IoT centralized monitoring method and device for industrial automation equipment

Abstract

The application relates to the technical field of production monitoring, and particularly discloses an Internet of Things centralized monitoring method and device for industrial automation equipment, which comprises the following steps: acquiring image information containing corresponding monitoring terminal parameters; receiving image information containing monitoring terminal parameters sent by a monitoring terminal, and performing regional identification on the image information; the monitoring terminal parameters comprise a monitoring terminal number; sending a monitoring instruction to the monitoring terminal according to the regional identification result, acquiring a detail image obtained by the monitoring terminal based on the monitoring instruction, and generating a monitoring report according to the detail image. The technical scheme of the application can acquire images of the whole region through multiple image acquisition devices with high degrees of freedom, update a regional model in real time, perform segmentation on the regional model into a device area and a personnel area, further acquire a detail image based on the segmentation result, and can play a good reference role and reduce the monitoring fatigue of monitoring personnel.

Description

Technical Field

[0001] This invention relates to the field of production monitoring technology, specifically to an IoT-based centralized monitoring method and device for industrial automation equipment. Background Technology

[0002] With societal progress and technological advancements, industrial automation is an inevitable trend. While existing automation technologies for production processes are gradually improving, monitoring largely relies on basic cameras. Supervisors monitor areas based on images captured by these cameras. This process inherently lacks flexibility. Although existing technologies like camera-and-ball camera systems offer expanded perspectives for supervisors, analyzing these images remains challenging. Summary of the Invention

[0003] The purpose of this invention is to provide a method and apparatus for centralized monitoring of industrial automation equipment via the Internet of Things (IoT) to solve the problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution:

[0005] A method for centralized IoT monitoring of industrial automation equipment, the method comprising:

[0006] The system receives environmental parameters input by the user, determines the image acquisition mode based on the environmental parameters, and sends the image acquisition mode to the monitoring terminal. When the monitoring terminal receives the image acquisition mode, it acquires image information containing the corresponding monitoring terminal parameters.

[0007] Receive image information containing monitoring terminal parameters sent by the monitoring terminal, and perform region identification on the image information; the monitoring terminal parameters include the monitoring terminal number;

[0008] Based on the region identification results, a monitoring command is sent to the monitoring terminal to obtain detailed images obtained by the monitoring terminal based on the monitoring command.

[0009] A monitoring report is generated based on the detailed images.

[0010] As a further aspect of the present invention: when the monitoring terminal receives the image acquisition mode, the step of acquiring image information containing corresponding monitoring terminal parameters includes:

[0011] The acquired image information is subjected to photoelectric conversion, and the photoelectric conversion data is statistically analyzed to obtain a histogram;

[0012] The histogram distribution change is obtained to determine whether there is smog and the smog concentration; in non-smog scenes, the image histogram distribution is relatively uniform, while in smog scenes, the image histogram is basically concentrated in the middle area, and the heavier the smog, the more concentrated the histogram.

[0013] When the histogram indicates the presence of haze, the image acquisition mode is set to fog-penetrating mode.

[0014] As a further aspect of the present invention: the step of receiving image information containing monitoring terminal parameters sent by the monitoring terminal, and performing region identification on the image information includes:

[0015] Receive image information containing monitoring terminal parameters sent by the monitoring terminal, and read the monitoring terminal number in the monitoring terminal parameters;

[0016] The location information of the monitoring terminal is obtained according to the monitoring terminal number, and the range information of the image information is determined according to the location information and the monitoring terminal parameters; the range information is described by the point information relative to the workshop.

[0017] The image information is filled into a preset environment model based on the range information;

[0018] The environmental model is subjected to region identification; wherein, the region identification process generates region labels, the region labels including equipment areas and personnel areas.

