WO2015196892A1 - 工业自动化数据的采集方法及装置、系统 - Google Patents

工业自动化数据的采集方法及装置、系统 Download PDF

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WO2015196892A1
WO2015196892A1 PCT/CN2015/080157 CN2015080157W WO2015196892A1 WO 2015196892 A1 WO2015196892 A1 WO 2015196892A1 CN 2015080157 W CN2015080157 W CN 2015080157W WO 2015196892 A1 WO2015196892 A1 WO 2015196892A1
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data
real
industrial automation
industrial
time data
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French (fr)
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解海波
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中兴通讯股份有限公司
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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/28Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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  • the invention relates to the field of industrial automation, in particular to a method, device and system for collecting industrial automation data.
  • industrial control software (hereinafter referred to as "industrial control software”) has become an inseparable part of industrial automation, but in practical applications, industrial control software is not isolated, but needs to be integrated with other application software.
  • industrial control software includes data acquisition, data communication, database, human-machine interface, etc., and its content is also enriched with the development of technology, from simple control to management. Factory informationization.
  • Solution 1 The data collection framework is directly linked to each automation device, and provides an adaptation layer for the communication protocol of each device. See Figure 1 (device 1, device 2, device 3 in Figure 1 is an automation device).
  • the disadvantage of this solution is that it requires a data acquisition framework to provide a collection adapter for each communication protocol.
  • the development difficulty and workload are very large, and it is only applicable to scenarios with small scale and few types of devices.
  • Modbus is an industrial communication bus protocol proposed by Modicon (now a brand of Schneider Electric), instrument bus (Meter) Bus, referred to as MBus), International Electrotechnical Commission 104 (International Electro Technical Commission 104, referred to as IEC104) Statute, DLT645 represents the People's Republic of China Power Industry Standard 645 Statute.
  • Solution 2 The problem of multi-device and multi-protocol is solved by industrial communication gateway, and the data storage layer adopts real-time database, see Figure 2.
  • the collection scheme of the industrial automation data cannot solve the technical problems such as the development difficulty and the use cost.
  • the embodiment of the invention provides a method and a device for collecting industrial automation data to solve at least the above technical problem.
  • an industrial automation data acquisition system comprising: an industrial communication gateway configured to collect data of an industrial automation device in real time; and a data acquisition server configured to be to the industrial
  • the communication gateway requests real-time data of the industrial automation device and stores it in memory.
  • system further includes: a relational database module configured to store historical data of the industrial automation device.
  • the system further includes: a query adaptation module, configured to receive a query request from the upper application system, and request the type of the requested data according to the query to the data collection server or the relationship type
  • the database forwards the query request, and feeds back the summarized query result to the upper application system, where the type of the data includes: real-time data and/or historical data.
  • the data collection server includes: an acquisition client, configured to communicate with the industrial communication gateway, and collect real-time data of the industrial automation device from the industrial communication gateway; an in-memory database module Set to store the real-time data.
  • the data collection server further includes: a historical data collection module, configured to: when the lifetime of the real-time data exceeds a preset threshold, real-time data exceeding the preset threshold is The in-memory database module is moved to the relational database module.
  • the historical data collection module is further configured to convert the real-time data moved to the relational database module from one-dimensional data to two-dimensional data.
  • the collecting client is further configured to convert the collected real-time data from one-dimensional data to two-dimensional data.
  • a method for collecting industrial automation data is provided, which is implemented by a data collection server in an industrial automation data collection system, the method comprising: requesting an industrial communication gateway Real-time data of industrial automated devices; storing the real-time data into memory.
  • the method further includes: when the lifetime of the real-time data exceeds a preset threshold, real-time data exceeding the preset threshold is moved by the memory To a relational database, wherein the relational database is used to store historical data of the industrialized automatic device.
  • an industrial automation data collecting device which is applied to a data collecting server in an industrial automation data collecting system, the device comprising: a requesting module, configured to Requesting real-time data of the industrial automation device from the industrial communication gateway; the storage module is configured to store the real-time data into the memory.
  • the technical means for storing the real-time data requested from the industrial communication gateway into the memory is adopted, and the technical solution that the industrial automation data collection scheme cannot take into consideration both the development difficulty and the use cost is solved in the related technology, thereby reducing The difficulty of development, while reducing costs.
  • FIG. 1 is a schematic diagram of a data collection framework according to the related art
  • FIG. 2 is a schematic diagram of another data collection framework according to the related art
  • FIG. 3 is a structural block diagram of an industrial automation data acquisition system according to an embodiment of the present invention.
  • FIG. 4 is a block diagram showing the structure of an industrial automation data acquisition system in accordance with a preferred embodiment of the present invention.
  • FIG. 5 is a flow chart of a method for collecting industrial automation data according to an embodiment of the present invention.
  • FIG. 6 is a structural block diagram of an apparatus for collecting industrial automation data according to an embodiment of the present invention.
  • FIG. 7 is a schematic structural diagram of an industrial automation data acquisition system according to a preferred embodiment of the present invention.
  • FIG. 8 is a flow chart showing a method of collecting industrial automation data according to a preferred embodiment of the present invention.
  • the data collection framework module
  • FIG. 3 is a block diagram showing the structure of an industrial automation data acquisition system in accordance with an embodiment of the present invention. As shown in Figure 3, the system includes:
  • the industrial communication gateway 30 is configured to collect data of industrial automation equipment in real time
  • the data collection server 32 is configured to request real-time data of the industrial automation device from the industrial communication gateway and store the data in the memory.
  • the data collection server 32 stores the requested real-time data into the memory instead of storing the real-time data into the real-time database, the development cost is reduced and the collection cost of the automation data is reduced.
  • the data collection server may include one or more servers, but is not limited thereto.
  • the above system may further include: a relational database module 34 configured to store historical data of the industrial automation device.
