An online detection method and system based on an aluminum profile quenching production line

Abstract

This application relates to the technical field of intelligent inspection, providing an online inspection method and system based on an aluminum profile quenching production line. The method includes first continuously acquiring real-time thermal images of multiple aluminum profiles to be inspected using a pre-set infrared thermal imager; then performing processing on each real-time thermal image: based on an edge contour detection algorithm, quickly determining multiple candidate area information and the corresponding temperature information of each candidate area; finally, accurately generating quenching uniformity evaluation information based on the multiple candidate area temperature information. This application overcomes the limitations of traditional manual sampling inspection, achieving comprehensive, non-destructive, and online inspection of the quenching quality of an entire batch of aluminum profiles. It continuously tracks the contour changes and temperature field distribution of each profile throughout the entire quenching process, thereby constructing a three-dimensional quality evaluation system from "single point" to "entire batch," and from "result" to "process."

Description

Technical Field

[0001] This application relates to the technical field of intelligent detection, and more specifically, to an online detection method and system based on an aluminum profile quenching production line. Background Technology

[0002] After aluminum profiles are extruded, the aluminum profile quenching production line rapidly cools them to fix them into a supersaturated solid solution state, thereby significantly improving the material's hardness, strength, and mechanical property stability, and preventing strength loss during natural aging.

[0003] Currently, aluminum profile quenching production lines typically rely on manual sampling inspection. This method not only has a limited scope of inspection, making it difficult to reflect the quenching uniformity and overall effect of the entire batch of profiles, but it is also susceptible to subjective factors, resulting in low reliability of the inspection results, and requires further improvement. Summary of the Invention

[0004] Based on this, the present application provides an online detection method and system based on an aluminum profile quenching production line to solve the problem of low reliability of detection results in the prior art.

[0005] In a first aspect, embodiments of this application provide an online inspection method based on an aluminum profile quenching production line, the method comprising: Based on a preset infrared thermal imager, real-time thermal image information corresponding to multiple aluminum profiles to be inspected is continuously acquired; For each of the real-time thermal image information: based on a preset edge contour detection algorithm, multiple candidate region information and the candidate region temperature information corresponding to each candidate region information are determined; Based on the temperature information of multiple candidate areas, quenching uniformity evaluation information is generated.

[0006] Compared with the prior art, the beneficial effects are as follows: The online detection method based on the aluminum profile quenching production line provided in this application embodiment allows the terminal equipment to first continuously acquire real-time thermal image information corresponding to multiple aluminum profiles to be detected based on a preset infrared thermal imager. Then, the processing is performed on each real-time thermal image information: using an edge contour detection algorithm, multiple candidate area information and the corresponding candidate area temperature information are quickly determined. Finally, based on the multiple candidate area temperature information, quenching uniformity effect evaluation information is accurately generated, thereby realizing comprehensive and effective quenching quality detection of the entire batch of aluminum profiles, greatly improving the reliability of the detection results, and to a certain extent solving the problem of low reliability of current detection results.

[0007] Secondly, embodiments of this application provide an online inspection system based on an aluminum profile quenching production line, the system comprising: Real-time thermal image information acquisition module: used to continuously acquire real-time thermal image information of multiple aluminum profiles to be inspected based on a preset infrared thermal imager; Candidate region information determination module: used to determine multiple candidate region information and the candidate region temperature information corresponding to each candidate region information based on a preset edge contour detection algorithm for each of the real-time thermal image information; Quenching uniformity effect evaluation information generation module: used to generate quenching uniformity effect evaluation information based on the temperature information of multiple candidate areas.

[0008] Thirdly, embodiments of this application provide a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect above.

[0009] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0010] It is understood that the beneficial effects of the second to fourth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below.

