CN110764462A

CN110764462A - PLC intelligent electric cabinet control method and device and PLC control server

Info

Publication number: CN110764462A
Application number: CN201911178226.XA
Authority: CN
Inventors: 严守龙; 刘平
Original assignee: Zhuhai Hengqin Huadi Technology Co Ltd
Current assignee: Zhuhai Hengqin Huadi Technology Co Ltd
Priority date: 2019-11-27
Filing date: 2019-11-27
Publication date: 2020-02-07
Anticipated expiration: 2039-11-27
Also published as: CN110764462B

Abstract

The embodiment of the application provides a PLC intelligent electric cabinet control method, a device and a PLC control server, by combining power distribution process information of the PLC intelligent electric cabinet in each preset power-on time period in the power-on process with electric equipment and working state information of the electric equipment, state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period can be obtained, so that the working state of the PLC intelligent electric cabinet in the power distribution process of the next preset power-on time period can be adaptively adjusted, the power distribution interaction effect between the PLC intelligent electric cabinet and the electric equipment is improved, the power distribution process can be adaptively adjusted according to the working state of the electric equipment, the electric equipment can be continuously in the working state within a parameter calibration range with the electric equipment, and the service life of the electric equipment is prolonged.

Description

PLC intelligent electric cabinet control method and device and PLC control server

Technical Field

The application relates to the technical field of PLC electric cabinets, in particular to a PLC intelligent electric cabinet control method and device and a PLC control server.

Background

PLC (Programmable Logic Controller) distribution cabinets are generally used in situations with dispersed loads and fewer loops, and provide protection, monitoring and control for electrical devices by distributing the power of a certain circuit of an upper-level distribution device to nearby electrical devices. However, because the PLC intelligent electric cabinet is actually powered on with the electric equipment, and for different electric equipment and different time periods, the working state of the power distribution process may cause a power distribution interaction effect that is difficult to achieve with the electric equipment due to various factors, and the PLC power distribution cabinet itself has a memory effect, and it is difficult to adaptively adjust the power distribution process according to the working state of the electric equipment, and then the electric equipment may not be in the working state within the parameter calibration range with itself, and the service life of the electric equipment is affected.

Disclosure of Invention

In order to overcome at least the above deficiencies in the prior art, the present application aims to provide a PLC intelligent electric cabinet control method, device and PLC control server, which can avoid the situation that the accuracy of the final result is reduced due to a plurality of unmatched problems possibly existing in the detection process, and effectively reduce the maintenance cost in the detection process.

In a first aspect, the application provides a PLC intelligent electric cabinet control method, which is applied to a PLC control server, where the PLC control server is in communication connection with a PLC intelligent electric cabinet and an electric device electrically connected to the PLC intelligent electric cabinet, respectively, and the method includes:

acquiring power distribution process information and working state information of the electric equipment in each preset power-on time period in the power-on process of the PLC intelligent electric cabinet and the electric equipment;

according to the acquired power distribution process information and the acquired working state information in each preset power-on time period, determining state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period;

and generating a control task set aiming at the PLC intelligent electric cabinet by taking the next preset power-on time period as a reference according to the determined state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period, and then sending the control task set to the PLC intelligent electric cabinet, so that the PLC intelligent electric cabinet adjusts the working state in the corresponding power distribution process according to the control task set in the next preset power-on time period.

In a possible design of the first aspect, the step of determining, according to the acquired power distribution process information and the acquired operating state information in each preset power-on period, state association information between the PLC intelligent electric cabinet and the electric device in each preset power-on period includes:

according to the acquired power distribution process information and the acquired working state information in each preset power-on time period, determining a power distribution process control parameter of each power distribution process in the power distribution process information and a working state process control parameter of each working state process in the working state information in each preset power-on time period;

obtaining the power distribution process control parameters of each power distribution process and the correlation among the working state process control parameters of each working state process according to the power distribution process control parameters of each power distribution process in the power distribution process information and the working state process control parameters of each working state process in the working state information in each preset power-on time period, and generating a correlation unit for representing the correlation among each working state process and each power distribution process according to the correlation;

determining the correlation information of the power distribution process information and the working state information according to each correlation unit;

determining a first associated characteristic value of each information associated node of the associated information in the power distribution process information according to the power distribution information parameter of each parameter type of the corresponding information associated node of each information associated node of the associated information in the power distribution process information, wherein the corresponding information associated nodes at least comprise information associated nodes of the same parameter type;

determining a second correlation characteristic value of each information correlation node of the correlation information corresponding to the information correlation node in the working state information according to the working state information parameter of each information correlation node of the correlation information corresponding to the information correlation node in the working state information;

generating a correlation characteristic curve of the correlation information according to the first correlation characteristic value and the second correlation characteristic value of each information correlation node of the correlation information;

and determining state associated information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period according to the associated characteristic curve of the associated information.

