CN114019946B - Method and device for processing monitoring data of industrial control terminal - Google Patents
Method and device for processing monitoring data of industrial control terminal Download PDFInfo
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- CN114019946B CN114019946B CN202111331235.5A CN202111331235A CN114019946B CN 114019946 B CN114019946 B CN 114019946B CN 202111331235 A CN202111331235 A CN 202111331235A CN 114019946 B CN114019946 B CN 114019946B
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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
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0208—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the configuration of the monitoring system
- G05B23/0213—Modular or universal configuration of the monitoring system, e.g. monitoring system having modules that may be combined to build monitoring program; monitoring system that can be applied to legacy systems; adaptable monitoring system; using different communication protocols
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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
- G05B2219/00—Program-control systems
- G05B2219/20—Pc systems
- G05B2219/24—Pc safety
- G05B2219/24065—Real time diagnostics
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- 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
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses a method and a device for processing monitoring data of an industrial control terminal, relates to the technical field of industrial control, and aims to solve the problem of poor processing efficiency of the monitoring data of the existing industrial control terminal. Comprising the following steps: acquiring equipment information and control function information of at least two industrial control terminals and process flow information matched with the industrial control terminals, and establishing a terminal control network based on the equipment information, the control function information and the process flow information; issuing each terminal node in a terminal control network to an industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on a prediction model to obtain at least one monitoring prediction result; determining a monitoring state matched with at least one monitoring prediction result according to a network level and a network attribute of a terminal control network; and if the monitoring states of the industrial control terminals in the terminal control network are the number of abnormal states which is larger than a preset monitoring threshold, sending monitoring alarm information.
Description
Technical Field
The invention relates to the technical field of industrial control, in particular to a method and a device for processing monitoring data of an industrial control terminal.
Background
The industrial control system is a business process control system which is composed of various automatic control components and process control components for collecting and monitoring real-time data and ensures automatic operation, process control and monitoring of industrial infrastructure, wherein the industrial automatic control terminal is a terminal for realizing automatic operation based on the industrial control system, and is called as an industrial control terminal for short. With the rapid development of network environments, the network security of the industrial control terminal is gradually exposed to the large environment of the internet, and the industrial control terminal needs to be monitored in real time according to special requirements in the industrial environment, such as requirements of material confidentiality, parameter security and the like, so as to ensure that the industrial control terminal performs industrial production in a safe and private environment.
At present, the existing monitoring of the industrial control terminals generally collects the operation data of each industrial control terminal, carries out artificial intelligent prediction or compares according to specific indexes to monitor each parameter in industrial production, however, the artificial intelligent prediction of the operation data is too dependent on the algorithm function, the conditions of too high algorithm robustness and poor precision may exist, and the operation of industrial production equipment is stiff due to the monitoring based on the characteristic indexes, so that the operation effectiveness of the industrial production is affected, and therefore, a method for processing the monitoring data of the industrial control terminal is needed to solve the problems.
Disclosure of Invention
In view of the above, the present invention provides a method and apparatus for processing monitoring data of an industrial control terminal, which mainly aims to solve the problem of poor processing efficiency of monitoring data of the existing industrial control terminal.
According to one aspect of the present invention, there is provided a method for processing monitoring data of an industrial control terminal, including:
acquiring equipment information and control function information of at least two industrial control terminals and process flow information matched with the industrial control terminals, and establishing a terminal control network based on the equipment information, the control function information and the process flow information, wherein the terminal control network comprises at least three layers of network structures, each layer of network structure comprises at least three physical models of the industrial control terminals corresponding to the equipment information, and prediction models matched with the process flow information are embedded in the physical models;
issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result;
determining a monitoring state matched with at least one monitoring prediction result according to a network level and a network attribute of the terminal control network, wherein the monitoring state is used for limiting the safety attribute of the industrial control terminal in the terminal control network;
and if the number of the monitoring states of the industrial control terminals in the terminal control network is greater than a preset monitoring threshold, sending monitoring alarm information to the industrial control terminals and the industrial control terminals with association relation with the industrial control terminals so as to monitor and process the industrial control terminals.