[0012] Figure 1 This is a schematic flowchart of an online detection method provided in an embodiment of this application; Figure 2 This is a flowchart illustrating step S300 in an online detection method provided in an embodiment of this application; Figure 3 This is a flowchart illustrating the process after step S300 in an online detection method provided in an embodiment of this application; Figure 4 This is a flowchart illustrating step S470 in an online detection method provided in an embodiment of this application; Figure 5 This is a flowchart illustrating the process after step S400 in an online detection method provided in an embodiment of this application; Figure 6 This is a block diagram of an online detection system provided in one embodiment of this application; Figure 7 This is a schematic diagram of a terminal device provided in an embodiment of this application. Detailed Implementation

[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

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

[0015] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0016] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0017] Please see Figure 1 , Figure 1 This is a flowchart illustrating the online inspection method based on an aluminum profile quenching production line provided in this embodiment. In this embodiment, the executing entity of the online inspection method is a terminal device. It is understood that the types of terminal devices include, but are not limited to, tablet computers, laptops, Ultra-Mobile Personal Computers (UMPCs), netbooks, Personal Digital Assistants (PDAs), etc. This embodiment does not impose any restrictions on the specific type of terminal device.

[0018] Please see Figure 1 The online detection method provided in this application includes, but is not limited to, the following steps: In S100, based on a preset infrared thermal imager, real-time thermal image information corresponding to multiple aluminum profiles to be inspected is continuously acquired.

[0019] Specifically, the terminal device can first continuously acquire real-time thermal image information of multiple aluminum profiles to be inspected based on a preset infrared thermal imager. The infrared thermal imager is located at the output end of the aluminum profile quenching production line. The multiple aluminum profiles to be inspected are multiple aluminum profiles of the same batch and model. The real-time thermal image information is used to describe the thermal image obtained by taking pictures of the aluminum profiles to be inspected using the infrared thermal imager.

[0020] In S200, for each real-time thermal image information: based on a preset edge contour detection algorithm, multiple candidate area information and the corresponding candidate area temperature information are determined.

[0021] Specifically, after the terminal device acquires multiple real-time thermal images, it can perform the following processing on each real-time thermal image: Based on a preset edge contour detection algorithm, edge contour extraction is performed on the real-time thermal image information to determine multiple candidate region information and the corresponding temperature information of each candidate region. The edge contour detection algorithm can be an edge contour detection algorithm based on the Sobel operator or the Prewitt operator; different candidate region information represents different thermal regions; and the candidate region temperature information is used to describe the temperature corresponding to the candidate region information.

[0022] In S300, quenching uniformity evaluation information is generated based on the temperature information of multiple candidate areas.

[0023] Specifically, after the terminal equipment determines multiple candidate area information and candidate area temperature information, the terminal equipment can accurately generate quenching uniformity effect evaluation information based on the multiple candidate area temperature information. The quenching uniformity effect evaluation information includes effect qualified information or effect abnormal information. Effect qualified information indicates that the quenching effect of the aluminum profile quenching production line is qualified, while effect abnormal information indicates that the quenching effect of the aluminum profile quenching production line is unqualified.

[0024] In some possible implementations, for accurate generation of quenching uniformity evaluation information, please refer to [link / reference]. Figure 2 Step S300 includes, but is not limited to, the following steps: In S310, based on the temperature information of multiple candidate areas, the information of the highest temperature area and the information of the lowest temperature area are determined.

[0025] Specifically, the terminal device can determine the highest temperature area information and the lowest temperature area information based on the temperature information of multiple candidate areas. The highest temperature area information is used to describe the candidate area information corresponding to the largest candidate area temperature information, and the lowest temperature area information is used to describe the candidate area information corresponding to the smallest candidate area temperature information.

[0026] In S320, the maximum temperature difference information is generated based on the information of the highest temperature area and the lowest temperature area.

[0027] Specifically, after the terminal device determines the information of the highest temperature area and the lowest temperature area, the terminal device can effectively generate the maximum temperature difference information by subtracting the lowest temperature area information from the highest temperature area information.

[0028] In S330, the maximum temperature difference information corresponding to each real-time thermal image information is compared with the preset temperature difference compliance threshold information.

[0029] Specifically, after the terminal device generates the maximum temperature difference information, the terminal device can compare the maximum temperature difference information corresponding to each real-time thermal image with the preset temperature difference compliance threshold information. The specific value of the temperature difference compliance threshold information can be customized in advance, such as 5 degrees Celsius.

[0030] In S340, if the maximum temperature difference information corresponding to each real-time thermal image is less than the temperature difference compliance threshold information, then the quenching uniformity effect evaluation information is determined to be qualified information; otherwise, the quenching uniformity effect evaluation information is determined to be abnormal information.

[0031] Specifically, if the maximum temperature difference information corresponding to each real-time thermal image is less than the temperature difference compliance threshold information, the terminal device can effectively determine that the quenching uniformity effect evaluation information is qualified; otherwise, the terminal device can effectively determine that the quenching uniformity effect evaluation information is abnormal.