In a possible design of the first aspect, the step of generating a correlation characteristic curve of the correlation information according to the first correlation characteristic value and the second correlation characteristic value of each information correlation node of the correlation information includes:

updating the association characteristic information of the information association node for updating the control strategy and the association characteristic information of the information association node for maintaining the strategy, which are determined last time, according to the first association characteristic value and the second association characteristic value of each information association node of the association information;

when the updated associated feature information of the information associated node for updating the control strategy and the updated associated feature information of the information associated node for maintaining the strategy meet preset conditions, determining an associated information sequence and a non-associated information sequence of the updating control strategy according to the associated feature information of each information associated node of the current updating control strategy;

determining an associated information sequence of the maintenance strategy according to associated characteristic information of each information associated node of the current maintenance strategy;

when the update quantity of the information associated node with the largest update quantity in the update control strategy is larger than the update quantity of the information associated node with the smallest update quantity in the maintenance strategy, moving the information associated node with the smallest update quantity in the update control strategy into the maintenance strategy, and moving the information associated node with the smallest update quantity in the maintenance strategy into the update control strategy;

and respectively generating an associated characteristic curve of the associated information according to the respective corresponding curve directions according to the updated control strategy after updating the information associated nodes and the associated characteristic information after maintaining each information associated node in the strategy.

In a possible design of the first aspect, the step of determining, according to the associated characteristic curve of the associated information, state associated information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on period includes:

obtaining node position information corresponding to each preset associated node in a state associated region passing through a set region around each intersected node according to the associated characteristic curve of the associated information;

according to the corresponding relation between node position information and effective associated attributes configured according to node position information corresponding to each preset associated node in a state associated area of a set area around each intersection node, and in the configured corresponding relation between the node position information and the effective associated attributes, determining that the corresponding associated attributes in the obtained node position information are target node position information of the effective associated attributes, wherein the associated attributes comprise effective associated attributes corresponding to node position information of at least part of adjustable parts of a power distribution process obtained by dividing the whole power distribution process of the PLC intelligent electric cabinet and effective associated attributes corresponding to node position information of at least part of adjustable parts of the working state process obtained by dividing the whole working state process of the electric equipment;

the corresponding relation between the node position information and the effective correlation attributes is configured in the following way:

determining a distribution process identifier of a distribution process in which a state association area corresponding to each intersection node is located in at least part of a distribution process obtained by dividing the whole distribution process of the PLC intelligent electric cabinet, and determining a working state process identifier of a working state process in which the state association area corresponding to each intersection node is located in at least part of a working state process obtained by dividing the whole working state process of the electric equipment;

acquiring first state associated coordinate information of at least part of power distribution process in the power distribution process corresponding to the power distribution process identifier and second state associated coordinate information of at least part of working state process in the working state process corresponding to the working state process identifier;

traversing each power distribution process according to the power distribution process identification, setting the node position information contained in the enclosed area defined by the first state associated coordinate information as an effective value to obtain an effective associated attribute, traversing each working state process according to the working state process identification, and setting the node position information contained in the enclosed area defined by the second state associated coordinate information as an effective value to obtain an effective associated attribute;

establishing a corresponding relation between the node position information and the effective correlation attribute contained in the at least partial power distribution process and the at least partial working state process;

and according to the target node position information of which the corresponding association attribute is the effective association attribute in the obtained node position information, determining the state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period.

