WO2019041145A1 - 一种数据读取周期的确定方法和装置 - Google Patents

一种数据读取周期的确定方法和装置 Download PDF

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Publication number
WO2019041145A1
WO2019041145A1 PCT/CN2017/099539 CN2017099539W WO2019041145A1 WO 2019041145 A1 WO2019041145 A1 WO 2019041145A1 CN 2017099539 W CN2017099539 W CN 2017099539W WO 2019041145 A1 WO2019041145 A1 WO 2019041145A1
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Prior art keywords
data
control system
industrial control
determining
group
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PCT/CN2017/099539
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English (en)
French (fr)
Inventor
王琪
袁勇
于禾
张明
吴腾飞
Original Assignee
西门子公司
王琪
袁勇
于禾
张明
吴腾飞
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Application filed by 西门子公司, 王琪, 袁勇, 于禾, 张明, 吴腾飞 filed Critical 西门子公司
Priority to CN201780079808.5A priority Critical patent/CN110300967B/zh
Priority to US16/479,011 priority patent/US10996642B2/en
Priority to PCT/CN2017/099539 priority patent/WO2019041145A1/zh
Priority to EP17923445.5A priority patent/EP3557453B1/en
Publication of WO2019041145A1 publication Critical patent/WO2019041145A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/05—Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
    • G05B19/058—Safety, monitoring
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/31—From computer integrated manufacturing till monitoring
    • G05B2219/31288—Archive collected data into history file
    • Y—GENERAL 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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/80—Management or planning

Definitions

  • the present invention relates to the field of industrial automation technologies, and in particular, to a method and apparatus for determining a data reading period.
  • An industrial control system usually includes many industrial equipment, such as field devices located in industrial sites.
  • Field devices may include: Programmable Logic Controller (PLC), data logger, and the like.
  • PLC Programmable Logic Controller
  • an industrial device may be composed of one or more components, for example, a friction wheel may include various components such as a rotor, a stator, a fan, and the like.
  • PLC Programmable Logic Controller
  • a friction wheel may include various components such as a rotor, a stator, a fan, and the like.
  • the read data can be a component's state parameter, etc., such as a rotor that can read a friction wheel.
  • the speed for example, can also read the temperature of the rotor.
  • FIG. 1 shows an example of an industrial control system 100 reading data of an industrial device 10.
  • a data gateway 20 in the industrial control system 100 reads data 30 from various data points 50 of various industrial devices 10 and uploads the read data 30 to the Mindsphere platform. 40 for use in industrial applications 60.
  • the data gateway reads data in a fixed data reading cycle. If the period is too long, the amount of data read is small, and the amount of information is insufficient. If the period is too small, the amount of data read is large, but the occupied storage resources, computing resources, and transmission resources are excessive. Therefore, the setting of this cycle plays an important role in the stable operation of the industrial control system.
  • the data read cycle is configured by experienced field engineers, but the configuration of the cycle depends on the experience of the field engineer, making it difficult to get the best configuration results, and it is time consuming and labor intensive.
  • the present invention provides a method and apparatus for determining a data read cycle for determining an industrial control system.
  • the data read cycle of the data in the system can automatically configure the data read cycle to obtain better configuration results.
  • a device for determining a data read cycle comprising: a feature analysis module for determining a relationship between data of the industrial control system in a simulation model of an industrial control system, and obtaining Timing information of the data of the simulation model when the simulation model is running; a data reading period analysis module, configured to determine, according to the relationship between the data according to the feature analysis module, and the data Timing information, determining a data read period of each of the items of data.
  • the automatic configuration data reading cycle is realized by extracting the data characteristics of the industrial control system and determining the data reading period according to the extracted data characteristics.
  • the simulation model is used to simulate the industrial control system in a particular state.
  • the industrial control system for a specific state is simulated, and the data characteristics of the industrial control system in the state are extracted, and the determined data read cycle has the characteristics of the specific state, and can be used for the industrial control system of the specific state. Analyze.
  • the device may further include a data packet module, configured to group the data packets, and the feature analysis module is configured to group the data packet module when obtaining timing information of the data.
  • the data reading period analyzing module is specifically configured to determine, according to the determined time series information of the group of data, the group of each group of data obtained by the grouping The data read cycle of the data.
  • each data is grouped, and the same data reading period is determined for the same group, so that the data in the same group is analyzed later.
  • the data grouping module is specifically configured to group the same type of data into groups, or group the data generated by each component belonging to the same template in the industrial control system, where the template It is used to define a set of components in an industrial control system and relationships between components in the set, and the templates can be reused or grouped into logically related data in the industrial control system.
  • the data read period analysis module is specifically configured to determine the data read period, so that an industrial application implemented according to the read data is satisfied by the industrial application.
  • the data read cycle is determined according to the requirements of a particular industrial application, from which data can be read to better perform the functions of industrial applications.
  • the device further includes a data mapping module, configured to determine an identifier of the data in an instance model of the industrial control system, and determine an identifier of the data in the simulation model, And determining, for each of the items of data, an identification of the data in the instance model and an identification of the data in the simulation model a mapping relationship between the two; further comprising: a periodic configuration module, configured to configure, in each of the items of data, the industrial control system according to the mapping relationship and the data reading period of the data The data read cycle of the item data.
  • a data mapping module configured to determine an identifier of the data in an instance model of the industrial control system, and determine an identifier of the data in the simulation model, And determining, for each of the items of data, an identification of the data in the instance model and an identification of the data in the simulation model a mapping relationship between the two; further comprising: a periodic configuration module, configured to configure, in each of the items of data, the industrial control system according to the mapping relationship and the data reading period of the data The data read cycle
  • the setting of the data read cycle of the actual industrial control system is realized by the above data mapping.
  • a method for determining a data read cycle includes: determining a relationship between data of the industrial control system in a simulation model of an industrial control system; and obtaining a location of the simulation model during operation Determining the time series information of each piece of data; determining a data reading period of each of the items of data according to the determined relationship between the pieces of data and the time series information of the pieces of data.
  • the automatic configuration data reading cycle is realized by extracting the data characteristics of the industrial control system and determining the data reading period according to the extracted data characteristics.
  • the simulation model is used to simulate the industrial control system in a particular state.
  • the industrial control system for a specific state is simulated, and the data characteristics of the industrial control system in the state are extracted, and the determined data read cycle has the characteristics of the specific state, and can be used for the industrial control system of the specific state. Analyze.
  • the data packets are further grouped, and for each group of data obtained by the group, timing information of the group of data is separately determined, and for each group of data obtained by the group, according to the determined data of the group. Timing information to determine the data read period of the set of data.
  • each data is grouped, and the same data reading period is determined for the same group, so that the data in the same group is analyzed later.
  • the data read cycle is determined such that an industrial application implemented in accordance with the read data includes the requirements of the industrial application.
  • the data read cycle is determined according to the requirements of a particular industrial application, from which data can be read to better perform the functions of industrial applications.
  • the method further determines an identifier of the data in an instance model of the industrial control system; determining an identifier of the data in the simulation model; for the data For each item, determine the instance Configuring a mapping relationship between the identifier of the data in the model and the identifier of the data in the simulation model, and configuring the data in the industrial control system according to the mapping relationship and the data reading period of the data The data read cycle.
  • the setting of the data read cycle of the actual industrial control system is realized by the above data mapping.
  • a device for determining a data reading period includes:
  • At least one memory for storing machine readable instructions
  • At least one processor for invoking the machine readable instructions to perform the method provided by the first aspect or any one of the possible implementations of the first aspect.
  • a fourth aspect a machine readable medium storing on a readable and readable medium, the machine readable instructions, when executed by at least one processor, causing the at least one processor to execute A method provided by the first aspect or any of the possible implementations of the first aspect.
  • Figure 1 is a schematic diagram of the acquisition of industrial equipment data in an industrial control system.
  • FIG. 2 is a schematic diagram of an operation principle of a device for determining a data reading period according to an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of grouping data in an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of an implementation manner of a device for determining a data read period according to an embodiment of the present invention.
  • FIG. 5 is a flowchart of a method for determining a data read cycle according to an embodiment of the present invention.