[0019] As a further aspect of the present invention: the step of filling the image information into a preset environment model according to the range information includes:

[0020] Read the point information from the range information, and locate the area to be filled in the environment model based on the point information;

[0021] Extract the existing image from the region to be filled, compare the image information with the existing image, and calculate the similarity based on the comparison result;

[0022] When the similarity reaches a preset similarity threshold, the image information is filled into a preset environment model;

[0023] When the similarity is less than a preset similarity threshold, the environment model is modified and filled.

[0024] As a further aspect of the present invention: the step of modifying and filling the environment model when the similarity is less than a preset similarity threshold includes:

[0025] When the similarity is less than a preset similarity threshold, the monitoring terminal parameters are queried according to the range information, and the monitoring terminal number in the monitoring terminal parameters is read.

[0026] Based on the monitoring terminal number, a cyclic acquisition command containing the acquisition frequency is sent to the corresponding monitoring terminal to obtain an image group;

[0027] The image group is input into the trained feature value analysis model to obtain the numerical group corresponding to the image group;

[0028] Calculate the mode in the set of values, read the image corresponding to the mode, and fill it into the environment model as image information.

[0029] As a further aspect of the present invention: the step of sending a monitoring command to the monitoring terminal based on the region identification result and obtaining the detailed image obtained by the monitoring terminal based on the monitoring command includes:

[0030] When the label obtained from the region recognition process is the device area, the device area image is extracted from the environment model to obtain the range information related to the device area image;

[0031] Contour recognition is performed on the image of the equipment area to determine the equipment size, and monitoring parameters of the monitoring terminal are determined based on the equipment size and location information;

[0032] The monitoring terminal is located based on the range information, and the monitoring parameters are sent to the corresponding monitoring terminal.

[0033] As a further aspect of the present invention: the step of sending a monitoring command to the monitoring terminal based on the region identification result and obtaining the detailed image obtained by the monitoring terminal based on the monitoring command further includes:

[0034] When the label obtained from the region recognition process is a personnel area, the personnel area image is extracted from the environment model to obtain the range information related to the personnel area image;

[0035] The system locates the monitoring terminal based on the range information, sends a heat source information acquisition command to the located monitoring terminal, and receives image information containing heat source information from the monitoring terminal.

[0036] The present invention also provides an IoT centralized monitoring device for industrial automation equipment, the device comprising:

[0037] The image information acquisition module is used to receive environmental parameters input by the user, determine the image acquisition mode based on the environmental parameters, and send the image acquisition mode to the monitoring terminal; when the monitoring terminal receives the image acquisition mode, it acquires image information containing the corresponding monitoring terminal parameters.

[0038] The region identification module is used to receive image information containing monitoring terminal parameters sent by the monitoring terminal, and to perform region identification on the image information; the monitoring terminal parameters include the monitoring terminal number;

[0039] The detailed image acquisition module is used to send monitoring instructions to the monitoring terminal based on the region recognition results and acquire detailed images obtained by the monitoring terminal based on the monitoring instructions.

[0040] The report generation module is used to generate a monitoring report based on the detailed images.

[0041] As a further aspect of the present invention: the region identification module includes:

[0042] The number reading unit is used to receive image information containing monitoring terminal parameters sent by the monitoring terminal, and read the monitoring terminal number in the monitoring terminal parameters;

[0043] The range determination unit is used to obtain the location information of the monitoring terminal according to the monitoring terminal number, and determine the range information of the image information according to the location information and the monitoring terminal parameters; the range information is described by the point information relative to the workshop.

[0044] An image filling unit is used to fill the image information into a preset environment model according to the range information;

[0045] The processing execution unit is used to perform area identification on the environment model; wherein, the area identification process generates area labels, and the area labels include equipment areas and personnel areas.

[0046] As a further aspect of the present invention: the image filling unit includes:

[0047] The positioning subunit is used to read the point information in the range information and locate the area to be filled in the environment model according to the point information.

[0048] The calculation subunit is used to extract the existing image within the area to be filled, compare the image information with the existing image, and calculate the similarity based on the comparison result;

[0049] An insertion subunit is used to fill the image information into a preset environment model when the similarity reaches a preset similarity threshold.