In a possible design of the first aspect, the step of determining, according to target node location information in which a corresponding correlation attribute in the determined obtained node location information is a valid correlation attribute, state correlation information between the PLC intelligent electric cabinet and the electric device in each preset power-on period includes:

according to target node position information, determining that the corresponding correlation attribute in the obtained node position information is an effective correlation attribute, performing position simulation on each target node position of the target node position information to obtain a first position simulation result and a second position simulation result, wherein the first position simulation result position is a correlation behavior confidence result of each target node position, and the second position simulation result position is a non-correlation behavior confidence result of each target node position;

generating corresponding association behaviors of each target node position according to the first position simulation result and the second position simulation result, and determining an association data area according to the association behaviors of each target node position;

extracting past associated data of the associated behaviors of the positions of the target nodes, taking a set threshold value as an associated window, and extracting an associated data sequence of which the associated area of the past associated data is overlapped with the associated data area;

processing the associated behaviors in the associated data sets according to a generating sequence according to any two adjacent associated data sets in the associated data sequence to form a plurality of associated behavior intervals, calculating the associated behavior interval between all the associated behaviors in the next associated data set and all the associated behaviors in the previous associated data set as the designated associated behaviors, identifying whether the associated behavior interval between only one associated behavior and one designated associated behavior meets the maximum associated behavior interval threshold value, if so, connecting the associated behavior and the corresponding designated associated behavior to form the associated behavior interval, updating the associated behavior interval to be the designated associated behavior, otherwise, expanding the associated behavior to be the designated associated behavior interval, and identifying whether the number of the associated behaviors contained in each associated behavior interval is larger than or equal to the set number of the associated behaviors, if so, calculating the association indication value of each target association behavior position by adopting the assigned association behavior in the association behavior interval, the last association behavior of the assigned association behavior and the association section of the association behavior in the next association data set, and otherwise, returning to execute the operation of calculating the association behavior interval between all association behaviors in the next association data set and all association behaviors in the last association data set as the assigned association behavior; calculating the association marking value of each target association behavior position by adopting the assigned association behaviors in the association behavior interval, the last association behavior of the assigned association behaviors and the association section of the association behaviors in the next association data set, and identifying whether at most one association behavior exists in the next association data set or not so that the association marking value meets the preset threshold value by adopting the association marking value of each target association behavior position; if the association behavior exists, the association behavior is connected with the corresponding designated association behavior to form an association behavior interval, the association behavior is updated to be the designated association behavior, and otherwise, the association behavior is expanded to be the designated association behavior as a new association behavior interval;

according to the generation sequence, the association behavior intervals, which are adjacent to each other in the connection sequence and have the association behavior interval between the initial association behavior and the last association behavior of the two association behavior intervals smaller than the maximum continuous association behavior interval of the association behaviors at the positions of the target association behaviors in the association behavior intervals, form association data set characteristics;

substituting the associated behaviors in each associated data set characteristic into a hidden Mark matrix to obtain an associated section of state associated designated information of each associated data set characteristic, obtaining the associated behavior characteristic of each target associated behavior position according to the past associated data, and processing the associated behavior characteristic of each target associated behavior position at set intervals to obtain a plurality of associated sections for identifying associated points;

matching according to state association designated information on the association data set characteristics and association sections of identification association points on the association behavior characteristics of the association behavior positions of the targets to obtain accumulated association behavior interval values;

and selecting the associated data set characteristic with the smallest accumulated associated behavior interval value of the associated behavior characteristics of the associated behavior positions of all the associated data set characteristics as the state associated information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period.

In a possible design of the first aspect, the step of generating a set of control tasks for the PLC intelligent electric cabinet based on the following preset power-on time period and sending the set of control tasks to the PLC intelligent electric cabinet according to the determined state association information between the PLC intelligent electric cabinet and the electric device in each preset power-on time period includes:

determining target specified information matched with the state association specified information characteristics of the prior control task of the PLC intelligent electric cabinet by taking the next preset power-on time period as a reference from each state association specified information of the state association information;

determining a control task corresponding to each designated control node in the target designated information according to the designated control node in the target designated information and a state association designated control node matched with the designated control node in the prior control task in characteristics;

and generating a control task set aiming at the PLC intelligent electric cabinet based on the control task corresponding to each designated control node in the target designated information, and then sending the control task set to the PLC intelligent electric cabinet.

In a possible design of the first aspect, the determining, according to the designated control node in the target designation information and the designated control node associated with the state matching with the designated control node feature in the previous control task, the control task corresponding to each designated control node in the target designation information includes:

determining a node control parameter of each designated control node according to the designated control node in the target designated information and the state association designated control node matched with the designated control node in the prior control task;

determining the number of nodes with the same node control parameters with the designated control node in other designated control nodes aiming at each designated control node;

determining the node control parameter of the designated control node corresponding to the maximum value of the number of the nodes of the same node control parameter corresponding to each designated control node as the global node control parameter corresponding to the target designated information, and taking the node control parameters of the rest designated control nodes as the branch node control parameters corresponding to each designated control node;

and determining a control task corresponding to each designated control node in the target designated information according to the global node control parameters and the corresponding branch node control parameters.

