Industrial equipment collaborative management system based on Internet of Things

Abstract

The invention discloses an industrial equipment collaborative management system based on the Internet of Things, relates to the technical field of production supervision, and effectively improves the response efficiency when each piece of production equipment or product is abnormal. According to the method, a product production sequence chain and a standard product deformation representation interval are established according to historical product production records, and a standard processing operation track path interval is established according to historical equipment operation records; and binding the standard processing operation track path interval and the standard product deformation representation interval to a product production sequence chain to obtain a production supervision path of each product, establishing a production line distribution network, matching the production supervision path according to the product name, inputting the production supervision path to the production line distribution network to obtain a product production execution chain, and sending the product production execution chain to the production line distribution network. And performing product processing simulation according to the newly generated product production execution chain and the currently executed product production execution chain, and correcting and executing the newly generated product production execution chain according to a product processing simulation result.

Description

Technical Field

[0001] The present invention relates to the technical field of production supervision, and in particular to an industrial equipment collaborative management system based on the Internet of Things. Background Art

[0002] With the rapid development of intelligent manufacturing, the intelligence and networking of industrial equipment have become the key to the transformation and upgrading of the manufacturing industry. By connecting devices such as sensors, actuators and control systems to the Internet, the real-time data transmission and remote monitoring between devices are the main focus of existing technologies. However, the existing IoT remote control technology has the following defects:

[0003] Data silo problem: Data between different devices and systems are often stored and managed independently, resulting in the inability to effectively integrate and share data, thereby limiting the analysis and application of global data and reducing the accuracy and timeliness of control decisions.

[0004] Insufficient real-time performance and responsiveness: Existing IoT systems often have problems with delays and slow response when processing large amounts of real-time data. Insufficient real-time performance may lead to delays in key information, affecting timely adjustment of equipment and rapid response to faults.

[0005] Therefore, how to solve the information island problem between various production equipment on the production line while improving the response efficiency when abnormalities occur in various production equipment or products is a difficulty in the existing technology. For this purpose, an industrial equipment collaborative management system based on the Internet of Things is provided. Summary of the invention

[0006] In order to solve the above technical problems, the purpose of the present invention is to provide an industrial equipment collaborative management system based on the Internet of Things.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] An industrial equipment collaborative management system based on the Internet of Things, comprising a control center, wherein the control center is communicatively connected to a production data analysis module, an equipment operation analysis module, and a production supervision module;

[0009] The production data analysis module is used to collect historical product production records and historical equipment operation records of various types of products, and establish a product processing dynamic image model and a product production sequence chain based on the historical product production records, and divide a number of standard product deformation representation intervals on the product processing dynamic image model;

[0010] The equipment operation analysis module is used to establish an equipment processing dynamic image model and a number of standard processing operation trajectory path intervals according to historical equipment operation records, and sequentially splice the product processing dynamic image model with the standard product deformation representation interval and the standard processing operation trajectory path interval on the equipment processing dynamic image model, and bind them to the product production sequence chain, thereby obtaining the production supervision path of each product;

[0011] The production supervision module is used to establish a production line distribution network according to the distribution of production equipment on the production line, and then match the production supervision path according to the name of the product to be produced, input the production supervision path into the production line distribution network to obtain the product production execution chain, and perform product processing simulation based on the latest generated product production execution chain and the product production execution chain being executed, and modify and execute the latest generated product production execution chain according to the product processing simulation results.

[0012] Furthermore, the process of establishing the product production sequence chain includes:

[0013] The production line is composed of cross-connected production links, on which m production equipment of different types are installed, and the horizontal spacing between each production equipment is the same;

[0014] Cameras, laser cameras and wireless communication devices are installed on each production equipment, and then the production data analysis module collects n copies of historical product production records and corresponding historical equipment operation records of several products through cameras and laser cameras;

[0015] The production data analysis module establishes a corresponding product production sequence chain according to the product production steps in each historical product production record, wherein the product production sequence chain is composed of a number of production step nodes, and directed connecting lines are set between each production step node according to the association relationship, and the step names of the corresponding production sub-steps are marked, wherein n and m are natural numbers greater than 0;

[0016] The historical product production record includes the product type name, data generation time, product production steps and historical production video data. The product production steps are composed of several production sub-steps, and the production sub-steps include step names and processing time.