[0050] The correction subunit is used to correct and fill the environment model when the similarity is less than a preset similarity threshold.

[0051] Compared with the prior art, the beneficial effects of the present invention are: the technical solution of the present invention acquires images of the entire area through multiple image acquisition devices with high degrees of freedom, updates the area model in real time, and divides the area model into equipment area and personnel area. Based on the segmentation results, detailed images are further acquired, which can play an excellent reference role and reduce the supervision fatigue of supervisory personnel. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0053] Figure 1 A flowchart illustrating a centralized IoT monitoring method for industrial automation equipment.

[0054] Figure 2 The first sub-flow diagram of the IoT centralized monitoring method for industrial automation equipment.

[0055] Figure 3 This is the second sub-flow diagram of the IoT centralized monitoring method for industrial automation equipment.

[0056] Figure 4 This is the third sub-process flowchart of the IoT centralized monitoring method for industrial automation equipment.

[0057] Figure 5 The fourth sub-flow diagram of the IoT centralized monitoring method for industrial automation equipment.

[0058] Figure 6 This is a block diagram showing the composition of an IoT centralized monitoring device for industrial automation equipment.

[0059] Figure 7 This is a block diagram showing the composition of the area identification module in an IoT centralized monitoring device for industrial automation equipment.

[0060] Figure 8 This is a block diagram showing the structural composition of the image filling unit in the region recognition module. Detailed Implementation

[0061] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0062] Example 1

[0063] Figure 1 The flowchart illustrates a method for centralized IoT monitoring of industrial automation equipment. In this embodiment of the invention, a method for centralized IoT monitoring of industrial automation equipment includes steps S100 to S400:

[0064] Step S100: Receive environmental parameters input by the user, determine the image acquisition mode based on the environmental parameters, and send the image acquisition mode to the monitoring terminal; when the monitoring terminal receives the image acquisition mode, it acquires image information containing the corresponding monitoring terminal parameters.

[0065] The technical solution of this invention has two ports: a central control center for performing the functions of steps S100 to S400, and a monitoring terminal. The monitoring terminal can be hardware or software. When the monitoring terminal is hardware, it can be a multi-functional image acquisition device with functions including thermal analysis and mode adjustment, the mode adjustment function being used to match different environments. When the monitoring terminal is software, it is installed in the aforementioned multi-functional image acquisition device. Step S100 is the interaction process between the central control center and the operator. The operator inputs environmental parameters, and then the central control center determines the image acquisition mode. The monitoring terminal then acquires image information according to this image acquisition mode.

[0066] Step S200: Receive image information containing monitoring terminal parameters sent by the monitoring terminal, and perform region identification on the image information; the monitoring terminal parameters include the monitoring terminal number;

[0067] After receiving the image information from the monitoring terminal, it is necessary to perform area identification on the image information. In the same workshop, the monitoring process is mainly divided into two processes: one is to monitor the equipment and the other is to monitor the staff. Traditional monitoring systems often do not distinguish between these two processes, which is the innovation of the technical solution of this invention.

[0068] Step S300: Send a monitoring command to the monitoring terminal based on the area identification result, and obtain the detailed image obtained by the monitoring terminal based on the monitoring command;

[0069] Step S400: Generate a monitoring report based on the detailed image;

[0070] After performing region recognition on the image information, the equipment area and personnel area can be determined. Then, further data collection can be carried out on these two areas through the monitoring terminal. Based on the collected data, a monitoring report can be generated. As for the type of monitoring report, it is highly related to the actual situation. For example, some companies will detect the degree of deformation of the equipment, while others will focus on the activity frequency of the staff. These all depend on the specific situation.

[0071] Furthermore, when the monitoring terminal receives the image acquisition mode, the step of acquiring image information containing the corresponding monitoring terminal parameters includes:

[0072] The acquired image information is subjected to photoelectric conversion, and the photoelectric conversion data is statistically analyzed to obtain a histogram;

[0073] The histogram distribution change is obtained to determine whether there is smog and the smog concentration; in non-smog scenes, the image histogram distribution is relatively uniform, while in smog scenes, the image histogram is basically concentrated in the middle area, and the heavier the smog, the more concentrated the histogram.