In a second aspect, an embodiment of the present application provides an electric cabinet controlling means of PLC intelligence, is applied to PLC control server, PLC control server respectively with the electric cabinet of PLC intelligence and with electric cabinet electric connection's consumer communication connection of PLC intelligence, the device includes:

the acquisition module is used for acquiring power distribution process information of the PLC intelligent electric cabinet in each preset power-on time period in the power-on process of the PLC intelligent electric cabinet and the electric equipment and working state information of the electric equipment;

the determining module is used for determining state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period according to the acquired power distribution process information and the acquired working state information in each preset power-on time period;

and the generating module is used for generating a control task set for the PLC intelligent electric cabinet based on the next preset power-on time period according to the determined state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period, and then sending the control task set to the PLC intelligent electric cabinet, so that the PLC intelligent electric cabinet adjusts the working state in the corresponding power distribution process according to the control task set in the next preset power-on time period.

In a third aspect, an embodiment of the present application provides a PLC control server, where the PLC control server includes a processor, a memory, and a network interface, where the memory, the network interface, and the processor are connected through a bus system, the network interface is used for being communicatively connected with a PLC intelligent electrical cabinet, the memory is used for storing a program, an instruction, or a code, and the processor is used for executing the program, the instruction, or the code in the memory, so as to implement the PLC intelligent electrical cabinet control method described in the first aspect or any one of the possible designs of the first aspect.

In a fourth aspect, an embodiment of the present application provides a readable storage medium, where instructions are stored, and when executed, the readable storage medium implements the PLC intelligent electric cabinet control method described in the first aspect or any one of the possible designs of the first aspect.

Based on any one of the above aspects, this application can obtain the state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period by combining the power distribution process information and the working state information of the electric equipment in each preset power-on time period in the power-on process with the electric equipment, so as to adaptively adjust the working state of the PLC intelligent electric cabinet in the power distribution process of the next preset power-on time period, thereby improving the power distribution interaction effect between the PLC intelligent electric cabinet and the electric equipment, adaptively adjusting the power distribution process aiming at the working state of the electric equipment, further enabling the electric equipment to be continuously in the working state within the parameter calibration range with the electric equipment, and prolonging the service life of the electric equipment.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.

Fig. 1 is a schematic view of an application scenario of a PLC intelligent electric cabinet control system provided in an embodiment of the present application;

fig. 2 is a schematic flow chart of a PLC intelligent electric cabinet control method provided in the embodiment of the present application;

FIG. 3 is a flow chart illustrating the sub-steps of step S120 shown in FIG. 2;

FIG. 4 is a flow chart illustrating the sub-steps of step S130 shown in FIG. 2;

fig. 5 is a schematic functional module diagram of a PLC intelligent electric cabinet control device provided in the embodiment of the present application;

fig. 6 is a block diagram schematically illustrating a structure of the server shown in fig. 1 according to an embodiment of the present disclosure.

Detailed Description

The present application will now be described in detail with reference to the drawings, and the specific operations in the method embodiments may also be applied to the apparatus embodiments or the system embodiments. In the description of the present application, "at least one" includes one or more unless otherwise specified. "plurality" means two or more. For example, at least one of A, B and C, comprising: a alone, B alone, a and B in combination, a and C in combination, B and C in combination, and A, B and C in combination. In this application, "/" means "or, for example, A/B may mean A or B; "and/or" herein is merely an association relationship describing the association candidate slave PLC intelligent electric cabinet, and means that there may be three relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone.

Fig. 1 is an interaction diagram of a PLC intelligent electrical cabinet control system 10 according to an embodiment of the present application. The PLC intelligent electric cabinet control system 10 may include a PLC control server 100, a PLC intelligent electric cabinet 200, and an electric device 300, and the PLC control server 100 may include a processor for executing an instruction operation. The PLC intelligent electrical cabinet control system 10 shown in fig. 1 is only one possible example, and in other possible embodiments, the PLC intelligent electrical cabinet control system 10 may include only one of the components shown in fig. 1 or may also include other components.