[0017] Furthermore, the process of establishing the product processing dynamic image model includes:

[0018] Divide the historical production video data corresponding to each product production step into a number of historical step video clips, and divide each historical step video clip into a number of historical step image data by frame, perform grayscale processing on each historical step image data, and obtain the pixel value of each pixel in the historical step image data;

[0019] The image data of each historical step are sequentially sorted, and the pixels at the same position of the image data of each historical step are sequentially overlapped according to the sorting result, a pixel change threshold is set, and the relationship between the pixel value difference between the pixels in the adjacent overlapping order and the pixel change threshold is judged, and the pixels are divided into static pixels and dynamic pixels according to the judgment result;

[0020] A corresponding product processing dynamic image model is established according to the image data of each historical step, and then a change annotation is set for the product processing dynamic image model according to the annotation of each pixel.

[0021] Furthermore, the process of dividing the standard product deformation characterization interval includes:

[0022] Overlapping and mapping product processing dynamic image models corresponding to the same product name and step name but generated according to different historical product production records, and dividing each product processing dynamic image model into a plurality of dynamic processing model blocks of the same size, wherein the dynamic processing model blocks are in the shape of six-sided cubes;

[0023] Obtain the pixel value of each pixel surface of each dynamic processing model block, and synchronously map each change annotation to the relevant pixel surface of the corresponding dynamic processing model block according to the location of the change annotation on the corresponding product processing dynamic image model;

[0024] Obtaining pixel gradient vectors between a pixel surface of a dynamic processing model block with a change mark and each pixel surface of eight adjacent dynamic processing model blocks;

[0025] A three-dimensional coordinate system is established, and then the pixel gradient vectors between the pixel plane with the change mark and other adjacent pixel planes are mapped on the three-dimensional coordinate system, and each pixel gradient vector is vector-superimposed to obtain the pixel offset vector of the pixel plane with the change mark in the corresponding time segment;

[0026] Then, adjacent pixel offset vectors with the same time segment label are connected in sequence to obtain the product deformation representation vector of the corresponding time segment and production sub-step.

[0027] Furthermore, the process of dividing the standard product deformation characterization interval also includes:

[0028] Overlap and map the product deformation representation vectors corresponding to the same product name and step name but generated according to different historical product production records, set several time nodes, and divide the product deformation representation vectors corresponding to the same position into several product deformation representation points through the time nodes;

[0029] Normally distribute the product deformation representation points at the same time node and position, and obtain the standard product deformation representation interval corresponding to the time node and step name according to the normal distribution result;

[0030] Each standard product deformation representation interval is mapped to the corresponding product processing dynamic image model in chronological order, and then each product processing dynamic image model is bound to the production step node in the corresponding product production sequence chain. At the same time, according to the duration of the historical step video clip corresponding to each production sub-step, the corresponding processing time is marked on each production step node.

[0031] Furthermore, the process of establishing the production supervision pathway includes:

[0032] After labeling the corresponding product name for each product production sequence chain, all product production sequence chains and historical equipment operation records are sent to the equipment operation analysis module;

[0033] The historical equipment operation record includes the name of the production equipment, the name of the processing step, the historical equipment operation data, the name of the processed product and the time when the data was generated;

[0034] The production data analysis module sets a number for each production equipment, adopts the process of establishing a product processing dynamic image model, generates a corresponding equipment processing dynamic image model according to the historical equipment operation data in each historical equipment operation record, generates a number of standard processing operation trajectory path intervals on the surface of the equipment processing dynamic image model, and marks the corresponding production equipment number on the equipment processing dynamic image model;

[0035] According to the data generation time in the historical equipment operation records and the historical product production records, the product processing dynamic image model and the equipment processing dynamic image model are spliced ​​to obtain the product production supervision model of each production sub-step, so that the standard processing operation trajectory path interval on the equipment processing dynamic image model corresponds to the standard product deformation representation interval on the product processing dynamic image model.

[0036] The product production supervision model of each production sub-step is bound to the corresponding production step node in the product production sequence chain, thereby obtaining the production supervision path of each product.

