction processing based on a preset contour extraction algorithm to generate a plurality of candidate area information.

[0026] Specifically, after the terminal device generates the gray scale image information, the terminal device can subject the gray scale image information to contour extraction processing based on a preset contour extraction algorithm to generate a plurality of candidate area information, where the candidate area information is used to describe an area formed by a closed contour line.

[0027] In S230, area average gray scale value information of each candidate area information is determined.

[0028] Specifically, after the terminal device generates the plurality of candidate region information, the terminal device can determine region average gray value information of each candidate region information, wherein the region average gray value information is used to describe the average gray value of the candidate region information.

[0029] In S240, the region average gray value information of each candidate region information is compared with the preset boundary gray value information respectively.

[0030] Specifically, after the terminal device determines the region average gray value information, the terminal device can compare the region average gray value information of each candidate region information with the preset boundary gray value information respectively, wherein the specific value of the boundary gray value information can be customized by the detection personnel, and exemplarily, the specific value of the boundary gray value information can be 15.

[0031] In S250, if the region average gray value information of the candidate region information is greater than the boundary gray value information, the terminal device determines that the candidate region information is the excessive adhesion region information.

[0032] Specifically, if the region average gray value information of the candidate region information is greater than the boundary gray value information, it indicates that the candidate region information is the region with excessive adhesion of the foaming material, and therefore the terminal device can determine that the candidate region information is the excessive adhesion region information.

[0033] In S300, the quality detection result information is generated according to the excessive adhesion region information.

[0034] Specifically, after the terminal device determines the excessive adhesion region information, the terminal device can accurately generate the quality detection result information according to the excessive adhesion region information, wherein the quality detection result information is the general abnormal adhesion information or the serious abnormal adhesion information.

[0035] In some possible implementation manners, in order to accurately generate the quality detection result information, please refer to Figure 3 , the step S300 includes but is not limited to the following steps: In S310, the adhesion region sub-area information of each excessive adhesion region information and the insulation tube region area information of the target insulation tube are obtained.

[0036] Specifically, the terminal device can obtain the adhesion region sub-area information of each excessive adhesion region information and the insulation tube region area information of the target insulation tube based on the grid method, wherein the adhesion region sub-area information is used to describe the area of the excessive adhesion region information, and the insulation tube region area information is used to describe the area corresponding to the target insulation tube in the gray-scale image information.

[0037] In S320, the adhesion region total area information is generated according to the sum of the plurality of adhesion region sub-area information.

[0038] Specifically, after the terminal device acquires the adhesion area sub-area information, the terminal device can generate total adhesion area information according to the sum of the plurality of adhesion area sub-area information, wherein the total adhesion area information is used to describe the sum of the plurality of adhesion area sub-area information.

[0039] In S330, the total adhesion area information is compared with the adhesion area information of the specified multiple of the heat preservation tube.

[0040] Specifically, after the terminal device generates the total adhesion area information, the terminal device can compare the total adhesion area information with the adhesion area information of the specified multiple of the heat preservation tube, wherein the specified multiple is a natural number between 0.25 and 0.4, and the specified multiple is preferably 0.25 when the production requirement is high.

[0041] In S340, if the total adhesion area information is less than the adhesion area information of the specified multiple of the heat preservation tube, the quality detection result information is determined to be general abnormal adhesion information, otherwise the quality detection result information is determined to be serious abnormal adhesion information.

[0042] Specifically, if the total adhesion area information is less than the adhesion area information of the specified multiple of the heat preservation tube, the terminal device can determine the quality detection result information to be general abnormal adhesion information, otherwise the terminal device can determine the quality detection result information to be serious abnormal adhesion information.

[0043] In some possible implementations, in order to facilitate the detection personnel to analyze the production abnormal situation, please refer to Figure 4 After step S300, the method further includes but is not limited to the following steps: In S400, the historical abnormal duration information and the current abnormal duration information of the heat preservation tube production line are acquired.