[0074] When the histogram indicates the presence of haze, the image acquisition mode is set to fog-penetrating mode.

[0075] It should be noted that in some workshops, there may be some fog in the air, which will affect the image quality acquired by the monitoring terminal. Therefore, the image acquisition mode of the monitoring terminal often includes fog penetration mode. The selection criteria for fog penetration mode are determined "autonomously" by the monitoring terminal. The above content provides a technical solution for "autonomous" determination.

[0076] Figure 2 The first sub-flowchart of the IoT centralized monitoring method for industrial automation equipment includes steps S201 to S204, wherein the step of receiving image information containing monitoring terminal parameters sent by the monitoring terminal and performing region identification on the image information includes:

[0077] Step S201: Receive image information containing monitoring terminal parameters sent by the monitoring terminal, and read the monitoring terminal number in the monitoring terminal parameters;

[0078] Step S202: Obtain the location information of the monitoring terminal according to the monitoring terminal number, and determine the range information of the image information according to the location information and the monitoring terminal parameters; the range information is described by the point information relative to the workshop;

[0079] Step S203: Fill the image information into the preset environment model according to the range information;

[0080] Step S204: Perform region identification on the environment model; wherein, the region identification process generates region labels, the region labels including equipment areas and personnel areas.

[0081] The number of monitoring terminals is not unique. Different angles and magnifications of the same monitoring terminal will result in different image information. Different monitoring terminals are located in different positions, and the image information they obtain is also likely to be different. Therefore, when receiving image information sent by the monitoring terminals, it is necessary to unify the image information. The unification method is to use the aforementioned environmental model, which is determined proportionally to the actual situation of the monitoring area. When each monitoring terminal obtains image information, it fills the environmental model in sequence.

[0082] Figure 3 This is a second sub-process flowchart of the IoT centralized monitoring method for industrial automation equipment. The step of filling the image information into a preset environment model based on the range information includes steps S2031 to S2034:

[0083] Step S2031: Read the point information in the range information, and locate the area to be filled in the environment model according to the point information;

[0084] Step S2032: Extract the existing image within the area to be filled, compare the image information with the existing image, and calculate the similarity based on the comparison result;

[0085] Step S2033: When the similarity reaches a preset similarity threshold, the image information is filled into a preset environment model;

[0086] Step S2034: When the similarity is less than a preset similarity threshold, the environment model is modified and filled.

[0087] Steps S2031 to S2034 specify the model filling process. When image information containing monitoring terminal parameters is received from the monitoring terminal, a monitoring range can be determined based on the position, angle and magnification of the monitoring terminal, which is the range information mentioned above. Based on this range information, the corresponding area is found in the environmental model and filled.

[0088] It is worth mentioning that the environment model must be continuously updated over time. During the update process, an image information detection process is added. The principle is to determine whether the new image information is distorted based on its similarity to existing images.

[0089] Furthermore, the step of modifying and filling the environment model when the similarity is less than a preset similarity threshold includes:

[0090] When the similarity is less than a preset similarity threshold, the monitoring terminal parameters are queried according to the range information, and the monitoring terminal number in the monitoring terminal parameters is read.

[0091] Based on the monitoring terminal number, a cyclic acquisition command containing the acquisition frequency is sent to the corresponding monitoring terminal to obtain an image group;

[0092] The image group is input into the trained feature value analysis model to obtain the numerical group corresponding to the image group;

[0093] Calculate the mode in the set of values, read the image corresponding to the mode, and fill it into the environment model as image information.

[0094] The above content provides a specific explanation of the situation where the similarity is insufficient. Insufficient similarity indicates that there has been a significant change in the new image information. Therefore, the monitoring terminal should continuously acquire image information multiple times. Based on the image information acquired multiple times, it can be determined whether the significant change is sustainable. This can effectively avoid the problem of individual image distortion caused by various reasons.