  • FIG. 6 is another flowchart of a method for determining a data read cycle according to an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of a process of configuring a data read cycle in an embodiment of the present invention.
  • the configuration of the data read cycle of an industrial device plays an important role in the stable operation of the industrial control system to which the industrial device belongs.
  • the field engineer's manual configuration cycle method relies on the experience of field engineers, making it difficult to get the best configuration results, and it is time consuming and labor intensive.
  • an industrial control system in different states is simulated by using simulation software, and a simulation model and simulation data are obtained, which can respectively be used for different states of the simulated industry.
  • the data characteristics of the control system ie, the relationship between the data and the timing information of the data
  • Line extraction, and the data read cycle is determined according to the extracted data characteristics.
  • the data read cycle may be determined by considering a requirement of a specific data service (eg, preventive maintenance) implemented by the data, and the determined data read cycle needs to meet the requirement to support the data service. .
  • a specific data service eg, preventive maintenance
  • the data to be read may be grouped according to the relationship between the data in advance, for example, the same type of data is grouped, or the data generated by each component belonging to the same predefined template is divided into one. Group, or alternatively, group logically related data into groups. Wherein, the timing information of the group of data is separately determined for each group of data, and the same data reading period is determined. This reduces the amount of data to be read without affecting the support of the data service, so that the read data can reflect events occurring in the industrial control system.
  • an instance model of the industrial control system may be obtained from the automation software or the field configuration data, and the identifier of the data in the instance model is mapped with the identifier of the data in the simulation model, thereby obtaining a mapping relationship and a simulation model according to the obtained
  • the data in the data is determined by the data read cycle to configure the data read cycle of the data in the industrial control system.
  • the determined data read cycle can be adjusted based on feedback from an industrial application to achieve optimal configuration of the data read cycle.
  • FIG. 2 is a schematic diagram of the working principle of the data reading period determining apparatus 200 according to an embodiment of the present invention.
  • the apparatus 200 acquires the simulation model 11 and the simulation data 12 from the simulation software 300 on the one hand, and obtains the instance model 13 from the automation software 400 and the field configuration data 500; on the one hand, the data read cycle 18 of the instance is generated.
  • the data read cycle 18 of the instance is configured on the data gateway 20.
  • the apparatus 200 can include a feature analysis module 2002 and a data read cycle analysis module 2003.
  • a data grouping module 2001, a data mapping module 2004, and a cycle configuration module 2005 may also be included. The operation of the apparatus 200 will now be described in conjunction with FIG.
  • the data grouping module 2001 is used to group the various data 30 in an industrial control system 100.
  • the data grouping module 2001 acquires the simulation model 11 from the simulation software 300.
  • the simulation software 300 can be a product lifecycle management (PLM) simulation software in different fields, such as a multi-domain mechatronics system simulation platform (Imagine Lab Amesim, LMS), process simulation (Process Simulate) and the like.
  • PLM product lifecycle management
  • the simulation software 300 can provide sufficient simulation models 11.
  • a simulation model 11 can be a text file that describes an individual components of an industrial control system 100.
  • the data grouping module 2001 can perform data grouping based on data mining techniques. For example, key components and data can be simulated in the LMS, and interrelated components can be assigned to a group, and data 30 belonging to the same group of components can be grouped into one group.
  • the data packet module 2001 finally obtains the data packet 14, ie the packet information of the data 30.
  • the data packet 14 can be a list including at least one packet, and one packet includes one piece of data 30 or a plurality of pieces of data 30.
  • data packet module 2001 may group data 30 as follows:
  • Method 1 grouping the same type of data 30 into one group
  • Method 2 The data 30 generated by each component belonging to the same template in the industrial control system 100 is divided into a group, wherein one template is used to define a set of components in an industrial control system 100 and a relationship between components in the set. And can be reused;
  • the third method divides the logically related data 30 in the industrial control system 100 into a group, that is, the data 30 belonging to the same logic block is divided into one group.
  • FIG. 3 is a schematic diagram of grouping data in an embodiment of the present invention.
  • three friction wheels 112 are connected to one rail 111, which are respectively a friction wheel 1, that is, 112 (1) in the figure, and the friction wheel 2, that is, 112 (2) in the figure, And the friction wheel 3, that is, 112 (3) in the figure.
  • Each of the friction wheels is connected to other components 113.
  • the friction wheel 1 is connected to the components 113 (1), 113 (2) and 113 (3).
  • the components connected to the line without arrows in the figure have a connection relationship. Between the components connected by the line with the arrow, the component pointed by the arrow acts after the component initiated by the arrow.
  • each component in a dashed box belongs to the same logic block or logic chain, and is grouped into one group.
  • packet 14 (1), packet 14 (2), and packet 14 (3) There are three packets in Figure 3: packet 14 (1), packet 14 (2), and packet 14 (3).
  • the feature analysis module 2002 is configured to analyze the features of the data 30, ie, the data features 15, which may include:
  • the feature analysis module 2002 can include two sub-modules, a relationship extraction module 2002a and a timing information acquisition module 2002b.
  • the relationship extraction module 2002a extracts the relationship between the data 30 in the industrial control system 100 from the simulation model 11. For example, the formulas satisfied between data 30 can be extracted from the LMS, and the logical relationship between the data 30 can be extracted from Process Simulate.
  • the relationship between the extracted data 30 can be used to reduce data identification and data transmission. For example, the speed is equal to the distance divided by the time. If the distance and time have been obtained, the speed can be calculated without the speed data.
  • the timing information acquisition module 2002b can extract the timing of the data 30 of the simulation model 11 runtime from the simulation data 12.
  • the simulation data 12 is from the simulation software 300 and may include a time point and duration of occurrence of the data 30, that is, timing information.
  • the timing information obtaining module 2002b may separately extract timing information for each packet obtained by the data grouping module 2001. Since the data reading periods of the data 30 in the same packet are the same, the data 30 in the same group is facilitated. Analyze.
  • the data features 15 obtained by the feature analysis module 2002 can be described by formulas or algorithms.
  • An example is as follows:
  • Timespan(PS2B_end-PS2A_end)>0 the second group of friction wheels, the time point when the proximity switch PS2B changes from “closed” to “off” is later than the time when the proximity switch PS2A changes from “closed” to “disconnected” )
  • Motorl_Rolling PS1A
  • indicates the relationship of . The whole formula indicates that either the proximity switch PS1A or PS1B is closed, and the first group of friction wheels rotates)
  • the data read period analysis module 2003 is configured to determine a data read period of each item of data 30 based on the relationship between the pieces of data 30 of the industrial control system 100 determined by the feature analysis module 2002 and the time series information of the pieces of data 30. Alternatively, if the data 30 is previously grouped by the data grouping module 2001, the data reading period analysis module 2003 may determine one data reading period for each group of data 30, that is, for the data 30 within the same group. , using the same number Data reading is performed according to the read cycle.
  • the data read cycle analysis module 2003 may cause an industrial application 60 implemented according to the read data 30 to satisfy the requirements of the industrial application 60 when determining the data read cycle.
  • the data 30 read using the determined data read cycle can better support the requirements of the industrial application 60.
  • the data mapping module 2004 is configured to determine an identification of each item of data 30 in an instance model 13 of the industrial control system 100, determine an identification of each item of data 30 in the simulation model 11, and for each of the items of data 30 The mapping relationship between the identification of the data 30 in the instance model 13 and the identification of the data 30 in the simulation model 11 is determined.
  • An example model of an industrial control system can come from software used by the industrial control system, such as: TIA portal software, PCS7, etc., or other software that can collectively build an instance model.
  • an instance model can be obtained for mapping data from a simulation model to an instance model.
  • mapping relationship 17 between the identification of the data 30 in the instance model 13 determined by the data mapping module 2004 and the identification of the data 30 in the simulation model 11 can be referred to the following description:
  • the arrow is the identifier of the data 30 in the simulation model 11 (here, the name of the data 30 in the simulation model 11), and the arrow is the identifier of the data 30 in the instance model 13 (here is the data in the example model 13) 30 address).
  • the mapping relationship 17 and the data read cycle of the data 30 are configured to configure the data read cycle of the item data 30 in the industrial control system 100.