  • the relational database module can be located in a separate server or in the same server as other hardware modules.
  • the system may further include: a query adaptation module 36, configured to receive a query request from the upper application system, and request the type of the requested data according to the query. Forwarding the query request to the data collection server or the relational database, and feeding back the summarized query result to the upper-layer application system, where the type of the data includes: real-time data and/or historical data.
  • a query adaptation module 36 configured to receive a query request from the upper application system, and request the type of the requested data according to the query. Forwarding the query request to the data collection server or the relational database, and feeding back the summarized query result to the upper-layer application system, where the type of the data includes: real-time data and/or historical data.
  • the data collection server 32 includes: an acquisition client 320 configured to communicate with the industrial communication gateway, and collect real-time data of the industrial automation device from the industrial communication gateway 30.
  • the in-memory database module 322 is configured to store the above real-time data. It should be noted that the collection client 320 and the in-memory database module may be located in the same server, or may be located in the first server and the second server, respectively.
  • the data collection server 32 may further include, but is not limited to, the following processing module: the historical data collection module 324 is configured to set when the lifetime of the real-time data exceeds a preset threshold. The real-time data exceeding the preset threshold is moved from the in-memory database module to the relational database module.
  • the historical data collection module can be implemented by one processor or by a server, and is not limited thereto.
  • the historical data collection module 324 is further configured to convert the real-time data moved to the relational database module 34 from one-dimensional data to two-dimensional data.
  • the collection client 320 is further configured to convert the collected real-time data from one-dimensional data to two-dimensional data.
  • the embodiment further provides an industrial automation data collection method, which is implemented by a data acquisition server in an industrial automation data acquisition system, as shown in FIG. 5, the method includes:
  • Step S502 requesting real-time data of the industrialized automatic device from the industrial communication gateway;
  • Step S504 storing the real-time data in the memory into the memory.
  • the real-time data is stored in the memory of the data collection server.
  • a storage scheme for the historical data may be further set, for example, after the step S504, when the lifetime of the real-time data exceeds a preset threshold, the preset threshold is exceeded.
  • the time data is moved from the above memory to the relational database, wherein the relational database is used to store historical data of the above industrialized automatic device.
  • the embodiment further provides an industrial automation data collection device, which is applied to a data collection server in an industrial automation data collection system, as shown in FIG. 6, the device includes:
  • the requesting module 60 is configured to request real-time data of the industrial automation device from the industrial communication gateway;
  • the storage module 62 is coupled to the request module 60 and configured to store the real-time data in the memory.
  • each of the foregoing modules may be implemented by using hardware or software.
  • the request module 60 and the storage module 62 are located in the same processor, and the request module 60 and the storage module 62 are respectively located in the first A processor and a second processor.
  • the storage module 62 can also be directly represented as a memory processor.
  • the industrial automation data acquisition system provided by the following embodiments, as shown in FIG. 7, is divided into the following layers:
  • the bottom layer is the industrial automation device 70, which provides different communication protocols to different devices;
  • the second layer is the industrial communication gateway 30, which can be provided by industrial automation manufacturers, can access industrial automation equipment supporting mainstream communication protocols, and provides data acquisition interface based on OPC protocol, wherein the above mainstream communication protocols include but are not limited to: international Electric Committee 104 (international Electro technical Commission 104, referred to as IEC104) protocol interface, OPC interface, Modbus (Modicon company proposed an industrial communication bus (bus) protocol) / Instrument Bus (Meter bus, referred to as MBus) interface, DLT645 (People's Republic of China Power Industry Standard 645 Protocol) interface.
  • IEC104 international Electro technical Commission 104
  • OPC interface OPC interface
  • Modbus Modicon company proposed an industrial communication bus (bus) protocol) / Instrument Bus (Meter bus, referred to as MBus) interface
  • DLT645 People's Republic of China Power Industry Standard 645 Protocol
  • Industrial communication gateway is a gateway device that can adapt to the mainstream protocol of mainstream automation equipment. It can perform real-time data acquisition on automation equipment and provide mainstream single and mainstream industrial communication protocols (such as OPC protocol) for external systems. data collection.
  • the third layer is an Extract Transform Load (ETL) framework module 32 (ie, the data collection server 32), which is responsible for collecting data from the industrial communication gateway 30 and performing necessary data cleaning and conversion;
  • ETL Extract Transform Load
  • the ETL framework module is divided into three parts: an OPC client (Client) 320 (ie, an acquisition client 320), an in-memory database module 322, and a historical data collection module 324.
  • the OPC Client 320 communicates with the industrial communication gateway based on the OPC protocol, and periodically collects the original device data from the communication gateway.
  • the acquisition process requires necessary cleaning and conversion of the data, and converts the one-dimensional data into two-dimensional data and then saves it to the memory. In the database.
  • the in-memory database module 322 can be a memory-based database that provides fast read and write.
  • the read/write capability is consistent with the real-time database. Only the quasi-real-time data (for example, within one hour) is stored in the in-memory database.
  • the historical data collection module 324 is responsible for periodically deleting obsolete data from the in-memory database (for example, 1 hour ago), and dumping the outdated data to the relational database module 34.
  • the dump process needs to perform data in the in-memory database. Necessary cleaning and conversion.
  • the fourth layer is a relational database module 34, which can be represented as a relational database, and is responsible for storing non-real-time data, that is, historical data (for example, one hour ago).
  • the fifth layer is the query adaptation module 36, which is responsible for distributing the query request of the upper application system 72.
  • the query adaptation module 36 is responsible for distributing the query request sent by the upper application system, and intelligently determining whether to query the real-time data or the historical data according to the query condition, or part of the real-time data plus some historical data, and then sending the query request to the memory.
  • the database or relational database finally summarizes the query results and returns them to the upper application system 72.
  • the sixth layer is the upper application system 72.
