Equipment data management method and system based on industrial Internet of Things

Abstract

The invention discloses an equipment data management method and system based on the industrial Internet of Things, and belongs to the field of the industrial Internet of Things. Equipment operation data obtained in real time is imported into an equipment fatigue analysis strategy for equipment operation fatigue analysis; and importing the obtained product quality data of equipment production into a product production quality analysis strategy for equipment production quality analysis, and importing the obtained equipment operation fatigue analysis result and the equipment production quality analysis result into a production speed analysis model for production speed analysis. According to the method, the obtained equipment operation data are comprehensively analyzed to estimate the operation fatigue condition of the equipment, and meanwhile, the equipment production quality analysis result is considered, so that the suitable production speed of the equipment is accurately estimated; and the production safety of the equipment is improved.

Description

Technical Field

[0001] The present invention belongs to the field of industrial Internet of Things, and specifically relates to a device data management method and system based on the industrial Internet of Things. Background Art

[0002] Industrial Internet of Things (IIoT) refers to the application of IoT technology in the field of industrial production. It integrates sensors, smart devices, networks, big data analysis and other technologies into the industrial production process to achieve real-time monitoring, data collection, intelligent analysis and optimization control of equipment. It is a new industrial form that extends the concept of IoT to the industrial field, uses advanced network technology to connect industrial equipment, collects and processes data, and realizes the intelligentization, automation and efficiency of the production process.

[0003] In the process of equipment production data management, the production speed of the equipment is mostly set in advance. During the production process, it is impossible to comprehensively analyze the acquired equipment operation data to predict the equipment operation fatigue, and thus it is impossible to take into account the equipment production quality analysis results, resulting in the inability to accurately estimate the suitable production speed of the equipment, causing the equipment to be at an inappropriate production speed, thereby reducing the safety of equipment production. Most of the above problems exist in the existing technologies. In order to solve the problems raised by this background technology, the present application designs an equipment data management method and system based on the industrial Internet of Things. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes an equipment data management method and system based on industrial Internet of Things.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: In the first aspect, a device data management method based on industrial Internet of Things comprises the following specific steps:

[0006] Obtain equipment operation data and product quality data produced by the equipment in real time through the Internet of Things gateway, and transmit them to the cloud platform in real time;

[0007] Import the real-time acquired equipment operation data into the equipment fatigue analysis strategy to conduct equipment operation fatigue analysis;

[0008] Import the acquired product quality data produced by the equipment into the product production quality analysis strategy to conduct equipment production quality analysis;

[0009] Import the acquired equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis;

[0010] The production of each production equipment is adjusted according to the production speed obtained by analysis.

[0011] It should be noted that, as a preferred technical solution for the device data management method based on the industrial Internet of Things, the specific steps of obtaining the device operation data and the product quality data produced by the device in real time through the Internet of Things gateway and transmitting them to the cloud platform in real time are:

[0012] S11, collecting the jitter frequency and jitter amplitude data of the device through the data collection terminal, and obtaining the operating temperature and operating power data of the device at the same time, and storing them in the first storage component;

[0013] S12, collecting image data of each functional component during the operation of the device through the image collection terminal, and storing the image data in the second storage component;

[0014] S13, collecting product quality production data during the operation of the equipment through the product quality collection terminal, and storing it in the third storage component;

[0015] S14. Transmit the collected data to the cloud platform in real time through the Internet of Things.

[0016] It should be noted here that as a preferred technical solution for the device data management method based on the industrial Internet of Things, the importing of the real-time acquired device operation data into the device fatigue analysis strategy for device operation fatigue analysis includes the following specific steps:

[0017] S21, obtaining the equipment operation jitter frequency and jitter amplitude data within the set evaluation period, and obtaining the equipment operation temperature and operation power data within the set evaluation period, and importing the obtained equipment operation jitter frequency and jitter amplitude data within the set evaluation period into the equipment jitter abnormal value calculation formula to calculate the equipment jitter abnormal value, wherein the equipment jitter abnormal value calculation formula is: Where N is the number of device jitters within the set evaluation period, ki is the jitter amplitude of the i-th device jitter within the set evaluation period, and kmax is the maximum value of the safe jitter amplitude range;

[0018] Through this step: Comprehensively analyze the operating jitter frequency and jitter amplitude data to understand the jitter health of the device during operation;