[0095] Figure 4The third sub-flowchart of the IoT centralized monitoring method for industrial automation equipment includes steps S301 to S303, whereby the step of sending a monitoring command to the monitoring terminal based on the area identification result and obtaining a detailed image obtained by the monitoring terminal based on the monitoring command is described.

[0096] Step S301: When the label obtained by the region recognition process is the device area, the device area image is captured in the environment model to obtain the range information related to the device area image;

[0097] Step S302: Perform contour recognition on the image of the equipment area to determine the equipment size, and determine the monitoring parameters of the monitoring terminal based on the equipment size and location information;

[0098] Step S303: Locate the monitoring terminal based on the range information and send the monitoring parameters to the corresponding monitoring terminal.

[0099] The above content is a further analysis of the equipment area image. Its purpose is to magnify each device so that the device occupies as much proportion as possible in the image information, thus providing a basis for the subsequent analysis process.

[0100] Figure 5 The fourth sub-flowchart of the IoT centralized monitoring method for industrial automation equipment further includes steps S304 to S305, namely, sending monitoring instructions to the monitoring terminal based on the area identification results and obtaining detailed images obtained by the monitoring terminal based on the monitoring instructions.

[0101] Step S304: When the label obtained from the region recognition process is a personnel area, the personnel area image is extracted from the environment model to obtain the range information related to the personnel area image;

[0102] Step S305: Locate the monitoring terminal based on the range information, send a heat source information acquisition command to the located monitoring terminal, and receive image information containing heat source information from the monitoring terminal.

[0103] Steps S304 to S305 involve further analysis of the personnel area. The most important information about the staff is their movement information. Through heat source analysis, the movement trajectory of the staff can be clearly obtained, thus providing a basis for the subsequent analysis process.

[0104] Example 2

[0105] Figure 6 This is a structural block diagram of an IoT centralized monitoring device for industrial automation equipment. In this embodiment of the invention, an IoT centralized monitoring device for industrial automation equipment, the device 10 includes:

[0106] The image information acquisition module 11 is used to receive environmental parameters input by the user, determine the image acquisition mode according to the environmental parameters, and send the image acquisition mode to the monitoring terminal; when the monitoring terminal receives the image acquisition mode, it acquires image information containing the corresponding monitoring terminal parameters.

[0107] The region identification module 12 is used to receive image information containing monitoring terminal parameters sent by the monitoring terminal, and to perform region identification on the image information; the monitoring terminal parameters include the monitoring terminal number;

[0108] The detailed image acquisition module 13 is used to send a monitoring command to the monitoring terminal based on the region recognition result and acquire the detailed image acquired by the monitoring terminal based on the monitoring command.

[0109] The report generation module 14 is used to generate a monitoring report based on the detailed images.

[0110] Figure 7 This is a structural block diagram of the area identification module 12 in the IoT centralized monitoring device for industrial automation equipment. The area identification module 12 includes:

[0111] The number reading unit 121 is used to receive image information containing monitoring terminal parameters sent by the monitoring terminal, and read the monitoring terminal number in the monitoring terminal parameters;

[0112] The range determination unit 122 is used to obtain the location information of the monitoring terminal according to the monitoring terminal number, and determine the range information of the image information according to the location information and the monitoring terminal parameters; the range information is described by the point information relative to the workshop.

[0113] Image filling unit 123 is used to fill the image information into a preset environment model according to the range information;

[0114] The processing execution unit 124 is used to perform area identification on the environment model; wherein, the area identification process generates area labels, the area labels including equipment area and personnel area.

[0115] Figure 8 The diagram shows the structural composition of the image filling unit 123 in the region recognition module. The image filling unit 123 includes:

[0116] The positioning subunit 1231 is used to read the point information in the range information and locate the area to be filled in the environment model according to the point information.

