Intelligent inspection method and system based on code scanning

Abstract

The invention discloses an intelligent inspection method and system based on code scanning. The method comprises the following steps: scanning a two-dimensional code of a to-be-inspected area to obtain detailed information of each device in the area; analyzing the detailed information to determine parameter data of each device, and screening the parameter data to determine characteristic parameter indexes with abnormal risks; evaluating the operation state of each device based on the characteristic parameter index to determine the state evaluation value of each device, and determining the inspection emergency degree of each device according to the state evaluation value; and making an inspection plan based on the inspection emergency degree of each device, and inspecting each device in the to-be-inspected area. According to the invention, the detailed information of each device in the to-be-inspected area is accurately obtained by using the two-dimensional code recognition technology, the inspection emergency degree of each device is determined through subsequent analysis and processing of the detailed information, and finally the inspection plan is made according to the inspection emergency degree of each device, so that the device is inspected quickly and accurately, and the inspection efficiency is improved. The equipment inspection efficiency is improved, and the occurrence of equipment abnormity is reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent inspection technology, and in particular to an intelligent inspection method and system based on code scanning. Background Art

[0002] Inspection refers to a series of steps and procedures for regular inspection, evaluation and maintenance of equipment. The purpose of inspection is to ensure that the equipment operates normally, safely and reliably, and to detect and deal with potential problems as early as possible to reduce the occurrence of failures and improve the reliability and availability of equipment.

[0003] However, traditional inspection methods usually rely on paper records or simple spreadsheets, and the efficiency of information acquisition and transmission is low, resulting in delayed transmission and processing of inspection information, affecting the timely understanding and processing of equipment status. In addition, due to the different urgency of potential risks in equipment and the different resources required, traditional inspection methods cannot quickly formulate inspection plans, nor can they prioritize maintenance of equipment with serious risks, resulting in the equipment problem not being handled in a timely manner, ultimately causing equipment abnormalities. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides an intelligent inspection method and system based on code scanning, comprising:

[0005] Scan the QR code of the area to be inspected to obtain detailed information corresponding to each device in the area to be inspected;

[0006] Analyze the detailed information of each device, determine the parameter data of each device, and screen the parameter data to determine the characteristic parameter indicators with abnormal risks;

[0007] Evaluate the operating status of each device based on the characteristic parameter index, determine the status evaluation value of each device, and determine the inspection urgency of each device based on the status evaluation value;

[0008] An inspection plan is developed based on the inspection urgency of each device, and each device in the inspection area is inspected according to the inspection plan.

[0009] Furthermore, the scanning of the QR code of the area to be inspected to obtain detailed information corresponding to each device in the area to be inspected includes:

[0010] Scan the QR code of the area to be inspected with a mobile device to obtain detailed information corresponding to each device in the area to be inspected;

[0011] The detailed information of each device is uploaded to the server, which decrypts the detailed information of each device and pre-processes the detailed information.

[0012] Furthermore, the detailed information of each device is parsed to determine the parameter data of each device, and the parameter data is screened to determine the characteristic parameter indicators with abnormal risks, including:

[0013] Parse the detailed information of each device into several groups of parameter data based on parameter type, and analyze the abnormal risk value of each group of parameter data;

[0014] Parameter data with abnormal risk values ​​exceeding the preset threshold are screened out and determined as characteristic parameter indicators with abnormal risks in each device.

[0015] Furthermore, the analysis of the abnormal risk of each group of parameter data includes:

[0016] The abnormal data in each group of parameter data are screened out through the abnormal screening model, and the duration of the abnormal data and the number of abnormal data in each group of parameter data are determined;

[0017] The abnormal risk value of each set of parameter data is calculated based on the duration of the abnormal data and the number of abnormal data.

[0018] Furthermore, the calculation formula of the abnormal risk value of the parameter data is as follows:

[0019] F=α*exp(D-D0)+β*exp(N-N0),

[0020] Among them, F represents the abnormal risk value of the parameter data, α represents the time coefficient, D represents the duration of the abnormal data, D0 represents the preset time length, β represents the quantity coefficient, N represents the number of abnormal data, N0 represents the preset number, and exp represents the natural exponential function.

