Intelligent operation and maintenance platform architecture of industrial robot and intelligent equipment

Abstract

The invention relates to an intelligent operation and maintenance platform architecture for an industrial robot and intelligent equipment, and the architecture comprises a cloud platform, an edge system, and an industrial field device, and the cloud platform, the edge system, and the industrial field device are in control connection in sequence. The cloud platform comprises a basic connection service, a trusted big data service, a system operation and maintenance service and an industrial application service; the industrial field device is a device connected to the cloud platform and reports data of the intelligent device and the industrial robot. According to the industrial robot and intelligent equipment operation and maintenance platform architecture provided by the embodiment of the invention, technologies of the Internet of Things, big data, cloud computing, edge computing and the like are fused, and comprehensive technical breakthrough is realized from aspects of massive heterogeneous data access, various industry mechanism models, efficient and reliable algorithms, an intelligent management platform and the like; and the whole process of intelligent equipment comprehensive management of the industrial robot from upper-layer design to scientific research to lower-layer management is facilitated.

Description

Technical Field

[0001] The present application relates to the technical field of industrial robots, and in particular to an intelligent operation and maintenance platform architecture for industrial robots and intelligent equipment. Background Art

[0002] The problem of labor shortage in some manufacturing industries has become increasingly prominent, and replacing people with industrial robots has become a must for many companies. In the steel industry, the application of intelligent equipment and industrial robots has become a strategic direction for the development of intelligent manufacturing. Some companies at home and abroad have begun to conduct relevant research to uniformly manage key equipment, remotely monitor, explore control models, and optimize maintenance costs. However, the operating model of industrial robots for more companies is still based on single-equipment operation and outsourced maintenance. On the whole, it is mainly based on post-maintenance, and has not formed a systematic operation idea. Not only has it failed to achieve the original intention of reducing costs and increasing efficiency, but it has become a work difficulty and corporate burden for equipment operation and maintenance personnel. Intelligent equipment and robots are widely distributed, and the data transmission protocols they use are not the same. In order to fully analyze and utilize their data, a platform is needed to parse the protocols of the connected equipment and uniformly manage operation and maintenance;

[0003] The following problems exist in the operation and maintenance of robots in the existing technology: 1. Difficulty in monitoring the status of robots: Since the robot is in a dynamic operating state, there is no way to monitor the working status and position information of the robot in real time, and it is difficult to quickly respond to faults and scheduling needs; 2. Difficulty in decentralized management of robots: Due to the vast area of ​​robot service, the management of information such as the robot's deployment location, maintenance records, operating data, and spare parts usage is complex and difficult to manage; 3. Difficulty in troubleshooting and maintenance: Due to the relatively complete modularization and structural packaging of service robots, it is difficult to quickly and accurately identify the cause and location of equipment failures, resulting in long repair time and high maintenance costs; 4. Insufficient analysis of operational data: There is a lack of collection and unified management of robot work data, and it is even more difficult to analyze the data, and it is impossible to optimize the business operation model and management strategy. Therefore, we propose an intelligent operation and maintenance platform architecture for industrial robots and intelligent equipment. Summary of the invention

[0004] This application provides an intelligent operation and maintenance platform architecture for industrial robots and intelligent equipment to solve the above-mentioned problems.

[0005] This application provides an intelligent operation and maintenance platform architecture for industrial robots and intelligent equipment, including:

[0006] A cloud platform, an edge system and an industrial field device, wherein the cloud platform, the edge system and the industrial field device are controlled and connected in sequence;

[0007] The cloud platform includes basic connection services, trusted big data services, system operation and maintenance services, and industrial application services;

[0008] The industrial field equipment refers to equipment connected to the cloud platform, reporting data of intelligent equipment and industrial robots. The industrial field equipment includes intelligent equipment and robots, and performs data uploading and control instruction reception;

[0009] The edge system refers to a software application deployed on an edge intelligent gateway, which performs protocol data analysis on industrial field equipment, and specifically has the functions of data uploading, cloud control command conversion, data preprocessing, and breakpoint resumption;

[0010] The so-called cloud platform is responsible for communicating with the edge system, specifically receiving and storing data, issuing control instructions, real-time monitoring of alarms, remote operation and maintenance work order processing, knowledge base maintenance, and big data model analysis and training.

