An industrial equipment detection processing method and system based on the internet of things

Abstract

This invention discloses an industrial equipment detection and processing method based on the Internet of Things (IoT), comprising at least one acquisition device, an edge side, and a cloud computing center electrically connected in sequence; the edge side includes a management module and a component module library, the component module library including multiple component modules; the acquisition device is connected to the edge side; the method is characterized by the following steps: Step 1: Selecting component modules from the component module library and setting the connection method for all component modules; Step 2: Based on the selection and setting in Step 1, the management module constructs a topology graph and calculates the current feature value for each component module in the topology graph; Step 3: Based on the feature value of each component module in the topology graph of the previous step, the management module reconstructs the topology graph and calculates the current feature value for each component module in the topology graph; Step 4: Repeating Step 3 until the feature values ​​of all component modules in the current topology graph are the same; Step 5: If the calculation result of Step 4 shows that the connection method selected and set in Step 1 conforms to the rules, then proceed to Step 6; if the calculation result of Step 4 shows that the connection method selected and set in Step 1 does not conform to the rules, then proceed to Step 1; Step 6: The acquisition device obtains the signal from the industrial equipment and sends the signal to the edge side; Step 7: The edge side calculates and obtains the target data value. The method of this invention can improve the application scope of the Internet of Things and enhance the agility of software systems.

Description

Technical Field

[0001] This invention relates to the field of automation, specifically to the inspection and processing of industrial equipment. Background Technology

[0002] Currently, equipment detection and diagnosis generally involve installing sensors on mechanical equipment to obtain corresponding signals, processing the data, and then drawing conclusions. For example, in the diagnosis of rolling bearing faults, existing technologies include CN111220388A, CN112857806A, CN107356432B, CN108956618B, CN102607845B, CN103542929A, and other technical solutions. These solutions all rely on fixed methods to collect, process, and detect data, ultimately leading to a conclusion.

[0003] The Industrial Internet of Things (IIoT) integrates various data acquisition and control sensors and controllers with sensing and monitoring capabilities, along with technologies such as mobile communication and intelligent analytics, into all aspects of industrial production processes. This significantly improves manufacturing efficiency, enhances product quality, reduces product costs and resource consumption, ultimately elevating traditional industries to a new stage of intelligent manufacturing. In terms of application, IIoT applications are characterized by real-time performance, automation, embedded (software) integration, security, and interconnectivity.

[0004] Industrial IoT extensively utilizes plug-ins. Plug-ins can be used in industries such as power, water conservancy, factories, and IoT; they allow for arbitrary simulation and configuration of actual field scenarios; and component configuration is flexible and easily expandable. Such IoT applications have advantages.

[0005] The prior art CN112326287A discloses an Internet of Things-based remote operation and maintenance system for construction machinery, including a status monitoring device and a remote monitoring center. The status monitoring device is installed on the construction machinery to collect the operating status data of each component in the construction machinery and send the collected operating status data to the remote monitoring center. The operating status data includes temperature data and vibration signal data of each component. The remote monitoring center is used to perform abnormal status analysis based on the received operating status data. When the analysis detects an abnormality in the operating status data corresponding to a certain component in the construction machinery, it issues an operation and maintenance alarm.

[0006] Prior art CN112327734A discloses an internet-based remote monitoring system for construction machinery, comprising: a monitoring terminal and a remote monitoring center. The monitoring terminal is installed on the construction machinery to monitor its operating status in real time and send the acquired operating status data to the remote control center. The remote monitoring center is communicatively connected to the monitoring terminal, receives the construction machinery operating status data sent by the monitoring terminal, performs anomaly analysis based on the acquired data, and issues an alarm when an abnormal state is detected. Prior art CN114548437A also discloses a similar method or system.

[0007] With the development of the Industrial Internet, personalized industrial software has become a reality. Different factories desire more convenient operation to achieve personalized functionality or meet evolving development needs. To apply the Industrial Internet of Things (IIoT) to equipment detection and diagnostics, thereby creating a simplified and personalized industrial detection data processing system and method while shortening the development cycle, this invention proposes an IoT-based industrial equipment data processing method and system. Summary of the Invention

[0008] The purpose of this invention is to provide an industrial equipment detection and processing method and system based on the Internet of Things.