[0032] Specifically, the abnormality information is categorized as either severe or routine. Severe abnormality information indicates that the quenching effect of the aluminum profile quenching production line is seriously unqualified, while routine abnormality information indicates that the quenching effect of the aluminum profile quenching production line is only moderately unqualified.

[0033] In some possible implementations, to delve deeper into the root causes of quenching anomalies and achieve a leap from phenomenon identification to mechanism analysis, please refer to [link to relevant documentation]. Figure 3 If the evaluation information for the uniformity of quenching is abnormal, then after step S300, the method further includes, but is not limited to, the following steps: In S400, the acquisition time information corresponding to each real-time thermal image is obtained.

[0034] Specifically, the terminal device can first obtain the acquisition time information corresponding to each real-time thermal image.

[0035] In S410, intermediate time information is determined based on multiple acquisition time information.

[0036] Specifically, after the terminal device acquires multiple acquisition time information, the terminal device can determine intermediate time information based on the multiple acquisition time information. The intermediate time information is used to describe the intermediate value among the multiple acquisition time information.

[0037] In S420, it is determined whether there are multiple abnormal thermal image information.

[0038] Specifically, after the terminal device determines the intermediate time information, the terminal device can quickly determine whether there are multiple abnormal thermal image information. Among them, abnormal thermal image information is used to describe the real-time thermal image information corresponding to the abnormal effect information.

[0039] In S430, if there are multiple abnormal thermal image information, the target thermal image information is determined based on the intermediate time information; otherwise, the abnormal thermal image information is determined as the target thermal image information.

[0040] Specifically, if there are multiple abnormal thermal image information, the terminal device can select the abnormal thermal image information whose acquisition time is closest to the median time as the target thermal image information based on the median time information; if there is only one abnormal thermal image information, the terminal device can directly determine the abnormal thermal image information as the target thermal image information. When there are multiple abnormal thermal image information, the acquisition time information corresponding to the target thermal image information is the one closest to the median time information among the multiple acquisition time information.

[0041] In S440, based on the target thermal image information, the first thermal image set information and the second thermal image set information are determined.

[0042] Specifically, after the terminal device determines the target thermal image information, it can quickly determine the first thermal image set information and the second thermal image set information by searching for real-time thermal image information adjacent to the acquisition time based on the target thermal image information. The first thermal image set information includes multiple consecutive first thermal image information, and the acquisition time information corresponding to each first thermal image information is earlier than the acquisition time information of the target thermal image information. The second thermal image set information includes multiple consecutive second thermal image information, and the acquisition time information corresponding to each second thermal image information is earlier than the acquisition time information of the target thermal image information.

[0043] In S450, the location information of the center point of the first region corresponding to each first thermal image information is determined based on the highest temperature region information of each first thermal image information, and the location information of the center point of the abnormal region is determined based on the highest temperature region information of the abnormal thermal image information, and the location information of the center point of the second region corresponding to each second thermal image information is determined based on the highest temperature region information of each second thermal image information.

[0044] Specifically, after the terminal device determines the first thermal image set information and the second thermal image set information, the terminal device can quickly determine the location information of the center point of the first region corresponding to each first thermal image set information based on the highest temperature region information corresponding to each first thermal image set information. Then, based on the highest temperature region information of the abnormal thermal image set information, the terminal device can quickly determine the location information of the center point of the abnormal region. Finally, based on the highest temperature region information corresponding to each second thermal image set information, the terminal device can quickly determine the location information of the center point of the second region corresponding to each second thermal image set information. Among these methods, existing technologies can be used to determine the center point of irregular shapes, such as finding the center point of the smallest bounding rectangle or the center of the largest inscribed circle, so they will not be elaborated here.

[0045] In S460, based on the time sequence from first to last, abnormal temperature point path information is generated according to the center point of multiple first region center point location information, abnormal region center point location information, and multiple second region center point location information.

[0046] Specifically, after the terminal device determines the location information of the center point of the first region, the terminal device can effectively generate abnormal temperature point path information based on the center points of multiple first region center point location information, abnormal region center point location information, and multiple second region center point location information in a first-to-last time sequence. The abnormal temperature point path information is used to describe the path obtained by sequentially connecting the center points of multiple first region center point location information, abnormal region center point location information, and multiple second region center point location information in a first-to-last time sequence.

