Heterogeneous equipment management and automatic inspection system based on model assembly

Abstract

The invention provides a heterogeneous equipment management and automatic inspection system based on model assembly, belongs to the technical field of heterogeneous equipment management and automatic inspection, provides a heterogeneous equipment management and automatic inspection system and method based on model assembly, and aims to solve the problems that heterogeneous equipment management is complex, the inspection efficiency is low, and the inspection efficiency is high. At present, effective inspection plans and intelligent scheduling are lacked, the management efficiency is low, the equipment availability is poor, and the maintenance cost is high. According to the system, the complexity of equipment is abstracted by using an equipment model, the equipment maintenance difficulty is reduced by using a scene mechanism, the equipment availability is improved by using an intelligent inspection mechanism, and an administrator is allowed to use a unified interface to manage and inspect various types of equipment. The method has a wide application prospect in industrial automation, intelligent transportation, smart home and other scenes.

Description

Technical Field

[0001] The present invention relates to the technical field of heterogeneous equipment management and automated inspection, and in particular to a heterogeneous equipment management and automated inspection system based on model combination. Background Art

[0002] With the rapid development of technologies such as the Internet of Things and edge computing, many companies and organizations face numerous challenges in managing a large number of heterogeneous devices. Devices produced by different manufacturers not only have their own unique communication protocols, but also have different data formats and management methods, which leads to data silos between devices and affects data sharing and information flow. Traditional equipment management models are often difficult to adapt to this complex equipment environment, which usually leads to high maintenance costs, reduced equipment availability, and potential safety hazards. At the same time, existing inspection measures usually rely on manual operations, which may cause errors due to human factors and are far from achieving real-time monitoring and rapid response. With the increasing demand for industrial automation and intelligence, there is an urgent need for an efficient system and method that can uniformly manage heterogeneous devices and realize comprehensive automated inspections to improve management efficiency and equipment availability. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides a heterogeneous equipment management and automated inspection system based on model combination, which makes full use of equipment model abstraction, intelligent inspection mechanism and dynamic adjustment strategy, and comprehensively manages heterogeneous equipment and its inspection tasks through standardized equipment models, effective inspection scheduling and resource optimization. The ultimate goal is to significantly improve equipment management efficiency, reduce maintenance costs, improve equipment reliability and safety, and at the same time improve the intelligence level of the inspection process to ensure higher quality services and realize full life cycle management of equipment management.

[0004] The technical solution of the present invention is:

[0005] A heterogeneous equipment management and automated inspection system based on model combination, including:

[0006] The device model management module is used to abstract different types of devices into a unified model, which includes information such as device attributes, operation interfaces, and communication protocols;

[0007] The scenario model assembly module is used to dynamically generate equipment assembly solutions based on equipment characteristics and management requirements to achieve flexible equipment management;

[0008] The automated inspection engine performs automated inspection tasks based on device models and configuration information, including status monitoring, performance analysis, and safety checks.

[0009] Furthermore,

[0010] The device model management module conveniently stores and retrieves model information of various heterogeneous devices through the device model library, and dynamically updates it in combination with user feedback.

[0011] The scenario model assembly module automatically adjusts the equipment assembly plan according to real-time data and equipment status, and generates customized inspection tasks based on actual scenarios.

[0012] The automated inspection engine includes an inspection plan generation module, a data collection and analysis module, and a result feedback and optimization module.

[0013] Furthermore,

[0014] The inspection plan generation module can dynamically plan the time and sequence of inspection tasks according to the scheduling algorithm and the importance of equipment to ensure that key equipment takes priority in the inspection tasks.

[0015] The inspection results are displayed through a visualization tool to help users quickly identify and solve equipment problems.

[0016] The inspection tasks can be manually scheduled by management personnel or automatically generated by the system, and have a management mechanism for setting priorities to ensure the effective execution of various tasks.

