CN115426419A - Super-fusion equipment data acquisition platform - Google Patents
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Abstract
Description
技术领域technical field
本发明涉及计算机辅助设计与制造领域，具体为超融合设备数据采集平台。The invention relates to the field of computer-aided design and manufacturing, in particular to a data collection platform for hyper-converged equipment.
背景技术Background technique
随着科技的进步以及社会的发展，企业在数据的采集方面也在发生变化，基本的数据采集过程结构相对稳定，一般分为数据采集端和服务器端，所述数据采集端利用各传感器对设备的实时数据进行采集，然后借助通信手段将采集的数据通过数据传输通道传输至服务器端，所述服务器端采取相应的措施对采集的数据进行存储。With the advancement of science and technology and the development of society, enterprises are also undergoing changes in data collection. The basic data collection process structure is relatively stable, generally divided into data collection end and server end. The data collection end uses various sensors to control equipment The real-time data is collected, and then the collected data is transmitted to the server through the data transmission channel by means of communication, and the server takes corresponding measures to store the collected data.
现有大部分的设备数采平台，仅能支持有限的标准通信协议，面对不同的客户需要二次开发，无法快速响应客户需求，大部分的设备数采平台，需要开发接口才能对接，需要一定的开发和时间成本，以及设备数采平台只能提供故障报警，相对比较简单单一，并且可视化终端比较单一。Most of the existing equipment data acquisition platforms can only support limited standard communication protocols. Different customers need secondary development and cannot quickly respond to customer needs. Most equipment data acquisition platforms need to develop interfaces to connect. Certain development and time costs, and the equipment data acquisition platform can only provide fault alarms, which are relatively simple and single, and the visual terminal is relatively single.
发明内容Contents of the invention
(一)解决的技术问题(1) Solved technical problems
针对现有技术的不足，本发明提供了超融合设备数据采集平台，解决了大部分的设备数采平台，需要开发接口才能对接，需要一定的开发和时间成本，以及设备数采平台只能提供故障报警，相对比较简单单一，并且可视化终端比较单一的问题。Aiming at the deficiencies of the existing technology, the present invention provides a hyper-converged equipment data acquisition platform, which solves most of the equipment data acquisition platforms, which require the development of an interface to connect, requires a certain amount of development and time costs, and the equipment data acquisition platform can only provide The fault alarm is relatively simple and single, and the visual terminal is relatively simple.
(二)技术方案(2) Technical solution
为实现以上目的，本发明通过以下技术方案予以实现：超融合设备数据采集平台，包括数据采集与存储、数据库模型和监控数据应用，所述数据采集与存储与数据库模型通过网络信号相连，所述数据库模型通过网络信号连接有监控数据应用，所述数据采集与存储内包括现场控制、数据采集和数据存储，所述数据采集通过现场控制采集数据兵器向数据存储发送数据，所述数据存储用于对采集的数据进行辨识、建模、分类以及存储，所述数据库模型包括数据模型、业务模型和算法模型，所述数据模型用于数据建模，所述业务模型用于业务建模，所述算法模型用于大数据的管理与分析，所述监控数据应用包括设备管理、设备分析、监控大数据分析和监控数据展示，所述设备管理用于对设备的业务管理，所述设备分析用于对设备的各项指标进行分析，所述监控大数据分析用于对设备各项参数进行提取以及设备状态的分析，所述监控数据展示用于通过PC端、手机端或大屏幕端实时显示设备状态采集、工艺参数和报警参数，实现可视化监控。In order to achieve the above objectives, the present invention is realized through the following technical solutions: a data collection platform for hyper-converged equipment, including data collection and storage, database models and monitoring data applications, the data collection and storage are connected to the database model through network signals, and the The database model is connected with monitoring data applications through network signals. The data collection and storage include on-site control, data collection and data storage. The data collection sends data to the data storage through the on-site control and collection data weapons. Identify, model, classify and store the collected data, the database model includes data model, business model and algorithm model, the data model is used for data modeling, the business model is used for business modeling, the The algorithm model is used for the management and analysis of big data. The monitoring data application includes equipment management, equipment analysis, monitoring big data analysis and monitoring data display. The equipment management is used for business management of equipment, and the equipment analysis is used for Analyze the various indicators of the equipment. The monitoring big data analysis is used to extract various parameters of the equipment and analyze the status of the equipment. The monitoring data display is used to display the equipment in real time through the PC, mobile phone or large screen. Status acquisition, process parameters and alarm parameters to realize visual monitoring.