[0021] Further, the operating status of each device is evaluated based on the characteristic parameter index to determine the status evaluation value of each device, including:

[0022] Obtain the abnormal risk value of the characteristic parameter indicator corresponding to each device, and calculate the sum of the abnormal risk values ​​of the characteristic parameter indicator corresponding to each device, and use the sum as the risk value of the operating state of each device;

[0023] Obtain the number of characteristic parameter indicators corresponding to each device, and calculate the average number of characteristic parameter indicators of all devices;

[0024] Calculate the difference between the number of characteristic parameter indicators corresponding to each device and the average number of characteristic parameter indicators of all devices, and use the difference as the evaluation coefficient of the operating status of each device;

[0025] The risk value of each equipment's operating status is multiplied by the assessment coefficient to obtain the status assessment value of each equipment.

[0026] Furthermore, the step of determining the inspection urgency of each device according to the status evaluation value includes:

[0027] Preset inspection urgency - status assessment value interval correspondence relationship, inspection urgency - status assessment value interval correspondence relationship For each status assessment value interval, a corresponding inspection urgency is associated;

[0028] The state evaluation value is obtained, and based on the mapping relationship between the state evaluation value interval to which the state evaluation value belongs and the inspection urgency-state evaluation value interval correspondence relationship, the inspection urgency corresponding to the state evaluation value interval is selected as the inspection urgency of each device.

[0029] Furthermore, the inspection plan is formulated based on the inspection urgency of each device, including:

[0030] Sort the inspection urgency of each device from the largest to the smallest, and set the sequence as the inspection order of each device in the area to be inspected;

[0031] Calculate the sum of the inspection urgency of all devices, and calculate the ratio of the inspection urgency of each device to the sum of the inspection urgency of all devices, and set the ratio as the resource allocation ratio of each device in the area to be inspected;

[0032] The inspection plan for each device is composed of the inspection sequence and resource allocation ratio of each device.

[0033] The present invention also provides an intelligent inspection system based on code scanning, comprising:

[0034] The acquisition module is used to scan the QR code of the area to be inspected and obtain the detailed information corresponding to each device in the area to be inspected;

[0035] The parsing module is used to parse the detailed information of each device, determine the parameter data of each device, and screen the parameter data to determine the characteristic parameter indicators with abnormal risks;

[0036] An evaluation module is used to evaluate the operating status of each device based on the characteristic parameter index, determine the status evaluation value of each device, and determine the inspection urgency of each device according to the status evaluation value;

[0037] The formulation module is used to formulate an inspection plan based on the inspection urgency of each device, and inspect each device in the inspection area according to the inspection plan.

[0038] Compared with the prior art, the intelligent inspection method and system based on code scanning in the embodiment of the present invention has the following beneficial effects:

[0039] The present invention utilizes two-dimensional code recognition technology to accurately obtain detailed information of each device in the area to be inspected, and determines the inspection urgency of each device through subsequent analysis and processing of the detailed information. Finally, an inspection plan is formulated based on the inspection urgency of each device to conduct rapid and accurate inspections of the equipment, thereby improving the efficiency of equipment inspections and reducing the occurrence of equipment abnormalities. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a schematic diagram of the process structure of the intelligent inspection method based on code scanning in an embodiment of the present invention;

[0041] Figure 2 It is a schematic diagram of the composition of an intelligent inspection system based on code scanning in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0043] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship are the orientation or position relationship shown in the accompanying drawings, which are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0044] The terms "second" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, a feature defined with "second" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "multiple" means two or more.