[0044] Specifically, the terminal device can acquire the historical abnormal duration information and the current abnormal duration information of the heat preservation tube production line, wherein the historical abnormal duration information is used to describe the cumulative duration of the heat preservation tube production line from startup to the last quality detection result information in history, and the current abnormal duration information is used to describe the cumulative duration of the heat preservation tube production line from startup to the quality detection result information in this round of production.

[0045] In S410, the duration difference value information is generated according to the historical abnormal duration information and the current abnormal duration information.

[0046] Specifically, after the terminal device acquires the historical abnormal duration information and the current abnormal duration information, the terminal device can generate the duration difference value information according to the historical abnormal duration information and the current abnormal duration information, wherein the duration difference value information is used to describe the difference between the historical abnormal duration information and the current abnormal duration information.

[0047] In S420, it is judged whether the time difference value information is less than the preset boundary time information.

[0048] Specifically, after the terminal device generates the time difference value information, the terminal device can judge whether the time difference value information is less than the preset boundary time information, wherein the specific value of the boundary time information can be customized by the detection personnel, for example, 15 minutes. In S430, if the time difference value information is less than the boundary time information, the average abnormal time information is generated according to the historical abnormal time information and the current abnormal time information.

[0049] Specifically, if the time difference value information is less than the boundary time information, it indicates that there is a high probability of production problems at this time node when producing the target insulation pipe of this type, so the terminal device can generate the average abnormal time information according to the historical abnormal time information and the current abnormal time information, wherein the average abnormal time information is used to describe the average value after adding the historical abnormal time information and the current abnormal time information.

[0050] In some possible implementation manners, in order to further facilitate the detection personnel to analyze the production abnormality, please refer to Figure 5 After step S430, the method further includes but is not limited to the following steps: In S500, the foaming agent formula information, the production parameter information of the insulation pipe production line and the type information of the target insulation pipe are obtained.

[0051] Specifically, the terminal device can obtain the foaming agent formula information, the production parameter information of the insulation pipe production line and the type information of the target insulation pipe.

[0052] In S510, the foaming agent formula information, the production parameter information and the type information are uploaded to the cloud database.

[0053] Specifically, after the terminal device obtains the foaming agent formula information, the production parameter information of the insulation pipe production line and the type information of the target insulation pipe, the terminal device can upload the foaming agent formula information, the production parameter information and the type information to the cloud database, thereby facilitating the detection personnel to remotely analyze the production abnormality.

[0054] In some possible implementation manners, in order to facilitate the analysis of the processing condition of the insulation integrated pipe, please refer to Figure 6 After step S300, the method further includes but is not limited to the following steps: In S600, the first cumulative processing quantity information of the target insulation pipe and the second cumulative processing quantity information of the quality abnormal insulation pipe are obtained.

[0055] Specifically, the terminal device can obtain the first cumulative processing quantity information of the target insulation pipe and the second cumulative processing quantity information of the insulation pipe with quality abnormality. The insulation pipe with quality abnormality is used to describe the target insulation pipe corresponding to general abnormal adhesion information and the target insulation pipe corresponding to severe abnormal adhesion information.

[0056] In S610, processing qualification rate information is generated based on the first cumulative processing quantity information and the second cumulative processing quantity information.

[0057] Specifically, after the terminal device obtains the first cumulative processing quantity information and the second cumulative processing quantity information, the terminal device can calculate the difference between the second cumulative processing quantity information and the first cumulative processing quantity information, and then generate the processing qualification rate information by dividing the difference by the quotient of the first cumulative processing quantity information.

[0058] For analysis of the processing of this integrated insulation pipe, please refer to the following for possible implementation methods. Figure 7 After step S300, the method further includes, but is not limited to, the following steps: In S700, the centroid information and weight information of each over-adhesion region are obtained.

[0059] Specifically, the terminal device can first obtain the centroid information and weight information of each over-adhesion region. The centroid information describes the specific location of the centroid of the over-adhesion region information, and the weight information describes the specific weight of the over-adhesion region information.