  • the hardware part of the embodiment generally comprises two parts: an industrial communication gateway and a data acquisition server.
  • the data collection server is configured to run an OPC client, an in-memory database, a historical data collection module, a relational database, and a query adaptation module, and may be deployed by one server or multiple server extensions.
  • the OPC Client can be implemented in open source, supports communication with the industrial communication gateway based on the OPC protocol, periodically collects raw device data from the communication gateway, performs necessary cleaning and conversion on the data, and converts the one-dimensional data into two-dimensional data before saving. Go to the in-memory database.
  • the in-memory database module can use SQLite, Redis, BerkeleyDB and other common in-memory databases according to the actual data size and performance requirements. The cost is low or even free.
  • the relational two-dimensional table structure or key-value structure can be provided on the data structure. And with the query api interface, it is very flexible and convenient in data usage.
  • the in-memory database module is only used to store real-time data, which may be quasi-real-time data, and the quasi-real-time data refers to data within N hours from the current time (N is a natural number), but is not limited thereto. Therefore, the basic data amount of the in-memory database can be controlled to a fixed scale, and the natural database has the advantages of fast reading and writing, which can ensure the real-time data collection efficiency and query efficiency.
  • the historical data acquisition module is also responsible for periodically deleting obsolete data from the in-memory database (for example, N hours ago), and dumping the outdated data into the relational database.
  • the dump process requires necessary cleaning, conversion, and timing of the data.
  • the frequency is related to N.
  • Relational database modules can use Sybase, Oracle, SqlServer and other mainstream relational databases.
  • the query adaptation module is responsible for distributing the query request sent by the upper application system, and intelligently determining whether to query the real-time data or the historical data according to the query condition, or part of the real-time data plus some historical data, and then sending the query request to the in-memory database or
  • the relational database finally summarizes the query results and returns them to the upper application system.
  • the separation condition N between the quasi-real-time data in the in-memory database and the historical data in the relational database can be flexibly adjusted, so that the performance of the data collection framework module can be flexibly adapted to different upper-layer application scenarios, for example:
  • Scenario A The upper application system is a real-time monitoring system.
  • the main function is to frequently refresh real-time data.
  • This requires the in-memory database to provide high query efficiency. Therefore, N is appropriately adjusted to make only a small amount of basic data in the in-memory database.
  • the invoicing and query efficiency of the in-memory database can be improved.
  • Scenario B The upper application system is a post-analysis system.
  • the main function is to perform statistics and analysis on historical data.
  • the frequency of relational databases will decrease, thereby avoiding the impact of frequent write operations on read operations and improving query efficiency.
  • the batch processing efficiency of relational databases is usually very high. Although the dump efficiency is degraded, the efficiency of a single dump does not decrease linearly.
  • Step S802 the industrial communication gateway collects the latest data from the industrial automation device, and according to different communication protocols of different devices, the industrial communication gateway adopts a corresponding protocol to establish a chain.
  • the industrial communication network tube integrates the communication protocol adaptation package of mainstream manufacturers, can support more than 80% of mainstream industrial automation equipment, and provides a single protocol (such as OPC, Modbus) for external system access.
  • the use of industrial communication gateways can greatly reduce the difficulty of data acquisition framework in the access of equipment and simplify the development process.
  • Step S804 the OPC Client establishes a chain with the industrial communication gateway through the OPC protocol, and periodically sends a data collection request to the gateway.
  • step S806 the industrial communication gateway returns the latest data to the OPC Client, and the communication protocol is OPC.
  • step S808 the OPC Client performs the necessary cleaning conversion on the collected data, and performs the storage in the format required by the in-memory database.
  • Step S810 the historical data collection module periodically sends an acquisition request to the in-memory database.
  • Step S812 the in-memory database returns the obsolete data to the historical data collection module according to the system setting, and simultaneously cleans out the obsolete data in the memory library.
  • step S814 after the historical data collection module receives the data, the data is cleaned and converted as necessary.
  • Step S816 the historical data collection module stores the cleaned and converted data into a relational database.
  • Step S820 the query adapting module intelligently judges whether it is necessary to query real-time data or historical data according to the query condition, or part of real-time data plus partial historical data.
  • step S822 if it is necessary to query the quasi-real-time data (monitoring class function), the data is directly requested from the in-memory database.
  • step S824 if the upper application needs to query the historical data (the function of the post-analysis class), the request is sent to the relational database.
  • the industrial communication gateway is introduced, which greatly reduces the workload of multiple protocols for accessing multiple automation devices, significantly saves labor costs, reduces development difficulty, and improves development efficiency.
  • the OPC Client+in-memory database is used instead of the real-time database, which significantly reduces the development cost.
  • the in-memory database + relational database is used to provide data to the upper-layer application system. Since the data structure is a two-dimensional table, it is more convenient to use. The data is more flexible.
  • a storage medium is further provided, wherein the software includes the above-mentioned software, including but not limited to: an optical disk, a floppy disk, a hard disk, an erasable memory, and the like.
  • modules or steps of the present invention described above can be implemented by a general-purpose computing device that can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they may be implemented by program code executable by the computing device such that they may be stored in the storage device by the computing device and, in some cases, may be different from the order herein.
  • the steps shown or described are performed, or they are separately fabricated into individual integrated circuit modules, or a plurality of modules or steps thereof are fabricated as a single integrated circuit module.
  • the invention is not limited to any specific combination of hardware and software.
  • the technical solution provided by the embodiment of the invention can be applied to the process of collecting industrial automation data, and adopts the technical means for storing real-time data requested from the industrial communication gateway into the memory, and solves the collection scheme of the industrial automation data in the related technology.
  • Technical issues such as development difficulty and cost of use cannot be balanced, thereby reducing the cost of development while reducing the cost.