[0045] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0046] like Figure 1As shown, in an embodiment of the present application, a smart inspection method based on code scanning is provided, including: S100: scanning the QR code of the area to be inspected, and obtaining detailed information corresponding to each device in the area to be inspected; S200: parsing the detailed information of each device, determining the parameter data of each device, and screening the parameter data to determine the characteristic parameter indicators with abnormal risks; S300: evaluating the operating status of each device based on the characteristic parameter indicators, determining the status evaluation value of each device, and determining the inspection urgency of each device according to the status evaluation value; S400: formulating an inspection plan based on the inspection urgency of each device, and inspecting each device in the area to be inspected according to the inspection plan.

[0047] Furthermore, the present invention utilizes QR code recognition technology to accurately obtain detailed information of each device in the area to be inspected, and determines the inspection urgency of each device through subsequent analysis and processing of the detailed information. Finally, an inspection plan is formulated based on the inspection urgency of each device to conduct rapid and accurate inspections of the equipment, thereby improving the efficiency of equipment inspections and reducing the occurrence of equipment abnormalities.

[0048] In an embodiment of the present application, a smart inspection method based on code scanning is provided, wherein the QR code of the area to be inspected is scanned to obtain detailed information corresponding to each device in the area to be inspected, including: scanning the QR code of the area to be inspected by a mobile device to obtain detailed information corresponding to each device in the area to be inspected; uploading the detailed information of each device to a server, and the server decrypts the detailed information of each device and pre-processes the detailed information.

[0049] Specifically, the inspector uses a mobile device (such as a smartphone or tablet) to scan the QR code of the area to be inspected. The QR code of each device contains detailed information about all the devices in the area. After scanning the QR code, the detailed information of the corresponding device is obtained. The mobile device uploads the obtained device detailed information to the server. After receiving the uploaded device detailed information, the server decrypts and preprocesses it to ensure that subsequent data analysis and application can be based on high-quality data. In this way, the inspector can quickly obtain detailed information about the device through the mobile device, and the server can uniformly manage, decrypt and preprocess this information, thereby providing basic support for subsequent data analysis, equipment management and maintenance to improve the accuracy and reliability of the data, while also simplifying the operating procedures of the inspectors and improving work efficiency.

[0050] In an embodiment of the present application, a smart inspection method based on code scanning is provided, which parses detailed information of each device, determines parameter data of each device, and screens the parameter data to determine characteristic parameter indicators with abnormal risks, including: parsing the detailed information of each device into several groups of parameter data based on parameter type, and analyzing the abnormal risk value of each group of parameter data; screening out parameter data with abnormal risk values ​​exceeding a preset threshold, and determining them as characteristic parameter indicators with abnormal risks in each device.

[0051] Specifically, based on the parameter type, the uploaded device detailed information is parsed and decomposed into several groups of parameter data. For each group of parameter data, the server analyzes the abnormal risk value; for those parameter data whose abnormal risk values ​​exceed the preset threshold, the server screens them out and determines them as characteristic parameter indicators with abnormal risks in each device. These characteristic parameter indicators are key parameters closely related to changes in device status and have important indicative significance for the operating status and safety of the device. Through the above steps, the server can perform intelligent analysis and processing on the device after receiving the detailed information, thereby realizing real-time monitoring of the device status and rapid identification of abnormal risks, helping to timely discover potential problems of the device, reduce the risk of equipment abnormalities, and provide important data support for subsequent maintenance and management work.

[0052] In an embodiment of the present application, a smart inspection method based on code scanning is provided, and the analysis of the abnormal risk of each group of parameter data includes: screening out abnormal data in each group of parameter data through an abnormal screening model, and determining the duration of the abnormal data and the number of abnormal data in each group of parameter data; calculating the abnormal risk value of each group of parameter data based on the duration of the abnormal data and the number of abnormal data.

[0053] Specifically, through the abnormal screening model, each set of parameter data is analyzed to screen out the abnormal data. Based on the deep learning model, the model identifies data points that are significantly deviated from the normal state and marks them as abnormal data. For the abnormal data in each set of parameter data, the server can determine the duration of the abnormal data and the number of abnormal data. Based on the duration of the abnormal data and the number of abnormal data, the abnormal risk value of each set of parameter data is calculated. The abnormal risk value is a comprehensive evaluation indicator that reflects the degree of influence of abnormal data on the stability and safety of the equipment status. Through this intelligent abnormal data analysis and abnormal risk value calculation, the stability and safety of the equipment status can be evaluated more accurately, which helps to timely discover abnormal conditions of the equipment and provide important data support for subsequent maintenance decisions and risk management.