[0060] For some possible implementations, please refer to [link to relevant documentation] for accurate generation of quality inspection results. Figure 8 Step S700 includes, but is not limited to, the following steps: In S701, for each over-adhesion region information: based on a preset integration method, the centroid information of the region corresponding to the over-adhesion region information is obtained.

[0061] Specifically, the terminal device can first perform this processing on the information of each over-adhesion region: based on a preset integration method, specifically obtain the centroid information of the region corresponding to the over-adhesion region information.

[0062] For example, the regional centroid information can be The terminal device can calculate the abscissa using a preset abscissa integration function, which can be: , In the formula, For the first The x-coordinate of the centroid information of each region the serial number of the region centroid point information, the sub-area information of the adhering region, the coordinate of any point in the excessive adhering region information on the x-axis; the coordinate of any point in the excessive adhering region information on the x-axis; Meanwhile, the terminal device can calculate the horizontal coordinate by using a preset longitudinal coordinate integral calculation function, which can be: , wherein, the longitudinal coordinate of the i-th region centroid point information, the coordinate of any point in the excessive adhering region information on the x-axis. the coordinate of any point in the excessive adhering region information on the x-axis.

[0063] In S702, the region weight information is generated according to the sub-area information of the adhering region divided by the total area information of the adhering region.

[0064] Specifically, after the terminal device obtains the region centroid point information, the terminal device can generate the region weight information according to the sub-area information of the adhering region divided by the total area information of the adhering region, wherein the value of the region weight information is the quotient value of the sub-area information of the adhering region divided by the total area information of the adhering region.

[0065] In S710, the region concentration information is generated according to the region centroid point information and the region weight information based on a preset region concentration calculation function.

[0066] Specifically, after the terminal device obtains the region centroid point information and the region weight information, the terminal device can accurately generate the region concentration information according to the region centroid point information and the region weight information by using a preset region concentration calculation function, so as to accurately and quickly determine the range where the excessive foaming material is specifically concentrated, which is beneficial for the detection personnel to optimize the specific process parameters based thereon.

[0067] In some possible implementation manners, in order to accurately generate the quality detection result information, please refer to Figure 9 , step S710 includes but is not limited to the following steps: In S711, the key centroid point information is determined according to the plurality of region centroid point information.

[0068] Specifically, the terminal device can determine the key centroid point information according to the plurality of region centroid point information by using a preset key centroid point calculation function, wherein the key centroid point information is ; the terminal device can calculate the horizontal coordinate by using a preset key centroid point horizontal coordinate calculation function, which can be: ,​ is a horizontal coordinate of the key centroid point information, is a serial number of the key centroid point information, is a total number of the excessive adhesion area information, is a starting value of the summation function, is the region weight information corresponding to the i-th region centroid point information. Meanwhile, the terminal device can calculate the horizontal coordinate through a preset key centroid point vertical coordinate calculation function, which can be: , is a vertical coordinate of the key centroid point information.

[0069] In S712, the key centroid point information, the region centroid point information and the region weight information are input to a preset region convergence degree calculation function to generate region convergence degree information.

[0070] Specifically, after determining the key centroid point information, the terminal device can input the key centroid point information, the region centroid point information and the region weight information to a preset region convergence degree calculation function to accurately generate the region convergence degree information, wherein the region convergence degree calculation function can be: , is the region convergence degree information; is the region average distance information, , is the shortest distance between the i-th region centroid point information and the key centroid point information, and in one possible implementation manner, . The implementation principle of the quality detection method of the heat preservation integrated pipe based on the embodiment of the present application is as follows: the terminal device can first acquire real-time image information of a target heat preservation pipe based on an industrial camera, then quickly determine the excessive adhesion area information in the real-time image information according to a gray scale conversion algorithm, and finally effectively generate quality detection result information according to the excessive adhesion area information, so as to realize real-time monitoring of unqualified heat preservation integrated pipes and effectively improve production reliability.

[0071] It should be noted that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0072] It should be noted that the size of the serial number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiment of the present application.