Abstract

一种工业自动化数据的采集方法及装置,系统。该系统包括工业通讯网关(30),设置为实时采集工业自动化设备的数据;数据采集服务器(32),设置为向工业通讯网关(30)请求工业自动化设备的实时数据并存储至内存中。采用上述技术方案,解决了相关技术中,工业自动化数据的采集方案不能兼顾开发难度和使用成本等技术问题,从而在降低开发难度的同时降低了成本。

Description

工业自动化数据的采集方法及装置、系统 技术领域
本发明涉及工业自动化领域,尤其是涉及一种工业自动化数据的采集方法及装置、系统。
背景技术
随着工业生产自动化程度的提高,工业控制软件(后文简称“工控软件”)成为工业自动化密不可分的一部分,但在实际应用中,工控软件并不是孤立的,而是需要与其他应用软件集成才能发挥其作用,因此从广义来讲工控软件包括数据采集、数据通信、数据库、人机界面等,其涵盖的内容也随着技术的发展不断的丰富,从单纯的控制走向与管理融为一体的工厂信息化。
当前的工控软件绝大多数是由各工业自动化设备制造商在其工业自动化设备的软硬件环境下开发的,是与自动化设备捆绑和专用的。在一个工厂中有各种不同的生产工艺和设备,要求根据不同的对象选用不同的自动化系统设备,如工控机、可编程逻辑控制器(Programmable Logic Controller,简称为PLC)、分布式控制系统(Distributed Control System,简称为DCS)等,即使同类的自动化系统,设备制造厂商不同,其工控软件和内部通讯协议也不相同,往往一个部门需要同时了解和掌握几种本质或功能都基本相同的工控软件,这给用户购买、使用、维护上带来极大的不便,增加了人力资源的消耗和投资。
为了满足统一管理和综合信息化的需要,对不同厂家的不同设备进行集中监控和管理的需求日趋强烈,此需求的核心是建立对自动化设备的数据采集框架,那么首先要解决的就是自动化设备多厂家、多协议的问题,目前主要的解决方案有:
方案一:数据采集框架直接与各自动化设备建链,并针对各个设备的通讯协议提供适配层,参见图1(图1中的设备1、设备2、设备3···为自动化设备)。此方案的缺点是需要数据采集框架对每一种通信协议提供采集适配器,开发难度和工作量非常大,仅适用于规模较小、设备种类较少的场景,其中,在图1中,包括:用于过程控制的OLE(Object Linking and Embedding for Process Control,简称为OPC),Modbus为Modicon(现为施耐德电气公司的一个品牌)公司提出的一种工业通信总线(bus)协议,仪表总线(Meter bus,简称为MBus),国际电工委员会104(International Electro  technical Commission 104,简称为IEC104)规约,DLT645表示中华人民共和国电力行业标准645规约。
方案二:采用工业通讯网关解决多设备、多协议的问题,数据存储层采用实时数据库,参见图2。
此方案的核心是引入了“工业通讯网关”和“实时数据库”,其中“工业通讯网关”负责解决多厂家多协议的采集,最终以单一主流协议(如用于过程控制的OLE,即OPC协议)对外部输出数据,“实时数据库”则作为采集客户端支持与“工业通讯网关”建链,并利用其高效的写操作将数据持久化。此方案的缺点在于:“实时数据库”成本较高。
针对相关技术中的上述问题,尚未提出有效地解决方案。
发明内容
针对相关技术中,工业自动化数据的采集方案不能兼顾开发难度和使用成本等技术问题,本发明实施例提供了一种工业自动化数据的采集方法及装置,以至少解决上述技术问题。
为了达到上述目的,根据本发明的一个实施例,提供了一种工业自动化数据的采集系统,包括:工业通讯网关,设置为实时采集工业自动化设备的数据;数据采集服务器,设置为向所述工业通讯网关请求所述工业自动化设备的实时数据并存储至内存中。
在本发明实施例中,所述系统还包括:关系型数据库模块,设置为存储所述工业自动化设备的历史数据。
在本发明实施例中,所述系统还包括:查询适配模块,设置为接收来自上层应用系统的查询请求,并按照该查询请求所请求数据的类型向所述数据采集服务器或所述关系型数据库转发所述查询请求,以及将汇总的查询结果反馈给所述上层应用系统,其中,所述数据的类型包括:实时数据和/或历史数据。
在本发明实施例中,所述数据采集服务器,包括:采集客户端,设置为与所述工业通讯网关进行通信,从所述工业通讯网关中采集所述工业自动化设备的实时数据;内存数据库模块,设置为存储所述实时数据。
在本发明实施例中,所述数据采集服务器,还包括:历史数据采集模块,设置为在所述实时数据的存活时间超过预设阈值时,将超过所述预设阈值的实时数据由所述内存数据库模块移至所述关系型数据库模块。
在本发明实施例中,所述历史数据采集模块,还设置为将移至所述关系型数据库模块的所述实时数据由一维数据转换为二维数据。
在本发明实施例中,所述采集客户端,还设置为将采集的所述实时数据由一维数据转换为二维数据。
为了达到上述目的,根据本发明的再一个实施例,还提供了一种工业自动化数据的采集方法,通过工业自动化数据的采集系统中的数据采集服务器实现,所述方法包括:向工业通讯网关请求工业化自动设备的实时数据;将所述实时数据存储至内存中。
在本发明实施例中,将所述实时数据存储至内存中之后,还包括:在所述实时数据的存活时间超过预设阈值时,将超过所述预设阈值的实时数据由所述内存移至关系型数据库中,其中,该关系型数据库用于存储所述工业化自动设备的历史数据。
为了达到上述目的,根据本发明的再一个实施例,还提供了一种工业自动化数据的采集装置,应用于工业自动化数据的采集系统中的数据采集服务器,所述装置包括:请求模块,设置为向工业通讯网关请求工业化自动设备的实时数据;存储模块,设置为将所述实时数据存储至内存中。
通过本发明实施例,采用将从工业通讯网关请求的实时数据存储至内存中的技术手段,解决了相关技术中,工业自动化数据的采集方案不能兼顾开发难度和使用成本等技术问题,从而在降低开发难度的同时,降低了成本。
附图说明
此处所说明的附图用来提供对本发明的进一步理解,构成本申请的一部分,本发明的示意性实施例及其说明用于解释本发明,并不构成对本发明的不当限定。在附图中:
图1为根据相关技术的数据采集框架示意图;
图2为根据相关技术的另一数据采集框架示意图;