[0019] S22, obtaining the equipment operating temperature and operating power data within the set evaluation period and the calculated equipment jitter abnormality value, and importing them into the equipment operation fatigue value calculation formula to calculate the equipment operation fatigue value, wherein the equipment operation fatigue value calculation formula is: Wherein, a is the temperature ratio coefficient, T is the set evaluation period, Tt is the equipment operating temperature at time t, Tm is the median value of the temperature safety range, Tmax is the maximum value of the temperature safety range, Tmin is the minimum value of the temperature safety range, Pt is the equipment operating power at time t, Pm is the median value of the equipment operating power safety range, Pmax is the maximum value of the equipment operating power safety range, Pmin is the minimum value of the equipment operating power safety range, dt is the time integral, and exp() is the exponential power of the natural constant e;

[0020] Through this step: the operation fatigue of the equipment is comprehensively analyzed through the equipment operation temperature, operation power data and the calculated equipment jitter abnormal value, and the operation fatigue of the equipment is accurately evaluated;

[0021] S23, obtaining image data of each functional component during the operation of the device, and importing the obtained image data of each functional component into a shape variable calculation formula to calculate the shape variable of each functional component, wherein the shape variable calculation formula is: S() is the area of ​​the image, As is the real-time image contour data of the functional component, Bs is the initial image contour data of the functional component, and the obtained deformation variables of each functional component are substituted into the calculation formula of the fatigue value of the functional component to calculate the fatigue value of the functional component, wherein the calculation formula of the fatigue value of the functional component is: Where, M is the number of functional components, Hj is the deformation variable of the jth functional component, and cj is the proportion coefficient of the jth functional component;

[0022] Through this step: a comprehensive analysis of the deformation of each functional component of the equipment is conducted;

[0023] S24. Obtain the calculated equipment operation fatigue value and functional component fatigue value, and substitute them into the equipment fatigue analysis value calculation formula to calculate the equipment fatigue analysis value, wherein the equipment fatigue analysis value calculation formula is: Y=Ysb+Yg.

[0024] It should be noted here that as a preferred technical solution for the equipment data management method based on the industrial Internet of Things, the importing of the acquired product quality data produced by the equipment into the product production quality analysis strategy for equipment production quality analysis includes the following specific steps:

[0025] S31. Acquire product quality production data during the operation of the equipment, where the product quality production data includes product yield rate data and production speed data;

[0026] S32, importing the yield rate data and the production speed data into the equipment production quality analysis value calculation formula to calculate the equipment production quality analysis value, wherein the equipment production quality analysis value calculation formula is: Among them, P is the yield rate and vc is the production speed data.

[0027] It should be noted here that, as a preferred technical solution for the equipment data management method based on the industrial Internet of Things, the importing of the acquired equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model for production speed analysis includes the following specific contents:

[0028] S41. Obtain the calculated equipment fatigue analysis value and equipment production quality analysis value and substitute them into the production overall abnormal value calculation formula to calculate the production overall abnormal value, wherein the production overall abnormal value calculation formula is: Where b is the equipment fatigue analysis ratio;

[0029] S42, obtain the current equipment production speed and the calculated overall production abnormal value and substitute them into the required production speed calculation formula to calculate the required production speed of the equipment, wherein the required production speed calculation formula is: Where Za is the set standard value of overall production abnormality, and ln() is the logarithm with the natural constant e as the base.

[0030] It should be noted that, as a preferred technical solution of the device data management method based on the industrial Internet of Things, the production of each production device is adjusted according to the production speed obtained by analysis, including the following specific contents:

[0031] Obtain the calculated required production speed of each device, and adjust the production speed of the device to the required production speed.

[0032] In the second aspect, an equipment data management system based on the industrial Internet of Things is implemented based on the above-mentioned equipment data management method based on the industrial Internet of Things, and specifically includes a data acquisition module, a fatigue analysis module, a production quality analysis module, a production speed analysis module and a production speed adjustment module, wherein the data acquisition module is used to obtain equipment operation data and product quality data produced by the equipment in real time through the Internet of Things gateway, and transmit them to the cloud platform in real time;

[0033] The fatigue analysis module is used to import the equipment operation data acquired in real time into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis;

[0034] The production quality analysis module is used to import the acquired product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis;

[0035] The production speed analysis module is used to import the acquired equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis;

[0036] The production speed adjustment module is used to adjust the production of each production equipment according to the production speed obtained by analysis;

[0037] It also includes the control module, which is used for a data acquisition module, a fatigue analysis module, a production quality analysis module, a production speed analysis module and a production speed adjustment module.