[0017] The system working steps are as follows:

[0018] a) Collect and store the attributes and status information of heterogeneous devices;

[0019] b) Generate a unified device model based on device type;

[0020] c) Implement dynamic configuration mechanism to optimize equipment management;

[0021] d) Perform automated inspection tasks and record inspection results;

[0022] e) Feedback inspection results through a visual interface to assist in the rapid resolution of equipment problems;

[0023] f) Dynamically adjust and optimize equipment management strategies based on inspection results and equipment status.

[0024] Going further,

[0025] Device model management module: Through standardized device models, ensure that devices from different manufacturers can interoperate smoothly in the system, simplify management processes, and improve overall efficiency. This module implements a unified description of device attributes and provides a standardized interactive interface to ensure the openness and scalability of the system for future compatibility and upgrades.

[0026] Scenario model assembly module: According to the characteristics of the equipment and the requirements of the application scenario, the equipment assembly plan is flexibly generated to solve the problem of collaborative work between equipment. By optimizing the collaborative relationship of the equipment, the efficient collaboration of the equipment in the same workflow is ensured, and the production and inspection efficiency is improved. This module supports user-defined scenario models to adapt to changing business needs.

[0027] Automated inspection engine: This engine is responsible for real-time monitoring of the external environment and equipment status, and timely and dynamically adjusts inspection tasks to ensure continuous and efficient operation of the system. It uses intelligent algorithms for careful scheduling, based on historical data and real-time status information, to maximize inspection efficiency and ensure that key equipment receives full attention in the inspection plan.

[0028] Going further,

[0029] Device Model Management Module

[0030] It plays a vital role in the entire system. It greatly simplifies the subsequent management process and improves the interoperability and flexibility of the system by abstracting different types of heterogeneous devices into a unified model.

[0031] Device model library: As the core component of the device model abstraction layer, it stores standardized models of various heterogeneous devices and provides a convenient and efficient device management solution. The model library covers multiple types of devices such as sensors, actuators, machine vision devices, programmable logic controllers (PLCs), flow meters, and thermostats. Each device model contains unique parameters and description information to facilitate users to quickly find and call it in subsequent management.

[0032] Convenient model search: Users can quickly search for suitable device models by device model, type, function, etc., avoiding the tedious process of re-establishing models. The design of the model library follows the principle of high modularity, allowing users to easily add new device models according to business needs, adapt to market changes, and maintain management flexibility.

[0033] Model mapping and conversion:

[0034] Physical device information mapping: The system uses an automated mechanism to identify and extract key information about physical devices, and maps it into corresponding device models to ensure the uniformity and interoperability of device information. Through this process, key information including the device's operating status, connection information, fault codes, etc. can be effectively managed.

[0035] Efficient data integration: With standardized interfaces, the information in the equipment model can be seamlessly integrated with other systems (such as monitoring systems and maintenance management systems). This interoperability greatly improves the efficiency of equipment management. For example, when the equipment status is updated, the system can quickly upload real-time data to the database and compare and analyze it with historical operating data to provide sufficient information for decision-making.

[0036] Scene model assembly module

[0037] The scenario model assembly module is responsible for flexibly generating equipment assembly solutions to cope with changing application scenarios. It aims to optimize equipment utilization efficiency through scenario management and model management, while improving the system's responsiveness.

[0038] Scenario model assembly module: built on detailed scenario management. By defining equipment object models related to application scenarios, the system can ensure more accurate equipment management and deployment. For example, in a factory production line, in order to cope with product changes and process adjustments, the system will flexibly generate specific equipment assembly solutions based on real-time demand conditions to ensure efficient use of resources.

[0039] Equipment object model definition: According to different application scenarios (such as production lines, maintenance sites, environmental monitoring, etc.), the equipment object model is defined to include not only equipment categories and functional characteristics, but also its role and positioning in related scenarios. These models not only contain the basic attributes of the equipment (such as equipment type, name, description), but also elaborate on the tasks, collaborative relationships and interactions that need to be performed in specific scenarios. For example, the object model of a conveyor belt may define its carrying capacity, speed adjustment mechanism, and coordinated operation parameters with other equipment (such as sensors, processors, etc.).