According to another aspect of the present invention, there is provided a monitoring data processing apparatus of an industrial control terminal, including:
the system comprises an acquisition module, a prediction module and a control module, wherein the acquisition module is used for acquiring equipment information, control function information and process flow information matched with the industrial control terminals of at least two industrial control terminals, establishing a terminal control network based on the equipment information, the control function information and the process flow information, wherein the terminal control network comprises at least three network structures, each network structure comprises at least three physical models of the industrial control terminals corresponding to the equipment information, and the physical models are embedded with the prediction models matched with the process flow information;
the processing module is used for issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result;
the determining module is used for determining a monitoring state matched with at least one monitoring prediction result according to the network level and the network attribute of the terminal control network, and the monitoring state is used for limiting the safety attribute of the industrial control terminal in the terminal control network;
and the sending module is used for sending monitoring alarm information to the industrial control terminal and the industrial control terminal with association relation with the industrial control terminal so as to monitor and process the industrial control terminal in abnormal condition if the number of the monitoring states of the industrial control terminal in the terminal control network is larger than a preset monitoring threshold value.
According to still another aspect of the present invention, there is provided a storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the method for processing monitoring data of an industrial control terminal as described above.
According to still another aspect of the present invention, there is provided a terminal including: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is used for storing at least one executable instruction, and the executable instruction enables the processor to execute the operation corresponding to the monitoring data processing method of the industrial control terminal.
By means of the technical scheme, the technical scheme provided by the embodiment of the invention has at least the following advantages:
compared with the prior art, the embodiment of the invention acquires the equipment information and the control function information of at least two industrial control terminals and the process flow information matched with the industrial control terminals, and establishes a terminal control network based on the equipment information, the control function information and the process flow information, wherein the terminal control network comprises at least three layers of network structures, each layer of network structure comprises at least three physical models of the industrial control terminals corresponding to the equipment information, and a prediction model matched with the process flow information is embedded in each physical model; issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result; determining a monitoring state matched with at least one monitoring prediction result according to a network level and a network attribute of the terminal control network, wherein the monitoring state is used for limiting the safety attribute of the industrial control terminal in the terminal control network; if the number of the monitoring states of the industrial control terminals in the terminal control network is greater than a preset monitoring threshold, monitoring alarm information is sent to the industrial control terminals and the industrial control terminals with association relation with the industrial control terminals so as to monitor the industrial control terminals for abnormal processing, thereby realizing the integrity monitoring of the terminals of the whole industrial control network, determining the monitoring effectiveness of each industrial control terminal in the whole network, greatly improving the flexibility of each device in the operation monitoring process, avoiding the stiff and single operation monitoring of a single device and further improving the monitoring accuracy and efficiency of the industrial control terminals.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
fig. 1 shows a flowchart of a method for processing monitoring data of an industrial control terminal according to an embodiment of the present invention;
fig. 2 shows a schematic diagram of a terminal control network structure according to an embodiment of the present invention;
FIG. 3 shows a block diagram of a monitoring data processing device of an industrial control terminal according to an embodiment of the present invention;
fig. 4 shows a schematic structural diagram of a terminal according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The embodiment of the invention provides a method for processing monitoring data of an industrial control terminal, as shown in fig. 1, comprising the following steps:
101. acquiring equipment information and control function information of at least two industrial control terminals and process flow information matched with the industrial control terminals, and establishing a terminal control network based on the equipment information, the control function information and the process flow information.