图3为根据本发明实施例的工业自动化数据的采集系统的结构框图;
图4为根据本发明优选实施例的工业自动化数据的采集系统的结构框图;
图5为根据本发明实施例的工业自动化数据的采集方法的流程图;
图6为根据本发明实施例的工业自动化数据的采集装置的结构框图;
图7为根据本发明优选实施例的工业自动化数据的采集系统的结构示意图;
图8为根据本发明优选实施例的工业自动化数据的采集方法的流程示意图。
具体实施方式
下文中将参考附图并结合实施例来详细说明本发明。需要说明的是,在不冲突的情况下,本申请中的实施例及实施例中的特征可以相互组合。
在解决多厂家多设备的数据采集需求时,如果采用数据采集框架(模块)直接与各自动化设备建链的方案,则势必需要数据采集框架对每一种通信协议提供采集适配器,开发难度和工作量非常大;如果采用“工业通讯网关”和“实时数据库”的方案,一方面“实时数据库”成本较高,另一方面“实时数据库”的数据结构都是一维的,比较适合实时监控,如果要做历史数据分析,则在数据使用上不太方便。为解决上述技术问题,本发明实施例提供了以下解决方案:
图3为根据本发明实施例的工业自动化数据的采集系统的结构框图。如图3所示,该系统包括:
工业通讯网关30,设置为实时采集工业自动化设备的数据;
数据采集服务器32,设置为向上述工业通讯网关请求上述工业自动化设备的实时数据并存储至内存中。
通过上述各个模块,由于数据采集服务器32将请求的实时数据存储至内存中,代替了将实时数据存储至实时数据库中,因此,在降低开发难度的同时,降低了自动化数据的采集成本。
在本实施例中,数据采集服务器可以包括一个或多个服务器,但不限于此。
在一个优选实施例中,为了满足用户对历史数据查询的要求,如图4所示,上述系统还可以包括:关系型数据库模块34,设置为存储上述工业自动化设备的历史数据。 该关系型数据库模块可以位于一个单独的服务器中,也可以和其它硬件模块位于同一服务器中。
为了实现对历史数据和实时数据的查询,如图4所示,上述系统还可以包括:查询适配模块36,设置为接收来自上层应用系统的查询请求,并按照该查询请求所请求数据的类型向上述数据采集服务器或上述关系型数据库转发上述查询请求,以及将汇总的查询结果反馈给上述上层应用系统,其中,上述数据的类型包括:实时数据和/或历史数据。
在一个优选实施例中,如图4所示,数据采集服务器32,包括:采集客户端320,设置为与上述工业通讯网关进行通信,从上述工业通讯网关30中采集上述工业自动化设备的实时数据;内存数据库模块322,设置为存储上述实时数据。需要说明的是,采集客户端320和内存数据库模块可以位于同一个服务器中,也可以分别位于第一服务器和第二服务器中。
为了实现对历史数据的采集,如图4所示,数据采集服务器32,还可以包括但不限于以下处理模块:历史数据采集模块324,设置为在上述实时数据的存活时间超过预设阈值时,将超过上述预设阈值的实时数据由上述内存数据库模块移至上述关系型数据库模块。该历史数据采集模块可以通过一个处理器实现,也可以通过一个服务器实现,并不限于此。
为便于数据的查询分析,历史数据采集模块324,还设置为将移至关系型数据库模块34的上述实时数据由一维数据转换为二维数据。采集客户端320,还设置为将采集的上述实时数据由一维数据转换为二维数据。
基于上述工业自动化数据的采集系统,本实施例还提供一种工业自动化数据的采集方法,该方法通过工业自动化数据的采集系统中的数据采集服务器实现,如图5所示,该方法包括:
步骤S502,向工业通讯网关请求工业化自动设备的实时数据;
步骤S504,将上述实时数据存储至内存中。即将实时数据存储至数据采集服务器的内存中。
在本实施例的一个优选实施方式中,还可以设置对历史数据的存储方案,例如在步骤S504之后,在上述实时数据的存活时间超过预设阈值时,将超过预设阈值的实 时数据由上述内存移至关系型数据库中,其中,该关系型数据库用于存储上述工业化自动设备的历史数据。
为实现上述方法,本实施例还提供一种工业自动化数据的采集装置,应用于工业自动化数据的采集系统中的数据采集服务器,如图6所示,该装置包括:
请求模块60,设置为向工业通讯网关请求工业化自动设备的实时数据;
存储模块62,连接至请求模块60,设置为将上述实时数据存储至内存中。
需要说明的是,上述各个模块是可以通过硬件或软件来实现的,对于前者,可以通过以下方式实现:请求模块60和存储模块62位于同一处理器中,请求模块60和存储模块62分别位于第一处理器和第二处理器中。当然,存储模块62也可以直接表现为内存处理器。
为了更好地理解上述实施例,以下结合一个优选实施例详细说明。
以下实施例所提供的工业自动化数据采集系统,如图7所示,该系统分为以下几层模块:
最底层是工业自动化设备70,不同设备对外提供不同的通讯协议;
第二层是工业通讯网关30,可由工业自动化厂家提供,可以接入支持主流通讯协议的工业自动化设备,并对外提供基于OPC协议的数据采集接口,其中,上述主流通讯协议包括但不限于:国际电工委员会104(international Electro technical Commission 104,简称为IEC104)规约接口,OPC接口、Modbus(Modicon公司提出的一种工业通信总线(bus)协议)/仪表总线(Meter bus,简称为MBus)接口、DLT645(中华人民共和国电力行业标准645规约)接口。
工业通讯网关是一种可以适配主流自动化设备的主流协议的网关设备,它可以对自动化设备进行实时数据采集,并对外提供主流单一、主流的工业通讯协议(例如OPC协议),供外部系统进行数据采集。
第三层是抽取-转换-加载(Extract Transform Load,简称为ETL))框架模块32(即数据采集服务器32),负责从工业通讯网关30采集数据,并进行必要的数据清洗和转换;
ETL框架模块分为OPC客户端(Client)320(即采集客户端320)、内存数据库模块322和历史数据采集模块324三部分。
OPC Client 320基于OPC协议与工业通讯网关进行通信,定时从通讯网关中采集原始的设备数据,采集过程需要对数据进行必要的清洗、转换,将一维数据转换为二维数据后再保存到内存数据库中。
内存数据库模块322,可以是一种基于内存技术、提供快速读写的数据库,其读写能力与实时数据库是一致的,内存数据库中只存放准实时数据(例如1小时之内的)。