[0037] Furthermore, the process of generating the product production execution chain includes:

[0038] Obtain the distribution of each production equipment in the production line and the names of the executable steps, establish production equipment nodes according to the distribution of each production equipment in the production line, mark each production equipment node with the corresponding production equipment number, and connect each production equipment node in sequence to obtain a production line distribution network;

[0039] According to the name of the product to be produced, the corresponding production supervision path is retrieved, and the production equipment nodes in the production line distribution network are matched according to the step names of each production step node in the production supervision path, and then the corresponding product production execution chain is output, and the corresponding processing time is marked. The product production execution chain is composed of several production equipment nodes, and each production equipment node is marked with the product name, processing step name and processing time.

[0040] Furthermore, the modification and execution process of the product production execution chain includes:

[0041] According to the processing time of each production sub-step, determine whether the newly generated product production execution chain will conflict with the product production execution chain being executed, regenerate the product production execution chain based on the judgment result and perform product processing simulation until the newly generated product production execution chain does not conflict with any product production execution chain being executed, or the currently unrecorded production equipment node cannot meet the processing steps of the corresponding product;

[0042] Each production equipment generates product processing tasks according to the product execution chain, and then each production equipment processes the raw materials in turn according to the product processing tasks. At the same time, the cameras on the production equipment collect real-time production video data and real-time equipment operation data and send them to the production supervision module;

[0043] The production supervision module generates the corresponding real-time product dynamic model and real-time equipment processing dynamic image model based on the real-time production video data and real-time equipment operation data, and then generates the real-time product deformation representation vector and real-time processing operation trajectory path at each time node based on the real-time product dynamic model and real-time equipment processing dynamic image model;

[0044] Determine whether the real-time product deformation representation vector and the real-time processing operation trajectory path in each time segment are within the standard processing operation trajectory path interval and the standard product deformation representation interval at the corresponding time node, and remove the corresponding product from the production line based on the judgment result.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention obtains the production supervision path of each product by binding the standard processing operation trajectory path interval and the standard product deformation characterization interval to the product production sequence chain, establishes a production line distribution network, matches the production supervision path according to the product name, inputs the production supervision path into the production line distribution network to obtain the product production execution chain, performs product processing simulation according to the latest generated product production execution chain and the product production execution chain being executed, and corrects and executes the latest generated product production execution chain according to the product processing simulation result, thereby solving the information island problem between various production equipment on the production line and improving the response efficiency to abnormalities of various production equipment or products. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention.

[0048] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0049] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0050] like Figure 1 As shown, the industrial equipment collaborative management system based on the Internet of Things includes a control center, and the control center is communicatively connected to a production data analysis module, an equipment operation analysis module, and a production supervision module;

[0051] The production data analysis module is used to collect historical product production records and historical equipment operation records of various types of products, and establish a product processing dynamic image model and a product production sequence chain based on the historical product production records, and divide a number of standard product deformation representation intervals on the product processing dynamic image model;

[0052] The equipment operation analysis module is used to establish an equipment processing dynamic image model and a number of standard processing operation trajectory path intervals according to historical equipment operation records, and sequentially splice the product processing dynamic image model with the standard product deformation representation interval and the standard processing operation trajectory path interval on the equipment processing dynamic image model, and bind them to the product production sequence chain, thereby obtaining the production supervision path of each product;

[0053] The production supervision module is used to establish a production line distribution network according to the distribution of production equipment on the production line, and then match the production supervision path according to the name of the product to be produced, input the production supervision path into the production line distribution network to obtain the product production execution chain, and perform product processing simulation based on the latest generated product production execution chain and the product production execution chain being executed, and modify and execute the latest generated product production execution chain according to the product processing simulation results.

[0054] Further, the working principle of the present invention is specifically described below through embodiments:

[0055] The historical product production records include product category name, data generation time, product production steps and historical production video data;

[0056] The product production step consists of several production sub-steps, each of which includes a step name and a processing time;

[0057] The production line is composed of cross-connected production links, on which m production equipment of different types are installed, and the horizontal spacing between each production equipment is the same;

[0058] Cameras, laser cameras and wireless communication devices are installed on each production equipment, and then the production data analysis module collects n copies of historical product production records and corresponding historical equipment operation records of several products through cameras and laser cameras;