[0009] To achieve the above-mentioned technical objectives, the present invention will adopt the following technical solution:

[0010] An IoT-based industrial equipment detection and processing method includes at least one data acquisition device, an edge device, and a cloud computing center electrically connected in sequence; the edge device includes a management module and a component module library, the component module library including multiple component modules; the data acquisition device is connected to the edge device; the method includes the following steps:

[0011] Step 1: Select a component module from the component module library and set the connection method for all component modules;

[0012] Step 2: Based on the selections and settings in Step 1, the management module constructs a topology graph and calculates the current feature value for each component module in the topology graph;

[0013] Step 3: Based on the feature values ​​of each component module in the topology graph from the previous step, the management module reconstructs the topology graph and calculates the current feature value for each component module in the topology graph;

[0014] Step 4: Repeat step 3 until all component modules in the current topology graph have the same feature values;

[0015] Step 5: If the calculation result of Step 4 shows that the connection method selected and set in Step 1 conforms to the rules, then proceed to Step 6; if the calculation result of Step 4 shows that the connection method selected and set in Step 1 does not conform to the rules, then proceed to Step 1.

[0016] Step 6: The acquisition device obtains the signal from the industrial equipment and sends the signal to the edge side;

[0017] Step 7: Calculate and obtain the target data value on the edge side.

[0018] Furthermore, the characteristic value is either 0 or 1; when the current component module has no input signal connection, the characteristic value is recorded as 0, and when the current component module has an input signal connection, the characteristic value is recorded as 1.

[0019] Furthermore, the rule set in step 5 is that the feature value of all component modules is 0.

[0020] Furthermore, it also includes step 8, which transmits the target data value from step 7 to the cloud computing center.

[0021] Furthermore, in step 5, if the calculation result of step 4 shows that the connection method selected and set in step 1 does not conform to the rules before entering step 1, step 5.1 is also included, in which suggestions for modifying the connection methods of all component modules are given.

[0022] Furthermore, the component module library also includes a first set of component modules, a second set of component modules, a third set of component modules, and a fourth set of component modules.

[0023] Furthermore, when users select component modules and set connection methods, the management module provides suggestions for selecting a set of component modules.

[0024] An industrial equipment detection and processing system based on the Internet of Things, which uses the above method, is characterized in that the edge side is a software module deployed and operated on an ARM hardware architecture.

[0025] Furthermore, the data acquisition device is wirelessly connected to the edge side.

[0026] Furthermore, the data acquisition devices include vibration, temperature, torque, pressure, and humidity sensors.

[0027] In summary, the beneficial effects of this invention are: 1. It provides an agile connection method for IoT-based processing devices, enabling rapid personalized installation and debugging. 2. It establishes communication between component modules that perform certain functions and manages these modules, thereby triggering notifications or monitoring events under different environments or conditions. 3. It allows for the dynamic addition, modification, deletion, and allocation of algorithm software or functions at the edge without affecting operation, dynamically realizing network connection, data acquisition, algorithm calculation, and data distribution. 4. After manual configuration, the edge software will not enter an infinite loop. Attached image description:

[0028] Figure 1 This is a schematic diagram of the component modules of the present invention;

[0029] Figure 2 This is a schematic diagram of the component module configuration of the present invention;

[0030] Figure 3 This is a schematic diagram of the intermediate topology of the component modules of the present invention after testing;

[0031] Figure 4 This is a schematic diagram of the final topology of the component modules of the present invention after testing;

[0032] Figure 5 This is a schematic diagram illustrating the configuration of the present invention using a plug-in as an example. Detailed implementation method:

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0034] See appendix Figure 1 , attached Figure 1A schematic diagram of a three-layer edge architecture is shown. The edge side is divided into three layers: input, processing, and output. Data output from the output layer then reaches the receiver layer. The receiver layer acquires device data from the edge side via wired or wireless protocols through plugins such as PLCs, sensors (including vibration, temperature, torque, pressure, and humidity sensors), Scada systems, Kafka, RabbitMQ, and RocketMQ. The edge side provides a multiplexed bidirectional transmission protocol for data communication using PAIR, PIPELINE, PUB / SUB, REQ / REP, BUS, and SURVEY. Users select different algorithm processing plugins to process the device data, obtain the final results, and report them to the cloud computing center. All the plugins and communication methods mentioned above are common in this field.