  • the period configuration module 2005 may generate the data read period 18 of the instance according to the simulated data read period 16 of the data 30 output by the mapping relationship 17 and the data read period analysis module 2003, and read the data of the instance.
  • the cycle 18 is sent to the data gateway 20.
  • the data gateway 20 reads the data 30 in accordance with the received data read cycle 18, thereby enabling configuration of the data read cycle.
  • the data read cycle is set in groups, and the data 30 in the same packet has the same data read cycle.
  • the data read cycle 18 can be referred to as follows:
  • ReadingCycle 200ms (packet 3: data read cycle is 200ms)
  • the data read cycle is given in packets, and for each packet, the data read cycle, the name of the data 30 in the simulation model 11, and the address in the instance model 13 are given.
  • the data gateway 20 sends the read data 30 to the industrial cloud platform 40 for use by various industrial applications 60 on the industrial cloud platform 40.
  • the data read cycle can be adjusted according to the usage, for example, it can be seen that the adjusted data read cycle 19 for some data 30 is sent to the data gateway 20, or will be directed to a certain The cycle adjustment commands of the data 30 are sent to the data gateway 20.
  • Data gateway 20 reads data 30 in accordance with the adjusted data read cycle 19.
  • the data grouping module 2001, the feature analysis module 2002, and the data mapping module 2004 all use the simulation model 11 when processing. Therefore, the use of the simulation software 300 and the simulation model 11 plays an important role in determining the data reading cycle.
  • the simulation software 300 and the simulation model 11 can be simulated according to the requirements of the industrial application 60.
  • Industrial control system 100 in various specific states. For example, an industrial control system 100 that simulates that all industrial equipment 10 are in a normal state, such as an industrial control system 100 that simulates one or some industrial equipment 10 or certain components of an industrial equipment 10 in a fault state.
  • a data feature 15 of each of the data 30 of the industrial control system 100 in a particular state is obtained, and a data read cycle is determined in accordance with the extracted data feature 15 embodying a particular state of the industrial control system 100, and the data is used
  • the data is read by the read cycle, and the data 30 reflecting the specific state of the industrial control system 100 can be efficiently acquired, which is advantageous for accurately implementing the industrial application 60.
  • Apparatus 200 can include:
  • At least one memory 2006 for storing machine readable instructions
  • At least one processor 2007 for invoking the above machine readable instructions to implement the functions of the apparatus 200 in any of the embodiments of the present invention.
  • the structure shown in FIG. 4 can be regarded as a hardware implementation of the structure shown in FIG. 2.
  • the feature analysis module 2002, the data read cycle analysis module 2003, the data grouping module 2001, the data mapping module 2004, and the periodic configuration module 2005 can all be regarded as part of the above machine readable instructions, and stored in at least one memory 2006, at least A processor 2007 is used to invoke the functions of the instructions in each of the above modules to implement the apparatus 200.
  • apparatus 200 can also include a user interface 2008 for effecting interaction with a user, such as an operation and maintenance personnel.
  • device 200 may also include at least one communication interface 2009, such as communication with emulation software 300, automation software 400, field configuration data 500 data gateway 20.
  • the apparatus 200 provided by the embodiment of the present invention may be part of the industrial control system 100 or may be implemented independently of the industrial control system 100.
  • FIG. 5 is a flowchart of a method for determining a data read period according to an embodiment of the present invention.
  • the method can be implemented by the aforementioned apparatus 200. As shown in FIG. 5, the method may include the following steps:
  • step S501 the data 30 of the industrial control system 100 are grouped, for example, the same type of data 30 can be grouped into one group; for example, data generated by each component belonging to the same template in the industrial control system 100.
  • 30 is divided into a group; for example, the logically correlated data 30 in the industrial control system 100 is grouped.
  • step S502 timing information of the group of data 30 is determined for each group of data 30 obtained by the grouping in step S501. And, the relationship between the pieces of data 30 is determined. The relationship between the obtained time series information and the data 30 is taken as the data feature 15 of each data 30 in the industrial control system 100.
  • step S503 the data reading period of each item in each of the data 30 is determined based on the determined relationship between the pieces of data 30 and the time series information of the pieces of data 30. Wherein, for each group of data 30 obtained by the grouping, the data reading period of the group of data 30 is determined according to the determined timing information of the group of data 30.
  • the determined data read cycle should satisfy: an industrial application 60 service implemented in accordance with the read data 30 satisfies the requirements of the industrial application 60.
  • step S504 a mapping relationship 17 between the identification of the item data 30 in the instance model 13 and the identification of the item data 30 in the simulation model 11 is determined.
  • step S505 the data reading period of the item data 30 in the industrial control system 100 is configured according to the mapping relationship determined in step S504 and the data reading period of the item data 30.
  • the data gateway 20 reads the data 30 in accordance with the data read cycle configured in step S505, and transmits the read data 30 to the industrial cloud platform 40 for use by various industrial applications 60 on the industrial cloud platform 40.
  • the data read cycle can be adjusted according to the usage, for example, it can be seen that the adjusted data read cycle 19 for some data 30 is sent to the data gateway 20, or will be directed to a certain The cycle adjustment commands of the data 30 are sent to the data gateway 20.
  • Data gateway 20 reads data 30 in accordance with the adjusted data read cycle 19.
  • FIG. 6 is another flowchart of a method for determining a data read cycle according to an embodiment of the present invention.
  • FIG. 5 illustrates a process flow of the apparatus 200.
  • FIG. 6 illustrates the method of determining the data read cycle provided by the embodiment of the present invention in conjunction with the interaction of the apparatus 200 with other devices.
  • the communication process includes the following steps:
  • the data grouping module 2001 acquires the simulation model 11 from the simulation software 300, which step can be implemented by AcquireSimulationModel().
  • the data grouping module 2001 performs data grouping.
  • the data grouping module 2001 extracts information of the data packets 14 of the various data 30 in the industrial control system 100 from the simulation model 11. This step can be performed by ExtractVariableGroupingInfo() achieve.
  • the feature analysis module 2002 acquires the simulation model 11 from the simulation software 300, and the step can be implemented by AcquireSimulationModel().
  • the feature analysis module 2002 acquires the simulation data 12 from the simulation software 300, which can be implemented by AcquireSimulationDataSet().
  • the feature analysis module 2002 acquires information of the data packet 14 from the data grouping module 2001. This step can be implemented by GetVariableGroups().
  • the feature analysis module 2002 mines the relationship between the data 30 from the simulation model 11. This step can be implemented by ExtractVariableRelation().
  • the feature analysis module 2002 mines the time series information of each group of data divided by the data grouping module 2001 from the simulation data 12. This step can be implemented by ExtractDataFeature().
  • the feature analysis module 2002 sets the obtained data feature 15 (including the inter-data relationship and the timing information of each set of data) to the data read cycle analysis module 2003. This step can be implemented by SetDataFeatureDesc().
  • the data read cycle analysis module 2003 determines the simulated data read cycle 16 based on the data feature 15 and the information of the data packet 14. This step can be implemented by CalculateReadingCycle().
  • the data read cycle analysis module 2003 sets the determined simulated data read cycle 16 to the cycle configuration module 2005. This step can be implemented by SetSimulationReadingCycle().
  • the periodic configuration module 2005 acquires the mapping relationship 17 from the data mapping module 2004. This step can be implemented by AcquireVariableMapping().
  • the data mapping module 2004 acquires the simulation model 11 of the industrial control system 100 from the simulation software 300. This step can be implemented by AcquireSimulationModel().
  • the data mapping module 2004 obtains an instance model 13 of the industrial control system 100 from the automation software 400 and/or the field configuration data 500. This step can be implemented by AcquireInstanceModel().
  • the data mapping module 2004 performs data mapping to determine a mapping relationship 17 between the identification of the data 30 in the instance model 13 and the identification of the data 30 in the simulation model 11. This step can be implemented by DoVariableMapping().
  • S615 The data mapping module 2004 sets a mapping relationship 17 to the periodic configuration module 2005. This step can be implemented by SetVariableMapping().
  • S616 The periodic configuration module 2005 changes the simulated data read cycle 16 to the data read cycle 18 of the instance according to the mapping relationship 17. This step can be implemented by GenerateInstanceReadingCyle().