[0040] Model management of specific equipment: By dynamically creating specific equipment models, the system can manage the characteristics and functions of each equipment in real time and adjust them at any time as needed. For example, when a new equipment is introduced or upgraded, the system automatically generates its data model to reflect the latest technical parameters, ensuring that the equipment information is always up to date and improving the accuracy of fault diagnosis and maintenance.

[0041] Definition and management of scenario models: Users can customize scenario models according to different application scenarios (such as production lines, maintenance sites, environmental monitoring, etc.). Each scenario model contains the device type, functional requirements, and operating modes related to the scenario. This flexibility ensures that the device can operate efficiently in a specific scenario. For example, in an environmental monitoring scenario, users may define a model to integrate temperature and humidity sensors, air quality monitors, and alarm systems to achieve comprehensive monitoring of environmental parameters.

[0042] Association between scenarios and models: The system can classify scenarios and closely associate specific scenarios with corresponding equipment object models for dynamic management. This linkage ensures rapid response to business needs. For example, when a device is marked as a key device on a production line, the system can automatically associate it with the corresponding inspection scenario to ensure that it receives priority attention in subsequent actual operations and reduce the risk of potential equipment failure.

[0043] Model update mechanism: As the usage of equipment changes, the equipment model should be updated flexibly. Equipment operation data (such as working hours, fault records, maintenance records, etc.) will be fed back to the management system in real time, and then the model parameters will be automatically adjusted to reflect the current operation status and performance indicators of the equipment in real time. In this way, the accuracy and timeliness of management information can be ensured, ensuring the effectiveness and reliability of decision support.

[0044] Task scheduling and management: Through the cycle management mechanism, the system can dynamically generate inspection tasks to ensure that the inspection process is more targeted and efficient. For example, the system may set a specific time interval or trigger an inspection task based on the equipment operation status, thereby achieving planned inspections and improving equipment operation efficiency.

[0045] Task scheduling generation and priority management: The system automatically generates reasonable inspection tasks based on the equipment's historical operating data, status information, fault records, and priority settings. At the same time, priorities are set to ensure that critical equipment and high-risk equipment receive more attention. For example, the system may set high priority for equipment with high failure frequency and critical production tasks, thereby optimizing the overall effectiveness of the inspection plan and ensuring that no unexpected equipment downtime occurs.

[0046] Automated inspection engine

[0047] The automated inspection engine is an important component of the system. It is responsible for executing preset inspection tasks and collecting and analyzing data from equipment operation in real time to enhance fault response efficiency and reduce potential losses caused by equipment failures.

[0048] Inspection task scheduling:

[0049] Intelligent scheduling algorithm: An intelligent scheduling algorithm based on multiple factors is used to comprehensively consider the device priority, historical fault records and real-time monitoring data to generate and optimize inspection tasks. This dynamic calculation method not only considers the current operating status of each device, but also analyzes the dependencies between devices to achieve the best configuration and resource utilization of inspection tasks. For example, if a certain device has a high failure rate, the scheduling system will ensure that the device takes priority in the inspection plan when generating inspection tasks, thereby reducing the risk of sudden failures.

[0050] Dynamic adjustment mechanism: During the inspection process, the system is highly flexible and can dynamically adjust the inspection tasks according to real-time monitoring data. For example, when the system detects that a certain device has a high temperature or abnormal vibration, the system will quickly prioritize the device in the next round of inspection tasks. Through big data and artificial intelligence technology, the system can predict and identify potential faults, thereby ensuring that equipment problems can be handled in the first place, minimizing downtime and maintenance costs.

[0051] Visual dashboard: The system provides a friendly visual interface, allowing managers to intuitively view the status and operating data of all equipment. Through data visualization, inspection results, historical data analysis and operating trends are clear at a glance, helping decision makers quickly understand the system operation status and make corresponding maintenance plans.

[0052] Fault warning and handling:

[0053] Intelligent early warning mechanism: Based on the historical data and real-time monitoring of the equipment, the system can realize fault early warning. When the operating parameters of the equipment exceed the set range or potential risks occur, the system will automatically generate an alarm and notify the relevant operation and maintenance personnel through mobile applications or emails to ensure that the problem can be paid attention to in the first time.