[0038] In a third aspect, an electronic device includes: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0039] The processor executes the above-mentioned device data management method based on industrial Internet of Things by calling the computer program stored in the memory.

[0040] In a fourth aspect, a computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned device data management method based on industrial Internet of Things.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention obtains equipment operation data and product quality data produced by the equipment in real time through the Internet of Things, transmits them to the cloud platform in real time, imports the equipment operation data obtained in real time into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis, imports the obtained product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis, imports the obtained equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis, and adjusts the production of each production equipment according to the production speed obtained from the analysis. The present invention first comprehensively analyzes the obtained equipment operation data to predict the equipment operation fatigue situation, while taking into account the equipment production quality analysis results to accurately predict the suitable production speed for the equipment, thereby improving the safety of equipment production. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a schematic diagram of the overall process of the device data management method based on the industrial Internet of Things of the present invention;

[0043] Figure 2 This is a schematic diagram of step S2 of the device data management method based on the industrial Internet of Things of the present invention;

[0044] Figure 3 It is a schematic diagram of the overall framework of the equipment data management system based on the industrial Internet of Things of the present invention. DETAILED DESCRIPTION

[0045] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0046] Example 1

[0047] To solve the technical problem raised in the background technology: in the process of equipment production data management, the production speed of the equipment is mostly set in advance, and it is impossible to comprehensively analyze the acquired equipment operation data during the production process to estimate the equipment operation fatigue, and thus it is impossible to take into account the equipment production quality analysis results, which leads to the inability to accurately estimate the production speed suitable for the equipment, resulting in the equipment being at an inappropriate production speed, thereby reducing the safety of equipment production; the present invention provides a preferred embodiment: as Figure 1-Figure 2 As shown, the device data management method based on the industrial Internet of Things includes the following specific steps:

[0048] S1. Obtain equipment operation data and product quality data produced by the equipment in real time through the Internet of Things gateway, and transmit them to the cloud platform in real time;

[0049] In this embodiment, the specific steps of obtaining the equipment operation data and the product quality data produced by the equipment in real time through the Internet of Things gateway and transmitting them to the cloud platform in real time are as follows:

[0050] S11, collecting the jitter frequency and jitter amplitude data of the device through the data collection terminal, and obtaining the operating temperature and operating power data of the device at the same time, and storing them in the first storage component;

[0051] S12, collecting image data of each functional component during the operation of the device through the image collection terminal, and storing the image data in the second storage component;

[0052] S13, collecting product quality production data during the operation of the equipment through the product quality collection terminal, and storing it in the third storage component;

[0053] S14, transmitting various collected data to the cloud platform in real time through the Internet of Things;

[0054] S2. Importing the real-time acquired equipment operation data into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis;

[0055] In this embodiment, the process of importing the real-time acquired equipment operation data into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis includes the following specific steps:

[0056] S21, obtaining the equipment operation jitter frequency and jitter amplitude data within the set evaluation period, and obtaining the equipment operation temperature and operation power data within the set evaluation period, and importing the obtained equipment operation jitter frequency and jitter amplitude data within the set evaluation period into the equipment jitter abnormal value calculation formula to calculate the equipment jitter abnormal value, wherein the equipment jitter abnormal value calculation formula is: Where N is the number of device jitters within the set evaluation period, ki is the jitter amplitude of the i-th device jitter within the set evaluation period, and kmax is the maximum value of the safe jitter amplitude range;

[0057] Through this step: Comprehensively analyze the operating jitter frequency and jitter amplitude data to understand the jitter health of the device during operation;

[0058] S22, obtaining the equipment operating temperature and operating power data within the set evaluation period and the calculated equipment jitter abnormality value, and importing them into the equipment operation fatigue value calculation formula to calculate the equipment operation fatigue value, wherein the equipment operation fatigue value calculation formula is: Wherein, a is the temperature ratio coefficient, T is the set evaluation period, Tt is the equipment operating temperature at time t, Tm is the median value of the temperature safety range, Tmax is the maximum value of the temperature safety range, Tmin is the minimum value of the temperature safety range, Pt is the equipment operating power at time t, Pm is the median value of the equipment operating power safety range, Pmax is the maximum value of the equipment operating power safety range, Pmin is the minimum value of the equipment operating power safety range, dt is the time integral, and exp() is the exponential power of the natural constant e;