  • the periodic configuration module 2005 configures the data read cycle 18 of the instance to the data gateway 20.
  • Cycle Configuration Module 2005 The data read cycle 18 of the instance can be set to a configuration application in the industrial application 60 running on the industrial cloud platform 40.
  • Data gateway 20 reads the data read cycle 18 of the instance from the configuration application.
  • the cycle configuration service on the cycle to set the cycle. This step can be implemented by SetReadingCycleConfig().
  • S618 The industrial application 60 analyzes the data read cycle required for its own function implementation. This step can be implemented by AnalyzeNeededReadingCycle(). This step can be performed before or after reading the data 30.
  • S619 The industrial application 60 adjusts the data read cycle of the data gateway 20. This step can be implemented by AdjustReadingCycleConfig().
  • FIG. 7 is a schematic diagram of a process of configuring a data read cycle in an embodiment of the present invention.
  • the simulation software 300 provides a simulation model 11, simulation data 12, and extracts information of the data packet 14 from the simulation model 11.
  • the data feature 15 is derived from the simulation model 11 and the simulation data 12 from the information of the data packet 14.
  • a mapping relationship 17 is obtained from the simulation model 11.
  • the data read cycle analysis module 2003 and the cycle configuration module 2005 obtain the data read cycle of the instance according to the mapping relationship 17 and the data feature 15 and finally configure it on the data gateway 20.
  • embodiments of the present invention also provide a machine readable medium storing machine readable instructions for causing a machine to perform a method as hereinbefore described.
  • a system or apparatus equipped with the machine readable medium on which software program code implementing the functions of any of the above-described embodiments is stored, and a computer of the system or apparatus is stored or a Central Processing Unit (CPU) or a Micro Processor Unit (MPU)) reads and executes program code stored in a storage medium.
  • CPU Central Processing Unit
  • MPU Micro Processor Unit
  • the program code itself read from the storage medium can implement the functions of any of the above embodiments, and thus the program code and the storage medium storing the program code constitute a part of the embodiment of the present invention.
  • Storage medium embodiments for providing program code include floppy disk, hard disk, magneto-optical disk, optical disk (such as Compact Disc Read-Only Memory (CD-ROM), recordable optical disk (Compact Disk-Recordable, CD-R) ), rewritable disc (Compact Disk-ReWritable, CD-RW), digital video disc-read only memory (DVD-ROM), digital versatile disc random access memory (Digital Versatile Disc-Random Access Memory, DVD-RAM) ), rewritable digital versatile disc (Digital Versatile Disc ⁇ ReWritable, DVD ⁇ RW), etc., magnetic tape, nonvolatile memory card, and read-only memory (ROM).
  • the program code can be downloaded from the server computer or via the communication network.
  • the program code read out from the storage medium is written into a memory provided in an expansion board inserted into the computer or written in a memory set in an extension unit connected to the computer, and then based on the program code.
  • the instructions cause a CPU or the like mounted on the expansion board or the expansion unit to perform part and all of the actual operations, thereby realizing the functions of any of the above embodiments.
  • the device structure described in the foregoing embodiments may be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by multiple physical entities, or may be multiple Some components in a standalone device are implemented together.
  • the hardware unit can be implemented mechanically or electrically.
  • a hardware unit can include permanently dedicated circuitry or logic (such as a dedicated processor, FPGA or ASIC) to perform the corresponding operations.