[0054] In an embodiment of the present application, a smart inspection method based on code scanning is provided, and the calculation formula of the abnormal risk value of the parameter data is as follows:

[0055] F=α*exp(D-D0)+β*exp(N-N0),

[0056] Among them, F represents the abnormal risk value of parameter data, α represents the time coefficient, D represents the duration of abnormal data, D0 represents the preset time length, β represents the quantity coefficient, N represents the number of abnormal data, N0 represents the preset number, and exp represents the natural exponential function.

[0057] In an embodiment of the present application, a smart inspection method based on code scanning is provided, which evaluates the operating status of each device based on characteristic parameter indicators and determines the status evaluation value of each device, including: obtaining the abnormal risk value of the characteristic parameter indicator corresponding to each device, and calculating the sum of the abnormal risk values ​​of the characteristic parameter indicators corresponding to each device, and using the sum as the risk value of the operating status of each device; obtaining the number of characteristic parameter indicators corresponding to each device, and calculating the average number of characteristic parameter indicators of all devices; calculating the difference between the number of characteristic parameter indicators corresponding to each device and the average number of characteristic parameter indicators of all devices, and using the difference as the evaluation coefficient of the operating status of each device; multiplying the risk value of the operating status of each device by the evaluation coefficient to obtain the status evaluation value of each device.

[0058] Specifically, for each device, obtain the abnormal risk value of its characteristic parameter index, and add them up to obtain the sum of the abnormal risk values ​​of the characteristic parameter index of each device; obtain the number of characteristic parameter indicators corresponding to each device, and calculate the average number of characteristic parameter indicators of all devices; calculate the difference between the number of characteristic parameter indicators corresponding to each device and the average number of characteristic parameter indicators of all devices, and use the difference as the evaluation coefficient of the operating status of each device; multiply the risk value of the operating status of each device by the evaluation coefficient to obtain the status evaluation value of each device. This method helps to comprehensively evaluate the operating status of the equipment, combines the abnormal risk value and the number of characteristic parameter indicators, and more comprehensively understands the status and risk level of the equipment, provides important reference for equipment maintenance and management, and helps optimize maintenance plans and reduce potential risks.

[0059] In an embodiment of the present application, a smart inspection method based on code scanning is provided, wherein the inspection urgency of each device is determined according to the status evaluation value, including: presetting a corresponding relationship between inspection urgency and status evaluation value interval, wherein each status evaluation value interval is associated with a corresponding inspection urgency; obtaining the status evaluation value, and based on a mapping relationship between the status evaluation value interval to which the status evaluation value belongs within the corresponding relationship between inspection urgency and status evaluation value interval, selecting the inspection urgency corresponding to the status evaluation value interval as the inspection urgency of each device.

[0060] Specifically, according to the actual situation, a table of inspection urgency-status assessment value interval correspondence is established. This table can associate the interval division of the status assessment value with the corresponding inspection urgency. For example, the status assessment value interval of 0-10 corresponds to low urgency, 11-20 corresponds to medium urgency, 21-30 corresponds to high urgency, and so on. For each device, its status assessment value is obtained, and based on the status assessment value interval to which the status assessment value belongs, the corresponding mapping relationship is found in the inspection urgency-status assessment value interval correspondence relationship. According to the mapping relationship, the inspection urgency corresponding to the status assessment value interval is selected as the inspection urgency of each device. Through this method, the inspection urgency can be dynamically determined according to the status assessment value of the device, thereby realizing the optimal configuration of inspection resources and investing more resources in devices with poor status to reduce potential risks and improve the reliability of equipment.