[0059] The production data analysis module establishes a corresponding product production sequence chain according to the product production steps in each historical product production record, wherein the product production sequence chain is composed of a plurality of production step nodes, and directed connection lines are set between each production step node according to the association relationship, and the step names of the corresponding production sub-steps are marked, wherein n is a natural number greater than 0;

[0060] At the same time, according to the number of production sub-steps and processing time of each product production step, the historical production video data corresponding to each product production step is divided into a number of historical step video clips, and each historical step video clip is divided into a number of historical step image data by frame;

[0061] Grayscale processing is performed on each historical step image data, and the pixel value of each pixel in the historical step image data is obtained, and then Gaussian blur is performed on each pixel of the historical step image data;

[0062] During the product processing, the surface, part or whole of the product is deformed due to the processing, so that the volume or surface of the product changes. Therefore, according to the division process of the image data of each historical step, the image data of each historical step is sorted in sequence, and the pixels at the same position of the image data of each historical step are overlapped in sequence according to the sorting result;

[0063] Setting a pixel change threshold value to determine the relationship between the pixel value difference between adjacent overlapping pixels and the pixel change threshold value;

[0064] If the pixel value difference is less than or equal to the pixel change threshold, it is determined that the pixel value of the pixel has not changed during the period between the corresponding historical step image data, and a static pixel and a corresponding time segment label are set for the pixel;

[0065] If the pixel value difference is greater than the pixel change threshold, it is determined that the pixel value has changed during the period between the corresponding historical step image data, and a dynamic pixel and a corresponding time segment label are set for the pixel;

[0066] A corresponding product processing dynamic image model is established based on the image data of each historical step. The volume or surface of the product processing dynamic image model changes over time, and then according to the annotations carried by each pixel, change annotations are set inside the product processing dynamic image model or at the annotation position.

[0067] Furthermore, the product processing dynamic image models corresponding to the same product name and step name but generated according to different historical product production records are overlapped and mapped, and each product processing dynamic image model is divided into a plurality of dynamic processing model blocks of the same size, and the dynamic processing model blocks are in the shape of a six-sided cube;

[0068] Obtain the pixel value of each pixel surface of each dynamic processing model block, and synchronously map each change annotation to the relevant pixel surface of the corresponding dynamic processing model block according to the location of the change annotation on the corresponding product processing dynamic image model;

[0069] According to the division order of each dynamic processing model block, the pixel gradient difference and gradient direction between the pixel surface of the dynamic processing model block with the change mark and each pixel surface of the eight adjacent dynamic processing model blocks are obtained;

[0070] According to each pixel gradient difference and gradient direction, a pixel gradient vector is established between each pixel plane with a change mark and other adjacent pixel planes, wherein the modulus of the pixel gradient vector is equal to the pixel gradient difference value, and the direction is the same as the gradient direction;

[0071] A three-dimensional coordinate system is established, and then the pixel gradient vectors between the pixel plane with the change mark and other adjacent pixel planes are mapped on the three-dimensional coordinate system, and each pixel gradient vector is vector-superimposed to obtain the pixel offset vector of the pixel plane with the change mark in the corresponding time segment;

[0072] Since the volume or surface changes of products during processing are continuous and regional, each pixel surface with a change mark must have a pixel surface with a change mark in its adjacent position;

[0073] Then, adjacent pixel offset vectors with the same time segment label are connected in sequence to obtain the product deformation representation vector corresponding to the time segment and production sub-step;

[0074] Overlap and map the product deformation representation vectors corresponding to the same product name and step name but generated according to different historical product production records, set several time nodes, and divide the product deformation representation vectors corresponding to the same position into several product deformation representation points through the time nodes;

[0075] Normally distribute the product deformation characterization points at the same time node and position, and select the 50% part of the center relative to the whole as the standard product deformation characterization point at the corresponding time node, connect the standard product deformation characterization points at each time node in sequence, and then obtain the standard product deformation characterization interval of the corresponding time node and step name;

[0076] Repeat the above process of generating standard product deformation representation intervals, and map each standard product deformation representation interval in chronological order onto the corresponding product processing dynamic image model, and then bind each product processing dynamic image model to the production step node in the corresponding product production sequence chain. At the same time, according to the duration of the historical step video clips corresponding to each production sub-step, mark the corresponding processing time for each production step node.