  • the hardware unit may also include programmable logic or circuitry (such as a general purpose processor or other programmable processor) that can be temporarily set by software to perform the corresponding operations.
  • programmable logic or circuitry such as a general purpose processor or other programmable processor
  • a specific implementation mechanical mode, or dedicated permanent circuit, or temporarily set circuit

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Abstract

本发明涉及工业自动化技术领域，尤其涉及一种数据读取周期的确定方法和装置。用以确定一个工业控制系统中的数据的数据读取周期，可自动配置数据读取周期，获得较佳的配置结果。本发明实施例中，利用仿真软件对不同状态下的一个工业控制系统进行仿真，得到仿真模型和仿真数据，可分别针对所仿真的不同状态的工业控制系统的数据特征进行提取，并按照提取的数据特征确定数据读取周期。实现了自动配置数据读取周期。

Description

一种数据读取周期的确定方法和装置 技术领域
本发明涉及工业自动化技术领域，尤其涉及一种数据读取周期的确定方法和装置。
背景技术
一个工业控制系统通常包括许多工业设备，比如位于工业现场的现场设备，现场设备可包括：可编程逻辑控制器(Programmable Logic Controller，PLC)、数据日志设备(data logger)等。其中，一个工业设备可由一个或多个组件(component)组成，比如一个摩擦轮可包括转子、定子、风扇等各个组件。为了保证一个工业控制系统的正常运行，通常需要从该系统中的一些组件处读取数据，读取的数据可以是一个组件的状态参数(variable)等，比如可读取一个摩擦轮的一个转子的转速，再比如：还可读取该转子的温度。
在一个工业控制系统中，通常由一个或多个数据网关(也可称为资产(asset))完成工业设备的数据读取以及上传，数据网关将读取到的数据上传到一个数据平台上，比如一个工业云平台上，该工业云平台上可运行各种工业应用，这些工业应用可基于上传到工业云平台上的数据实现一些功能，比如：预防性维护(preventive maintenance)、设备状态监控(Device Health Monitoring)等。图1示出了一个工业控制系统100读取工业设备10的数据的例子。如图1所示，该工业控制系统100中的一个数据网关20从各个工业设备10的各个数据采集点(data point)50处读取数据30，并将读取到的数据30上传至Mindsphere平台40，供工业应用60使用。
通常，数据网关会以一个固定的数据读取周期(reading cycle)读取数据。若该周期过长，则读取的数据量少，信息量不足；若该周期过小，则读取的数据量大，但占用的存储资源、计算资源以及传输资源等会过大。因此该周期的设置对于工业控制系统的稳定运行起着重要的作用。
目前，由有经验的现场工程师来配置该数据读取周期，但周期的配置依赖于现场工程师的经验，难以得到最佳配置结果，且耗时耗力。
发明内容
有鉴于此，本发明提供一种数据读取周期的确定方法和装置，用以确定一个工业控制系 统中的数据的数据读取周期，可自动配置数据读取周期，获得较佳的配置结果。
第一方面，提供一种数据读取周期的确定装置，包括：一个特征分析模块，用于确定一个工业控制系统的一个仿真模型中所述工业控制系统的各项数据之间的关系，以及得到所述仿真模型运行时的所述各项数据的时序信息；一个数据读取周期分析模块，用于根据所述特征分析模块确定的所述各项数据之间的关系以及所述各项数据的时序信息，确定所述各项数据中每一项的数据读取周期。
其中，通过提取工业控制系统的数据特征，并按照提取的数据特征确定数据读取周期，实现了自动配置数据读取周期。
可选地，所述仿真模型用于模拟处于一种特定状态下的所述工业控制系统。
其中，针对特定状态的工业控制系统进行仿真，并提取该状态下的工业控制系统的数据特征，据此确定的数据读取周期具有该特定状态的特征，可用于对该特定状态的工业控制系统进行分析。
可选地，该装置还可包括一个数据分组模块，用于将所述各项数据分组；而特征分析模块在得到所述各项数据的时序信息时，具体用于对于所述数据分组模块分组得到的每一组数据，分别确定该组数据的时序信息，所述数据读取周期分析模块，具体用于对于分组得到的每一组数据，按照确定的该组数据的时序信息，确定该组数据的数据读取周期。
其中，在分析时序信息之前，对各项数据进行分组，并对同一个分组确定同一个数据读取周期，便于后续对同一个分组中的数据进行分析。
可选地，所述数据分组模块具体用于将同一种类型的数据分为一组，或将所述工业控制系统中属于同一模板的各组件产生的数据分为一组，其中，所述模板用于定义一个工业控制系统中组件的集合及集合中组件间的关系，且所述模板可重复使用，或将所述工业控制系统中逻辑上相互关联的数据分为一组。
这里，提供了不同的分组方式。
可选地，所述数据读取周期分析模块具体用于确定所述数据读取周期，使得依据读取到的所述各项数据而实现的一个工业应用满足所述工业应用的要求。
按照特定的工业应用的要求确定数据读取周期，据此读取数据能够更好地实现工业应用的功能。
可选地，该装置还包括一个数据映射模块，用于确定所述工业控制系统的一个实例模型中的所述各项数据的标识，确定所述仿真模型中的所述各项数据的标识，以及对于所述各项数据中的每一项，确定所述实例模型中的该数据的标识与所述仿真模型中的该数据的标识之 间的映射关系；还包括一个周期配置模块，用于对于所述各项数据中的每一项，根据所述映射关系以及该项数据的所述数据读取周期，配置工业控制系统中的该项数据的数据读取周期。
通过上述数据映射实现对实际的工业控制系统的数据读取周期的设置。
第二方面，提供一种数据读取周期的确定方法，包括：确定一个工业控制系统的一个仿真模型中所述工业控制系统的各项数据之间的关系；得到所述仿真模型运行时的所述各项数据的时序信息；根据确定的所述各项数据之间的关系以及所述各项数据的时序信息，确定所述各项数据中每一项的数据读取周期。
其中，通过提取工业控制系统的数据特征，并按照提取的数据特征确定数据读取周期，实现了自动配置数据读取周期。
可选地，所述仿真模型用于模拟处于一种特定状态下的所述工业控制系统。
其中，针对特定状态的工业控制系统进行仿真，并提取该状态下的工业控制系统的数据特征，据此确定的数据读取周期具有该特定状态的特征，可用于对该特定状态的工业控制系统进行分析。
可选地，还方法中还将所述各项数据分组，对于分组得到的每一组数据，分别确定该组数据的时序信息，对于分组得到的每一组数据，按照确定的该组数据的时序信息，确定该组数据的数据读取周期。
其中，在分析时序信息之前，对各项数据进行分组，并对同一个分组确定同一个数据读取周期，便于后续对同一个分组中的数据进行分析。
可选地，将同一种类型的数据分为一组，或将所述工业控制系统中属于同一模板的各组件产生的数据分为一组，其中，所述模板用于定义一个工业控制系统中组件的集合及集合中组件间的关系，且所述模板可重复使用，或将所述工业控制系统中逻辑上相互关联的数据分为一组。
这里，提供了不同的分组方式。
可选地，确定所述数据读取周期，使得依据读取到的所述各项数据而实现的一工业应用满足该工业应用的要求。
按照特定的工业应用的要求确定数据读取周期，据此读取数据能够更好地实现工业应用的功能。
可选地，该方法中还确定所述工业控制系统的一个实例模型中的所述各项数据的标识；确定所述仿真模型中的所述各项数据的标识；对于所述各项数据中的每一项，确定所述实例 模型中的该数据的标识与所述仿真模型中的该数据的标识之间的映射关系，根据所述映射关系以及该项数据的所述数据读取周期，配置工业控制系统中的该项数据的数据读取周期。
通过上述数据映射实现对实际的工业控制系统的数据读取周期的设置。
第三方面，提供一种数据读取周期的确定装置，包括：
至少一个存储器，用于存储机器可读指令；
至少一个处理器，用于调用所述机器可读指令，执行第一方面或第一方面的任一种可能的实现方式提供的方法。
第四方面，提供一种机器可读介质，所述可读可读介质上存储有机器可读指令，所述机器可读指令在被至少一个处理器执行时，使所述至少一个处理器执行第一方面或第一方面的任一种可能的实现方式提供的方法。
附图说明
图1为一个工业控制系统中采集工业设备数据的示意图。
图2为本发明实施例提供的数据读取周期的确定装置的工作原理的示意图。
图3为本发明实施例中将数据进行分组的示意图。
图4为本发明实施例提供的数据读取周期的确定装置的一种实现方式的示意图。
图5为本发明实施例提供的数据读取周期的确定方法的一个流程图。
图6为本发明实施例提供的数据读取周期的确定方法的另一流程图。
图7为本发明实施例中配置数据读取周期的一个过程的示意图。
附图标记列表：
Figure PCTCN2017099539-appb-000001
Figure PCTCN2017099539-appb-000002
具体实施方式
如前所述，一个工业设备的数据读取周期的配置对于该工业设备所属的工业控制系统的稳定运行起着重要的作用。而现场工程师手动配置周期的方法依赖于现场工程师的经验，难以得到最佳配置结果，且耗时耗力。