[0047] In S470, based on the abnormal temperature point path information and the preset fluctuation range information, the abnormal effect information is determined to be either severe abnormal information or normal abnormal information.

[0048] Specifically, after the terminal device generates abnormal temperature point path information, the terminal device can accurately determine whether the abnormal effect information is severe abnormal information or normal abnormal information based on the abnormal temperature point path information and the preset fluctuation range information.

[0049] In some possible implementations, in order to facilitate accurate quantification of the degree of quenching anomalies, in-depth location of the root cause of the quenching anomalies, and to facilitate optimization of the aluminum profile quenching production line, the method may include, but is not limited to, the following steps before step S470: In S4701, the fluctuation range information is determined based on the location information of the center point of the abnormal area and the preset fluctuation radius information.

[0050] Specifically, the terminal device can effectively determine the fluctuation range information based on the location information of the center point of the abnormal area and the preset fluctuation radius information. The fluctuation range information is used to describe the circular area formed by the location information of the center point of the abnormal area as the center point and the fluctuation radius information as the radius. The specific value of the fluctuation radius information can be customized by the production personnel according to the specific size of the aluminum profile, for example, one-fifth of the width of the aluminum profile.

[0051] Accordingly, please refer to Figure 4 Step S470 includes, but is not limited to, the following steps: In S471, it is determined whether the path information of the abnormal temperature point is completely within the fluctuation range information.

[0052] Specifically, after the terminal device determines the fluctuation range information, the terminal device can determine whether the abnormal temperature point path information is completely within the fluctuation range information.

[0053] In S472, if the abnormal temperature point path information is completely within the fluctuation range information, the effect abnormal information is determined to be normal abnormal information; otherwise, the effect abnormal information is determined to be severe abnormal information.

[0054] Specifically, if the path information of the abnormal temperature point is completely within the fluctuation range information, it indicates that the range of abnormal quenching points is relatively consistent. Therefore, the terminal equipment can determine that the abnormal effect information is a normal abnormal information. Otherwise, it indicates that the range of abnormal quenching points is relatively unstable. Therefore, the terminal equipment can determine that the abnormal effect information is a serious abnormal information.

[0055] In some possible implementations, to facilitate production personnel in tracing and remotely analyzing the root causes of quenching anomalies, and to provide reliable data support for process optimization and quality closure, please refer to [link to relevant documentation]. Figure 5 If the abnormality information is a severe abnormality, then after step S300, the method further includes, but is not limited to, the following steps: In S500, based on the acquisition time information corresponding to each first thermal image information, the first historical processing dataset information of the production line to be inspected is obtained, and based on the acquisition time information of the abnormal thermal image information, the second historical processing data information of the production line to be inspected is obtained, and based on the acquisition time information corresponding to each second thermal image information, the third historical processing dataset information of the production line to be inspected is obtained.

[0056] Specifically, the terminal device can obtain the first historical processing dataset information of the production line under inspection based on the acquisition time information corresponding to each first thermal image information, and obtain the second historical processing data information of the production line under inspection based on the acquisition time information of the abnormal thermal image information, and obtain the third historical processing dataset information of the production line under inspection based on the acquisition time information corresponding to each second thermal image information. The first historical processing dataset information is used to describe the set of processing data of the aluminum profile quenching production line at the acquisition time information corresponding to the first thermal image information; the second historical processing data information is used to describe the processing data of the aluminum profile quenching production line at the acquisition time information of the abnormal thermal image information; and the third historical processing data information is used to describe the set of processing data of the aluminum profile quenching production line at the acquisition time information of the second thermal image information.

[0057] In S510, the first historical processing dataset information, the second historical processing dataset information, and the third historical processing dataset information are sent to the designated terminal.

[0058] Specifically, after the terminal device obtains the first historical processing dataset information, the terminal device can send the first historical processing dataset information, the second historical processing dataset information, and the third historical processing dataset information to a designated terminal, where the designated terminal can be the terminal where the production personnel are located.