[0077] Furthermore, after the production data analysis module labels the corresponding product name for each product production sequence chain, the entire product production sequence chain and historical equipment operation records are sent to the equipment operation analysis module;

[0078] The historical equipment operation record includes the name of the production equipment, the name of the processing step, the historical equipment operation data, the name of the processed product and the time when the data was generated;

[0079] The production data analysis module sets a number for each production equipment 1 、a 2 、a 3 ,……,a m , and set the same number for each historical equipment operation record according to each production equipment number, where m is a natural number greater than 0;

[0080] The process of establishing a product processing dynamic image model is adopted to generate a corresponding equipment processing dynamic image model according to the historical equipment operation data in each historical equipment operation record, and a plurality of standard processing operation trajectory path intervals are generated on the surface of the equipment processing dynamic image model, and the corresponding production equipment number is marked on the equipment processing dynamic image model;

[0081] Since the volume or appearance deformation of the product during the processing is directly related to the production equipment, the volume or appearance deformation of the product processing dynamic image model is related to the dynamic change of the equipment processing dynamic image model, that is, there is a mapping association between the standard processing operation trajectory path interval on the equipment processing dynamic image model and the standard product deformation representation interval on the product processing dynamic image model;

[0082] According to the data generation time in the historical equipment operation records and the historical product production records, the product processing dynamic image model and the equipment processing dynamic image model are spliced ​​to obtain the product production supervision model of each production sub-step, so that the standard processing operation trajectory path interval on the equipment processing dynamic image model corresponds to the standard product deformation representation interval on the product processing dynamic image model.

[0083] The product production supervision model of each production sub-step is bound to the corresponding production step node in the product production sequence chain, thereby obtaining the production supervision path of each product.

[0084] Furthermore, the equipment operation analysis module sends the production supervision path of all products to the production supervision module. At the same time, the production supervision module communicates with each production equipment on the production line and obtains the distribution of each production equipment on the production line and the names of the executable steps according to the communication connection results.

[0085] Establish production equipment nodes according to the distribution of each production equipment in the production line, mark each production equipment node with a corresponding production equipment number, and connect each production equipment node in sequence to obtain a production line distribution network, wherein directed connection lines are set between the production equipment nodes, and the arrows of the directed connection lines indicate the product processing direction;

[0086] The staff uploads the name of the product to be produced to the production supervision module, and then the production supervision module retrieves the corresponding production supervision path according to the product name, and matches the production equipment nodes in the production line distribution network according to the step names of each production step node in the production supervision path, and then outputs the corresponding product production execution chain and marks the corresponding processing time. The product production execution chain is composed of several production equipment nodes, and each production equipment node is marked with the product name, processing step name and processing time;

[0087] The newly generated product production execution chain and the product production execution chain being executed are simultaneously input into the production line distribution network, and then the product processing simulation is performed. According to the processing time of each production sub-step, it is determined whether the newly generated product production execution chain will conflict with the product production execution chain being executed;

[0088] If there is any conflict, the conflicting production equipment node number is recorded, and then the product production execution chain is regenerated by bypassing the recorded production equipment node number, and the product processing simulation is re-performed;

[0089] If the regenerated product production execution chain still conflicts with the product production execution chain being executed, continue to regenerate until the latest generated product production execution chain does not conflict with any product production execution chain being executed, or the currently unrecorded production equipment nodes cannot meet the processing steps of the corresponding products.

[0090] Further, the production supervision module sends the product production execution chain to the wireless communication device of the corresponding production equipment according to the production equipment node number in the product production execution chain;

[0091] Whenever the production equipment receives a new product execution chain, it extracts the processing step name and processing time from the product execution chain according to its own number, and then automatically generates a product processing task, wherein the product processing task includes the processing step name, processing time and execution start time;

[0092] The staff puts the raw materials of the products on the production line, and then each production equipment processes the raw materials in turn according to the product processing tasks. At the same time, the cameras on the production equipment collect real-time production video data and real-time equipment operation data and send them to the production supervision module;

[0093] The production supervision module generates the corresponding real-time product dynamic model and real-time equipment processing dynamic image model based on the real-time production video data and real-time equipment operation data, and then generates the real-time product deformation representation vector and real-time processing operation trajectory path at each time node based on the real-time product dynamic model and real-time equipment processing dynamic image model;