In some embodiments, the PLC control server 100 may be a single server or a server group. The operation server group may be centralized or distributed (for example, the PLC control server 100 may be a distributed system). In some embodiments, the PLC control server 100 may be local or remote to the PLC intelligent electrical cabinet 200. For example, the PLC control server 100 may access information stored in the PLC intelligent electric cabinet 200, the electric devices 300, and the database, or any combination thereof, via a network. As another example, the PLC control server 100 may be directly connected to at least one of the PLC intelligent electric cabinet 200, the electric devices 300, and a database to access information and/or data stored therein. In some embodiments, the PLC control server 100 may be implemented on a cloud platform; by way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud (community cloud), a distributed cloud, an inter-cloud, a multi-cloud, and the like, or any combination thereof. In some embodiments, the PLC control server 100, the PLC intelligent electrical cabinet 200, and the electrical device 300 may be implemented on an electronic device having one or more components shown in fig. 2 in the embodiments of the present application.

In some embodiments, the PLC control server 100 may include a processor. The processor may process information and/or data related to the service request to perform one or more of the functions described herein. A processor may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, a Processor may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a reduced Instruction Set computer (reduced Instruction Set computer), a microprocessor, or the like, or any combination thereof.

The network may be used for the exchange of information and/or data. In some embodiments, one or more components (e.g., PLC control server 100, PLC intelligent electrical cabinet 200, powered device 300, and a database) in PLC intelligent electrical cabinet control system 10 may send information and/or data to other components. In some embodiments, the network may be any type of wired or wireless network, or combination thereof. Merely by way of example, the Network 130 may include a wired Network, a Wireless Network, a fiber optic Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a Public Switched Telephone Network (PSTN), a bluetooth Network, a ZigBee Network, a Near Field Communication (NFC) Network, or the like, or any combination thereof. In some embodiments, the network may include one or more network access points. For example, the network may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of the interaction scenario may connect to the network to exchange data and/or information.

The aforementioned database may store data and/or instructions. In some embodiments, the database may store data obtained from the PLC intelligent electrical cabinet 200 and/or the powered device 300. In some embodiments, the database may store data and/or instructions for the exemplary methods described herein. In some embodiments, the database may include mass storage, removable storage, volatile Read-write Memory, or Read-Only Memory (ROM), among others, or any combination thereof. By way of example, mass storage may include magnetic disks, optical disks, solid state drives, and the like; removable memory may include flash drives, floppy disks, optical disks, memory cards, zip disks, tapes, and the like; volatile read-write Memory may include Random Access Memory (RAM); the RAM may include Dynamic RAM (DRAM), Double data Rate Synchronous Dynamic RAM (DDR SDRAM); static RAM (SRAM), Thyristor-Based Random Access Memory (T-RAM), Zero-capacitor RAM (Zero-RAM), and the like. By way of example, ROMs may include Mask Read-Only memories (MROMs), Programmable ROMs (PROMs), Erasable Programmable ROMs (PERROMs), Electrically Erasable Programmable ROMs (EEPROMs), compact disk ROMs (CD-ROMs), digital versatile disks (ROMs), and the like. In some embodiments, the database may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, across clouds, multiple clouds, or the like, or any combination thereof.

In some embodiments, a database may be connected to the network to communicate with one or more components of the PLC intelligent electrical cabinet control system 10 (e.g., PLC control server 100, PLC intelligent electrical cabinet 200, powered device 300, etc.). One or more components in the PLC intelligent electrical cabinet control system 10 may access data or instructions stored in a database via a network. In some embodiments, the database may be directly connected to one or more components in the PLC intelligent electrical cabinet control system 10 (e.g., the PLC control server 100, the PLC intelligent electrical cabinet 200, the electrical device 300, etc.); alternatively, in some embodiments, the database may also be part of the PLC control server 100.

In a possible design, the PLC intelligent electrical cabinet 200 provided in this embodiment may be integrated manually and remotely, and may support manual key control output and computer control output, and may also perform local area control and external network control. In other possible designs, the PLC intelligent electric cabinet 200 may be further provided with various sensors to sense the ambient environmental information, for example, a humidity sensing sensor to sense the temperature information of the ambient environment. In addition, PLC intelligence electric cabinet 200 specifically can carry out the collection of electric current, voltage at the actual motion in-process to, PLC intelligence electric cabinet 200 also can control many electronic box intelligence antithetical couplets simultaneously.