[0054] Automated processing suggestions: After identifying a problem, the system not only issues an alarm, but also automatically provides preliminary troubleshooting suggestions based on the knowledge base, including recommended inspection steps, possible causes of the fault and solutions, to help operation and maintenance personnel quickly carry out disposal work and improve the efficiency and accuracy of troubleshooting.

[0055] Data storage and management module

[0056] This module is dedicated to establishing a complete and efficient database system to facilitate the unified storage, management and analysis of the large amount of data generated during the inspection process.

[0057] Efficient storage mechanism: It adopts a combination of time series database and relational database to ensure the best balance between data security, scalability and access efficiency, and to ensure convenient retrieval and management of historical data and real-time data.

[0058] Data management strategy: Set reasonable data retention and archiving policies to properly manage different types of devices and data, ensure the integrity and security of important data, and optimize the use of storage resources.

[0059] User interface: This module provides an intuitive visual user interaction interface, allowing users to implement functions such as equipment management, inspection task configuration, inspection result viewing and data analysis, ensuring that users can operate and manage conveniently and quickly, thereby improving management efficiency.

[0060] Going further,

[0061] Technical steps

[0062] 1. Device model configuration and construction of device model library

[0063] Equipment model definition: Use JSON format to refine the attributes and operation behaviors of the equipment model to ensure the standardization and applicability of the equipment model. The content of the model should cover the working conditions, use site, fault information, performance parameters, maintenance records and related operation guides of the equipment. The standardized model not only simplifies the sharing and transmission of equipment information, but also facilitates subsequent model expansion and compatibility.

[0064] Model library construction: Create a centrally managed device model library to provide comprehensive device information for the system by integrating models of different devices. The construction of the model library should support version control to facilitate tracking of model change history, and have retrieval and filtering functions to quickly access relevant information of the required devices.

[0065] 2. Data Collection and Processing

[0066] Real-time data collection: Build an efficient data collection module to obtain real-time operation data from various devices. Make reasonable choices for data collection frequency and methods (such as polling, event-driven, etc.) to ensure that the operation data of the equipment is timely and sufficient. The module supports a variety of data access methods, such as sensor interface, API call and data stream processing, to ensure comprehensive coverage of data sources.

[0067] Data cleaning and preprocessing: Implement systematic data cleaning and filtering algorithms to remove outliers and noise to ensure the accuracy and reliability of subsequent analysis. In view of the diversity of data, perform necessary data format conversion (such as timestamp formatting and numerical standardization) to adapt to subsequent analysis and application. In addition, record data modifications during the cleaning process for traceability and auditing.

[0068] Storage design: Design an efficient data storage solution to store the cleaned data in a suitable time series database to facilitate subsequent query and analysis.

[0069] 3. Intelligent inspection task scheduling

[0070] Scheduling algorithm implementation: Develop and implement intelligent scheduling algorithms that comprehensively consider factors such as equipment priority, historical fault records, and real-time status to generate and optimize inspection tasks. The algorithm implementation combines scenario models to dynamically adjust the execution timing and sequence of tasks to ensure that inspection work is highly efficient under limited resource conditions.

[0071] Task management system: Design and implement the task management module, which is responsible for generating, assigning and monitoring the execution of inspection tasks. The system has the function of viewing the task status in real time and supports the automation and intelligent management of tasks, so that operation and maintenance personnel can focus on handling higher priority matters. Task history records are also required for subsequent statistics and analysis.

[0072] 4.Data analysis and inspection report generation

[0073] Real-time monitoring and visualization: Build a user monitoring panel and use visualization tools (such as charts, dashboards, heat maps, etc.) to display the operating status and historical data of the equipment in real time to ensure that managers can understand the equipment status at any time. This interface should have a friendly user experience, allowing managers to quickly understand various operating indicators and intuitively evaluate the health status of the equipment. By setting key performance indicators and alarm thresholds, the operability of the system is enhanced so that timely measures can be taken.