优选的，所述现场控制包括分布式控制系统、自动化设备、组态软件和PLC及其他控制系统，所述分布式控制系统、自动化设备、组态软件和PLC及其他控制系统用于采集设备的各项指标数据，所述数据采集包括OPC协议、Modbus协议、Socket协议和其他数据接入方，所述OPC协议、Modbus协议、Socket协议和其他数据接入方用于主流的通讯方式，通过OPC协议、Modbus协议、Socket协议和其他数据接入方等协议可以将采集的数据发布到不同终端，包括PC端、手机端或大屏幕端，所述数据存储包括数据辨识、数据建模、数据分类和数据存储，所述数据辨识用于数据的辨识，所述数据建模用于对数据进行建模，所述数据分类用于对建模后的数据进行分类，所述数据存储用于对分类后的数据进行存储。Preferably, the on-site control includes a distributed control system, automation equipment, configuration software and PLC and other control systems, and the distributed control system, automation equipment, configuration software and PLC and other control systems are used for acquisition equipment Various index data, the data collection includes OPC protocol, Modbus protocol, Socket protocol and other data access parties, the OPC protocol, Modbus protocol, Socket protocol and other data access parties are used for mainstream communication methods, through OPC Protocol, Modbus protocol, Socket protocol and other data access parties can publish the collected data to different terminals, including PC, mobile phone or large screen. The data storage includes data identification, data modeling, and data classification and data storage, the data identification is used for data identification, the data modeling is used for modeling data, the data classification is used for classifying modeled data, and the data storage is used for classifying The subsequent data is stored.
优选的，所述数据模型包括实时数据库模型、应用数据库模型和知识库模型，所述实时数据库模型、应用数据库模型和知识库模型用于实现数据建模的载体，所述业务模型包括流程设计、接口设计和框架设计，所述流程设计、接口设计和框架设计用于业务模型的建立，所述算法模型包括关联规则算法、神经网络算法和遗传算法，所述关联规则算法、神经网络算法和遗传算法用于实现大数据的监控与分析。Preferably, the data model includes a real-time database model, an application database model and a knowledge base model, the real-time database model, the application database model and the knowledge base model are used to implement data modeling carriers, and the business model includes process design, Interface design and framework design, the process design, interface design and framework design are used for the establishment of business models, the algorithm model includes association rule algorithm, neural network algorithm and genetic algorithm, the association rule algorithm, neural network algorithm and genetic algorithm Algorithms are used to monitor and analyze big data.
优选的，所述设备管理包括故障维修、计划维修、技术改造、备件管理、设备档案和设备可视化，所述故障维修用于设备故障的维修，所述计划维修用于计划对设备进行维修，所述技术改造用于对设备技术进行改进和创新，所述备件管理用于对设备备件的管理，所述设备档案用于对设备档案的管理维护，所述设备可视化用于对设备数据指标的可视化展示。Preferably, the equipment management includes failure maintenance, planned maintenance, technical transformation, spare parts management, equipment archives and equipment visualization, the failure maintenance is used for equipment failure maintenance, and the planned maintenance is used for planning maintenance of equipment, so The technical transformation is used to improve and innovate equipment technology, the spare parts management is used to manage equipment spare parts, the equipment archives are used to manage and maintain equipment archives, and the equipment visualization is used to visualize equipment data indicators exhibit.