[0094] Determine whether the real-time product deformation representation vector and the real-time processing operation trajectory path in each time segment are within the standard processing operation trajectory path interval and the standard product deformation representation interval at the corresponding time node. If both are within the relevant interval, it is determined that the production at the corresponding time node is normal;

[0095] Otherwise, the production is judged to be abnormal. If the production is judged to be abnormal for three consecutive time nodes, the abnormal processing part is marked on the real-time product dynamic model according to the real-time product deformation representation vector with abnormality and the location of the real-time processing operation trajectory path;

[0096] The production supervision module generates product abnormality warnings to the staff based on the abnormal processing parts on the real-time product dynamic model, and then the staff removes the corresponding products from the production line based on the product abnormality warnings;

[0097] Repeat the above product processing operations until all product processing is completed.

[0098] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The industrial equipment collaborative management system based on the Internet of Things includes a control center, which is characterized by: The control center is communicatively connected to a production data analysis module, an equipment operation analysis module, and a production supervision module; The production data analysis module is used to collect historical product production records and historical equipment operation records of various types of products, and establish a product processing dynamic image model and a product production sequence chain based on the historical product production records, and divide a number of standard product deformation representation intervals on the product processing dynamic image model; The equipment operation analysis module is used to establish an equipment processing dynamic image model and a number of standard processing operation trajectory path intervals according to historical equipment operation records, and sequentially splice the product processing dynamic image model with the standard product deformation representation interval and the standard processing operation trajectory path interval on the equipment processing dynamic image model, and bind them to the product production sequence chain, thereby obtaining the production supervision path of each product; The production supervision module is used to establish a production line distribution network according to the distribution of production equipment on the production line, and then match the production supervision path according to the name of the product to be produced, input the production supervision path into the production line distribution network to obtain the product production execution chain, and perform product processing simulation based on the latest generated product production execution chain and the product production execution chain being executed, and modify and execute the latest generated product production execution chain according to the product processing simulation results.

2. The industrial equipment collaborative management system based on the Internet of Things according to claim 1 is characterized in that: The process of establishing the product production sequence chain includes: The production line is equipped with m production equipment of different types, and the horizontal spacing between each production equipment is the same. A camera and a wireless communication device are installed on each production equipment, and then the production data analysis module collects n historical product production records of several products and corresponding historical equipment operation records through cameras and laser cameras; Establish a corresponding product production sequence chain according to the product production steps in each historical product production record, wherein the product production sequence chain consists of a number of production step nodes, and each production step node is marked with a step name of a corresponding production sub-step, where n is a natural number greater than 0; The historical product production record includes the product type name, data generation time, product production steps and historical production video data. The product production steps are composed of several production sub-steps, and the production sub-steps include step names and processing time.

3. The industrial equipment collaborative management system based on the Internet of Things according to claim 2 is characterized in that: The process of establishing the product processing dynamic image model includes: Divide the historical production video data corresponding to each product production step into a number of historical step video clips, divide each historical step video clip into a number of historical step image data, and obtain the pixel value of each pixel in the historical step image data; Overlap the pixels at the same position of the image data of each historical step in sequence, set a pixel change threshold, determine the relationship between the pixel value difference between the pixels in the adjacent overlapping order and the pixel change threshold, and set the pixel as a static pixel or a dynamic pixel label according to the determination result; A corresponding product processing dynamic image model is established according to the image data of each historical step, and then a change annotation is set for the product processing dynamic image model according to the annotation of each pixel.

4. The industrial equipment collaborative management system based on the Internet of Things according to claim 3 is characterized in that: The process of dividing the standard product deformation characterization interval includes: Overlapping and mapping product processing dynamic image models corresponding to the same product name and step name but generated according to different historical product production records, and dividing each product processing dynamic image model into a plurality of dynamic processing model blocks of the same size, wherein the dynamic processing model blocks are in the shape of six-sided cubes; Obtain the pixel value of each pixel surface of each dynamic processing model block, and synchronously map each change annotation to the relevant pixel surface of the corresponding dynamic processing model block according to the location of the change annotation on the corresponding product processing dynamic image model; Obtaining pixel gradient vectors between a pixel surface of a dynamic processing model block with a change mark and each pixel surface of eight adjacent dynamic processing model blocks; A three-dimensional coordinate system is established, and then the pixel gradient vectors between the pixel plane with the change mark and other adjacent pixel planes are mapped on the three-dimensional coordinate system, and each pixel gradient vector is vector-superimposed to obtain the pixel offset vector of the pixel plane with the change mark in the corresponding time segment; Adjacent pixel offset vectors with the same time segment label are connected in sequence to obtain the product deformation representation vector corresponding to the time segment and production sub-step.