[0011] Preferably, the basic connection service is responsible for accessing and storing edge data, uniformly processing the intervening data, and forming a unified standard format to facilitate subsequent big data processing and training.

[0012] Preferably, the trusted big data service includes an industrial AI model library and industrial big data analysis, and the industrial AI model library contains trained AI algorithm models.

[0013] Preferably, the AI ​​algorithm model includes a predictive maintenance algorithm for industrial robots and intelligent equipment. Based on industrial big data analysis and deep learning models, it analyzes and predicts the operating status of industrial robots and provides reliable operation and maintenance suggestions for robots and intelligent equipment.

[0014] Preferably, the system operation and maintenance service includes basic operation and maintenance service components, authority and user management, system status monitoring and security management components.

[0015] Preferably, the industrial application service refers to the industrial application market, including low-code development of application components, application construction and deployment, application management, and application distribution, which is used for full life cycle management of industrial applications and facilitates users to quickly build industrial scenario applications based on application scenarios.

[0016] Preferably, the edge system is deployed on a self-developed edge intelligent terminal, which is responsible for processing and forwarding the received data. It mainly includes device collection and parsing services, data storage services, and edge computing and analysis services. The edge system supports offline operation and can still perform device data collection and monitoring services even when the network is disconnected.

[0017] Preferably, the equipment collection and analysis service refers to collecting equipment data and analyzing industrial protocols using the collected original operation data of intelligent equipment and robots, and can collect a variety of industrial protocols, such as EtherNet / IP, Profinet, ModbusTCP, DeviceNet, CC-LINK;

[0018] The data storage service refers to a storage service for data supported by the self-developed gateway, which can temporarily store the received data to prevent network interruption between the edge gateway and the platform and perform the function of resuming transmission after network disconnection;

[0019] The edge computing and analysis service refers to the pre-processing of edge data, processing the data between different devices into a unified format, and then uploading it to the cloud platform. It also supports real-time monitoring and early warning of device operation data, and can provide real-time early warning of abnormal data.

[0020] Preferably, the intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment also includes the construction of cloud platform and edge terminal communication and message transmission middleware, and the construction of the cloud platform also includes private cloud, public cloud and hybrid cloud.

[0021] Preferably, the long-cycle big data model training performed by the cloud platform includes a six-arm robot predictive maintenance model, a bearing vibration detection model, and an inspection robot predictive maintenance model. The cloud-edge collaborative data service of the cloud platform sets established project goals in the edge system, and performs data collection, data format conversion, data preprocessing, and data sending. After the cloud platform receives the edge data, it uses the cloud-edge collaborative algorithm training framework, and the data between factories can complete the training of the predictive maintenance model without leaving the factory.

[0022] The above technical solution provided by the embodiment of the present application has the following advantages compared with the prior art:

[0023] The industrial robot and intelligent equipment operation and maintenance platform architecture provided in the embodiment of the present application integrates technologies such as the Internet of Things, big data, cloud computing, and edge computing, and achieves all-round technological breakthroughs in terms of massive heterogeneous data access, multiple industry mechanism models, efficient and reliable algorithms, and intelligent management platforms. It helps to open up the entire process of comprehensive management of industrial robots and intelligent equipment from top-level design to scientific research to bottom-level management; (2) It is scalable and can meet the management needs of different types of robots and intelligent equipment in industrial scenarios, and can provide successful demonstration experience for the construction of a national industrial robot and intelligent equipment management system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0025] 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 or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0026] Figure 1 It is a schematic diagram of the overall principle of the intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment of the present invention;