本发明实施例中，利用仿真软件(simulation software)对不同状态下的一个工业控制系统进行仿真，得到仿真模型(simulation model)和仿真数据(simulation data)，可分别针对所仿真的不同状态的工业控制系统的数据特征(即各项数据之间的关系及数据的时序信息)进 行提取，并按照提取的数据特征确定数据读取周期。
可选地，在确定数据读取周期时可考虑数据所实现的一项特定的数据服务(比如：预防性维护)的要求，确定的数据读取周期需要满足该要求，以支持该项数据服务。
可选地，可预先根据数据之间的关系将要读取的数据进行分组，比如将同一种类型的数据分为一组，或者将属于同一预先定义的模板的各组件所产生的数据分为一组，再或者，将逻辑上相互关联的数据分为一组。其中，分别对每一组数据分别确定该组数据的时序信息，确定相同的数据读取周期。这样可减少要读取的数据量而不会影响对数据服务的支持，使得读取到的数据能够体现工业控制系统中发生的事件。
可选地，可从自动化软件或现场配置数据中获取工业控制系统的实例模型，将实例模型中的数据的标识与仿真模型中的数据的标识进行映射，从而根据得到的映射关系以及针对仿真模型中的数据确定的数据读取周期来配置工业控制系统中的数据的数据读取周期。
可选地，该确定的数据读取周期可以根据一个工业应用的反馈进行调整，以实现数据读取周期的最佳配置。
下面结合附图对本发明实施例提供的方法和设备进行详细说明。
图2为本发明实施例提供的数据读取周期的确定装置200的工作原理的示意图。如图2所示，该装置200一方面从仿真软件300处获取仿真模型11和仿真数据12，从自动化软件400和现场配置数据500处获取实例模型13；一方面生成实例的数据读取周期18并在数据网关20上配置该实例的数据读取周期18。
该装置200可包括一个特征分析模块2002和一个数据读取周期分析模块2003。此外，还可包括一个数据分组模块2001、一个数据映射模块2004和一个周期配置模块2005。下面结合图2介绍装置200的工作原理。
1)数据分组模块2001
数据分组模块2001用于将一个工业控制系统100中的各项数据30进行分组。
数据分组模块2001从仿真软件300处获取仿真模型11。其中，仿真软件300可为不同领域的产品生命周期管理(Product Lifecycle Management，PLM)仿真软件，比如：多领域机电一体化系统仿真平台(Imagine Lab Amesim，LMS)、过程仿真(Process Simulate)等。仿真软件300可以提供足够的仿真模型11。一个仿真模型11可以是一个文本文件，描述了一个工业控制系统100中包括个各个组件。
数据分组模块2001可基于数据挖掘技术进行数据分组。比如：在LMS中可以仿真关键组件和数据，相互关联的组件可以被分配在一组，属于同一组组件的数据30可以被分为一组。数据分组模块2001最终得到数据分组14，即数据30的分组信息。数据分组14可以是一个列表，该列表中包括至少一个分组，一个分组中包括一项数据30或多项数据30。
可选地，数据分组模块2001可按照如下方式对数据30进行分组：
方式一、将同一种类型的数据30分为一组；
方式二、将工业控制系统100中属于同一模板(template)的各组件产生的数据30分为一组，其中，一个模板用于定义一个工业控制系统100中组件的集合及集合中组件间的关系，且可重复使用；
方式三、将工业控制系统100中逻辑上相互关联的数据30分为一组，即属于同一个逻辑块(logic block)的数据30分为一组。
图3为本发明实施例中将数据进行分组的示意图。图3中，按照一个仿真模型11，一个轨道111上连接有3个摩擦轮112，分别为摩擦轮1，即图中的112(1)，摩擦轮2，即图中的112(2)，以及摩擦轮3，即图中的112(3)。每个摩擦轮都连接有其他组件113。比如：摩擦轮1与组件113(1)、113(2)和113(3)连接。图中不带箭头的线所连接的组件之间具有连接关系。带箭头的线所连接的组件之间，箭头指向的组件在箭头发起的组件之后作用。图3中，一个虚线框中的各个组件属于同一个逻辑框(logic block)或逻辑链(logic chain)，分为一组。图3中有三个分组：分组14(1)、分组14(2)和分组14(3)。
2)特征分析模块2002
特征分析模块2002用于分析数据30的特征，即数据特征15，该特征可包括：
各项数据30之间的关系，以及
各项数据30的时序信息，其中时序信息用于表示各项数据30之间所满足的时间条件。
特征分析模块2002可包括两个子模块，分别是关系提取模块2002a和时序信息获取模块2002b。
其中，关系提取模块2002a从仿真模型11中提取工业控制系统100中的各项数据30之间的关系。比如：数据30之间满足的公式可从LMS中提取，数据30之间的逻辑关系可从Process Simulate中提取。提取到的各项数据30之间的关系可用于减少数据识别和数据传输。比如：速度等于距离除以时间，如果已经得到了距离和时间，则可计算得到速度，无需再获取速度这项数据。
时序信息获取模块2002b可从仿真数据12中提取仿真模型11运行时各项数据30的时序 信息。其中，仿真数据12来自仿真软件300，可包括一项数据30发生的时间点和时长，即时序信息。可选地，时序信息获取模块2002b可针对数据分组模块2001得到的每一个分组，分别提取时序信息，由于同一个分组中的数据30的数据读取周期相同，这样便于对同一分组中的数据30进行分析。
特征分析模块2002得到的数据特征15可以用公式或算法进行描述。一个例子如下所示：
Data feature description(时序信息描述)
For Spring Loose Failure(对于弹簧松动故障)：
1)Timespan(PS2B_end-PS2A_end)＞0(第二组摩擦轮，接近开关PS2B由“闭合”变为“断开”的时间点晚于接近开关PS2A由“闭合”变“断开”的时间点)
2)Timespan(PS2B_start-PS2A_start)＞0(第二组摩擦轮，接近开关PS2B由“断开”变“闭合”的时间点晚于接近开关PS2A由“断开”变“闭合”的时间点)
3)Timespan(PS2A_fail＝1)＞Timespan(PS2A＝1)(第二组摩擦轮，接近开关PS2A在故障状态下“闭合”的时长大于在正常状态下“闭合”的时长)
4)Timespan(PS2A＝1)＝2s(第二组摩擦轮，接近开关PS2A在正常状态下“闭合”的时长为2s)
5)Timespan(PS2A_fail＝1)＞3s(第二组摩擦轮，接近开关PS2A在故障状态下“闭合”的时长大于3s)
……
Variable relation description(各项数据之间的关系的描述)
1)Motorl_Rolling＝PS1A||PS1B(用于表示三项数据Motor1_Rolling、PS1A和PS1B之间的关系，其中，Motor1_Rolling表示第一组摩擦轮转动，PS1A表示接近开关PS1A闭合，PS1B表示接近开关PS1B闭合，||表示或的关系。整个公式表示接近开关PS1A或PS1B任一一个闭合，第一组摩擦轮转动)
2)Motor2_Rolling＝PS2A||PS2B(用于表示接近开关PS2A或PS2B任一个闭合，第二组摩擦轮转动)
3)数据读取周期分析模块2003
数据读取周期分析模块2003用于根据特征分析模块2002确定的工业控制系统100的各项数据30之间的关系以及各项数据30的时序信息，确定每一项数据30的数据读取周期。可选地，若由数据分组模块2001预先对各项数据30进行了分组，则数据读取周期分析模块2003可针对每一组数据30确定一个数据读取周期，即对于同一分组内的数据30，采用相同的数 据读取周期进行数据读取。
可选地，数据读取周期分析模块2003在确定数据读取周期时，可使得依据读取到的各项数据30而实现的一个工业应用60满足该工业应用60的需求。这样，采用确定的数据读取周期读取到的数据30才能更好地支持工业应用60的要求。
4)数据映射模块2004
数据映射模块2004，用于确定工业控制系统100的一个实例模型13中的各项数据30的标识，确定仿真模型11中的各项数据30的标识，以及对于各项数据30中的每一项，确定实例模型13中的该数据30的标识与仿真模型11中的该数据30的标识之间的映射关系。
一个工业控制系统的实例模型可来自该工业控制系统所使用的软件，比如：博途(TIA portal)软件、PCS7等，或者其他能共建立实例模型的软件。在这类软件中可以获取实例模型，用于进行数据的从仿真模型到实例模型的映射。
数据映射模块2004确定的实例模型13中的数据30的标识与仿真模型11中的数据30的标识之间的映射关系17可参考如下描述：
Variable mapping(映射关系)
PS0-＞DB0.I0.0
PS1A-＞DB0.I1.0
PS1B-＞DB0.I2.0
PS2A-＞DB0.I3.0
PS2B-＞DB0.I4.0
PS3A-＞DB0.I5.0
PS3B-＞DB0.I6.0
PS4-＞DB0.I7.0
Motor1_Rolling-＞DB3.I1.0
Motor2_Rolling-＞DB3.I2.0
Motor3_Rolling-＞DB3.I3.0
上述映射关系17中，箭头前为仿真模型11中数据30的标识(这里为仿真模型11中的数据30的名称)，箭头后为实例模型13中数据30的标识(这里为实例模型13中数据30的地址)。
5)周期配置模块2005
周期配置模块2005，用于对于各项数据30中的每一项，根据数据映射模块2004确定的 映射关系17以及该项数据30的数据读取周期，配置工业控制系统100中的该项数据30的数据读取周期。其中，周期配置模块2005可按照映射关系17和数据读取周期分析模块2003输出的各项数据30的仿真的数据读取周期16，生成实例的数据读取周期18，并将实例的数据读取周期18发送至数据网关20。数据网关20按照收到的数据读取周期18读取各项数据30，从而实现对数据读取周期的配置。