[0035] Figure 1 The diagram illustrates several functions that could potentially be implemented by component modules on the edge side. Each of these functions can correspond to a single component module. In industrial applications, Figure 1 The component modules shown can generally perform certain functions on their own. To achieve a specific purpose, they can be combined to achieve more complex purposes.

[0036] The processing procedure for vibration acceleration data from one of the channels on the edge side is as follows:

[0037] Users select the appropriate component modules based on the current situation and set the processing flow. The selection and setting results are shown in the attached figure. Figure 2 As shown. These component modules can be represented or named as plugins.

[0038] Appendix Figure 2In this process, data signals, such as vibration acceleration data, are collected through acquisition devices. At the processing nodes, data is distributed to multiple topics, nodes, or component modules as needed by the user. The edge-side management module treats all topics, nodes, or component modules with information inflow or outflow as points in the topology map for sorting and detection. For example, "RocketMQ Plugin 1" has three topics: "Iot / topicA," "Iot / topicB," and "Iot / topicC"; "RocketMQ Plugin 2" has three topics: "Iot / topicX," "Iot / topicY," and "Iot / topicZ"; and "RocketMQ Plugin 3" has three topics: "Iot / topicX," "Iot / topicE," and "Iot / topicF." Topics are treated as detection points for topology detection. The edge-side "PLC Plugin," "Sensor Plugin," and "RocketMQ Plugin 1" collect acceleration data from factory equipment to reduce the pressure on cloud processing and effectively improve the utilization rate of edge devices. The data is processed at the edge, and the final results are reported to the receiver.

[0039] To check the topology of the vibration acceleration data and avoid infinite loops, the management module removes detection points with eigenvalues ​​of 0 from left to right of the graph, thus separating them. After removing "PLC Plugin," "Sensor Plugin," "Iot / topicA," "Iot / topicB," and "Iot / topicC," the component's topology is shown in the attached figure. Figure 3 In this invention, the feature value is either 0 or 1; when the current component module has no input signal connection, the feature value is recorded as 0; when the current component module has an input signal connection, the feature value is recorded as 1. For example, when a component module only outputs a signal to the next component module without any signal input, the feature value is recorded as 0; if the component module receives other signal inputs while simultaneously outputting a signal to the next component module, the feature value is recorded as 1.

[0040] For appendix Figure 3 The topology map is then used to calculate the feature values ​​of each detection point. After multiple calculations, the result is shown in the attached figure. Figure 4 The topology diagram shown is attached. Figure 4 In this process, the feature value of each detection point is 1. At this point, it is determined that the final topology map has been obtained. It is then discovered that there are cyclical flow patterns within this topology map, such as... Figure 4 As shown by the dashed lines in the diagram. Assuming the connection method of the dashed lines in the diagram is the initially set connection method, then... Figure 4 There is a real-world example of a vicious cycle in this process.

[0041] Figure 4The dotted lines in the middle reflect... Figure 2 In this system, due to the manually configured connection method, an infinite loop occurs and the system fails to run at the edge. Connection errors cannot be detected manually.

[0042] The processing or detection shown in the above diagrams from left to right is merely for illustrative purposes. In this invention, the topology graph is drawn from left to right in the direction of information flow; therefore, detection is performed from left to right. If, in this invention, the topology graph represents the direction of information flow from right to left or from top to bottom, then detection should also be performed in the corresponding direction.

[0043] The calculation method of the present invention is based on the principles of computer graphics. It abstracts the component modules of the data processing device into a topological graph, and then performs abstract calculations on the topological graph, thereby avoiding the data processing method from getting stuck in an infinite loop.