[0059] Through this step: the operation fatigue of the equipment is comprehensively analyzed through the equipment operation temperature, operation power data and the calculated equipment jitter abnormal value, and the operation fatigue of the equipment is accurately evaluated;

[0060] At the same time, the time range of the evaluation can be one day, one week or one month. The frequency of the evaluation, that is, the time interval for data collection, can be every minute, every hour or every shift. Increased jitter may indicate wear or imbalance of equipment components; abnormal temperature increase may be a sign of overheating or failure, and abnormal power consumption may be a sign of reduced efficiency or failure. Therefore, the equipment operating temperature, operating power data and calculated equipment jitter abnormality values ​​are used here to conduct a comprehensive analysis of the equipment's operating fatigue.

[0061] S23, obtaining image data of each functional component during the operation of the device, and importing the obtained image data of each functional component into a shape variable calculation formula to calculate the shape variable of each functional component, wherein the shape variable calculation formula is: S() is the area of ​​the image, As is the real-time image contour data of the functional component, Bs is the initial image contour data of the functional component, and the obtained deformation variables of each functional component are substituted into the calculation formula of the fatigue value of the functional component to calculate the fatigue value of the functional component, wherein the calculation formula of the fatigue value of the functional component is: Where, M is the number of functional components, Hj is the deformation variable of the jth functional component, and cj is the proportion coefficient of the jth functional component;

[0062] Through this step: a comprehensive analysis of the deformation of each functional component of the equipment is conducted;

[0063] The purpose of comprehensive analysis of the deformation of each functional component of the equipment is multifaceted, mainly to ensure the normal operation of the equipment, improve production efficiency, reduce maintenance costs and enhance the safety of the equipment; by analyzing the deformation data, potential failure points such as wear, cracks or other structural problems can be identified; deformation data can help predict possible equipment failures, so that maintenance can be carried out in advance to avoid downtime caused by sudden failures;

[0064] S24, obtaining the calculated equipment operation fatigue value and functional component fatigue value, and substituting them into the equipment fatigue analysis value calculation formula to calculate the equipment fatigue analysis value, wherein the equipment fatigue analysis value calculation formula is: Y=Ysb+Yg;

[0065] S3, importing the acquired product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis;

[0066] In this embodiment, importing the acquired product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis includes the following specific steps:

[0067] S31. Acquire product quality production data during the operation of the equipment, where the product quality production data includes product yield rate data and production speed data;

[0068] S32, importing the yield rate data and the production speed data into the equipment production quality analysis value calculation formula to calculate the equipment production quality analysis value, wherein the equipment production quality analysis value calculation formula is: Among them, P is the yield rate, vc is the production speed data;

[0069] S4, importing the obtained equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis;

[0070] In this embodiment, the obtained equipment operation fatigue analysis results and equipment production quality analysis results are imported into the production speed analysis model to perform production speed analysis, including the following specific contents:

[0071] S41. Obtain the calculated equipment fatigue analysis value and equipment production quality analysis value and substitute them into the production overall abnormal value calculation formula to calculate the production overall abnormal value, wherein the production overall abnormal value calculation formula is: Where b is the equipment fatigue analysis ratio;

[0072] S42, obtain the current equipment production speed and the calculated overall production abnormal value and substitute them into the required production speed calculation formula to calculate the required production speed of the equipment, wherein the required production speed calculation formula is: Where Za is the set production overall abnormal standard value, ln() is the logarithm with the natural constant e as the base;

[0073] S5. Adjust the production of each production equipment according to the production speed obtained by analysis;

[0074] In this embodiment, adjusting the production of each production equipment according to the production speed obtained by analysis includes the following specific contents:

[0075] Obtain the calculated required production speed of each device, adjust the production speed of the device to the required production speed, and automatically adjust the operating parameters of the device by programming or using an industrial control system (such as PLC);