[0074] Data analysis algorithms: Implement a variety of data analysis techniques to obtain the operating status and trends of the equipment. This includes data mining, statistical analysis, and machine learning methods to conduct in-depth analysis of operating data and discover potential patterns and anomalies. For example, regression analysis is used to predict the future performance of equipment, or cluster analysis is implemented to identify equipment operating patterns. These analyses can help the operation and maintenance team understand equipment behavior at a higher level and provide decision support.

[0075] Inspection data summary and report generation: After completing data analysis, all collected monitoring and analysis data are summarized and a detailed inspection report is automatically generated. The report should include key findings, operating performance indicators, fault records, maintenance recommendations, and equipment health assessments, so that managers can summarize and reflect. Report generation should support custom templates to meet the specific needs of different users.

[0076] Automation and preservation of reports: The system should realize the automatic generation of inspection reports, which are automatically created and sent to relevant managers on a regular basis (such as daily, weekly or monthly). The generated reports should support multiple formats (such as PDF, Word, etc.) and be saved in the document management system for subsequent review and evaluation. Automated report generation not only saves human resources, but also improves work efficiency.

[0077] Abnormality and fault identification: Combined with the above data analysis, the system can identify abnormalities and potential faults of equipment in real time. By building an intelligent fault detection model, the system will regularly analyze the collected data according to the set rules and algorithms, and mark abnormal indicators. When abnormalities occur, the system will specifically list these abnormalities in the inspection report and attach recommended treatment measures.

[0078] The beneficial effects of the present invention are

[0079] 1) The present invention greatly simplifies the complexity of the equipment through model abstraction, making the management of heterogeneous equipment more convenient and efficient. Through the equipment model library and grouping function, it promotes the unified management of various heterogeneous equipment and significantly improves the execution efficiency and flexibility of the management process.

[0080] 2) The built-in automatic inspection mechanism of the present invention can effectively release the administrator's time and improve the efficiency and quality of inspection. The automatic inspection module supports dynamic adjustment of inspection frequency and task type, optimizes the use of human resources and enhances the accuracy and scientificity of inspection.

[0081] 3) The design of the system's visual interface facilitates management personnel to deeply analyze inspection results, allowing users to discover and handle equipment problems in a shorter time, thereby effectively reducing safety hazards and economic losses that may be caused by potential equipment failures.

[0082] 4) Managers can monitor all devices uniformly through a centralized platform, improve management visibility and response capabilities, ensure rapid response and effective control, and further improve the efficiency of overall equipment management. BRIEF DESCRIPTION OF THE DRAWINGS

[0083] Figure 1 It is a schematic diagram of the workflow of the present invention. DETAILED DESCRIPTION

[0084] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0085] The technical solution of the present invention is specifically as follows:

[0086] 1. Device model configuration and construction of device model library

[0087] Equipment model definition: Use JSON format to refine the attributes and operation behaviors of the equipment model to ensure the standardization and applicability of the equipment model. The content of the model should cover the working conditions, use site, fault information, performance parameters, maintenance records and related operation guides of the equipment. The standardized model not only simplifies the sharing and transmission of equipment information, but also facilitates subsequent model expansion and compatibility.

[0088] Model library construction: Create a centrally managed device model library to provide comprehensive device information for the system by integrating models of different devices. The construction of the model library should support version control to facilitate tracking of model change history, and have retrieval and filtering functions to quickly access relevant information of the required devices.

[0089] 2. Data Collection and Processing

[0090] Real-time data collection: Build an efficient data collection module to obtain real-time operation data from various devices. Make reasonable choices for data collection frequency and methods (such as polling, event-driven, etc.) to ensure that the operation data of the equipment is timely and sufficient. The module supports a variety of data access methods, such as sensor interface, API call and data stream processing, to ensure comprehensive coverage of data sources.