[0073] ​​​​The embodiment of the application further provides a quality detection system based on a heat preservation integrated pipe, for the convenience of description, only the part related to the application is shown, such as Figure 10 As shown in the figure, the system 100 comprises: A real-time image information acquisition module 101: configured to acquire real-time image information of a target heat preservation pipe based on a preset industrial camera; An excessive adhesion area information determination module 102: configured to determine excessive adhesion area information in the real-time image information according to a preset gray scale conversion algorithm; A quality detection result information generation module 103: configured to generate quality detection result information according to the excessive adhesion area information.

[0074] Optionally, the system 100 further comprises: A region centroid point information acquisition module: configured to acquire region centroid point information and region weight information corresponding to each excessive adhesion area information; A region convergence degree information generation module: configured to generate region convergence degree information based on a preset region convergence degree calculation function according to the region centroid point information and the region weight information.

[0075] Optionally, the region centroid point information acquisition module comprises: A region centroid point information acquisition module: configured to acquire, for each excessive adhesion area information, region centroid point information corresponding to the excessive adhesion area information based on a preset integration method; A region weight information generation module: configured to generate region weight information according to adhesion area sub-area information divided by adhesion area total area information; Optionally, the region convergence degree information generation module comprises: A key centroid point information determination module: configured to determine key centroid point information according to a plurality of region centroid point information; A region convergence degree information generation module: configured to input the key centroid point information, the region centroid point information and the region weight information into a preset region convergence degree calculation function to generate region convergence degree information.

[0076] Optionally, the excessive adhesion area information determination module 102 comprises: A gray scale image information generation sub-module: configured to perform gray scale conversion processing on the real-time image information based on a preset gray scale conversion algorithm to generate gray scale image information; A candidate region information generation sub-module: configured to perform contour extraction processing on the gray scale image information based on a preset contour extraction algorithm to generate a plurality of candidate region information; A region average gray scale value information determination sub-module: configured to determine region average gray scale value information of each candidate region information; The region average gray value information comparison submodule is configured to compare the region average gray value information of each candidate region information with preset boundary gray value information respectively. The excessive adhesion region information determination submodule is configured to determine the candidate region information as the excessive adhesion region information if the region average gray value information of the candidate region information is greater than the boundary gray value information. Correspondingly, the quality detection result information is the general abnormal adhesion information or the serious abnormal adhesion information; the quality detection result information generation module 103 comprises: The adhesion region sub-area information acquisition submodule is configured to acquire adhesion region sub-area information of each excessive adhesion region information and the test tube region area information of the target test tube. The adhesion region total area information generation submodule is configured to generate the adhesion region total area information according to a sum of the plurality of adhesion region sub-area information. The adhesion region total area information comparison submodule is configured to compare the adhesion region total area information with the test tube region area information of a specified multiple, wherein the specified multiple is a natural number between 0.25 and 0.4. The general abnormal adhesion information determination submodule is configured to determine the quality detection result information as the general abnormal adhesion information if the adhesion region total area information is less than the test tube region area information of the specified multiple, otherwise, determine the quality detection result information as the serious abnormal adhesion information.

[0077] Optionally, the system 100 further comprises: The historical abnormal duration information acquisition module is configured to acquire historical abnormal duration information and current abnormal duration information of the test tube production line, wherein the historical abnormal duration information is used to describe a cumulative duration of the test tube production line from start to the last quality detection result information in history, and the current abnormal duration information is used to describe a cumulative duration of the test tube production line from start to the quality detection result information in this round of production. The duration difference value information generation module is configured to generate duration difference value information according to the historical abnormal duration information and the current abnormal duration information. The duration difference value information judgment module is configured to judge whether the duration difference value information is less than preset boundary duration information. The average abnormal duration information generation module is configured to generate average abnormal duration information according to the historical abnormal duration information and the current abnormal duration information if the duration difference value information is less than the boundary duration information.