历史数据采集模块324,负责定时的从内存数据库中删除过时数据(例如1小时之前的),并把过时的数据转储到里关系型数据库模块34,转储过程需要对内存数据库中的数据进行必要的清洗、转换。
第四层是关系型数据库模块34,可以表现为关系型数据库,负责存储非实时的数据,即历史数据(例如1小时之前的)。
第五层是查询适配模块36,负责分发上层应用系统72的查询请求。该查询适配模块36,负责分发上层应用系统发来的查询请求,根据查询条件智能判断需要查询实时数据还是历史数据,抑或是部分实时数据加部分历史数据,然后再把查询请求下发到内存数据库或关系型数据库,最后把查询结果汇总,返回给上层应用系统72。
第六层是上层应用系统72。
由此可见,本实施例的硬件部分大概包括两部分:工业通讯网关和数据采集服务器。其中,该数据采集服务器用于运行OPC Client、内存数据库、历史数据采集模块、关系型数据库和查询适配模块,可以一台服务器,也可以多台服务器分机部署。
OPC Client可以采用开源实现,支持基于OPC协议与工业通讯网关通信,定时从通讯网关中采集原始的设备数据,对数据进行必要的清洗、转换,并将一维数据转换为二维数据后再保存到内存数据库中。
内存数据库模块,根据实际数据规模和性能要求,可以采用SQLite、Redis、BerkeleyDB等常见内存数据库,成本较低甚至是免费的,在数据结构上可以提供关系型二维表结构,或者key-value结构,并辅以查询api接口,在数据使用上非常灵活方便。
内存数据库模块在本实施例中仅用于存储实时数据,该实时数据可以为准实时数据,准实时数据是指距离当前时间N小时之内的数据(N为自然数),但不限于此。由此可以把内存数据库的基础数据量一直控制在固定规模,再加上内存数据库天然具备的快速读写的优势,可以保证实时数据的采集效率和查询效率。
历史数据采集模块,还负责定时的从内存数据库中删除过时数据(例如N小时之前的),并把过时数据转储到里关系型数据库,转储过程需要对数据进行必要的清洗、转换,定时频率与N有关。
关系型数据库模块,根据实际数据规模和性能要求,可以采用Sybase、Oracle、SqlServer等主流关系型数据库。
查询适配模块,负责分发上层应用系统发来的查询请求,根据查询条件智能判断需要查询实时数据还是历史数据,抑或是部分实时数据加部分历史数据,然后再把查询请求下发到内存数据库或关系型数据库,最后把查询结果汇总,返回给上层应用系统。
内存数据库中的准实时数据与关系数据库中的历史数据的分隔条件N可以灵活调整,由此可以使数据采集框架模块的性能具有一定的伸缩性,可以灵活的满足不同的上层应用场景,例如:
场景A:上层应用系统是一个实时监控系统,主要功能是频繁刷新实时数据,这就要求内存数据库提供较高的查询效率,因此将N适当调小,使得内存数据库中仅保存少量的基础数据,相应的,内存数据库的入库、查询效率就得以提高。
场景B:上层应用系统是一个后分析系统,主要功能是对历史数据进行统计、分析,这就要求关系型数据库提供较高的查询效率,因此将N适当调大,相应的过时数据转储到关系型数据库的频率就会下降,由此避免了频繁的写操作对读操作的影响,查询效率就得以提高。另外关系型数据库的批量处理效率通常是很高的,尽管转储效率下降,但单次转储的效率并不是线性下降的。
基于上述框架,本实施例提供的工业自动化数据的采集方法的流程,如图8所示:
步骤S802,工业通讯网关从工业自动化设备采集最新数据,根据不同设备的不同通讯协议,工业通讯网关采用相应协议与之建链。工业通讯网管内部集成了主流厂家的通讯协议适配包,可以支持接入超过80%的主流工业自动化设备,并对外提供单一协议(如OPC、Modbus)供外部系统访问。使用工业通讯网关可以极大降低数据采集框架在设备接入环节的开发难度,简化开发流程。
步骤S804,OPC Client通过OPC协议与工业通讯网关建链,定时向网关发送数据采集请求。
步骤S806,工业通讯网关将最新数据返回给OPC Client,通讯协议为OPC。
步骤S808,OPC Client将采集到的数据进行必要的清洗转换,以内存数据库要求的格式进行入库。
步骤S810,历史数据采集模块定时向内存数据库发送采集请求。
步骤S812,内存数据库根据系统设置,把过时数据返回给历史数据采集模块,同时清理内存库中的过时数据。
步骤S814,历史数据采集模块收到数据后,对数据进行必要的清洗、转换。
步骤S816,历史数据采集模块把清洗、转换后的数据入库到关系型数据库。
步骤S818,上层应用系统向查询适配模块发送查询请求。
步骤S820,查询适配模块根据查询条件智能判断需要查询实时数据还是历史数据,抑或是部分实时数据加部分历史数据
步骤S822,如果需要查询准实时数据(监控类功能),则直接向内存数据库请求数据。
步骤S824,上层应用如果需要查询历史数据(后分析类的功能),则向关系型数据库发送请求。
步骤S826,查询适配模块合并查询结果
步骤S828,返回查询结果到上层应用系统
综上所述,本发明实施例实现了以下有益效果:
与现有方案一相比,引入了工业通讯网关,大大减少了接入多种自动化设备的多种协议的工作量,显著节省了人力成本,降低了开发难度,提高了开发效率。与现有方案二相比,利用OPC Client+内存数据库代替实时数据库,显著降低了开发成本,利用内存数据库+关系型数据库对上层应用系统提供数据,由于数据结构是二维表,在使用上更加方便,数据展现更加灵活。
在另外一个实施例中,还提供了一种软件,该软件用于执行上述实施例及优选实施方式中描述的技术方案。
在另外一个实施例中,还提供了一种存储介质,该存储介质中存储有上述软件,该存储介质包括但不限于:光盘、软盘、硬盘、可擦写存储器等。
显然,本领域的技术人员应该明白,上述的本发明的各模块或各步骤可以用通用的计算装置来实现,它们可以集中在单个的计算装置上,或者分布在多个计算装置所组成的网络上,可选地,它们可以用计算装置可执行的程序代码来实现,从而,可以将它们存储在存储装置中由计算装置来执行,并且在某些情况下,可以以不同于此处的顺序执行所示出或描述的步骤,或者将它们分别制作成各个集成电路模块,或者将它们中的多个模块或步骤制作成单个集成电路模块来实现。这样,本发明不限制于任何特定的硬件和软件结合。