[0091] Data cleaning and preprocessing: Implement systematic data cleaning and filtering algorithms to remove outliers and noise to ensure the accuracy and reliability of subsequent analysis. In view of the diversity of data, perform necessary data format conversion (such as timestamp formatting and numerical standardization) to adapt to subsequent analysis and application. In addition, record data modifications during the cleaning process for traceability and auditing.

[0092] Storage design: Design an efficient data storage solution to store the cleaned data in a suitable time series database to facilitate subsequent query and analysis.

[0093] 3. Intelligent inspection task scheduling

[0094] Scheduling algorithm implementation: Develop and implement intelligent scheduling algorithms that comprehensively consider factors such as equipment priority, historical fault records, and real-time status to generate and optimize inspection tasks. The algorithm implementation combines scenario models to dynamically adjust the execution timing and sequence of tasks to ensure that inspection work is highly efficient under limited resource conditions.

[0095] Task management system: Design and implement the task management module, which is responsible for generating, assigning and monitoring the execution of inspection tasks. The system has the function of viewing the task status in real time and supports the automation and intelligent management of tasks, so that operation and maintenance personnel can focus on handling higher priority matters. Task history records are also required for subsequent statistics and analysis.

[0096] 4.Data analysis and inspection report generation

[0097] Real-time monitoring and visualization: Build a user monitoring panel and use visualization tools (such as charts, dashboards, heat maps, etc.) to display the operating status and historical data of the equipment in real time to ensure that managers can understand the equipment status at any time. This interface should have a friendly user experience, allowing managers to quickly understand various operating indicators and intuitively evaluate the health status of the equipment. By setting key performance indicators and alarm thresholds, the operability of the system is enhanced so that timely measures can be taken.

[0098] Data analysis algorithms: Implement a variety of data analysis techniques to obtain the operating status and trends of the equipment. This includes data mining, statistical analysis, and machine learning methods to conduct in-depth analysis of operating data and discover potential patterns and anomalies. For example, regression analysis is used to predict the future performance of equipment, or cluster analysis is implemented to identify equipment operating patterns. These analyses can help the operation and maintenance team understand equipment behavior at a higher level and provide decision support.

[0099] Inspection data summary and report generation: After completing data analysis, all collected monitoring and analysis data are summarized and a detailed inspection report is automatically generated. The report should include key findings, operating performance indicators, fault records, maintenance recommendations, and equipment health assessments, so that managers can summarize and reflect. Report generation should support custom templates to meet the specific needs of different users.

[0100] Automation and preservation of reports: The system should realize the automatic generation of inspection reports, which are automatically created and sent to relevant managers on a regular basis (such as daily, weekly or monthly). The generated reports should support multiple formats (such as PDF, Word, etc.) and be saved in the document management system for subsequent review and evaluation. Automated report generation not only saves human resources, but also improves work efficiency.

[0101] Abnormality and fault identification: Combined with the above data analysis, the system can identify abnormalities and potential faults of equipment in real time. By building an intelligent fault detection model, the system will regularly analyze the collected data according to the set rules and algorithms, and mark abnormal indicators. When abnormalities occur, the system will specifically list these abnormalities in the inspection report and attach recommended treatment measures.

[0102] Workflow

[0103] The workflow of the automated inspection engine covers the entire process of equipment model construction, data collection, task scheduling, inspection execution, data analysis and feedback optimization. The specific steps are as follows:

[0104] 1. Device model and configuration phase

[0105] New device model: Build a standardized device model and define device characteristics, including key information such as performance parameters, maintenance cycle, and operating status. When a new device is connected to the system, the model will automatically fill in the corresponding attributes to ensure the accuracy and consistency of the information. This stage reduces the management complexity between different devices through standardization and improves the maintainability of the system.

[0106] Device grouping and scene association: Different devices are combined into manageable complete device groups according to business needs, providing a basis for subsequent inspection tasks. The system supports users to flexibly manage devices according to functions and scenes, and enhance the ability of devices to work together. This flexibility of grouping and scene association can effectively respond to actual application needs in complex environments.