[0076] It should be noted here that the equipment fatigue analysis proportion coefficient, the proportion coefficient of the j-th functional component and the temperature proportion coefficient here can be obtained by the entropy weight method and the fitting method. The preferred value-taking method is: obtain 500 sets of equipment operation data and product quality data produced by the equipment, and at the same time obtain the ranking of the healthy operation time of the equipment at each production speed, obtain the equipment operation data and the product quality data produced by the equipment and substitute them into the production speed analysis model for production speed analysis to obtain the required production speed, import the required production speed and the ranking of the healthy operation time of the equipment at each production speed into the fitting software, and output the equipment fatigue analysis proportion coefficient, the proportion coefficient of the j-th functional component and the temperature proportion coefficient that meet the highest sorting judgment accuracy;

[0077] It should be noted that the advantages of this embodiment over the prior art are as follows: the present invention obtains equipment operation data and product quality data produced by the equipment in real time through the Internet of Things, transmits them to the cloud platform in real time, imports the equipment operation data obtained in real time into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis, imports the obtained product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis, imports the obtained equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis, and adjusts the production of each production equipment according to the production speed obtained from the analysis. The present invention first conducts a comprehensive analysis of the obtained equipment operation data to predict the equipment operation fatigue situation, while taking into account the equipment production quality analysis results to accurately predict the suitable production speed for the equipment, thereby improving the safety of equipment production.

[0078] Example 2

[0079] like Figure 3 As shown, the equipment data management system based on the industrial Internet of Things is implemented based on the above-mentioned equipment data management method based on the industrial Internet of Things, which specifically includes a data acquisition module, a fatigue analysis module, a production quality analysis module, a production speed analysis module and a production speed adjustment module, wherein the data acquisition module is used to obtain the equipment operation data and the product quality data produced by the equipment in real time through the Internet of Things gateway, and transmit it to the cloud platform in real time;

[0080] Fatigue analysis module, used to import the real-time acquired equipment operation data into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis;

[0081] A production quality analysis module, used to import the acquired product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis;

[0082] A production speed analysis module, used to import the acquired equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis;

[0083] The production speed adjustment module is used to adjust the production of each production equipment according to the production speed obtained by analysis;

[0084] It also includes a control module for a data acquisition module, a fatigue analysis module, a production quality analysis module, a production speed analysis module and a production speed adjustment module.

[0085] Example 3

[0086] This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor;

[0087] The processor executes the above-mentioned device data management method based on industrial Internet of Things by calling the computer program stored in the memory.

[0088] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement the device data management method based on the industrial Internet of Things provided by the above method embodiment. The electronic device may also include other components for implementing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0089] Example 4

[0090] This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon;

[0091] When the computer program runs on a computer device, the computer device executes the above-mentioned device data management method based on the industrial Internet of Things.

[0092] For example, the computer readable storage medium can be a read-only memory, a random access memory, a read-only CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.

[0093] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

Claims

1. A device data management method based on industrial Internet of Things, characterized in that: It includes the following specific steps: Obtain equipment operation data and product quality data produced by the equipment in real time through the Internet of Things gateway, and transmit them to the cloud platform in real time; Import the real-time acquired equipment operation data into the equipment fatigue analysis strategy to conduct equipment operation fatigue analysis; Import the acquired product quality data produced by the equipment into the product production quality analysis strategy to conduct equipment production quality analysis; Import the acquired equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis; The production of each production equipment is adjusted according to the production speed obtained by analysis.

2. The device data management method based on industrial Internet of Things according to claim 1, characterized in that: The method of importing the real-time acquired equipment operation data into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis includes the following specific steps: The device operating jitter frequency and jitter amplitude data within the set evaluation period are obtained, and the device operating temperature and operating power data within the set evaluation period are obtained. The device operating jitter frequency and jitter amplitude data within the set evaluation period are imported into the device jitter abnormal value calculation formula to calculate the device jitter abnormal value. The device jitter abnormal value calculation formula is: Where N is the number of device jitters within the set evaluation period, ki is the jitter amplitude of the i-th device jitter within the set evaluation period, and kmax is the maximum value of the safe jitter amplitude range; The equipment operating temperature, operating power data and calculated equipment jitter abnormality values ​​within the set evaluation period are obtained and imported into the equipment operation fatigue value calculation formula to calculate the equipment operation fatigue value. The equipment operation fatigue value calculation formula is: Wherein, a is the temperature ratio coefficient, T is the set evaluation period, Tt is the equipment operating temperature at time t, Tm is the median value of the temperature safety range, Tmax is the maximum value of the temperature safety range, Tmin is the minimum value of the temperature safety range, Pt is the equipment operating power at time t, Pm is the median value of the equipment operating power safety range, Pmax is the maximum value of the equipment operating power safety range, Pmin is the minimum value of the equipment operating power safety range, dt is the time integral, and exp() is the exponential power of the natural constant e; The image data of each functional component during the operation of the device is obtained, and the image data of each functional component obtained is imported into the shape variable calculation formula to calculate the shape variable of each functional component, wherein the shape variable calculation formula is: S() is the area of ​​the image, As is the real-time image contour data of the functional component, and Bs is the initial image contour data of the functional component. The obtained deformation variables of each functional component are substituted into the calculation formula of the fatigue value of the functional component to calculate the fatigue value of the functional component, wherein the calculation formula of the fatigue value of the functional component is: Where, M is the number of functional components, Hj is the deformation variable of the jth functional component, and cj is the proportion coefficient of the jth functional component; The calculated equipment operation fatigue value and functional component fatigue value are obtained, and substituted into the equipment fatigue analysis value calculation formula to calculate the equipment fatigue analysis value, wherein the equipment fatigue analysis value calculation formula is: Y=Ysb+Yg.