优选的，所述设备分析包括设备状态分析、设备故障分析、设备控制分析、历史故障分析、频发故障分析和故障时序趋势，所述设备状态分析用于对设备状态进行分析，所述设备故障分析用于对设备发生故障的原因进行分析，所述设备控制分析用于对设备控制状态进行分析，所述历史故障分析用于对设备历史发生故障的数据进行分析，所述频发故障分析用于对设备频繁发生故障的原因进行分析，所述故障时序趋势用于设备发生时间顺序地分析。Preferably, the equipment analysis includes equipment status analysis, equipment failure analysis, equipment control analysis, historical failure analysis, frequent failure analysis and failure timing trend, the equipment status analysis is used to analyze the equipment status, and the equipment failure The analysis is used to analyze the cause of equipment failure, the equipment control analysis is used to analyze the equipment control state, the historical failure analysis is used to analyze the data of equipment failure history, and the frequent failure analysis is used In order to analyze the reasons for frequent equipment failures, the failure timing trend is used to analyze equipment occurrence time sequence.
优选的，所述监控大数据分析包括特征参数提取、动态参数提取、设备可靠性分析、设备状态趋势预测、设备状态转换识别和多维分析应用，所述特征参数提取用于提取设备的特征参数，所述动态参数提取用于提取设备的动态参数，所述设备可靠性分析用于分析设备的可靠性，所述设备状态趋势预测用于分析设备未来状态的变化趋势，所述设备状态转换识别用于设备状态转换识别的分析，所述多维分析应用用于对设备进行多方面的分析。Preferably, the monitoring big data analysis includes feature parameter extraction, dynamic parameter extraction, equipment reliability analysis, equipment state trend prediction, equipment state transition identification and multi-dimensional analysis applications, and the feature parameter extraction is used to extract the feature parameters of the equipment, The dynamic parameter extraction is used to extract the dynamic parameters of the equipment, the equipment reliability analysis is used to analyze the reliability of the equipment, the equipment state trend prediction is used to analyze the change trend of the future state of the equipment, and the equipment state transition identification is used to Based on the analysis of equipment state transition recognition, the multi-dimensional analysis application is used to analyze equipment in various aspects.
优选的，所述监控数据展示包括监控设备全景展示、监控信息集中展示、故障信息实时监控、预警信息实时监控、趋势数据统一展示和大数据分析展示，所述监控设备全景展示用于对监控的设备进行全方面的展示，所述监控信息集中展示用于对设备监控信息的集中展示，所述故障信息实时监控用于对设备故障信息进行实时监控，所述预警信息实时监控用于对预警信息进行实时监控，所述趋势数据统一展示用于对设备信息发展趋势数据的统一展示，所述大数据分析展示用于对设备数据分析后展示。Preferably, the monitoring data display includes panoramic display of monitoring equipment, centralized display of monitoring information, real-time monitoring of fault information, real-time monitoring of early warning information, unified display of trend data and big data analysis display, and the panoramic display of monitoring equipment is used for monitoring All-round display of equipment, the centralized display of monitoring information is used for centralized display of equipment monitoring information, the real-time monitoring of fault information is used for real-time monitoring of equipment fault information, and the real-time monitoring of early warning information is used for Real-time monitoring is carried out, the unified display of the trend data is used for the unified display of equipment information development trend data, and the big data analysis display is used for display of equipment data after analysis.