可选地，若数据30经过了数据分组模块2001进行分组，则数据读取周期按组来设置，同一分组内的数据30具有相同的数据读取周期。
数据读取周期18可参考如下描述：
Reading cycle(数据读取周期)
1)Groupl：ReadingCycle＝200ms(分组1：数据读取周期为200ms)
Name＝PS0，Address＝DB0.I0.0(数据30的名称为PS0，地址为DB0.I0.0)
Name＝PS1A，Address＝DB0.I1.0(数据30的名称为PS1A，地址为DB0.I1.0)
Name＝PS1B，Address＝DB0.I2.0(数据30的名称为PS1B，地址为DB0.I2.0)
2)Group2：ReadingCycle＝200ms(分组2：数据读取周期为200ms)
Name＝PS2A，Address＝DB0.I3.0(数据30的名称为PS2A，地址为DB0.I3.0)
Name＝PS2B，Address＝DB0.I4.0(数据30的名称为PS2B，地址为DB0.I4.0)
3)Group3：ReadingCycle＝200ms(分组3：数据读取周期为200ms)
Name＝PS3A，Address＝DB0.I5.0(数据30的名称为PS3A，地址为DB0.I5.0)
Name＝PS3B，Address＝DB0.I6.0(数据30的名称为PS3B，地址为DB0.I6.0)
Name＝PS4，Address＝DB0.I7.0(数据30的名称为PS4，地址为DB0.I7.0)
上述描述中，数据读取周期是按照分组给出的，对于每一个分组，给出了数据读取周期、数据30在仿真模型11中的名称以及在实例模型13中的地址。
数据网关20将读取到的数据30发送至工业云平台40，供工业云平台40上的各项工业应用60使用。工业应用60在使用了收到的数据30后，可根据使用情况调整数据读取周期，比如：可见针对某些数据30的调整后的数据读取周期19发送至数据网关20，或者将针对某些数据30的周期调整指令发送至数据网关20。数据网关20按照调整后的数据读取周期19读取数据30。
上述数据分组模块2001、特征分析模块2002和数据映射模块2004在进行处理时均会用到仿真模型11。因此，仿真软件300及仿真模型11的使用对于数据读取周期的确定起着重要的作用。本发明实施例中，仿真软件300和仿真模型11可根据工业应用60的需求模拟处 于各种特定状态下的工业控制系统100。比如：模拟所有工业设备10均处于正常状态下的工业控制系统100，再比如：模拟某一个或一些工业设备10或者一个工业设备10的某些组件处于故障状态下的工业控制系统100。得到处于一种特定状态下的工业控制系统100的各项数据30的数据特征15，并按照该提取的体现了工业控制系统100特定状态的数据特征15来确定数据读取周期，并使用该数据读取周期进行数据读取，能够高效地获取体现工业控制系统100的特定状态的数据30，有利于准确地实现工业应用60。
图4为装置200的一种实现方式的示意图。装置200可包括：
至少一个存储器2006，用于存储机器可读指令；
至少一个处理器2007，用于调用上述机器可读指令，实现本发明任一实施例中装置200的功能。
其中，图4所示的结构可视为图2所示结构的一种硬件实现方式。其中，特征分析模块2002、数据读取周期分析模块2003、数据分组模块2001、数据映射模块2004、周期配置模块2005均可视为上述机器可读指令的一部分，存储于至少一个存储器2006中，至少一个处理器2007，用于调用上述各模块中的指令实现装置200的功能。
此外，装置200还可包括一个用户接口2008，用于实现与用户的交互，比如与操作维护人员之间的交互。当装置200需要与其他设备之间进行消息传递时，装置200还可包括至少一个通信接口2009，比如与仿真软件300、自动化软件400、现场配置数据500数据网关20之间的通信。
图4中的各个组成部分可以总线的方式连接，实现组成部分之间的消息传递。
本发明实施例提供的装置200可为工业控制系统100的一部分，也可独立于工业控制系统100实现。
图5为本发明实施例提供的一种数据读取周期的确定方法的流程图。该方法可由前述的装置200实施。如图5所示，该方法可包括如下步骤：
S501：数据分组。
步骤S501中，将工业控制系统100的各项数据30进行分组，比如：可将同一种类型的数据30分为一组；再比如：将工业控制系统100中属于同一模板的各组件产生的数据30分为一组；再比如：将工业控制系统100中逻辑上相互关联的数据30分为一组。
S502：特征分析。
步骤S502中，对于步骤S501中分组得到的每一组数据30，分别确定该组数据30的时序信息。并且，确定各项数据30之间的关系。将得到的时序信息和数据30之间的关系作为工业控制系统100中各项数据30的数据特征15。
S503：周期分析。
步骤S503中，根据确定的各项数据30之间的关系以及各项数据30的时序信息，确定各项数据30中每一项的数据读取周期。其中，对于分组得到的每一组数据30，按照确定的该组数据30的时序信息，确定该组数据30的数据读取周期。可选地，确定的数据读取周期应满足：依据读取到的各项数据30而实现的一个工业应用60服务满足该工业应用60的要求。
S504：数据映射。
步骤S504中，确定实例模型13中的一项数据30的标识与仿真模型11中的该项数据30的标识之间的映射关系17。
S505：周期配置。
步骤S505中，根据步骤S504中确定的映射关系以及该项数据30的数据读取周期，配置工业控制系统100中的该项数据30的数据读取周期。
S506：周期调整。
数据网关20按照步骤S505中配置的数据读取周期读取数据30，并将读取到的数据30发送至工业云平台40，供工业云平台40上的各项工业应用60使用。工业应用60在使用了收到的数据30后，可根据使用情况调整数据读取周期，比如：可见针对某些数据30的调整后的数据读取周期19发送至数据网关20，或者将针对某些数据30的周期调整指令发送至数据网关20。数据网关20按照调整后的数据读取周期19读取数据30。
该方法的其他可选实现方式可结合图1～图4以及前面对装置200的描述，这里不再赘述。
图6为本发明实施例提供的数据读取周期的确定方法的另一流程图。图5描述了装置200的处理流程，图6结合了装置200与其他装置的交互来说明本发明实施例提供的数据读取周期的确定方法。如图6所示，该交流流程包括如下步骤：
S601：数据分组模块2001从仿真软件300处获取仿真模型11，该步骤可由AcquireSimulationModel()实现。
S602：数据分组模块2001进行数据分组。数据分组模块2001从仿真模型11中提取工业控制系统100中的各项数据30的数据分组14的信息。该步骤可由ExtractVariableGroupingInfo() 实现。
S603：特征分析模块2002从仿真软件300处获取仿真模型11，该步骤可由AcquireSimulationModel()实现。
S604：特征分析模块2002从仿真软件300处获取仿真数据12，该步骤可由AcquireSimulationDataSet()实现。
S605：特征分析模块2002从数据分组模块2001处获取数据分组14的信息。该步骤可由GetVariableGroups()实现。
S606：特征分析模块2002从仿真模型11中挖掘出各项数据30之间的关系。该步骤可由ExtractVariableRelation()实现。
S607：特征分析模块2002从仿真数据12中挖掘出数据分组模块2001所分的每一组数据的时序信息。该步骤可由ExtractDataFeature()实现。
S608：特征分析模块2002将得到的数据特征15(包括数据间关系和每一组数据的时序信息)设置给数据读取周期分析模块2003。该步骤可由SetDataFeatureDesc()实现。
S609：数据读取周期分析模块2003根据数据特征15以及数据分组14的信息，确定仿真的数据读取周期16。该步骤可由CalculateReadingCycle()实现。
S610：数据读取周期分析模块2003将确定的仿真的数据读取周期16设置给周期配置模块2005。该步骤可由SetSimulationReadingCycle()实现。
S611：周期配置模块2005向数据映射模块2004获取映射关系17。该步骤可由AcquireVariableMapping()实现。
S612：数据映射模块2004从仿真软件300处获取工业控制系统100的仿真模型11。该步骤可由AcquireSimulationModel()实现。
S613：数据映射模块2004从自动化软件400和/或现场配置数据500处获取工业控制系统100的实例模型13。该步骤可由AcquireInstanceModel()实现。
S614：数据映射模块2004进行数据映射，确定实例模型13中的数据30的标识与仿真模型11中的数据30的标识之间的映射关系17。该步骤可由DoVariableMapping()实现。
S615：数据映射模块2004向周期配置模块2005设置映射关系17。该步骤可由SetVariableMapping()实现。
S616：周期配置模块2005根据映射关系17将仿真的数据读取周期16变为实例的数据读取周期18。该步骤可由GenerateInstanceReadingCyle()实现。
S617：周期配置模块2005向数据网关20配置实例的数据读取周期18。周期配置模块2005 可向工业云平台40上运行的工业应用60中的配置应用设置该实例的数据读取周期18。数据网关20从该配置应用出读取该实例的数据读取周期18。上的周期配置服务来设置该周期。该步骤可由SetReadingCycleConfig()实现。