[0117] The calculation subunit 1232 is used to extract the existing image in the area to be filled, compare the image information with the existing image, and calculate the similarity based on the comparison result;

[0118] Insertion subunit 1233 is used to fill the image information into a preset environment model when the similarity reaches a preset similarity threshold;

[0119] The correction subunit 1234 is used to perform correction filling on the environment model when the similarity is less than a preset similarity threshold.

[0120] The functions achievable by the IoT centralized monitoring method for industrial automation equipment are all performed by computer equipment, which includes one or more processors and one or more memories. The one or more memories store at least one piece of program code, which is loaded and executed by the one or more processors to implement the IoT centralized monitoring method for industrial automation equipment.

[0121] The processor fetches instructions from memory one by one, analyzes the instructions, and then performs the corresponding operations according to the instructions, generating a series of control commands to enable the various parts of the computer to act automatically, continuously, and in a coordinated manner, forming an organic whole. This enables the input of programs and data, as well as the calculation and output of results. The arithmetic or logical operations generated in this process are all performed by the arithmetic unit. The memory includes a read-only memory (ROM), which is used to store computer programs. The memory is protected by an external protection device.

[0122] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0123] Those skilled in the art will understand that the above description of the service equipment is merely an example and does not constitute a limitation on the terminal equipment. It may include more or fewer components than described above, or a combination of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0124] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the terminal device, connecting various parts of the user terminal via various interfaces and lines.

[0125] The aforementioned memory can be used to store computer programs and / or modules. The aforementioned processor implements various functions of the aforementioned terminal device by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as information collection template display function, product information publishing function, etc.); the data storage area may store data created based on the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that different product providers need to publish, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0126] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable medium. Based on this understanding, all or part of the modules / units in the systems of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable medium, and when executed by a processor, it can implement the functions of the various system embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0127] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0128] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for centralized monitoring of Internet of Things of industrial automation equipment, characterized in that, The method comprises: receiving user input environment parameters, determining an image acquisition mode according to the environment parameters, and sending the image acquisition mode to a monitoring terminal; the monitoring terminal acquires image information containing corresponding monitoring terminal parameters when receiving the image acquisition mode; receiving image information containing monitoring terminal parameters sent by the monitoring terminal, and performing region identification on the image information; the monitoring terminal parameters include a monitoring terminal number; sending a monitoring instruction to the monitoring terminal according to the region identification result, and acquiring a detail image obtained by the monitoring terminal based on the monitoring instruction; generating a monitoring report according to the detail image; the step of receiving image information containing monitoring terminal parameters sent by the monitoring terminal and performing region identification on the image information comprises: receiving image information containing monitoring terminal parameters sent by the monitoring terminal, reading a monitoring terminal number in the monitoring terminal parameters; acquiring position information of the monitoring terminal according to the monitoring terminal number, determining range information of the image information according to the position information and the monitoring terminal parameters; the range information is described by point position information relative to a workshop; filling the image information into a preset environment model according to the range information; performing region identification on the environment model; wherein, the region identification process generates a region label, and the region label includes a device area and a personnel area; the step of filling the image information into the preset environment model according to the range information comprises: reading point position information in the range information, positioning a to-be-filled area in the environment model according to the point position information; extracting a stored image in the to-be-filled area, comparing the image information with the stored image, and calculating a similarity according to the comparison result; when the similarity reaches a preset similarity threshold, filling the image information into the preset environment model; when the similarity is less than the preset similarity threshold, performing formal filling on the environment model; the step of performing formal filling on the environment model when the similarity is less than the preset similarity threshold comprises: when the similarity is less than the preset similarity threshold, querying the monitoring terminal parameters according to the range information, and reading a monitoring terminal number in the monitoring terminal parameters; sending a cyclic acquisition instruction containing an acquisition frequency to the corresponding monitoring terminal based on the monitoring terminal number, and obtaining an image group; inputting the image group into a trained feature value analysis model to obtain a numerical group corresponding to the image group; calculating a mode in the numerical group, reading an image corresponding to the mode as image information, and filling the image information into the environment model.