[0107] 2. Scene model assembly stage

[0108] Scenario model construction: Based on specific business needs, models for different operating scenarios are built to define scenario requirements and goals. These scenarios may include specific environmental conditions, equipment requirements, or operating specifications, thus providing more intuitive guidance for inspection tasks.

[0109] Associating scenarios with device models: Associating the created device models with the corresponding scenario models to ensure that the inspection tasks can take into account the matching of device characteristics with scenario requirements. This stage ensures the connection between workflow and actual operations and maximizes the utilization efficiency of equipment.

[0110] 3. Data collection stage

[0111] Real-time data acquisition: The data acquisition module acquires the operating data of various devices or sensors in real time according to the set time interval or trigger conditions, and ensures that the processed data is accurately and effectively transmitted to the data storage module. This process not only improves the timeliness of the data, but also enhances the reliability of the data, providing a high-quality information foundation for subsequent analysis.

[0112] Data cleaning and storage: The collected data is cleaned to remove outliers and noise. The cleaned data will be stored in the database for subsequent query and analysis. This stage ensures that the data stored in the system is highly credible, thereby improving the effectiveness and accuracy of the analysis results.

[0113] 4. Intelligent inspection task scheduling stage

[0114] Automatic inspection task generation: The system automatically generates inspection tasks based on the collected equipment data and related scene information, and optimizes them according to the scheduling algorithm to ensure the adaptive characteristics of equipment inspection work. Based on the intelligent analysis of historical data, the rationality and necessity of inspection tasks are judged more accurately, which greatly improves the effectiveness and pertinence of inspections.

[0115] Task execution and feedback: During the inspection task execution, the system tracks and monitors the task through automated means and records the inspection results in real time. When an abnormality or failure is detected, the system will generate an early warning and quickly notify relevant personnel for follow-up processing. This real-time monitoring mechanism ensures efficient response and problem handling capabilities during the inspection process.

[0116] 5. Data analysis and reporting stage

[0117] Data analysis: Using built-in rule engines and algorithm tools, the data collected during the inspection process is analyzed in real time to identify potential failure modes and operating trends, and provide equipment operation reports for decision makers to refer to. This process ensures that decision makers can understand the operating status of the equipment in a timely manner and make corresponding management decisions.

[0118] Report generation: Based on the analysis results, the system automatically generates an inspection report, including inspection data, problem findings, recommended measures, etc. This report can help decision makers quickly understand the equipment operation status and health assessment, and provide a clear reference for subsequent measures.

[0119] 6. Problem Solving and Decision-Making Stage

[0120] Fault confirmation and handling: For problems identified in the inspection report, the system automatically provides assistance to help relevant personnel confirm the fault and handle it later, and record the handling process. This process incorporates the analysis results of historical data into the fault handling suggestions to ensure that the handling measures are both efficient and reasonable.

[0121] Decision support: The system comprehensively summarizes the data results and provides decision support for equipment replacement, maintenance or optimization. This measure helps managers make scientific and reasonable decisions, thereby improving the operating efficiency and safety of equipment.

[0122] 7. Feedback and iterative optimization stage

[0123] Evaluation and feedback: Regularly evaluate the performance of the inspection engine, analyze relevant feedback and inspection results, and determine optimization areas and improvement directions. This process promotes continuous optimization and iteration of the system to cope with future business changes and enhance system adaptability.

[0124] System optimization: Based on the evaluation results, we continuously adjust the inspection strategy, task scheduling algorithm and data analysis model to continuously improve system performance and inspection efficiency, ensuring that the system always maintains the best operating state in a rapidly changing business environment.

[0125] The invention is applied to equipment management and monitoring in industrial automation and intelligent systems. By building an intelligent solution based on the equipment model, the management efficiency of heterogeneous equipment is improved, the inspection process is optimized, and real-time data analysis and decision support are realized. This technology is applicable to a variety of industries, including manufacturing, transportation, energy management, and smart home.