3. The device data management method based on industrial Internet of Things according to claim 2, characterized in that: The step of importing the acquired product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis includes the following specific steps: Obtain product quality production data during equipment operation, including product yield rate data and production speed data; The yield rate data and production speed data are imported into the equipment production quality analysis value calculation formula to calculate the equipment production quality analysis value, where the equipment production quality analysis value calculation formula is: Among them, P is the yield rate and vc is the production speed data.

4. The device data management method based on industrial Internet of Things according to claim 3, characterized in that: The method of importing the obtained equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis includes the following specific contents: Obtain the calculated equipment fatigue analysis value and equipment production quality analysis value and substitute them into the production overall abnormal value calculation formula to calculate the production overall abnormal value, where the production overall abnormal value calculation formula is: Where b is the equipment fatigue analysis ratio; Obtain the current equipment production speed and the calculated overall production abnormality value and substitute them into the required production speed calculation formula to calculate the required production speed of the equipment. The required production speed calculation formula is: Where Za is the set standard value of overall production abnormality, and ln() is the logarithm with the natural constant e as the base.

5. The device data management method based on industrial Internet of Things according to claim 4, characterized in that: The adjustment of the production of each production equipment according to the production speed obtained by analysis includes the following specific contents: Obtain the calculated required production speed of each device, and adjust the production speed of the device to the required production speed.

6. The device data management method based on industrial Internet of Things according to claim 5, characterized in that: The specific steps of obtaining the equipment operation data and the product quality data produced by the equipment in real time through the Internet of Things gateway and transmitting them to the cloud platform in real time are as follows: Collecting the jitter frequency and jitter amplitude data of the equipment operation through the data acquisition terminal, and obtaining the equipment operation temperature and operation power data at the same time, and storing them in the first storage component; The image data of each functional component in the operation process of the device is collected by the image collection terminal and stored in the second storage component; The product quality production data during the operation of the equipment is collected through the product quality collection terminal and stored in the third storage component; The various collected data are transmitted to the cloud platform in real time through the Internet of Things.

7. An equipment data management system based on industrial Internet of Things, which is implemented based on the equipment data management method based on industrial Internet of Things according to any one of claims 1 to 6, characterized in that: It specifically includes a data acquisition module, a fatigue analysis module, a production quality analysis module, a production speed analysis module and a production speed adjustment module, wherein the data acquisition module is used to obtain the equipment operation data and the product quality data produced by the equipment in real time through the Internet of Things gateway, and transmit it to the cloud platform in real time; The fatigue analysis module is used to import the equipment operation data acquired in real time into the equipment fatigue analysis strategy to perform equipment operation fatigue analysis; The production quality analysis module is used to import the acquired product quality data produced by the equipment into the product production quality analysis strategy to perform equipment production quality analysis; The production speed analysis module is used to import the acquired equipment operation fatigue analysis results and equipment production quality analysis results into the production speed analysis model to perform production speed analysis; The production speed adjustment module is used to adjust the production of each production equipment according to the production speed obtained by analysis.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the device data management method based on industrial Internet of Things as described in any one of claims 1 to 6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes the device data management method based on the industrial Internet of Things as described in any one of claims 1 to 6.

Images