[0078] Optionally, the system 100 further comprises: The foaming agent formula information acquisition module is configured to acquire foaming agent formula information, production parameter information of the test tube production line and model information of the target test tube. Foaming agent formula information uploading module: used for uploading foaming agent formula information, production parameter information and model information to a cloud database.

[0079] Optionally, the system 100 further comprises: Cumulative processing quantity information obtaining module: used for obtaining first cumulative processing quantity information of the target heat preservation pipe and second cumulative processing quantity information of the quality abnormal heat preservation pipe, wherein the quality abnormal heat preservation pipe is used for describing the target heat preservation pipe corresponding to the general abnormal adhesion information and the target heat preservation pipe corresponding to the serious abnormal adhesion information; Processing qualified rate information generating module: used for generating processing qualified rate information according to the first cumulative processing quantity information and the second cumulative processing quantity information.

[0080] It should be noted that the information interaction, execution process and the like between the above modules, since based on the same concept as the method embodiments of the present application, the specific functions and the technical effects brought by them can be referred to the method embodiments part, and will not be repeated here.

[0081] The present application also provides a terminal device, as shown in Figure 11 The terminal device 110 of this embodiment comprises a processor 111, a memory 112, and a computer program 113 stored in the memory 112 and executable on the processor 111. The processor 111 implements the steps in the above quality detection method embodiments when executing the computer program 113, for example Figure 1 Steps S100 to S300 shown in the figure; or the processor 111 implements the functions of the modules in the above device when executing the computer program 113, for example Figure 10 The functions of the modules 101 to 103 shown in the figure.

[0082] The terminal device 110 can be a desktop computer, a notebook computer, a palm computer and a cloud server, etc. The terminal device 110 includes but is not limited to the processor 111 and the memory 112. Those skilled in the art can understand that Figure 11 The terminal device 110 is only an example and does not constitute a limitation on the terminal device 110, and can include more or fewer components than shown, or combine certain components, or different components, for example, the terminal device 110 can also include an input / output device, a network access device, a bus, etc.

[0083] The processor 111 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0084] The memory 112 can be an internal storage unit of the terminal device 110, for example, a hard disk or a memory of the terminal device 110. The memory 112 can also be an external storage device of the terminal device 110, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal device 110. Further, the memory 112 can include both the internal storage unit and the external storage device of the terminal device 110. The memory 112 can also store the computer program 113 and other programs and data required by the terminal device 110. The memory 112 can also be used to temporarily store data that has been output or will be output.

[0085] An embodiment of the present application further provides a computer readable storage medium storing a computer program. The computer program, when executed by a processor, can implement the steps of the above-mentioned various method embodiments. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc.

[0086] The above are preferred embodiments of the present application, which do not limit the protection scope of the present application. Therefore, any equivalent changes made according to the methods, principles and structures of the present application should be covered within the protection scope of the present application.

Claims

1. A quality inspection method based on integrated thermal insulation pipe, characterized in that, The method includes: Based on a pre-set industrial camera, real-time image information of the target insulation pipe is acquired; Based on a preset grayscale conversion algorithm, the information of the over-adhesion region in the real-time image information is determined; Based on the information about the over-adhesion area, quality inspection result information is generated; The method further includes, after generating quality inspection result information based on the over-adhesion region information: Obtain the centroid information and weight information of each of the aforementioned over-adhesion regions; Based on a preset regional clustering calculation function, regional clustering information is generated according to the regional centroid information and regional weight information.