5. The industrial equipment collaborative management system based on the Internet of Things according to claim 4 is characterized in that: The process of dividing the standard product deformation characterization interval also includes: Overlap and map the product deformation representation vectors corresponding to the same product name and step name but generated according to different historical product production records, set several time nodes, and divide the product deformation representation vectors corresponding to the same position into several product deformation representation points through the time nodes; Normally distribute the product deformation representation points at the same time node and position, and obtain the standard product deformation representation interval corresponding to the time node and step name according to the normal distribution result; Each standard product deformation representation interval is mapped onto the corresponding product processing dynamic image model in chronological order, and then each product processing dynamic image model is bound to the production step node in the corresponding product production sequence chain, and each production step node is marked with the corresponding processing time.

6. The industrial equipment collaborative management system based on the Internet of Things according to claim 5 is characterized in that: The process of establishing the production supervision path includes: The historical equipment operation record includes the name of the production equipment, the name of the processing step, the historical equipment operation data, the name of the processed product and the time when the data was generated; The production data analysis module sets a number for each production equipment, adopts the process of establishing a product processing dynamic image model, generates a corresponding equipment processing dynamic image model according to the historical equipment operation data in each historical equipment operation record, generates a number of standard processing operation trajectory path intervals on the surface of the equipment processing dynamic image model, and marks the corresponding production equipment number on the equipment processing dynamic image model; According to the data generation time in the historical equipment operation records and historical product production records, the product processing dynamic image model and the equipment processing dynamic image model are spliced ​​to obtain the product production supervision model of each production sub-step, and the standard processing operation trajectory path interval is made to correspond one-to-one with the standard product deformation representation interval. The product production supervision model of each production sub-step is bound to the corresponding production step node in the product production sequence chain, and then the production supervision path of each product is obtained.

7. The industrial equipment collaborative management system based on the Internet of Things according to claim 6 is characterized in that: The generation process of the product production execution chain includes: Obtain the distribution of each production equipment on the production line and the names of its executable steps, establish production equipment nodes according to the distribution of each production equipment on the production line, mark the corresponding production equipment numbers, and connect each production equipment node in sequence to obtain a production line distribution network; According to the name of the product to be produced, the corresponding production supervision path is retrieved, and the production equipment nodes in the production line distribution network are matched according to the step names of each production step node in the production supervision path, and then the product production execution chain is output, and the corresponding processing time is marked. The product production execution chain is composed of several production equipment nodes, and each production equipment node is marked with the product name, processing step name and processing time.

8. The industrial equipment collaborative management system based on the Internet of Things according to claim 7 is characterized in that: The modification and execution process of the product production execution chain includes: According to the processing time of each production sub-step, determine whether the newly generated product production execution chain will conflict with the product production execution chain being executed, regenerate the product production execution chain based on the judgment result and perform product processing simulation until the newly generated product production execution chain does not conflict with any product production execution chain being executed, or the currently unrecorded production equipment node cannot meet the processing steps of the corresponding product; Each production equipment generates product processing tasks according to the product execution chain, and then each production equipment processes the raw materials in turn according to the product processing tasks. At the same time, the cameras on the production equipment collect real-time production video data and real-time equipment operation data and send them to the production supervision module; The production supervision module generates the corresponding real-time product dynamic model and real-time equipment processing dynamic image model based on the real-time production video data and real-time equipment operation data, and then generates the real-time product deformation representation vector and real-time processing operation trajectory path at each time node based on the real-time product dynamic model and real-time equipment processing dynamic image model; Determine whether the real-time product deformation representation vector and the real-time processing operation trajectory path in each time segment are within the standard processing operation trajectory path interval and the standard product deformation representation interval at the corresponding time node, and remove the corresponding product from the production line based on the judgment result.

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