工作原理：在使用本发明的超融合设备数据采集平台时，首先通过现场控制中的分布式控制系统、自动化设备、组态软件或者PLC及其他控制系统采集设备的各种信息数据，然后支持Modbus协议、OPC协议、Socket协议等主流通讯方式，将信息数据输送到数据存储中，通过数据辨识、数据建模、数据分类实现数据存储；通过实时数据库模型、应用数据库模型和知识库模型等载体实现数据建模，通过流程设计、接口设计、框架设计等建立业务模型，通过关联规则算法、神经网络算法和遗传算法等各类算法模型实现大数据的管理与分析，通过设备管理可以实现故障维修、计划维修、技术改造、备件管理、设备档案管理和设备可视化的功能，通过设备分析可以对设备状态、设备故障、设备控制、历史故障、频发故障以及故障时序趋势进行分析，有利于对设备进行管理，通过监控大数据分析可以对设备特征参数和动态参数进行提取，对设备的可靠性进行分析，并且可以对设备状态趋势预测、设备状态转换识别和多维分析应用，通过监控数据展示可以对监控设备全景展示、监控信息集中展示、故障信息实时监控、预警信息实时监控、趋势数据统一展示和大数据分析展示，通过Modbus协议、OPC协议、Socket等协议可以将采集的数据发布到不同终端，包括PC端、手机端或大屏幕端，实现可视化监控。Working principle: When using the hyper-converged equipment data acquisition platform of the present invention, first collect various information data of the equipment through the distributed control system, automation equipment, configuration software or PLC and other control systems in the field control, and then support Modbus Protocol, OPC protocol, Socket protocol and other mainstream communication methods, transfer information data to data storage, and realize data storage through data identification, data modeling, and data classification; realize through real-time database model, application database model and knowledge base model and other carriers Data modeling, establish business models through process design, interface design, framework design, etc., realize big data management and analysis through various algorithm models such as association rule algorithm, neural network algorithm and genetic algorithm, and realize fault maintenance, With the functions of planned maintenance, technical transformation, spare parts management, equipment file management and equipment visualization, equipment status, equipment failure, equipment control, historical failure, frequent failure and failure timing trend can be analyzed through equipment analysis, which is beneficial to the equipment. Management, through the analysis of monitoring big data, the characteristic parameters and dynamic parameters of the equipment can be extracted, the reliability of the equipment can be analyzed, and the equipment status trend prediction, equipment status transition identification and multi-dimensional analysis can be applied, and the monitoring data can be displayed through the monitoring data display. Panoramic display of equipment, centralized display of monitoring information, real-time monitoring of fault information, real-time monitoring of early warning information, unified display of trend data and big data analysis display, the collected data can be released to different terminals through protocols such as Modbus protocol, OPC protocol, and Socket, including PC terminal, mobile phone terminal or large screen terminal to realize visual monitoring.
(三)有益效果(3) Beneficial effects
本发明提供了超融合设备数据采集平台。具备以下有益效果：The invention provides a hyper-converged device data acquisition platform. Has the following beneficial effects:
1、本发明通过现场控制中的分布式控制系统、自动化设备、组态软件或者PLC及其他控制系统采集设备的各种信息数据，每台设备都处于24小时全天候的监控过程中，企业管理者可在办公室随时查看设备状态、任务生产进度，并通过系统的设备分析和监控大数据分析功能，从海量数据中可以对设备特征参数和动态参数进行提取，对设备的可靠性进行分析，并且可以对设备状态趋势预测、设备状态转换识别和多维分析应用，从而提取、分析出各种图形与报表，得到设备的各种数据、运行趋势、异常情况，管理者可以一目了然，很好地实现了生产过程实时的、透明化管理。1. The present invention collects various information data of the equipment through the distributed control system, automation equipment, configuration software or PLC and other control systems in the on-site control. Each equipment is in the 24-hour monitoring process, and the enterprise manager You can check the equipment status and task production progress at any time in the office, and through the system's equipment analysis and monitoring big data analysis function, you can extract equipment characteristic parameters and dynamic parameters from massive data, analyze equipment reliability, and can For equipment status trend prediction, equipment status conversion identification and multi-dimensional analysis application, various graphics and reports can be extracted and analyzed, and various data, operation trends and abnormal conditions of equipment can be obtained. Managers can see at a glance and realize production well. Real-time and transparent management of the process.