2. The method according to claim 1, characterized in that, The step of determining the over-adhesion region information in the real-time image information according to the preset grayscale conversion algorithm includes: Based on a preset grayscale conversion algorithm, grayscale conversion processing is performed on real-time image information to generate grayscale image information; Based on a preset contour extraction algorithm, the grayscale image information is subjected to contour extraction processing to generate multiple candidate region information. Determine the average grayscale value of each of the candidate regions; The average gray value of each candidate region is compared with the preset limit gray value. If the average gray value of the candidate region is greater than the limit gray value, then the candidate region is determined to be an over-adhesion region. Accordingly, the quality inspection result information is either general abnormal adhesion information or severe abnormal adhesion information; the step of generating quality inspection result information based on the excessive adhesion area information includes: Obtain the sub-area information of the adhesion region of each of the aforementioned excessive adhesion regions and the area information of the insulation region of the target insulation pipe; The total area information of the adhesion region is generated based on the sum of the area information of multiple adhesion region sub-areas. Compare the total area information of the adhesion region with the area information of the insulation pipe region by a specified multiple, wherein the specified multiple is a natural number between 0.25 and 0.4; If the total area of ​​the adhesion region is less than a specified multiple of the area of ​​the insulation pipe region, then the quality inspection result is determined to be general abnormal adhesion information; otherwise, the quality inspection result is determined to be severe abnormal adhesion information.

3. The method according to claim 2, characterized in that, The step of obtaining the centroid information and weight information of each of the over-adhesion regions includes: For each of the aforementioned over-adhesion region information: based on a preset integration method, obtain the region centroid information corresponding to the over-adhesion region information; Region weight information is generated by dividing the sub-area information of the adhesion region by the total area information of the adhesion region. Accordingly, the method for generating regional clustering information based on a preset regional clustering calculation function, according to the regional centroid information and regional weight information, includes: Based on the information of multiple centroid points in the aforementioned regions, determine the key centroid point information; Input the key centroid information, the regional centroid information, and the regional weight information into a preset regional clustering calculation function to generate regional clustering information.

4. The method according to claim 2, characterized in that, After generating quality inspection result information based on the over-adhesion region information, the method further includes: Obtain historical and current abnormal duration information of the thermal insulation pipe production line. The historical abnormal duration information describes the cumulative duration of the thermal insulation pipe production line from start-up to the most recent quality inspection result information in history. The current abnormal duration information describes the cumulative duration of the thermal insulation pipe production line from start-up to the quality inspection result information in this round of production. Based on the historical and current abnormal duration information, a duration difference information is generated. Determine whether the duration difference information is less than a preset limit duration information; If the duration difference information is less than the threshold duration information, then the average abnormal duration information is generated based on the historical abnormal duration information and the current abnormal duration information.

5. The method according to claim 4, characterized in that, After generating average abnormal duration information based on the historical abnormal duration information and the current abnormal duration information if the duration difference information is less than the threshold duration information, the method further includes: Obtain the foaming agent formula information, the production parameter information of the insulation pipe production line, and the model information of the target insulation pipe; Upload the foaming agent formula information, production parameter information, and model information to the cloud database.

6. The method according to claim 1, characterized in that, After generating quality inspection result information based on the over-adhesion region information, the method further includes: Obtain the first cumulative processing quantity information of the target insulation pipe and the second cumulative processing quantity information of the insulation pipe with quality abnormality, wherein the insulation pipe with quality abnormality is used to describe the target insulation pipe corresponding to general abnormal adhesion information and the target insulation pipe corresponding to severe abnormal adhesion information; Based on the first and second cumulative processing quantity information, the processing qualification rate information is generated.

7. A quality inspection system based on an integrated thermal insulation pipe, characterized in that, The system includes: Real-time image information acquisition module: used to acquire real-time image information of the target insulation pipe based on a preset industrial camera; Over-adhesion region information determination module: used to determine the over-adhesion region information in the real-time image information according to a preset grayscale conversion algorithm; Quality inspection result information generation module: used to generate quality inspection result information based on the information of the over-adhesion area.

8. The system according to claim 7, characterized in that, The system includes: Cumulative processing quantity information acquisition module: used to acquire the first cumulative processing quantity information of the target insulation pipe and the second cumulative processing quantity information of the insulation pipe with quality abnormality, wherein the insulation pipe with quality abnormality is used to describe the target insulation pipe corresponding to general abnormal adhesion information and the target insulation pipe corresponding to severe abnormal adhesion information; Processing pass rate information generation module: used to generate processing pass rate information based on the first cumulative processing quantity information and the second cumulative processing quantity information.

9. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6.

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