[0059] The implementation principle of the online detection method based on the aluminum profile quenching production line in this application embodiment is as follows: The terminal equipment can first continuously acquire real-time thermal image information corresponding to multiple aluminum profiles to be detected based on a preset infrared thermal imager, and then perform the following processing on each real-time thermal image information: Based on the edge contour detection algorithm, multiple candidate area information and the corresponding candidate area temperature information are quickly determined. Finally, based on the multiple candidate area temperature information, quenching uniformity effect evaluation information is accurately generated, thereby realizing comprehensive quenching quality detection of the entire batch of aluminum profiles and effectively improving detection reliability.

[0060] It should be noted that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0061] Embodiments of this application also provide an online inspection system based on an aluminum profile quenching production line. For ease of explanation, only the parts relevant to this application are shown, such as... Figure 6 As shown, the system 60 includes: Real-time thermal image information acquisition module 61: used to continuously acquire real-time thermal image information corresponding to multiple aluminum profiles to be inspected based on a preset infrared thermal imager; Candidate area information determination module 62: Used to determine multiple candidate area information and the candidate area temperature information corresponding to each candidate area information based on a preset edge contour detection algorithm for each real-time thermal image information; Quenching uniformity effect evaluation information generation module 63: used to generate quenching uniformity effect evaluation information based on the temperature information of multiple candidate areas.

[0062] Optionally, the quenching uniformity effect evaluation information includes whether the effect is qualified or abnormal; the above-mentioned quenching uniformity effect evaluation information generation module 63 includes: The highest temperature area information determination submodule is used to determine the highest temperature area information and the lowest temperature area information based on the temperature information of multiple candidate areas. Maximum temperature difference information generation submodule: used to generate maximum temperature difference information based on the highest temperature area information and the lowest temperature area information; Maximum temperature difference information comparison submodule: used to compare the maximum temperature difference information corresponding to each real-time thermal image with the preset temperature difference compliance threshold information; The "Results Acceptable" submodule is used to determine the quenching uniformity effect assessment information as acceptable if the maximum temperature difference information corresponding to each real-time thermal image is less than the temperature difference compliance threshold information; otherwise, it determines the quenching uniformity effect assessment information as abnormal.

[0063] Optionally, the abnormal effect information can be classified as either severe or normal. If the quenching uniformity evaluation information is classified as abnormal, then the system 60 further includes: Acquisition Time Information Acquisition Module: Used to acquire the acquisition time information corresponding to each real-time thermal image; Intermediate time information determination module: used to determine intermediate time information based on multiple acquisition time information; Quantity judgment module: used to determine whether there are multiple abnormal thermal image information, where abnormal thermal image information is used to describe the real-time thermal image information corresponding to the abnormal effect information; Target thermal image information determination module: If there are multiple abnormal thermal image information, the target thermal image information is determined based on the intermediate time information; otherwise, the abnormal thermal image information is determined as the target thermal image information. When there are multiple abnormal thermal image information, the acquisition time information corresponding to the target thermal image information is the one closest to the intermediate time information among the multiple acquisition time information. Thermal image set information determination module: used to determine first thermal image set information and second thermal image set information based on target thermal image information. The first thermal image set information includes multiple consecutive first thermal image information, and the acquisition time information corresponding to each first thermal image information is earlier than the acquisition time information of the target thermal image information. The second thermal image set information includes multiple consecutive second thermal image information, and the acquisition time information corresponding to each second thermal image information is earlier than the acquisition time information of the target thermal image information. The module for determining the location information of the center point of the region is used to determine the location information of the center point of the first region corresponding to each first thermal image information based on the highest temperature region information of each first thermal image information, and to determine the location information of the center point of the abnormal region based on the highest temperature region information of the abnormal thermal image information, and to determine the location information of the center point of the second region corresponding to each second thermal image information based on the highest temperature region information of each second thermal image information. Abnormal temperature point path information generation module: used to generate abnormal temperature point path information based on the time sequence from first to last, according to the center point of multiple first region center point location information, abnormal region center point location information, and multiple second region center point location information; Severe Anomaly Information Determination Module: Based on the abnormal temperature point path information and preset fluctuation range information, this module determines whether the abnormal information is severe or normal.