2、本发明不仅可融合市面上常见的Modbus协议、OPC协议、Socket等通信协议，还可融合常见的组态软件、控制系统等，从而可快速响应不同客户的不同需求，通过数据辨识、数据分类、规则策略实现数据存储；通过实时数据库、应用数据库、知识库等载体实现数据建模，通过流程设计、接口设计、框架设计等建立业务模型，通过各类算法模型实现大数据的管理与分析，通过提供平台二次开发工具，通过模型定制，结合业务导入，搭载二次开发平台可快速定制客户化的智慧管控信息系统，作为一体化管理平台，本平台功能齐全，涉及的功能包括生产、能耗、设备监控、报警、维护、数据分析功能等，全方面涵盖企业生产管理的各个环节。并且可以根据企业进行定制化设计，帮助企业解决各项管理难题，提高效率。2. The present invention can not only integrate the common Modbus protocol, OPC protocol, Socket and other communication protocols on the market, but also integrate common configuration software, control systems, etc., so that it can quickly respond to different needs of different customers, through data identification, data Realize data storage by classification, rules and strategies; realize data modeling through real-time databases, application databases, knowledge bases and other carriers, establish business models through process design, interface design, framework design, etc., and realize big data management and analysis through various algorithm models , by providing secondary development tools for the platform, through model customization, combined with business import, the secondary development platform can quickly customize a customized intelligent management and control information system. As an integrated management platform, this platform has complete functions, and the functions involved include production, Energy consumption, equipment monitoring, alarm, maintenance, data analysis functions, etc., cover all aspects of enterprise production management in all aspects. And it can be customized according to the enterprise design to help enterprises solve various management problems and improve efficiency.
3、本发明通过监控数据展示可以对监控设备全景展示、监控信息集中展示、故障信息实时监控、预警信息实时监控、趋势数据统一展示和大数据分析展示，通过Modbus协议、OPC协议、Socket等协议可以将采集的数据发布到不同终端，包括PC端、手机端或大屏幕端，实现可视化监控，并为客户提供不同的可视化体验。3. The present invention can display the panorama of monitoring equipment, centralized display of monitoring information, real-time monitoring of fault information, real-time monitoring of early warning information, unified display of trend data and big data analysis display through monitoring data display, through Modbus protocol, OPC protocol, Socket and other protocols The collected data can be released to different terminals, including PC, mobile phone or large screen, to realize visual monitoring and provide customers with different visual experience.
附图说明Description of drawings
图1为本发明的整体系统示意图；Fig. 1 is the overall system schematic diagram of the present invention;
图2为本发明的数据采集与存储示意图；Fig. 2 is a schematic diagram of data acquisition and storage of the present invention;
图3为本发明的现场控制示意图；Fig. 3 is the scene control schematic diagram of the present invention;
图4为本发明的数据采集示意图；Fig. 4 is the data acquisition schematic diagram of the present invention;
图5为本发明的数据存储示意图；Fig. 5 is a schematic diagram of data storage of the present invention;
图6为本发明的数据库模型示意图；Fig. 6 is a schematic diagram of the database model of the present invention;
图7为本发明的数据模型示意图；Fig. 7 is a schematic diagram of the data model of the present invention;
图8为本发明的业务模型示意图；Fig. 8 is a schematic diagram of the business model of the present invention;
图9为本发明的算法模型示意图；Fig. 9 is a schematic diagram of an algorithm model of the present invention;
图10为本发明的监控数据应用示意图；Fig. 10 is a schematic diagram of monitoring data application of the present invention;
图11为本发明的设备管理示意图；Fig. 11 is a schematic diagram of device management in the present invention;
图12为本发明的设备分析示意图；Fig. 12 is a schematic diagram of equipment analysis of the present invention;
图13为本发明的监控大数据分析示意图；Fig. 13 is a schematic diagram of monitoring big data analysis of the present invention;
图14为本发明的监控数据展示示意图。Fig. 14 is a schematic diagram showing the monitoring data of the present invention.