[0044] get Figure 4 After reviewing the topology diagram, the management module discovered that the connection shown by the dashed line caused an infinite loop. In this invention, the above will not be directly displayed to the user. Figure 4 The topology graph is used by the management module to determine that all current feature values ​​are 1, thus deriving... Figure 2 The structure shown is not functioning correctly. In this case, the management module indicates that the connection shown by the dashed line exists in the topology diagram.

[0045] After the above prompts are given, the edge side further accepts manual settings. Referring to the prompts given by the management module, module deletions or connection adjustments are made to the component modules. After the adjustments are completed, the management module repeats the aforementioned tests.

[0046] In this invention, after the edge side is set and detected, the corresponding data processing is performed.

[0047] See Figure 2 , Figure 2 Although it is a topology diagram, it shows the nodes through which the signal flows. The data collected from the acquisition module is cleaned and then sent to data processing plugins such as the "noise reduction plugin," "integration calculation," and "RocketMQ plugin 2" topicX, before being sent to the next process.

[0048] The "Denoising Processing Plugin" sends data to the "Streaming Computing Plugin," "Kuiceality Algorithm Plugin," and "Variance Algorithm Plugin" for data accumulation, eigenvalue calculation, and deviation analysis. Finally, it sends data from the "Trend Algorithm," "Integral Algorithm," and "Spectrum Analysis" algorithms to the "RocketMQ Plugin 3" topic. "RocketMQ Plugin 3" includes three topics: "Iot / topicX," "Iot / topicE," and "Iot / topicF."

[0049] exist Figure 2 In this context, if "IoT / topicX" is selected, then during data transmission and flow, the following will occur: Figure 2 The dotted line in the diagram indicates that the information flow along this dotted line can lead to an infinite loop. By implementing checks in the aforementioned management module and adjusting the component modules, the infinite loop problem can be resolved, ultimately ensuring the method runs normally.

[0050] The present invention provides an IoT-based industrial equipment detection and processing method, comprising at least one acquisition device; the acquisition device can be a sensor for acquiring various signals such as light, electricity, and vibration; the edge side can be a microcontroller or a containerized deployment running on an ARM hardware architecture; and the cloud computing center is a remote computing center. The cloud computing center is provided with unified control and configuration by the device. The acquisition device, the edge side, and the cloud computing center are connected by signals. The connection can be wired or wireless, such as Bluetooth, Wi-Fi, or common wireless connections like 4G or 5G. The edge side includes a management module and a component module library, the component module library containing multiple component modules; the acquisition device is connected to the edge side; the component modules are connected through certain connection methods, which can realize certain processing functions; these processing functions are manually selected and set according to actual needs. The present invention also includes the following steps:

[0051] Step 1: Manual operation, select component modules from the component module library and set the connection method of all component modules; due to different applicable occasions and required functions, in this invention, it is necessary to manually examine and select the planned component modules, and at the same time conceive the connection method of the component modules.

[0052] Step 2: Based on the selection and settings in Step 1, the management module constructs a topology diagram and calculates the current characteristic value for each component module in the topology diagram. This characteristic value is either 0 or 1; when the current component module has no input signal connection, the characteristic value is recorded as 0; when the current component module has an input signal connection, the characteristic value is recorded as 1. This characteristic value is used to calculate whether the set connection method of the component module meets specific requirements.

[0053] Step 3: Based on the feature values ​​of each component module in the topology graph from the previous step, the management module reconstructs the topology graph and calculates the current feature value for each component module in the topology graph;

[0054] Step 4: Repeat step 3 until the feature values ​​of all component modules in the current topology graph are the same; for example, the final calculated feature values ​​are all 0 or all 1.

[0055] Step 5: If the calculation result of Step 4 shows that the connection method selected and set in Step 1 conforms to the rule, proceed to Step 6; if the calculation result of Step 4 shows that the connection method selected and set in Step 1 does not conform to the rule, proceed to Step 1. The rule is: if all feature values ​​are 0, it is considered that there is no cyclic fault problem in the manual setting. If all feature values ​​are 1, it is considered that there is a cyclic fault problem.