In the embodiment of the invention, the industrial control terminal comprises but is not limited to a control system terminal in the industries such as chemical industry, steel industry, petroleum industry and the like, and is used as a terminal device of an online production device, after receiving a control signal from an industrial control host, the industrial control terminal starts the production device to perform production operation in an industrial process based on the online production device, and collects various monitoring data in the production device to monitor or feeds back to the industrial control host, wherein the monitoring data comprise but are not limited to time, inlet and outlet temperatures, inlet and outlet pressures, feeding quantity, discharging quantity and the like collected by different production devices. The industrial control server serving as the current execution main body can respectively perform data communication with different industrial control terminals so as to acquire monitoring data generated by each industrial control terminal. Before the process, in order to accurately process the full-automatic monitoring data, firstly, equipment information, control function information and matched process flow information of at least two industrial control terminals are acquired to establish a terminal control network. Specifically, the equipment information is the equipment model, equipment manufacturer and the like of the industrial control terminal, the control function information is the specific function of the industrial control terminal for executing control operation, including but not limited to a heating temperature extremum range, a pressure adjustment extremum range, a refrigeration range, distillation parameters, filtering parameters and the like, and the process flow information is the flow of industrial production produced by the current industrial control terminal, including but not limited to the flow steps of compressing materials after heating, then performing distillation refrigeration and the like. After the equipment information, the control function information and the process flow information are acquired, a terminal control network is established. The terminal control network comprises at least three layers of network structures, each layer of network structure comprises at least three physical models of the industrial control terminal corresponding to the equipment information, a prediction model matched with the technological process information is embedded in the physical models, namely, a network of at least three layers of network structures is constructed, each layer of network comprises three physical models and three equipment nodes, so that the three pieces of equipment information are respectively embedded into the corresponding equipment nodes, and the corresponding physical model in one equipment node is explained. The physical model in the embodiment of the invention is an analog simulation model which is matched with industrial control equipment based on control function information or equipment information and is constructed in computer software, including but not limited to MATLAB software, chemical process software Aspenplus or HYSYS and the like, and an open source interface between the physical model and each analog software can be used as a connection port in a current execution end, so that the purpose of constructing the physical model based on each analog model software is realized and the purpose of exporting the physical model based on each analog model software is realized. Meanwhile, in the process of carrying out process operation simulation on physical models obtained based on different control function information and equipment information, in order to realistically simulate the complete process of process operation, a prediction model is embedded in each physical model, so that the physical model predicts and transports transmitted material parameters and the like under the driving of the prediction model, and all predicted data in the process operation are obtained.
In one embodiment of the present invention, for further defining and describing, the establishing a terminal control network based on the equipment information, the control function information, and the process flow information includes: constructing a three-level annular network, and acquiring a physical model corresponding to each industrial control terminal, wherein each layer of network in the three-level annular network is distributed with at least three equipment nodes so as to distribute the physical model matched with each industrial control terminal at the equipment nodes according to the equipment information; and calling a prediction model which is trained and matched with the equipment information, and embedding the prediction model into a physical model matched with the equipment information to complete the construction of a terminal control network.
In order to realize the construction of the terminal control network, as shown in the terminal control network schematic diagram in fig. 2, the constructed terminal control network comprises three layers of ring networks, at least three device nodes are respectively distributed in each layer, namely, at least 9 device nodes are distributed in the three layers of ring networks, and physical models matched with each industrial control terminal are distributed at each device node according to device information, wherein if the number of the industrial control terminals is smaller than 9, energy detection sensors, such as liquid flow sensors and gas flow sensors, are configured at redundant device nodes, the corresponding physical models are corresponding to a liquid flow meter physical model and a gas flow meter physical model, and at this time, the prediction model can be a preconfigured linear function of energy parameter micro-loss as a process flow passing through the liquid flow sensors and the gas flow sensors.
In addition, the prediction model embedded in each physical model is obtained by training based on the training samples corresponding to the process flow information and the equipment information.
In one embodiment of the present invention, for further definition and explanation, the method further includes: acquiring training samples corresponding to the process flow information and the equipment information, and establishing a three-layer convolutional neural network; and carrying out model training on the three-layer convolutional neural network based on the training sample to obtain a prediction model matched with different industrial control terminals, wherein the weight of the convolutional layer of the prediction model is obtained by converting the positions of nodes of different industrial control terminals in a process flow.