[0027] Figure 2 This is a block diagram of the overall principle of the intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment of the present invention;

[0028] Figure 3 This is a schematic diagram of the intelligent operation and maintenance platform architecture control platform for industrial robots and intelligent equipment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0028] Various embodiments of the present application may exist in the form of a range. It should be understood that the description in the form of a range is only for convenience and simplicity and should not be understood as a hard limit to the scope of the present application; therefore, it should be considered that the range description has specifically disclosed all possible sub-ranges and single values ​​within the range. For example, it should be considered that the range description from 1 to 6 has specifically disclosed sub-ranges, such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6, etc., as well as single numbers within the range, such as 1, 2, 3, 4, 5 and 6, which are applicable regardless of the range. In addition, whenever a numerical range is indicated in the present application, it is meant to include any quoted numbers (fractions or integers) within the indicated range. Unless otherwise specified, various raw materials, reagents, instruments and equipment used in the present application, etc., can be purchased from the market or can be prepared by existing equipment.

[0029] In the present application, in the absence of any contrary description, the directional words used, such as "upper" and "lower", are specifically the directions of the drawings in the accompanying drawings. In addition, in the present application, the terms "include", "comprise", etc. refer to "including but not limited to". In the present application, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. In the present application, "and / or" describes the association relationship of the associated objects, indicating that three relationships may exist, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone. Wherein A, B can be singular or plural. In the present application, "at least one" refers to one or more, and "plural" refers to two or more. "At least one", "at least one of the following" or similar expressions refer to any combination of these items, including any combination of singular items or plural items. For example, "at least one of a, b, or c" or "at least one of a, b and c" can both mean: a, b, c, ab, i.e. a and b, ac, bc or abc, where a, b, c can be single or plural, respectively.

[0030] like Figures 1 to 3 As shown: This embodiment of the application provides a smart operation and maintenance platform architecture for industrial robots and intelligent equipment, including:

[0031] A cloud platform, an edge system and an industrial field device, wherein the cloud platform, the edge system and the industrial field device are controlled and connected in sequence;

[0032] The cloud platform includes basic connection services, trusted big data services, system operation and maintenance services, and industrial application services;

[0033] The industrial field equipment refers to equipment connected to the cloud platform, reporting data of intelligent equipment and industrial robots. The industrial field equipment includes intelligent equipment and robots, and performs data uploading and control instruction reception;

[0034] The edge system refers to a software application deployed on an edge intelligent gateway, which performs protocol data analysis on industrial field equipment, and specifically has the functions of data uploading, cloud control command conversion, data preprocessing, and breakpoint resumption;

[0035] The so-called cloud platform is responsible for communicating with the edge system, specifically receiving and storing data, issuing control instructions, real-time monitoring of alarms, remote operation and maintenance work order processing, knowledge base maintenance, and big data model analysis and training.

[0036] The basic connection service is responsible for accessing and storing edge data, uniformly processing the intervening data, and forming a unified standard format to facilitate subsequent big data processing and training.

[0037] The trusted big data service includes an industrial AI model library and industrial big data analysis, and the industrial AI model library contains trained AI algorithm models.

[0038] The AI ​​algorithm model includes a predictive maintenance algorithm for industrial robots and intelligent equipment. Based on industrial big data analysis and deep learning models, it analyzes and predicts the operating status of industrial robots and provides reliable operation and maintenance recommendations for robots and intelligent equipment.

[0039] The system operation and maintenance services include basic operation and maintenance service components, authority and user management, system status monitoring and security management components.

[0040] The industrial application service refers to the industrial application market, including low-code development of application components, application construction and deployment, application management, and application distribution, which is used for full life cycle management of industrial applications and facilitates users to quickly build industrial scenario applications based on application scenarios.

[0041] The edge system is deployed on the self-developed edge intelligent terminal, which is responsible for processing and forwarding the received data. It mainly includes device collection and analysis services, data storage services, and edge computing and analysis services. The edge system supports offline operation and can still perform device data collection and monitoring services even when the network is disconnected.