S618：工业应用60分析自身功能实现所需要的数据读取周期。该步骤可由AnalyzeNeededReadingCycle()实现。该步骤可在读取数据30之前或之后执行。
S619：工业应用60调整数据网关20的数据读取周期。该步骤可由AdjustReadingCycleConfig()实现。
图7为本发明实施例中配置数据读取周期的一个过程的示意图。图7中，仿真软件300提供仿真模型11、仿真数据12，从仿真模型11中提取数据分组14的信息。由数据分组14的信息从仿真模型11和仿真数据12中得到数据特征15。由仿真模型11得到映射关系17。数据读取周期分析模块2003和周期配置模块2005按照映射关系17和数据特征15得到实例的数据读取周期，最终配置到数据网关20上。
基于相同的技术构思，本发明实施例还提供了一种机器可读介质，该机器可读介质上存储用于使一机器执行如本文前述方法的机器可读指令。具体地，可以提供配有该机器可读介质的系统或者装置，在该机器可读介质上存储着实现上述实施例中任一实施例的功能的软件程序代码，且使该系统或者装置的计算机(或中央处理器(Central Processing Unit，CPU)或微处理器(Micro Processor Unit，MPU))读出并执行存储在存储介质中的程序代码。
在这种情况下，从存储介质读取的程序代码本身可实现上述实施例中任何一项实施例的功能，因此程序代码和存储程序代码的存储介质构成了本发明实施例的一部分。
用于提供程序代码的存储介质实施例包括软盘、硬盘、磁光盘、光盘(如只读光盘驱动器(Compact Disc Read-Only Memory，CD-ROM)、可录光盘(Compact Disk-Recordable，CD-R)、可擦写光盘(Compact Disk-ReWritable，CD-RW)、数字视盘(Digital Video Disc-Read OnlyMemory，DVD-ROM)、数字多功能光盘随机存储器(Digital Versatile Disc-Random Access Memory，DVD-RAM)、可重写型数字多功能光盘(Digital Versatile Disc±ReWritable，DVD±RW)等)、磁带、非易失性存储卡和只读存储器(Read-Only Memory，ROM)。可选择地，可以由通信网络从服务器计算机上或云上下载程序代码。
此外，应该清楚的是，不仅可以通过执行计算机所读出的程序代码，而且可以通过基于程序代码的指令使计算机上操作的操作系统等来完成部分或者全部的实际操作，从而实现上 述实施例中任意一项实施例的功能。
此外，可以理解的是，将由存储介质读出的程序代码写到插入计算机内的扩展板中所设置的存储器中或者写到与计算机相连接的扩展单元中设置的存储器中，随后基于程序代码的指令使安装在扩展板或者扩展单元上的CPU等来执行部分和全部实际操作，从而实现上述实施例中任一实施例的功能。
需要说明的是，上述各流程和各设备结构图中不是所有的步骤和模块都是必须的，可以根据实际的需要忽略某些步骤或模块。各步骤的执行顺序不是固定的，可以根据需要进行调整。上述各实施例中描述的设备结构可以是物理结构，也可以是逻辑结构，即，有些模块可能由同一物理实体实现，或者，有些模块可能分由多个物理实体实现，或者，可以由多个独立设备中的某些部件共同实现。
以上各实施例中，硬件单元可以通过机械方式或电气方式实现。例如，一个硬件单元可以包括永久性专用的电路或逻辑(如专门的处理器，FPGA或ASIC)来完成相应操作。硬件单元还可以包括可编程逻辑或电路(如通用处理器或其它可编程处理器)，可以由软件进行临时的设置以完成相应操作。具体的实现方式(机械方式、或专用的永久性电路、或者临时设置的电路)可以基于成本和时间上的考虑来确定。
上文通过附图和优选实施例对本发明进行了详细展示和说明，然而本发明不限于这些已揭示的实施例，基与上述多个实施例本领域技术人员可以知晓，可以组合上述不同实施例中的代码审核手段得到本发明更多的实施例，这些实施例也在本发明的保护范围之内。

Claims (14)

  1. 一种数据读取周期的确定装置(200)，其特征在于，包括：
    一个特征分析模块(2002)，用于确定一个工业控制系统(100)的一个仿真模型中所述工业控制系统(100)的各项数据(30)之间的关系，以及得到所述仿真模型运行时的所述各项数据(30)的时序信息；
    一个数据读取周期分析模块(2003)，用于根据所述特征分析模块(2002)确定的所述各项数据(30)之间的关系以及所述各项数据(30)的时序信息，确定所述各项数据(30)中每一项的数据读取周期。
  2. 如权利要求1所述的装置(200)，其特征在于，所述仿真模型用于模拟处于一种特定状态下的所述工业控制系统(100)。
  3. 如权利要求1或2所述的装置(200)，其特征在于，还包括：
    一个数据分组模块(2001)，用于将所述各项数据(30)分组；
    特征分析模块(2002)在得到所述各项数据(30)的时序信息时，具体用于对于所述数据分组模块(2001)分组得到的每一组数据(30)，分别确定该组数据(30)的时序信息；
    所述数据读取周期分析模块(203)，具体用于对于分组得到的每一组数据(30)，按照确定的该组数据(30)的时序信息，确定该组数据(30)的数据读取周期。
  4. 如权利要求3所述的装置(200)，其特征在于，所述数据分组模块(2001)具体用于：
    将同一种类型的数据(30)分为一组，或
    将所述工业控制系统(100)中属于同一模板的各组件产生的数据(30)分为一组，其中，所述模板用于定义一个工业控制系统(100)中组件的集合及集合中组件间的关系，且所述模板可重复使用，或
    将所述工业控制系统(100)中逻辑上相互关联的数据(30)分为一组。
  5. 如权利要求1～4任一项所述的装置(200)，其特征在于，所述数据读取周期分析模块(2003)具体用于：
    确定所述数据读取周期，使得依据读取到的所述各项数据(30)而实现的一个工业应用满足所述工业应用的要求。
  6. 如权利要求1～5任一项所述的装置(200)，其特征在于，还包括：
    一个数据映射模块(2004)，用于：
    确定所述工业控制系统(100)的一个实例模型中的所述各项数据(30)的标识，
    确定所述仿真模型中的所述各项数据(30)的标识，以及
    对于所述各项数据(30)中的每一项，确定所述实例模型中的该数据(30)的标识与所述仿真模型中的该数据(30)的标识之间的映射关系；
    一个周期配置模块(2005)，用于对于所述各项数据(30)中的每一项，根据所述映射关系以及该项数据(30)的所述数据读取周期，配置工业控制系统(100)中的该项数据(30)的数据读取周期。
  7. 一种数据读取周期的确定方法，其特征在于，包括：
    确定一个工业控制系统(100)的一个仿真模型中所述工业控制系统(100)的各项数据(30)之间的关系；
    得到所述仿真模型运行时的所述各项数据(30)的时序信息；
    根据确定的所述各项数据(30)之间的关系以及所述各项数据(30)的时序信息，确定所述各项数据(30)中每一项的数据读取周期。
  8. 如权利要求7所述的方法，其特征在于，所述仿真模型用于模拟处于一种特定状态下的所述工业控制系统(100)。
  9. 如权利要求7或8所述的方法，其特征在于，
    还包括：将所述各项数据(30)分组；
    得到所述各项数据(30)的时序信息，包括：对于分组得到的每一组数据(30)，分别确定该组数据(30)的时序信息；
    确定所述各项数据(30)中每一项的数据读取周期，包括：对于分组得到的每一组数据(30)，按照确定的该组数据(30)的时序信息，确定该组数据(30)的数据读取周期。
  10. 如权利要求9所述的方法，其特征在于，将所述各项数据(30)分组，包括：
    将同一种类型的数据(30)分为一组，或
    将所述工业控制系统(100)中属于同一模板的各组件产生的数据(30)分为一组，其中，所述模板用于定义一个工业控制系统(100)中组件的集合及集合中组件间的关系，且所述模板可重复使用，或
    将所述工业控制系统(100)中逻辑上相互关联的数据(30)分为一组。
  11. 如权利要求7～10任一项所述的方法，其特征在于，确定所述各项数据(30)中的每一项的数据读取周期，包括：
    确定所述数据读取周期，使得依据读取到的所述各项数据(30)而实现的一工业应用满足该工业应用的要求。
  12. 如权利要求7～11任一项所述的方法，其特征在于，所述方法还包括：
    确定所述工业控制系统(100)的一个实例模型中的所述各项数据(30)的标识；
    确定所述仿真模型中的所述各项数据(30)的标识；
    对于所述各项数据(30)中的每一项，
    确定所述实例模型中的该数据(30)的标识与所述仿真模型中的该数据(30)的标识之间的映射关系；
    根据所述映射关系以及该项数据(30)的所述数据读取周期，配置工业控制系统(100)中的该项数据(30)的数据读取周期。
  13. 一种数据读取周期的确定装置(200)，其特征在于，包括：
    至少一个存储器(2006)，用于存储机器可读指令；
    至少一个处理器(2007)，用于调用所述机器可读指令，执行如权利要求7～12任一项所述的方法。
  14. 一种机器可读介质，其特征在于，所述可读可读介质上存储有机器可读指令，所述机器可读指令在被至少一个处理器执行时，使所述至少一个处理器执行权利要求7～12中任一项所述的方法。
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