[0064] Optionally, the system 60 also includes: Fluctuation range information determination module: used to determine fluctuation range information based on the location information of the center point of the abnormal area and the preset fluctuation radius information. The fluctuation range information describes a circular area with the location information of the center point of the abnormal area as the center point and the fluctuation radius information as the radius. Accordingly, the above-mentioned serious anomaly information determination module includes: Abnormal Temperature Point Path Information Judgment Submodule: Used to determine whether the abnormal temperature point path information is completely within the fluctuation range information; The regular anomaly information determination submodule is used to determine the effect anomaly information as regular anomaly information if the path information of the abnormal temperature point is completely within the fluctuation range information; otherwise, it is determined as severe anomaly information.

[0065] Optionally, if the abnormality information is a severe abnormality, the system 60 further includes: Historical processing dataset information acquisition module: It is used to acquire the first historical processing dataset information of the production line to be inspected based on the acquisition time information corresponding to each first thermal image information, and to acquire the second historical processing dataset information of the production line to be inspected based on the acquisition time information of abnormal thermal image information, and to acquire the third historical processing dataset information of the production line to be inspected based on the acquisition time information corresponding to each second thermal image information. Historical processing dataset information sending module: used to send the first historical processing dataset information, the second historical processing dataset information, and the third historical processing dataset information to the designated terminal.

[0066] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0067] This application also provides a terminal device, such as... Figure 7 As shown, the terminal device 70 of this embodiment includes: a processor 71, a memory 72, and a computer program 73 stored in the memory 72 and executable on the processor 71. When the processor 71 executes the computer program 73, it implements the steps described in the online detection method embodiment above, for example... Figure 1 Steps S100 to S300 are shown; or, when processor 71 executes computer program 73, it implements the functions of each module in the above-described device, for example... Figure 6 The functions of modules 61 to 63 are shown.

[0068] The terminal device 70 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device, and includes, but is not limited to, a processor 71 and a memory 72. Those skilled in the art will understand that... Figure 7 This is merely an example of terminal device 70 and does not constitute a limitation on terminal device 70. It may include more or fewer components than shown, or combine certain components, or different components. For example, terminal device 70 may also include input / output devices, network access devices, buses, etc.

[0069] The processor 71 can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.; the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0070] The memory 72 can be an internal storage unit of the terminal device 70, such as the hard disk or memory of the terminal device 70. The memory 72 can also be an external storage device of the terminal device 70, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 70. Furthermore, the memory 72 can include both internal storage units and external storage devices of the terminal device 70. The memory 72 can also store computer program 73 and other programs and data required by the terminal device 70. The memory 72 can also be used to temporarily store data that has been output or will be output.

[0071] One embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0072] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the methods, principles and structures of this application should be covered within the scope of protection of this application.

Claims

1. An online inspection method based on an aluminum profile quenching production line, characterized in that, The method includes: Based on a preset infrared thermal imager, real-time thermal image information corresponding to multiple aluminum profiles to be inspected is continuously acquired; For each of the real-time thermal image information: based on a preset edge contour detection algorithm, multiple candidate region information and the candidate region temperature information corresponding to each candidate region information are determined; Based on the temperature information of multiple candidate areas, quenching uniformity evaluation information is generated.

2. The method according to claim 1, characterized in that, The quenching uniformity evaluation information includes either satisfactory or abnormal results; the step of generating quenching uniformity evaluation information based on the temperature information of multiple candidate areas includes: Based on the temperature information of multiple candidate regions, the information of the highest temperature region and the information of the lowest temperature region are determined. Based on the information of the highest temperature region and the lowest temperature region, the maximum temperature difference information is generated; The maximum temperature difference information corresponding to each of the real-time thermal images is compared with the preset temperature difference compliance threshold information. If the maximum temperature difference information corresponding to each of the real-time thermal images is less than the temperature difference compliance threshold information, then the quenching uniformity effect evaluation information is determined to be qualified; otherwise, the quenching uniformity effect evaluation information is determined to be abnormal.