[0126] The above description is only a preferred embodiment of the present invention, which is only used to illustrate the technical solution of the present invention, and is not used to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. Heterogeneous equipment management and automated inspection system based on model combination, characterized by: include The device model management module is used to abstract different types of devices into a unified model, which includes the device's attributes, operation interface and communication protocol information; The scenario model assembly module is used to dynamically generate equipment assembly solutions based on equipment characteristics and management requirements to achieve flexible equipment management; The automated inspection engine performs automated inspection tasks based on device models and configuration information, including status monitoring, performance analysis, and safety inspections. The data storage and management module establishes a database system to uniformly store, manage and analyze the data generated during the inspection process.

2. The method according to claim 1, characterized in that Device model management module: realizes unified description of device attributes and provides standardized interactive interfaces to ensure the openness and scalability of the system for future compatibility and upgrades; Scenario model assembly module: flexibly generates equipment assembly solutions based on equipment characteristics and application scenario requirements to solve the problem of collaborative work between devices; Supports user-defined scenario models to adapt to changing business needs; Automated inspection engine: responsible for real-time monitoring of the external environment and equipment status, and timely and dynamic adjustment of inspection tasks; Use intelligent algorithms for careful scheduling, based on historical data and real-time status information, to maximize inspection efficiency and ensure that key equipment receives adequate attention in the inspection plan; The data storage and management module provides an intuitive visual user interaction interface, allowing users to manage equipment, configure inspection tasks, view inspection results and perform data analysis.

3. The system according to claim 2, characterized in that The device model management module stores and retrieves model information of various heterogeneous devices through the device model library, and dynamically updates it in combination with user feedback.

4. The system according to claim 2, characterized in that The scenario model assembly module automatically adjusts the equipment assembly plan according to real-time data and equipment status, and generates customized inspection tasks based on actual scenarios.

5. The system according to claim 4, characterized in that Automatically generate reasonable inspection tasks based on the equipment's historical operating data, status information, fault records and priority settings; at the same time, set priorities to ensure that critical equipment and high-risk equipment receive more attention.

6. The system according to claim 2, characterized in that The automated inspection engine includes an inspection plan generation module, a data collection and analysis module, and a result feedback and optimization module; The inspection plan generation module can dynamically plan the time and sequence of inspection tasks according to the scheduling algorithm and the importance of equipment to ensure that key equipment takes priority in the inspection tasks; The data acquisition and analysis module acquires the operating data of various devices or sensors in real time according to the set time interval or trigger conditions, and ensures that the processed data is accurately and effectively transmitted to the data storage and management module; Analyze the data collected during the inspection in real time, identify potential failure modes and operating trends, and provide equipment operation reports for decision makers to refer to; The result feedback and optimization module tracks and monitors the tasks through automated means during the execution of inspection tasks, and records the inspection results in real time; When an abnormality or failure is detected, an early warning is generated and relevant personnel are quickly notified for follow-up processing.

7. The system according to claim 6, characterized in that The inspection results are displayed through a visualization tool to help users quickly identify and solve equipment problems.

8. The system according to claim 6, characterized in that The inspection tasks can be manually scheduled by management personnel or automatically generated, and have a management mechanism for setting priorities to ensure the effective execution of various tasks.

9. The system according to claim 1, characterized in that The visual dashboard provides a friendly visual interface, allowing managers to intuitively view the status and operating data of all equipment; Fault warning is achieved based on equipment historical data and real-time monitoring; when the equipment's operating parameters exceed the set range or potential risks occur, the system will automatically generate an alarm and notify the relevant operation and maintenance personnel through mobile applications or emails; After a problem is identified, not only will an alarm be issued, but preliminary troubleshooting suggestions will also be automatically provided based on the knowledge base, including recommended inspection steps, fault causes and solutions.

10. The system according to claim 1, characterized in that The system working steps are as follows: a) Collect and store the attributes and status information of heterogeneous devices; b) Generate a unified device model based on device type; c) Implement dynamic configuration mechanism to optimize equipment management; d) Perform automated inspection tasks and record inspection results; e) Feedback inspection results through a visual interface to assist in the rapid resolution of equipment problems; f) Dynamically adjust and optimize equipment management strategies based on inspection results and equipment status.

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