[0056] Step 6: The acquisition device obtains the signal from the industrial equipment and sends the signal to the edge side; after being sent to the edge side, the signal passes through the plug-in at each detection point in sequence and is calculated accordingly.

[0057] Step 7: Calculate and obtain the target data value on the edge side.

[0058] After obtaining the target data, it is transmitted to the cloud computing center via the transmission module.

[0059] In step 5, if the calculation result of step 4 shows that the connection method selected and set in step 1 does not conform to the rules before entering step 1, step 5.1 is also included, in which suggestions for modifying the connection methods of all component modules are given.

[0060] The steps described above are performed at the edge, where the component modules are deployed and operated on the ARM hardware architecture.

[0061] See appendix Figure 5 In the edge side, when selecting a component module, taking a plugin as an example, first select the plugin, and then configure the plugin; after configuration, submit the configuration. The configuration is checked by the management module. If the configuration is invalid, return to the plugin configuration step and reconfigure the plugin under the prompt; if the configuration is valid, the configuration is saved.

[0062] The above description is merely a specific embodiment of this application. Under the guidance of the above teachings, those skilled in the art can make other improvements or modifications based on the above embodiments. Those skilled in the art should understand that the above specific description is only to better explain the purpose of this application, and the scope of protection of this application should be determined by the scope of the claims.

[0063] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features but not others included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.

Claims

1. An industrial equipment detection and processing method based on the Internet of Things, comprising at least one data acquisition device, an edge device, and a cloud computing center electrically connected in sequence; the edge device includes a management module and a component module library, the component module library including multiple component modules; the data acquisition device is connected to the edge device; characterized in that... Includes the following steps: Step 1: Select a component module from the component module library and set the connection method for all component modules; Step 2: Based on the selection and settings in Step 1, the management module constructs a topology graph. When the current component module has no input signal connection, the feature value is recorded as 0; when the current component module has an input signal connection, the feature value is recorded as 1. Step 3: Based on the feature values ​​of each component module in the topology graph from the previous step, the management module reconstructs the topology graph and calculates the current feature value for each component module in the topology graph; Step 4: Repeat step 3 until all component modules in the current topology graph have the same feature values; Step 5: If the calculation result of Step 4 is the connection method selected and set in Step 1, and all feature values ​​are 0, then it is considered that there is no cycle fault problem in the manual setting, and proceed to Step 6; if the calculation result of Step 4 is the connection method selected and set in Step 1, and all feature values ​​are 1, then it is considered that there is a cycle fault problem, and proceed to Step 1. Step 6: The acquisition device obtains the signal from the industrial equipment and sends the signal to the edge side; Step 7: Calculate and obtain the target data value on the edge side.

2. The industrial equipment detection and processing method based on the Internet of Things according to claim 1, characterized in that: It also includes step 8, which transmits the target data value from step 7 to the cloud computing center.

3. The industrial equipment detection and processing method based on the Internet of Things according to claim 1, characterized in that: In step 5, if the calculation result of step 4 shows that the connection method selected and set in step 1 does not conform to the rules before entering step 1, step 5.1 is also included, in which suggestions for modifying the connection methods of all component modules are given.

4. The industrial equipment detection and processing method based on the Internet of Things according to claim 1, characterized in that: It also includes the first set of component modules, the second set of component modules, the third set of component modules, and the fourth set of component modules in the component module library.

5. The industrial equipment detection and processing method based on the Internet of Things according to claim 4, characterized in that: When a user selects a component module and sets the connection method, the management module provides suggestions for selecting a set of component modules.

6. An industrial equipment detection and processing system based on the Internet of Things, which uses the method as described in any one of claims 1-5, characterized in that, The edge side consists of software modules that are deployed and run on the ARM hardware architecture.

7. The industrial equipment detection and processing system based on the Internet of Things according to claim 6, characterized in that: The data acquisition device is connected to the edge wirelessly.

8. The industrial equipment detection and processing system based on the Internet of Things according to claim 6, characterized in that: The data acquisition devices are vibration, temperature, torque, pressure, and humidity sensors.

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