3. The method according to claim 2, characterized in that, The abnormal effect information is either severe abnormal information or normal abnormal information; if the quenching uniformity effect evaluation information is abnormal effect information, then after generating the quenching uniformity effect evaluation information based on the temperature information of multiple candidate areas, the method further includes: Obtain the acquisition time information corresponding to each of the aforementioned real-time thermal images; Based on the multiple acquisition time information, the intermediate time information is determined; Determine whether there are multiple abnormal thermal image information, wherein the abnormal thermal image information is used to describe the real-time thermal image information corresponding to the abnormal effect information; If there are multiple abnormal thermal image information, the target thermal image information is determined based on the intermediate time information; otherwise, the abnormal thermal image information is determined to be the target thermal image information. When there are multiple abnormal thermal image information, the acquisition time information corresponding to the target thermal image information is the one closest to the intermediate time information among the multiple acquisition time information. Based on the target thermal image information, a first thermal image set and a second thermal image set are determined. The first thermal image set includes multiple consecutive first thermal image information, and the acquisition time information corresponding to each first thermal image information is earlier than the acquisition time information of the target thermal image information. The second thermal image set includes multiple consecutive second thermal image information, and the acquisition time information corresponding to each second thermal image information is earlier than the acquisition time information of the target thermal image information. Based on the highest temperature region information corresponding to each of the first thermal image information, the location information of the center point of the first region corresponding to each of the first thermal image information is determined; based on the highest temperature region information of the abnormal thermal image information, the location information of the center point of the abnormal region is determined; and based on the highest temperature region information corresponding to each of the second thermal image information, the location information of the center point of the second region corresponding to each of the second thermal image information is determined. Based on the chronological order, abnormal temperature point path information is generated according to the center point of multiple first region center point location information, the abnormal region center point location information, and multiple second region center point location information. Based on the abnormal temperature point path information and the preset fluctuation range information, the abnormal effect information is determined to be either severe abnormal information or normal abnormal information.

4. The method according to claim 3, characterized in that, Before determining whether the abnormal effect information is a severe abnormality or a normal abnormality based on the abnormal temperature point path information and the preset fluctuation range information, the method further includes: Based on the location information of the center point of the abnormal region and the preset fluctuation radius information, the fluctuation range information is determined, wherein the fluctuation range information is used to describe a circular region formed with the location information of the center point of the abnormal region as the center point and the fluctuation radius information as the radius. Accordingly, determining whether the abnormal effect information is severe or normal based on the abnormal temperature point path information and the preset fluctuation range information includes: Determine whether the abnormal temperature point path information is completely within the fluctuation range information; If the abnormal temperature point path information is completely within the fluctuation range information, then the effect abnormal information is determined to be normal abnormal information; otherwise, the effect abnormal information is determined to be severe abnormal information.

5. The method according to claim 4, characterized in that, If the abnormal effect information is a severe abnormality, then after generating quenching uniformity effect evaluation information based on the temperature information of multiple candidate areas, the method further includes: Based on the acquisition time information corresponding to each of the first thermal image information, the first historical processing dataset information of the production line to be inspected is obtained, and based on the acquisition time information of the abnormal thermal image information, the second historical processing data information of the production line to be inspected is obtained, and based on the acquisition time information corresponding to each of the second thermal image information, the third historical processing dataset information of the production line to be inspected is obtained. Send the first historical processing dataset information, the second historical processing dataset information, and the third historical processing dataset information to the designated terminal.

6. An online inspection system based on an aluminum profile quenching production line, characterized in that, The system includes: Real-time thermal image information acquisition module: used to continuously acquire real-time thermal image information of multiple aluminum profiles to be inspected based on a preset infrared thermal imager; Candidate region information determination module: used to determine multiple candidate region information and the candidate region temperature information corresponding to each candidate region information based on a preset edge contour detection algorithm for each of the real-time thermal image information; Quenching uniformity effect evaluation information generation module: used to generate quenching uniformity effect evaluation information based on the temperature information of multiple candidate areas.

7. The system according to claim 6, characterized in that, The quenching uniformity effect evaluation information includes either qualified or abnormal effect information; the quenching uniformity effect evaluation information generation module includes: The highest temperature area information determination submodule is used to determine the highest temperature area information and the lowest temperature area information based on the temperature information of multiple candidate areas. Maximum temperature difference information generation submodule: used to generate maximum temperature difference information based on the highest temperature region information and the lowest temperature region information; Maximum temperature difference information comparison submodule: used to compare the maximum temperature difference information corresponding to each of the real-time thermal images with the preset temperature difference compliance threshold information; The submodule for determining the effectiveness qualification information is used to determine the quenching uniformity effect evaluation information as effective qualification information if the maximum temperature difference information corresponding to each of the real-time thermal images is less than the temperature difference compliance threshold information; otherwise, it determines the quenching uniformity effect evaluation information as effective abnormal information.

8. 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 5.

9. 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 5.

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