[0042] The equipment collection and analysis service refers to the collection of equipment data and analysis of industrial protocols using the collected raw data of the operation of intelligent equipment and robots. It can collect a variety of industrial protocols, such as EtherNet / IP, Profinet, ModbusTCP, DeviceNet, and CC-LINK.

[0043] The data storage service refers to a storage service for data supported by the self-developed gateway, which can temporarily store the received data to prevent network interruption between the edge gateway and the platform and perform the function of resuming transmission after network disconnection;

[0044] The edge computing and analysis service refers to the pre-processing of edge data, processing the data between different devices into a unified format, and then uploading it to the cloud platform. It also supports real-time monitoring and early warning of device operation data, and can provide real-time early warning of abnormal data.

[0045] The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment also includes the construction of cloud platform and edge communication and message transmission middleware. The construction of the cloud platform also includes private cloud, public cloud and hybrid cloud.

[0046] The long-cycle big data model training performed by the cloud platform includes a six-arm robot predictive maintenance model, a bearing vibration detection model, and an inspection robot predictive maintenance model. The cloud-edge collaborative data service of the cloud platform sets established project goals on the edge system, and performs data collection, data format conversion, data preprocessing, and data transmission. After the cloud platform receives the edge data, it uses the cloud-edge collaborative algorithm training framework, and the data between factories can complete the training of the predictive maintenance model without leaving the factory.

[0047] Implementation case, Figure 3 It is the overall platform architecture of the intelligent equipment and robot operation and management platform. The cloud platform includes independent data processing modules, big data modules and control modules. In terms of services, it provides users with various services based on the cloud platform, including model training, model publishing, model application, visualization display and industrial big data model library.

[0048] The cloud platform of the entire industrial robot and intelligent equipment intelligent operation and maintenance platform is divided into factory-level and group-level intelligent management and control platforms;

[0049] Among them, the group-level intelligent operation and maintenance platform is deployed on the public cloud server. The trusted big data service is mainly responsible for model training, data analysis, and data mining; the group resource collaboration service is mainly responsible for the collaborative processing of group resources, including remote diagnosis, resource collaboration, knowledge collaboration, etc.; the industrial application service mainly provides application services for industrial data, including low-code development components, application distribution and deployment, and application management; it also includes model aggregation training, summary training of factory-level data, and training of group-level equipment intelligent operation and maintenance models by equipment; it also includes unified management of user and organizational structure permissions.

[0050] The factory-level intelligent management and control platform is deployed in the private cloud servers of each factory. The data access and aggregation service is mainly responsible for accessing and storing the data reported by the edge, pre-processing the data, and forwarding the processed valid data to the group-level intelligent management and control platform through the rule engine component; the remote operation and maintenance service is responsible for sending the equipment training model to the edge, remote configuration of the edge terminal, and operation and maintenance work order management components; the basic support service is mainly responsible for user authority management and system security protection management.

[0051] The edge is mainly deployed at various production sites. It is a self-developed edge gateway, which is mainly responsible for data collection, industrial protocol parsing, processing and reporting of equipment data; at the same time, it runs the edge device model, runs the model sent by the cloud platform, monitors abnormal situations, and uploads alarm data to the cloud; it collaborates with the cloud platform to support data breakpoint resumption, and can maintain stable operation of business and data in offline conditions.

[0052] The present invention discloses an intelligent operation and maintenance platform architecture for industrial robots and intelligent equipment, which is an intelligent operation and maintenance platform architecture for industrial robots and intelligent equipment that integrates technologies such as big data, cloud computing, and edge computing. It realizes real-time dynamic monitoring of mobile robots, timely fault alarms, and accurate fault predictions, and promotes efficient services, intelligent management, and scientific decision-making.

[0053] The above is only a specific implementation of the present application, so that those skilled in the art can understand or implement the present application. It will be apparent to those skilled in the art that various modifications to these embodiments are possible, and the general principles defined in the present application can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown in the present application, but will conform to the widest scope consistent with the principles and novel features applied for by the present application.