具体实施方式detailed description
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
实施例：Example:
如图1-14所示，本发明实施例提供超融合设备数据采集平台，包括数据采集与存储、数据库模型和监控数据应用，数据采集与存储与数据库模型通过网络信号相连，数据库模型通过网络信号连接有监控数据应用，数据采集与存储内包括现场控制、数据采集和数据存储，数据采集通过现场控制采集数据兵器向数据存储发送数据，数据存储用于对采集的数据进行辨识、建模、分类以及存储，数据库模型包括数据模型、业务模型和算法模型，数据模型用于数据建模，业务模型用于业务建模，算法模型用于大数据的管理与分析，监控数据应用包括设备管理、设备分析、监控大数据分析和监控数据展示，设备管理用于对设备的业务管理，设备分析用于对设备的各项指标进行分析，监控大数据分析用于对设备各项参数进行提取以及设备状态的分析，监控数据展示用于通过PC端、手机端或大屏幕端实时显示设备状态采集、工艺参数和报警参数，实现可视化监控，每台设备都处于24小时全天候的监控过程中，企业管理者可在办公室随时查看设备状态、任务生产进度，并通过系统的设备分析和监控大数据分析功能，从海量数据中可以对设备特征参数和动态参数进行提取，对设备的可靠性进行分析，并且可以对设备状态趋势预测、设备状态转换识别和多维分析应用，从而提取、分析出各种图形与报表，得到设备的各种数据、运行趋势、异常情况，管理者可以一目了然，很好地实现了生产过程实时的、透明化管理，不仅可融合市面上常见的Modbus协议、OPC协议、Socket等通信协议，还可融合常见的组态软件、控制系统等，从而可快速响应不同客户的不同需求，通过数据辨识、数据分类、规则策略实现数据存储；通过实时数据库、应用数据库、知识库等载体实现数据建模，通过流程设计、接口设计、框架设计等建立业务模型，通过各类算法模型实现大数据的管理与分析，通过提供平台二次开发工具，通过模型定制，结合业务导入，搭载二次开发平台可快速定制客户化的智慧管控信息系统，作为一体化管理平台，本平台功能齐全，涉及的功能包括生产、能耗、设备监控、报警、维护、数据分析功能等，全方面涵盖企业生产管理的各个环节。并且可以根据企业进行定制化设计，帮助企业解决各项管理难题，提高效率。As shown in Figure 1-14, the embodiment of the present invention provides a hyper-converged device data collection platform, including data collection and storage, database model and monitoring data application, data collection and storage are connected to the database model through network signals, and the database model is connected through network signals Connected with monitoring data applications, data acquisition and storage include on-site control, data acquisition and data storage. Data acquisition sends data to data storage through on-site control and collection of data weapons. Data storage is used to identify, model, and classify the collected data And storage, database model includes data model, business model and algorithm model, data model is used for data modeling, business model is used for business modeling, algorithm model is used for management and analysis of big data, monitoring data application includes equipment management, equipment Analysis and monitoring Big data analysis and monitoring data display, equipment management is used for business management of equipment, equipment analysis is used for analyzing various indicators of equipment, and monitoring big data analysis is used for extracting equipment parameters and equipment status The analysis and monitoring data display is used to display equipment status collection, process parameters and alarm parameters in real time through PC, mobile phone or large screen to realize visual monitoring. Each equipment is in the process of monitoring 24 hours a day You can check the equipment status and task production progress at any time in the office, and through the system's equipment analysis and monitoring big data analysis function, you can extract equipment characteristic parameters and dynamic parameters from massive data, analyze equipment reliability, and can For equipment status trend prediction, equipment status conversion identification and multi-dimensional analysis application, various graphics and reports can be extracted and analyzed, and various data, operation trends and abnormal conditions of equipment can be obtained. Managers can see at a glance and realize production well. The real-time and transparent management of the process can not only integrate common communication protocols such as Modbus protocol, OPC protocol, and Socket on the market, but also integrate common configuration software and control systems, so that it can quickly respond to different needs of different customers. Data identification, data classification, rules and strategies realize data storage; realize data modeling through real-time databases, application databases, knowledge bases and other carriers, establish business models through process design, interface design, framework design, etc., and realize big data through various algorithm models Management and analysis of the platform, through the provision of secondary development tools for the platform, through model customization, combined with business import, the secondary development platform can quickly customize the customized intelligent management and control information system. As an integrated management platform, this platform has complete functions and involves Functions include production, energy consumption, equipment monitoring, alarm, maintenance, data analysis functions, etc., covering all aspects of enterprise production management in all aspects. And it can be customized according to the enterprise design to help enterprises solve various management problems and improve efficiency.