For a specific model training process of the prediction model, training samples corresponding to the process flow information and the equipment information can be obtained, monitoring sample values corresponding to different process flow information and different equipment information are marked in the training samples, and the training samples are used for training the established three-layer convolutional neural network. The method and the device for predicting the convolution layer weight of the industrial control terminal are characterized in that the convolution layer weight of the prediction model is obtained by converting the node positions of different industrial control terminals in the process flow, namely the convolution layer weight of the three-layer convolution network is limited, namely the sequence of the node positions of the industrial control terminals in the process flow is converted into corresponding weight values, for example, if the number of all the process flow nodes is 5, the node positions corresponding to the process flow information of the industrial control terminal to be embedded is 3, the configuration of the convolution layer weight of one layer in the corresponding prediction model is 3/5, and the rest of the convolution layer weights are respectively configured to be (1-3/5)/2, meanwhile, the training method of the convolution neural network is the same as that of the prior art, the embodiment of the invention does not have specific limitation, so that the prediction model embedded in the physical model corresponding to each industrial control terminal is matched with the respective process flow node positions, and the prediction accuracy of the industrial control terminal in the process flow and the simulation accuracy of the physical model in the terminal control network are greatly improved.
It should be noted that, since the terminal control network is a three-layer ring network, the outermost layer is three industrial control terminals which start to operate in the process flow, the innermost layer is the last industrial control terminal which is used as output, the output of the current ring layer is used as the input of the next ring layer, and meanwhile, the input of the current ring layer is used as the input auxiliary parameter of the next ring layer, so that errors caused by damage of intermediate equipment are reduced when the prediction model predicts. Meanwhile, when the prediction model is trained, the training samples also contain input auxiliary parameter sample values, so that the training of the prediction model is completed, wherein the input auxiliary parameters can be introduced into the prediction model in one physical model connected with the previous layer in each layer, and the prediction models of other physical models can still be trained according to normal monitoring sample values, so that the process simulation accuracy of the three-layer annular network is realized.
102. And issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result.
In the embodiment of the invention, in order to combine the constructed physical model and the corresponding prediction model, the industrial control terminal can predict based on the prediction model, reduce the data processing pressure in the current industrial control server, and send each terminal node to the corresponding industrial control terminal, so that each industrial control terminal can collect the monitoring data and simultaneously predict the monitoring data. The issuing process is to issue each physical model and the prediction model to the corresponding industrial control terminal according to the matched equipment information, and meanwhile, if auxiliary parameters need to be input in the prediction model based on the terminal control network, the issued terminal node includes source information for acquiring the input auxiliary parameters, that is, output of other industrial control terminals is used as the auxiliary parameters needed to be input, for example, the industrial control terminal 4 belongs to a terminal at a second process node position in a three-layer annular network, and the loaded prediction model needs output parameters of the industrial control terminal 2 at a last process node position in the first layer as the auxiliary parameters of the prediction model in the physical model of the engineering terminal 4, so that the monitoring data are predicted based on the prediction model, and a monitoring prediction result is obtained.
103. And determining a monitoring state matched with at least one monitoring prediction result according to the network level and the network attribute of the terminal control network.
In the embodiment of the invention, in order to ensure the security of the whole terminal control network, the industrial control server of the current execution subject acquires the monitoring prediction result from each industrial control terminal, and determines the monitoring state of each industrial control terminal relative to the whole terminal control network according to the network level and the network attribute, namely, the monitoring state is used for limiting the security attribute of the industrial control terminal in the terminal control network.
In an embodiment of the present invention, for further defining and describing, the determining, according to the network hierarchy and the network attribute of the terminal control network, the monitoring state matched with the at least one monitoring prediction result includes: analyzing the network level and the network attribute controlled by the terminal; and searching the monitoring states corresponding to all monitoring prediction results matched with different network levels and network attributes in the terminal control network according to the preset corresponding relation of the monitoring states.