Claims

1. A smart operation and maintenance platform architecture for industrial robots and intelligent equipment, characterized in that: include: A cloud platform, an edge system and an industrial field device, wherein the cloud platform, the edge system and the industrial field device are controlled and connected in sequence; The cloud platform includes basic connection services, trusted big data services, system operation and maintenance services, and industrial application services; The industrial field equipment refers to equipment connected to the cloud platform, reporting data of intelligent equipment and industrial robots. The industrial field equipment includes intelligent equipment and robots, and performs data uploading and control instruction reception; The edge system refers to a software application deployed on an edge intelligent gateway, which performs protocol data analysis on industrial field equipment, and specifically has the functions of data uploading, cloud control command conversion, data preprocessing, and breakpoint resumption; The so-called cloud platform is responsible for communicating with the edge system, specifically receiving and storing data, issuing control instructions, real-time monitoring of alarms, remote operation and maintenance work order processing, knowledge base maintenance, and big data model analysis and training.

2. According to claim 1, the intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment is characterized by: The basic connection service is responsible for accessing and storing edge data, uniformly processing the intervening data, and forming a unified standard format to facilitate subsequent big data processing and training.

3. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 1, characterized in that: The trusted big data service includes an industrial AI model library and industrial big data analysis, and the industrial AI model library contains trained AI algorithm models.

4. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 3 is characterized by: The AI ​​algorithm model includes a predictive maintenance algorithm for industrial robots and intelligent equipment. Based on industrial big data analysis and deep learning models, it analyzes and predicts the operating status of industrial robots and provides reliable operation and maintenance recommendations for robots and intelligent equipment.

5. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 1, characterized in that: The system operation and maintenance services include basic operation and maintenance service components, authority and user management, system status monitoring and security management components.

6. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 1, characterized in that: The industrial application service refers to the industrial application market, including low-code development of application components, application construction and deployment, application management, and application distribution, which is used for full life cycle management of industrial applications and facilitates users to quickly build industrial scenario applications based on application scenarios.

7. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 1, characterized in that: The edge system is deployed on the self-developed edge intelligent terminal, which is responsible for processing and forwarding the received data. It mainly includes device collection and analysis services, data storage services, and edge computing and analysis services. The edge system supports offline operation and can still perform device data collection and monitoring services even when the network is disconnected.

8. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 7, characterized in that: The equipment collection and analysis service refers to the collection of equipment data and analysis of industrial protocols using the collected raw data of the operation of intelligent equipment and robots. It can collect a variety of industrial protocols, such as EtherNet / IP, Profinet, ModbusTCP, DeviceNet, and CC-LINK. The data storage service refers to a storage service for data supported by the self-developed gateway, which can temporarily store the received data to prevent network interruption between the edge gateway and the platform and perform the function of resuming transmission after network disconnection; The edge computing and analysis service refers to the pre-processing of edge data, processing the data between different devices into a unified format, and then uploading it to the cloud platform. It also supports real-time monitoring and early warning of device operation data, and can provide real-time early warning of abnormal data.

9. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 1, characterized in that: The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment also includes the construction of cloud platform and edge communication and message transmission middleware. The construction of the cloud platform also includes private cloud, public cloud and hybrid cloud.

10. The intelligent operation and maintenance platform architecture of industrial robots and intelligent equipment according to claim 1, characterized in that: The long-cycle big data model training performed by the cloud platform includes a six-arm robot predictive maintenance model, a bearing vibration detection model, and an inspection robot predictive maintenance model. The cloud-edge collaborative data service of the cloud platform sets established project goals on the edge system, and performs data collection, data format conversion, data preprocessing, and data transmission. After the cloud platform receives the edge data, it uses the cloud-edge collaborative algorithm training framework, and the data between factories can complete the training of the predictive maintenance model without leaving the factory.

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