以上仅为本发明的优选实施例而已,并不用于限制本发明,对于本领域的技术人员来说,本发明可以有各种更改和变化。凡在本发明的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本发明的保护范围之内。
工业实用性
本发明实施例提供的技术方案,可以应用于工业自动化数据的采集过程中,采用将从工业通讯网关请求的实时数据存储至内存中的技术手段,解决了相关技术中,工业自动化数据的采集方案不能兼顾开发难度和使用成本等技术问题,从而在降低开发难度的同时,降低了成本。

Claims (10)

  1. 一种工业自动化数据的采集系统,包括:
    工业通讯网关,设置为实时采集工业自动化设备的数据;
    数据采集服务器,设置为向所述工业通讯网关请求所述工业自动化设备的实时数据并存储至内存中。
  2. 根据权利要求1所述的系统,其中,所述系统还包括:
    关系型数据库模块,设置为存储所述工业自动化设备的历史数据。
  3. 根据权利要求2所述的系统,其中,所述系统还包括:
    查询适配模块,设置为接收来自上层应用系统的查询请求,并按照该查询请求所请求数据的类型向所述数据采集服务器或所述关系型数据库转发所述查询请求,以及将汇总的查询结果反馈给所述上层应用系统,其中,所述数据的类型包括:实时数据和/或历史数据。
  4. 根据权利要求2所述的系统,其中,所述数据采集服务器,包括:
    采集客户端,设置为与所述工业通讯网关进行通信,从所述工业通讯网关中采集所述工业自动化设备的实时数据;
    内存数据库模块,设置为存储所述实时数据。
  5. 根据权利要求4所述的系统,其中,所述数据采集服务器,还包括:
    历史数据采集模块,设置为在所述实时数据的存活时间超过预设阈值时,将超过所述预设阈值的实时数据由所述内存数据库模块移至所述关系型数据库模块。
  6. 根据权利要求5所述的系统,其中,所述历史数据采集模块,还设置为将移至所述关系型数据库模块的所述实时数据由一维数据转换为二维数据。
  7. 根据权利要求4所述的系统,其中,所述采集客户端,还设置为将采集的所述实时数据由一维数据转换为二维数据。
  8. 一种工业自动化数据的采集方法,通过工业自动化数据的采集系统中的数据采集服务器实现,所述方法包括:
    向工业通讯网关请求工业化自动设备的实时数据;
    将所述实时数据存储至内存中。
  9. 根据权利要求8所述的方法,其中,将所述实时数据存储至内存中之后,还包括:
    在所述实时数据的存活时间超过预设阈值时,将超过所述预设阈值的实时数据由所述内存移至关系型数据库中,其中,该关系型数据库用于存储所述工业化自动设备的历史数据。
  10. 一种工业自动化数据的采集装置,应用于工业自动化数据的采集系统中的数据采集服务器,所述装置包括:
    请求模块,设置为向工业通讯网关请求工业化自动设备的实时数据;
    存储模块,设置为将所述实时数据存储至内存中。
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106375393A (zh) * 2016-08-30 2017-02-01 重庆钢铁集团电子有限责任公司 实时数据采集系统及实时数据通讯中断后自动恢复的方法
CN111149069A (zh) * 2017-09-29 2020-05-12 西门子股份公司 用于机械资产的基于云端的监控的测量数据的自动分配
CN112487315A (zh) * 2020-12-17 2021-03-12 中国农业银行股份有限公司 一种数据处理方法和装置
CN112688921A (zh) * 2020-12-09 2021-04-20 浙江蓝卓工业互联网信息技术有限公司 一种工业数据采集系统
US20220155744A1 (en) * 2020-11-13 2022-05-19 Grace Technologies, Inc. Industrial automation integration method for internet of things technologies
CN116567038A (zh) * 2023-07-07 2023-08-08 长沙智医云科技有限公司 一种医疗设备运行监控系统

Families Citing this family (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107291060B (zh) * 2016-03-31 2019-08-02 上海海事大学 基于Oracle数据库的大规模工业信息控制系统及其控制方法
CN106202302A (zh) * 2016-07-01 2016-12-07 龙官波 数据采集方法、装置及系统
CN108415348A (zh) * 2017-02-09 2018-08-17 顺丰速运有限公司 一种监控自动化设备的方法、系统和相关装置
CN109218277A (zh) * 2017-07-07 2019-01-15 华中科技大学 一种多协议数据采集方法及装置
CN113220776B (zh) * 2017-08-10 2022-06-17 成都天衡智造科技有限公司 一种工业数据处理系统和方法
CN107992949A (zh) * 2017-11-09 2018-05-04 北京许继电气有限公司 工业数据分析方法和系统
CN108650325B (zh) * 2018-05-17 2021-06-22 浙江中控技术股份有限公司 一种工业数据采集方法、相关设备及系统
CN108877188B (zh) * 2018-05-17 2020-10-16 济南诚博信息科技有限公司 一种环保数据并发采集及多网络发布方法和装置
CN108919759A (zh) * 2018-06-30 2018-11-30 共享智能铸造产业创新中心有限公司 数字化工厂工控系统及其数据处理方法
CN109521738A (zh) * 2018-11-15 2019-03-26 天津德通电气股份有限公司 基于协议传输的工厂数据处理系统及方法
CN109688424A (zh) * 2018-12-29 2019-04-26 深圳中移视讯技术有限公司 视音频数据传输方法、执法采集工作站及可读存储介质