Specifically, the determination of the monitoring state is specifically analyzing a network hierarchy and a network attribute of terminal control, the network hierarchy is used for representing the node position of each physical model in a terminal control network, the network attribute is used for representing the functional effect of each physical model on process flow information in the terminal control network, for example, the larger the network attribute is, the larger the strength of the physical model in the process flow is, the network attribute is a numerical value between 0 and 1, the network attribute of the general physical model with the heating function is the largest, the corresponding specific numerical value can be preset based on a technician, the embodiment of the invention is not specifically limited, and the corresponding network hierarchy is the ratio of the node position corresponding to the physical model to all the node positions. In addition, after the network levels and network attributes corresponding to the industrial control terminals are determined, monitoring states corresponding to all monitoring prediction results matched with different network levels and network attributes in the terminal control network are searched according to a preset monitoring state corresponding relation, and monitoring states corresponding to different monitoring prediction results by different network levels and different network attributes are recorded in the preset monitoring state corresponding relation, so that monitoring states corresponding to the industrial control terminals, including abnormal states and normal states, are accurately searched and matched.
104. And if the number of the monitoring states of the industrial control terminals in the terminal control network is greater than a preset monitoring threshold, sending monitoring alarm information to the industrial control terminals and the industrial control terminals with association relation with the industrial control terminals.
In the embodiment of the invention, in order to ensure the safety of the whole terminal control network, if the number of each industrial control terminal in an abnormal state is greater than a preset monitoring threshold value, the whole terminal control network is determined to be in the abnormal state, and monitoring alarm information is sent to the industrial control terminal and the industrial control terminal with an association relation with the industrial control terminal so as to monitor and process the industrial control terminal.
In an embodiment of the present invention, for further defining and describing, sending monitoring alarm information to the industrial control terminal and the industrial control terminal having an association relationship with the industrial control terminal includes: searching for adjacent industrial control terminals which are matched in the same network level, and determining the industrial control terminal to be alerted and the industrial control terminal with the association relation; and sending monitoring alarm information to the industrial control terminal and the industrial control terminal with the association relation.
In order to ensure the safety of a terminal control network of a whole network, when monitoring alarm information is sent to industrial control terminals with association relation, specifically searching for adjacent industrial control terminals which belong to the same network level and are matched with process flow information, and determining the industrial control terminal to be alarmed and the industrial control terminal with association relation, namely, in the same ring layer, if one industrial control terminal is in a monitoring abnormal state, taking the industrial control terminal as an object for sending the monitoring alarm information based on the matched adjacent industrial control terminal. The industrial control terminal to be alerted and the industrial control terminal with the association relationship are determined to be the industrial control terminal with abnormal state, the industrial control terminal with the association relationship is the adjacent industrial control terminal, so that the current execution main body sends the monitoring alert information to the industrial control terminal and the industrial control terminal with the association relationship, and the embodiment of the invention is not particularly limited in the specific form of the monitoring alert information.
In addition, the embodiment of the invention further comprises the following steps: if the monitoring states of the industrial control terminals in the terminal control network are the number of abnormal states which is smaller than or equal to a preset monitoring threshold, the monitoring states of the industrial control terminals are recorded according to the network form in the terminal control network, and extraction processing is carried out according to a preset time interval. The network form is the node position of each industrial control terminal in the three-layer annular network so as to store the corresponding monitoring state, and the current execution main body can extract according to a preset time interval so as to manually perform secondary monitoring processing for analyzing the historical data.
Compared with the prior art, the embodiment of the invention acquires the equipment information and the control function information of at least two industrial control terminals and the process flow information matched with the industrial control terminals, and establishes a terminal control network based on the equipment information, the control function information and the process flow information, wherein the terminal control network comprises at least three layers of network structures, each layer of network structure comprises at least three physical models of the industrial control terminals corresponding to the equipment information, and a prediction model matched with the process flow information is embedded in the physical models; issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result; determining a monitoring state matched with at least one monitoring prediction result according to a network level and a network attribute of the terminal control network, wherein the monitoring state is used for limiting the safety attribute of the industrial control terminal in the terminal control network; if the number of the monitoring states of the industrial control terminals in the terminal control network is greater than a preset monitoring threshold, monitoring alarm information is sent to the industrial control terminals and the industrial control terminals with association relation with the industrial control terminals so as to monitor the industrial control terminals for abnormal processing, thereby realizing the integrity monitoring of the terminals of the whole industrial control network, determining the monitoring effectiveness of each industrial control terminal in the whole network, greatly improving the flexibility of each device in the operation monitoring process, avoiding the stiff and single operation monitoring of a single device and further improving the monitoring accuracy and efficiency of the industrial control terminals.