现场控制包括分布式控制系统、自动化设备、组态软件和PLC及其他控制系统，分布式控制系统、自动化设备、组态软件和PLC及其他控制系统用于采集设备的各项指标数据，数据采集包括OPC协议、Modbus协议、Socket协议和其他数据接入方，OPC协议、Modbus协议、Socket协议和其他数据接入方用于主流的通讯方式，通过OPC协议、Modbus协议、Socket协议和其他数据接入方等协议可以将采集的数据发布到不同终端，包括PC端、手机端或大屏幕端，数据存储包括数据辨识、数据建模、数据分类和数据存储，数据辨识用于数据的辨识，数据建模用于对数据进行建模，数据分类用于对建模后的数据进行分类，数据存储用于对分类后的数据进行存储。On-site control includes distributed control system, automation equipment, configuration software and PLC and other control systems, distributed control system, automation equipment, configuration software and PLC and other control systems are used to collect various index data of equipment, data acquisition Including OPC protocol, Modbus protocol, Socket protocol and other data access parties, OPC protocol, Modbus protocol, Socket protocol and other data access parties are used in mainstream communication methods, through OPC protocol, Modbus protocol, Socket protocol and other data access parties Protocols such as inbound can publish the collected data to different terminals, including PC, mobile phone or large screen. Data storage includes data identification, data modeling, data classification and data storage. Data identification is used for data identification. Modeling is used to model data, data classification is used to classify modeled data, and data storage is used to store classified data.
数据模型包括实时数据库模型、应用数据库模型和知识库模型，实时数据库模型、应用数据库模型和知识库模型用于实现数据建模的载体，业务模型包括流程设计、接口设计和框架设计，流程设计、接口设计和框架设计用于业务模型的建立，算法模型包括关联规则算法、神经网络算法和遗传算法，关联规则算法、神经网络算法和遗传算法用于实现大数据的监控与分析。The data model includes real-time database model, application database model and knowledge base model, and the real-time database model, application database model and knowledge base model are used to realize the carrier of data modeling. Interface design and framework design are used to establish business models. Algorithmic models include association rule algorithms, neural network algorithms, and genetic algorithms. Association rule algorithms, neural network algorithms, and genetic algorithms are used to monitor and analyze big data.
设备管理包括故障维修、计划维修、技术改造、备件管理、设备档案和设备可视化，故障维修用于设备故障的维修，计划维修用于计划对设备进行维修，技术改造用于对设备技术进行改进和创新，备件管理用于对设备备件的管理，设备档案用于对设备档案的管理维护，设备可视化用于对设备数据指标的可视化展示。Equipment management includes failure maintenance, planned maintenance, technical transformation, spare parts management, equipment files and equipment visualization, failure maintenance is used for equipment failure maintenance, planned maintenance is used for planning maintenance of equipment, and technical transformation is used for improving equipment technology and Innovation, spare parts management is used for the management of equipment spare parts, equipment files are used for the management and maintenance of equipment files, and equipment visualization is used for visual display of equipment data indicators.