CN109886041B (zh) * 2019-01-30 2021-09-24 新奥数能科技有限公司 实时数据的采集方法及装置
CN111106998A (zh) * 2019-12-30 2020-05-05 江苏欧联智能科技有限公司 一种工业边缘计算服务网关
CN112988876B (zh) * 2021-04-14 2023-04-07 济南工程职业技术学院 一种工业数据采集管理方法及系统
CN115168477B (zh) * 2022-08-04 2023-06-27 东方合智数据科技(广东)有限责任公司 一种基于互联网的包装行业的数据集成方法及相关设备

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1580941A1 (en) * 2004-03-23 2005-09-28 Agilent Technologies Inc Method of operating sensor net and sensor apparatus
CN101075932A (zh) * 2007-06-29 2007-11-21 当代天启技术(北京)有限公司 数据远程计量的方法和系统
CN101626351A (zh) * 2008-07-09 2010-01-13 青岛高校信息产业有限公司 多协议数据采集网关
CN202014273U (zh) * 2011-03-09 2011-10-19 江苏润龙合同能源管理有限公司 基于合同能源管理的能耗远程采集系统
JP4952437B2 (ja) * 2007-08-14 2012-06-13 沖電気工業株式会社 ネットワーク監視装置、ネットワーク監視システム

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101895483A (zh) * 2009-05-22 2010-11-24 青岛高校信息产业有限公司 基于嵌入式实时数据库的网关应用系统
CN101800766A (zh) * 2009-12-30 2010-08-11 上海交通大学 基于Web的工业污水处理远程监控系统
CN102221829A (zh) * 2010-04-15 2011-10-19 深圳市先阳软件技术有限公司 一种企业生产设备管控一体化系统和方法
US9477936B2 (en) * 2012-02-09 2016-10-25 Rockwell Automation Technologies, Inc. Cloud-based operator interface for industrial automation
CN103123484B (zh) * 2012-12-26 2016-02-03 辽宁省电力有限公司电力科学研究院 变电站状态监测数据标准化接入系统及方法
CN103092920B (zh) * 2012-12-26 2017-04-12 新浪网技术(中国)有限公司 半结构化数据的存储方法及存储系统
CN103580284B (zh) * 2013-10-31 2016-06-29 广州瑞信电力科技有限公司 低压集抄系统

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1580941A1 (en) * 2004-03-23 2005-09-28 Agilent Technologies Inc Method of operating sensor net and sensor apparatus
CN101075932A (zh) * 2007-06-29 2007-11-21 当代天启技术(北京)有限公司 数据远程计量的方法和系统
JP4952437B2 (ja) * 2007-08-14 2012-06-13 沖電気工業株式会社 ネットワーク監視装置、ネットワーク監視システム
CN101626351A (zh) * 2008-07-09 2010-01-13 青岛高校信息产业有限公司 多协议数据采集网关
CN202014273U (zh) * 2011-03-09 2011-10-19 江苏润龙合同能源管理有限公司 基于合同能源管理的能耗远程采集系统

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106375393A (zh) * 2016-08-30 2017-02-01 重庆钢铁集团电子有限责任公司 实时数据采集系统及实时数据通讯中断后自动恢复的方法
CN111149069A (zh) * 2017-09-29 2020-05-12 西门子股份公司 用于机械资产的基于云端的监控的测量数据的自动分配
US20220155744A1 (en) * 2020-11-13 2022-05-19 Grace Technologies, Inc. Industrial automation integration method for internet of things technologies
US11835933B2 (en) * 2020-11-13 2023-12-05 Grace Technologies, Inc. Industrial automation integration method for internet of things technologies
CN112688921A (zh) * 2020-12-09 2021-04-20 浙江蓝卓工业互联网信息技术有限公司 一种工业数据采集系统
CN112487315A (zh) * 2020-12-17 2021-03-12 中国农业银行股份有限公司 一种数据处理方法和装置
CN116567038A (zh) * 2023-07-07 2023-08-08 长沙智医云科技有限公司 一种医疗设备运行监控系统
CN116567038B (zh) * 2023-07-07 2023-10-13 长沙智医云科技有限公司 一种医疗设备运行监控系统

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