Further, as an implementation of the method shown in fig. 1, an embodiment of the present invention provides a monitoring data processing apparatus of an industrial control terminal, as shown in fig. 3, where the apparatus includes:
the obtaining module 21 is configured to obtain device information and control function information of at least two industrial control terminals, and process flow information matched with the industrial control terminals, and establish a terminal control network based on the device information, the control function information, and the process flow information, where the terminal control network includes at least three network structures, each network structure includes at least three physical models of the industrial control terminals corresponding to the device information, and a prediction model matched with the process flow information is embedded in the physical models;
the processing module 22 is configured to issue each terminal node in the terminal control network to the industrial control terminal, collect monitoring data generated by the industrial control terminal, and respectively perform prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result;
a determining module 23, configured to determine, according to a network hierarchy and a network attribute of the terminal control network, a monitoring state matched with at least one monitoring prediction result, where the monitoring state is used to define a security attribute of the industrial control terminal in the terminal control network;
and the sending module 24 is configured to send monitoring alarm information to the industrial control terminal and the industrial control terminal having an association relationship with the industrial control terminal if the number of the monitoring states of the industrial control terminal in the terminal control network is greater than a preset monitoring threshold value, so as to perform monitoring exception handling on the industrial control terminal.
Compared with the prior art, the embodiment of the invention acquires the equipment information and the control function information of at least two industrial control terminals and the process flow information matched with the industrial control terminals, and establishes a terminal control network based on the equipment information, the control function information and the process flow information, wherein the terminal control network comprises at least three layers of network structures, each layer of network structure comprises at least three physical models of the industrial control terminals corresponding to the equipment information, and a prediction model matched with the process flow information is embedded in each physical model; issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result; determining a monitoring state matched with at least one monitoring prediction result according to a network level and a network attribute of the terminal control network, wherein the monitoring state is used for limiting the safety attribute of the industrial control terminal in the terminal control network; if the number of the monitoring states of the industrial control terminals in the terminal control network is greater than a preset monitoring threshold, monitoring alarm information is sent to the industrial control terminals and the industrial control terminals with association relation with the industrial control terminals so as to monitor the industrial control terminals for abnormal processing, thereby realizing the integrity monitoring of the terminals of the whole industrial control network, determining the monitoring effectiveness of each industrial control terminal in the whole network, greatly improving the flexibility of each device in the operation monitoring process, avoiding the stiff and single operation monitoring of a single device and further improving the monitoring accuracy and efficiency of the industrial control terminals.
According to one embodiment of the present invention, there is provided a storage medium storing at least one executable instruction for executing the monitoring data processing method of the industrial control terminal in any of the above method embodiments.
Fig. 4 is a schematic structural diagram of a terminal according to an embodiment of the present invention, and the specific embodiment of the present invention is not limited to the specific implementation of the terminal.
As shown in fig. 4, the terminal may include: a processor (processor) 302, a communication interface (Communications Interface) 304, a memory (memory) 306, and a communication bus 308.
Wherein: processor 302, communication interface 304, and memory 306 perform communication with each other via communication bus 308.
A communication interface 304 for communicating with network elements of other devices, such as clients or other servers.
The processor 302 is configured to execute the program 310, and may specifically execute relevant steps in the embodiment of the method for processing monitoring data of the industrial control terminal.
In particular, program 310 may include program code including computer-operating instructions.