[0061] In an embodiment of the present application, a smart inspection method based on code scanning is provided, wherein an inspection plan is formulated based on the inspection urgency of each device, including: sorting the inspection urgency of each device from large to small, and setting the sequence as the inspection order of each device in the area to be inspected; calculating the sum of the inspection urgency of all devices, and calculating the ratio of the inspection urgency of each device to the sum of the inspection urgency of all devices, and setting the ratio as the resource allocation ratio of each device in the area to be inspected; and forming an inspection plan for each device by the inspection order and resource allocation ratio of each device.

[0062] Specifically, the inspection urgency of each device is sorted from large to small to obtain an equipment sequence, which will be used as the inspection order of each device in the inspection area; the sum of the inspection urgency of all devices is calculated, and then the ratio of the inspection urgency of each device to the sum of the inspection urgency of all devices is calculated, and the ratio is set as the resource allocation ratio of each device in the inspection area; the inspection order and resource allocation ratio of each device constitute the inspection plan of each device, and according to the order of the equipment and the resource allocation ratio, the inspection order and the allocated inspection resources of each device are determined to formulate the final inspection plan. Through this method, inspection resources can be reasonably allocated according to the inspection urgency of the equipment, the inspection plan can be optimized, and more resources can be invested in equipment with high urgency to reduce potential risks and improve the reliability of equipment.

[0063] like Figure 2 As shown, in an embodiment of the present application, a smart inspection system based on code scanning is provided, including: an acquisition module, used to scan the QR code of the area to be inspected, and obtain detailed information corresponding to each device in the area to be inspected; a parsing module, used to parse the detailed information of each device, determine the parameter data of each device, and screen the parameter data to determine the characteristic parameter indicators with abnormal risks; an evaluation module, used to evaluate the operating status of each device based on the characteristic parameter indicators, determine the status evaluation value of each device, and determine the inspection urgency of each device according to the status evaluation value; a formulation module, used to formulate an inspection plan based on the inspection urgency of each device, and inspect each device in the area to be inspected according to the inspection plan.

[0064] In summary, the embodiments of the present invention provide an intelligent inspection method and system based on code scanning, which includes: scanning the QR code of the area to be inspected to obtain detailed information of each device in the area; analyzing the detailed information to determine the parameter data of each device, and screening the parameter data to determine the characteristic parameter index with abnormal risk; evaluating the operating status of each device based on the characteristic parameter index to determine the status evaluation value of each device, and determining the inspection urgency of each device according to the status evaluation value; formulating an inspection plan based on the inspection urgency of each device, and inspecting each device in the area to be inspected. The present invention uses QR code recognition technology to accurately obtain detailed information of each device in the area to be inspected, and through subsequent analysis and processing of the detailed information, determines the inspection urgency of each device, and finally formulates an inspection plan based on the inspection urgency of each device, so as to quickly and accurately inspect the equipment, thereby improving the efficiency of equipment inspection and reducing the occurrence of equipment abnormalities.

[0065] Finally, it should be noted that it is obvious that those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0066] The above is only an example of implementation of the present invention, but it cannot be used to limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be regarded as falling within the scope of protection of the present invention and being restricted. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0067] The term "comprises" or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that includes a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0068] So far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings, but it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0069] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. An intelligent inspection method based on code scanning, characterized in that: include: Scan the QR code of the area to be inspected to obtain detailed information corresponding to each device in the area to be inspected; Analyze the detailed information of each device, determine the parameter data of each device, and screen the parameter data to determine the characteristic parameter indicators with abnormal risks; Evaluate the operating status of each device based on the characteristic parameter index, determine the status evaluation value of each device, and determine the inspection urgency of each device based on the status evaluation value; An inspection plan is developed based on the inspection urgency of each device, and each device in the inspection area is inspected according to the inspection plan.

2. According to claim 1, the intelligent inspection method based on code scanning is characterized in that: Scan the QR code of the area to be inspected to obtain detailed information corresponding to each device in the area to be inspected, including: Scan the QR code of the area to be inspected with a mobile device to obtain detailed information corresponding to each device in the area to be inspected; The detailed information of each device is uploaded to the server, which decrypts the detailed information of each device and pre-processes the detailed information.