2. The IoT centralized monitoring method of industrial automation devices according to claim 1, characterized in that, the step of acquiring image information containing corresponding monitoring terminal parameters by the monitoring terminal when receiving the image acquisition mode comprises: performing photoelectric conversion on the collected image information, and performing statistics on the photoelectric conversion data to obtain a histogram; judging the histogram distribution change to judge whether there is haze and haze density; wherein, in a non-haze scene, the image histogram distribution is relatively uniform, in a haze scene, the image histogram is basically concentrated in the middle area, and the heavier the haze, the more concentrated the histogram; when it is judged from the histogram that there is haze, the image acquisition mode is determined as a haze-penetrating mode.

3. The IoT centralized monitoring method of an industrial automation device according to claim 1 or 2, characterized by, The step of sending monitoring instructions to the monitoring end according to the region identification result and acquiring detail images acquired by the monitoring end based on the monitoring instructions comprises: When the label obtained by the region identification process is the equipment region, an equipment region image is intercepted in the environment model, and range information related to the equipment region image is acquired; The equipment region image is subjected to contour recognition, the equipment size is determined, and monitoring parameters of the monitoring end are determined according to the equipment size and the position information; The monitoring parameters are sent to the corresponding monitoring end according to the range information.

4. The IoT centralized monitoring method of industrial automation devices according to claim 3, characterized in that, The step of sending monitoring instructions to the monitoring end according to the region identification result and acquiring detail images acquired by the monitoring end based on the monitoring instructions further comprises: When the label obtained by the region identification process is the personnel region, a personnel region image is intercepted in the environment model, and range information related to the personnel region image is acquired; The monitoring end is positioned according to the range information, the heat source information acquisition instruction is sent to the positioned monitoring end, and the image information containing the heat source information fed back by the monitoring end is received.

5. An industrial automation device IoT centralized monitoring apparatus for implementing the industrial automation device IoT centralized monitoring method according to any one of claims 1 to 4, characterized by The Internet of Things centralized monitoring device of the industrial automation equipment comprises the following modules: An image information acquisition module is configured to receive environment parameters input by a user, determine an image acquisition mode according to the environment parameters, and send the image acquisition mode to the monitoring end; when the image acquisition mode is received, the monitoring end acquires image information containing corresponding monitoring end parameters; A region identification module is configured to receive image information containing monitoring end parameters sent by the monitoring end, and perform region identification on the image information; the monitoring end parameters comprise a monitoring end number; A detail image acquisition module is configured to send monitoring instructions to the monitoring end according to the region identification result, and acquire detail images acquired by the monitoring end based on the monitoring instructions; A report generation module is configured to generate a monitoring report according to the detail images.

6. The IoT centralized monitoring arrangement of industrial automation equipment according to claim 5, characterized by, The region identification module comprises: A number reading unit is configured to receive image information containing monitoring end parameters sent by the monitoring end, and read the monitoring end number in the monitoring end parameters; A range determination unit is configured to acquire position information of the monitoring end according to the monitoring end number, and determine range information of the image information according to the position information and the monitoring end parameters; the range information is described by point position information relative to the workshop; An image filling unit is configured to fill the image information to a preset environment model according to the range information; A processing execution unit is configured to perform region identification on the environment model; wherein, a region label is generated by the region identification process, and the region label comprises an equipment region and a personnel region.

7. The IoT centralized monitoring arrangement of industrial automation equipment according to claim 6, characterized by, The image filling unit comprises: A positioning subunit is configured to read the point position information in the range information, and position a to-be-filled region in the environment model according to the point position information; A calculation subunit is configured to extract an existing image in the to-be-filled region, compare the image information with the existing image, and calculate a similarity according to the comparison result; An insertion subunit is configured to fill the image information to the preset environment model when the similarity reaches a preset similarity threshold; A correction subunit is configured to perform formal filling on the environment model when the similarity is less than the preset similarity threshold.

Images