The processor 302 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in the terminal may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
Memory 306 for storing programs 310. Memory 306 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
Program 310 may be specifically operable to cause processor 302 to:
acquiring equipment information and control function information of at least two industrial control terminals and process flow information matched with the industrial control terminals, and establishing a terminal control network based on the equipment information, the control function information and the process flow information, wherein the terminal control network comprises at least three layers of network structures, each layer of network structure comprises at least three physical models of the industrial control terminals corresponding to the equipment information, and prediction models matched with the process flow information are embedded in the physical models;
issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result;
determining a monitoring state matched with at least one monitoring prediction result according to a network level and a network attribute of the terminal control network, wherein the monitoring state is used for limiting the safety attribute of the industrial control terminal in the terminal control network;
and if the number of the monitoring states of the industrial control terminals in the terminal control network is greater than a preset monitoring threshold, sending monitoring alarm information to the industrial control terminals and the industrial control terminals with association relation with the industrial control terminals so as to monitor and process the industrial control terminals.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. The monitoring data processing method of the industrial control terminal is characterized by comprising the following steps of:
acquiring equipment information, control function information and process flow information matched with the industrial control terminals of at least two industrial control terminals, and establishing a terminal control network based on the equipment information, the control function information and the process flow information, wherein the terminal control network comprises at least three network structures, each network structure comprises at least three physical models of the industrial control terminals corresponding to the equipment information, and a prediction model matched with the process flow information is embedded in each physical model;
issuing each terminal node in the terminal control network to the industrial control terminal, collecting monitoring data generated by the industrial control terminal, and respectively carrying out prediction processing on the monitoring data collected by the industrial control terminal based on the prediction model to obtain at least one monitoring prediction result;
determining a monitoring state matched with at least one monitoring prediction result according to the network level and the network attribute of the terminal control network, wherein the monitoring state is used for limiting the safety attribute of the industrial control terminal in the terminal control network;
if the number of the monitoring states of the industrial control terminals in the terminal control network is greater than a preset monitoring threshold, sending monitoring alarm information to the industrial control terminals and the industrial control terminals with association relation with the industrial control terminals so as to monitor and process the industrial control terminals;
wherein said establishing a terminal control network based on said equipment information, said control function information and said process flow information comprises:
constructing a three-level annular network, and acquiring a physical model corresponding to each industrial control terminal, wherein at least three equipment nodes are distributed in each layer of network in the three-level annular network so as to distribute the physical model matched with each industrial control terminal at the equipment nodes according to the equipment information;
and calling a prediction model which is subjected to model training and is matched with the equipment information, embedding the prediction model into a physical model which is matched with the equipment information, and completing construction of a terminal control network, wherein the prediction model is obtained by training based on the training samples corresponding to the process flow information and the equipment information.
2. The method according to claim 1, wherein the method further comprises:
acquiring training samples corresponding to the process flow information and the equipment information, and establishing a three-layer convolutional neural network;
and carrying out model training on the three-layer convolutional neural network based on the training sample to obtain a prediction model matched with different industrial control terminals, wherein the weight of the convolutional layer of the prediction model is obtained by converting the positions of nodes of different industrial control terminals in a process flow.
3. The method of claim 1, wherein determining a monitoring state matching at least one monitoring prediction according to a network hierarchy and network attributes of the terminal control network comprises:
analyzing a network level and network attributes of the terminal control, wherein the network level is used for representing the position information of each physical model in the terminal control network, and the network attributes are used for representing the functional effect of each physical model in the terminal control network on the process flow information;
and searching the monitoring states corresponding to all monitoring prediction results matched with different network levels and network attributes in the terminal control network according to the corresponding relation of the preset monitoring states, wherein the corresponding relation of the preset monitoring states records the monitoring states corresponding to the different network levels and the different network attributes aiming at the different monitoring prediction results.
4. The method of claim 3, wherein the sending the monitoring alarm information to the industrial control terminal and the industrial control terminal having an association relationship with the industrial control terminal comprises:
searching for adjacent industrial control terminals which are matched in the same network level, and determining the industrial control terminal to be alerted and the industrial control terminal with the association relation;
sending monitoring alarm information to the industrial control terminal and the industrial control terminal with the association relation;
the method further comprises the steps of:
if the number of the monitoring states of the industrial control terminals in the terminal control network is smaller than or equal to a preset monitoring threshold, the monitoring states of the industrial control terminals are recorded according to the network form in the terminal control network, and extraction processing is carried out according to a preset time interval.
5. A storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the method for processing monitor data for an industrial control terminal according to any one of claims 1-4.
6. A terminal, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction, where the executable instruction causes the processor to perform an operation corresponding to the method for processing monitoring data of an industrial control terminal according to any one of claims 1 to 4.
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