3. The intelligent inspection method based on code scanning according to claim 2 is characterized in that: The detailed information of each device is parsed to determine the parameter data of each device, and the parameter data is screened to determine the characteristic parameter indicators with abnormal risks, including: Parse the detailed information of each device into several groups of parameter data based on parameter type, and analyze the abnormal risk value of each group of parameter data; Parameter data with abnormal risk values ​​exceeding the preset threshold are screened out and determined as characteristic parameter indicators with abnormal risks in each device.

4. The intelligent inspection method based on code scanning according to claim 3 is characterized in that: The analysis of abnormal risks of each group of parameter data includes: The abnormal data in each group of parameter data are screened out through the abnormal screening model, and the duration of the abnormal data and the number of abnormal data in each group of parameter data are determined; The abnormal risk value of each set of parameter data is calculated based on the duration of the abnormal data and the number of abnormal data.

5. The intelligent inspection method based on code scanning according to claim 4 is characterized in that: The calculation formula of the abnormal risk value of the parameter data is as follows: F=α*exp(D-D0)+β*exp(N-N0), Among them, F represents the abnormal risk value of parameter data, α represents the time coefficient, D represents the duration of abnormal data, D0 represents the preset time length, β represents the quantity coefficient, N represents the number of abnormal data, N0 represents the preset number, and exp represents the natural exponential function.

6. The intelligent inspection method based on code scanning according to claim 3 is characterized in that: The step of evaluating the operating status of each device based on the characteristic parameter index to determine the status evaluation value of each device includes: Obtain the abnormal risk value of the characteristic parameter indicator corresponding to each device, and calculate the sum of the abnormal risk values ​​of the characteristic parameter indicator corresponding to each device, and use the sum as the risk value of the operating state of each device; Obtain the number of characteristic parameter indicators corresponding to each device, and calculate the average number of characteristic parameter indicators of all devices; Calculate the difference between the number of characteristic parameter indicators corresponding to each device and the average number of characteristic parameter indicators of all devices, and use the difference as the evaluation coefficient of the operating status of each device; The risk value of each equipment's operating status is multiplied by the assessment coefficient to obtain the status assessment value of each equipment.

7. The intelligent inspection method based on code scanning according to claim 5 is characterized in that: Determining the inspection urgency of each device according to the status evaluation value includes: Preset inspection urgency - status assessment value interval correspondence relationship, inspection urgency - status assessment value interval correspondence relationship For each status assessment value interval, a corresponding inspection urgency is associated; The state evaluation value is obtained, and based on the mapping relationship between the state evaluation value interval to which the state evaluation value belongs and the inspection urgency-state evaluation value interval correspondence relationship, the inspection urgency corresponding to the state evaluation value interval is selected as the inspection urgency of each device.

8. The intelligent inspection method based on code scanning according to claim 5 is characterized in that: The inspection plan is formulated based on the inspection urgency of each device, including: Sort the inspection urgency of each device from the largest to the smallest, and set the sequence as the inspection order of each device in the area to be inspected; Calculate the sum of the inspection urgency of all devices, and calculate the ratio of the inspection urgency of each device to the sum of the inspection urgency of all devices, and set the ratio as the resource allocation ratio of each device in the area to be inspected; The inspection plan for each device is composed of the inspection sequence and resource allocation ratio of each device.

9. An intelligent inspection system based on code scanning, characterized in that: include: The acquisition module is used to scan the QR code of the area to be inspected and obtain the detailed information corresponding to each device in the area to be inspected; The parsing module is used to parse the detailed information of each device, determine the parameter data of each device, and screen the parameter data to determine the characteristic parameter indicators with abnormal risks; An evaluation module is used to evaluate the operating status of each device based on the characteristic parameter index, determine the status evaluation value of each device, and determine the inspection urgency of each device according to the status evaluation value; The formulation module is used to formulate an inspection plan based on the inspection urgency of each device, and inspect each device in the inspection area according to the inspection plan.

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