设备分析包括设备状态分析、设备故障分析、设备控制分析、历史故障分析、频发故障分析和故障时序趋势，设备状态分析用于对设备状态进行分析，设备故障分析用于对设备发生故障的原因进行分析，设备控制分析用于对设备控制状态进行分析，历史故障分析用于对设备历史发生故障的数据进行分析，频发故障分析用于对设备频繁发生故障的原因进行分析，故障时序趋势用于设备发生时间顺序地分析。Equipment analysis includes equipment status analysis, equipment failure analysis, equipment control analysis, historical failure analysis, frequent failure analysis and failure timing trend. Equipment status analysis is used to analyze equipment status, and equipment failure analysis is used to analyze the cause of equipment failure. The equipment control analysis is used to analyze the equipment control state, the historical fault analysis is used to analyze the historical fault data of the equipment, the frequent fault analysis is used to analyze the reasons for the frequent faults of the equipment, and the fault time series trend is used Time-sequential analysis of equipment occurrences.
监控大数据分析包括特征参数提取、动态参数提取、设备可靠性分析、设备状态趋势预测、设备状态转换识别和多维分析应用，特征参数提取用于提取设备的特征参数，动态参数提取用于提取设备的动态参数，设备可靠性分析用于分析设备的可靠性，设备状态趋势预测用于分析设备未来状态的变化趋势，设备状态转换识别用于设备状态转换识别的分析，多维分析应用用于对设备进行多方面的分析。Monitoring big data analysis includes feature parameter extraction, dynamic parameter extraction, equipment reliability analysis, equipment status trend prediction, equipment status transition recognition and multi-dimensional analysis applications. Feature parameter extraction is used to extract feature parameters of equipment, and dynamic parameter extraction is used to extract equipment The equipment reliability analysis is used to analyze the reliability of the equipment, the equipment status trend prediction is used to analyze the change trend of the equipment's future status, the equipment status transition identification is used to analyze the equipment status transition identification, and the multi-dimensional analysis application is used to analyze the equipment status. Perform multifaceted analysis.
监控数据展示包括监控设备全景展示、监控信息集中展示、故障信息实时监控、预警信息实时监控、趋势数据统一展示和大数据分析展示，监控设备全景展示用于对监控的设备进行全方面的展示，监控信息集中展示用于对设备监控信息的集中展示，故障信息实时监控用于对设备故障信息进行实时监控，预警信息实时监控用于对预警信息进行实时监控，趋势数据统一展示用于对设备信息发展趋势数据的统一展示，大数据分析展示用于对设备数据分析后展示，通过监控数据展示可以对监控设备全景展示、监控信息集中展示、故障信息实时监控、预警信息实时监控、趋势数据统一展示和大数据分析展示，通过Modbus协议、OPC协议、Socket等协议可以将采集的数据发布到不同终端，包括PC端、手机端或大屏幕端，实现可视化监控，并为客户提供不同的可视化体验。Monitoring data display includes panoramic display of monitoring equipment, centralized display of monitoring information, real-time monitoring of fault information, real-time monitoring of early warning information, unified display of trend data and big data analysis display. Panoramic display of monitoring equipment is used to display all aspects of monitoring equipment. Centralized display of monitoring information is used for centralized display of equipment monitoring information, real-time monitoring of fault information is used for real-time monitoring of equipment fault information, real-time monitoring of early warning information is used for real-time monitoring of early warning information, unified display of trend data is used for real-time monitoring of equipment information Unified display of development trend data, big data analysis display is used to display equipment data after analysis. Through monitoring data display, it can display panoramic display of monitoring equipment, centralized display of monitoring information, real-time monitoring of fault information, real-time monitoring of early warning information, and unified display of trend data And big data analysis shows that through Modbus protocol, OPC protocol, Socket and other protocols, the collected data can be published to different terminals, including PC, mobile phone or large screen, to realize visual monitoring and provide customers with different visual experiences.
尽管已经示出和描述了本发明的实施例，对于本领域的普通技术人员而言，可以理解在不脱离本发明的原理和精神的情况下可以对这些实施例进行多种变化、修改、替换和变型，本发明的范围由所附权利要求及其等同物限定。Although the embodiments of the present invention have been shown and described, those skilled in the art can understand that various changes, modifications and substitutions can be made to these embodiments without departing from the principle and spirit of the present invention. and modifications, the scope of the invention is defined by the appended claims and their equivalents.
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