In order to solve the technical problem in the foregoing background art, fig. 2 is a schematic flowchart of a PLC intelligent electric cabinet control method provided in this embodiment, and the PLC intelligent electric cabinet control method provided in this embodiment may be executed by the PLC control server 100 shown in fig. 1, and the PLC intelligent electric cabinet control method is described in detail below.

Step S110, acquiring power distribution process information and operating state information of the electrical equipment 300 during each preset power-on time period during the power-on process of the PLC intelligent electrical cabinet 200 with the electrical equipment 300.

Step S120, determining state association information between the PLC intelligent electric cabinet 200 and the electric device 300 in each preset power-on time period according to the acquired power distribution process information and the acquired working state information in each preset power-on time period.

Step S130, according to the determined state association information between the PLC intelligent electric cabinet 200 and the electric device 300 in each preset power-on time period, generating a control task set for the PLC intelligent electric cabinet 200 based on the next preset power-on time period, and then sending the control task set to the PLC intelligent electric cabinet 200, so that the PLC intelligent electric cabinet 200 adjusts the working state in the corresponding power distribution process in the next preset power-on time period according to the control task set.

Based on the above steps, in this embodiment, by combining the power distribution process information of the PLC intelligent electric cabinet 200 in each preset power-on period in the power-on process with the electric device 300 and the working state information of the electric device 300, the state association information between the PLC intelligent electric cabinet 200 and the electric device 300 in each preset power-on period can be obtained, so as to adaptively adjust the working state of the PLC intelligent electric cabinet 200 in the power distribution process of the next preset power-on period, thereby improving the power distribution interaction effect between the PLC intelligent electric cabinet 200 and the electric device 300, adaptively adjusting the power distribution process according to the working state of the electric device 300, further enabling the electric device 300 to be continuously in the working state within the parameter range calibrated with itself, and improving the service life of the electric device.

In one possible design, referring to fig. 3 in conjunction with step S120, the following steps may be further implemented:

and a substep S121, determining a power distribution process control parameter of each power distribution process in the power distribution process information and a working state process control parameter of each working state process in the working state information in each preset power-on time period according to the obtained power distribution process information and the working state information in each preset power-on time period.

And a substep S122, obtaining the correlation between the power distribution process control parameters of each power distribution process and the working state process control parameters of each working state process in the working state information according to the power distribution process control parameters of each power distribution process in the power distribution process information and the working state process control parameters of each working state process in each preset power-on time period, and generating a correlation unit for representing the correlation between each working state process and each power distribution process according to the correlation.

And a substep S123 of determining the association information of the power distribution process information and the working state information according to each correlation association unit.

And a substep S124 of determining a first associated characteristic value of each information associated node of the associated information in the power distribution process information according to the power distribution information parameter of each parameter type of the information associated node corresponding to each information associated node of the associated information in the power distribution process information, wherein the corresponding information associated nodes at least comprise information associated nodes of the same parameter type.

And a substep S125, determining a second associated characteristic value of each information-related node of the associated information corresponding to the information-related node in the working state information according to the working state information parameter of each information-related node of the associated information corresponding to the information-related node in the working state information.

And a substep S126 of generating a correlation characteristic curve of the correlation information according to the first correlation characteristic value and the second correlation characteristic value of each information correlation node of the correlation information.

And a substep S127 of determining the state association information between the PLC intelligent electric cabinet 200 and the electric equipment 300 in each preset power-on time period according to the association characteristic curve of the association information.

In one possible design, for sub-step S126, the last determined associated feature information of the information associated node that updates the control policy and the associated feature information of the information associated node that maintains the policy may be updated specifically according to the first associated feature value and the second associated feature value of each information associated node of the associated information. And when the updated associated characteristic information of the information associated node for updating the control strategy and the updated associated characteristic information of the information associated node for maintaining the strategy meet preset conditions, determining an associated information sequence and a non-associated information sequence of the updating control strategy according to the associated characteristic information of each information associated node of the current updating control strategy. And then, determining the associated information sequence of the maintenance strategy according to the associated characteristic information of each information associated node of the current maintenance strategy. And when the update quantity of the information associated node with the largest update quantity in the update control strategy is larger than that of the information associated node with the smallest update quantity in the maintenance strategy, moving the information associated node with the smallest update quantity in the update control strategy into the maintenance strategy, and moving the information associated node with the smallest update quantity in the maintenance strategy into the update control strategy. And then, generating an associated characteristic curve of the associated information according to the respective corresponding curve directions according to the associated characteristic information of each information associated node in the updated control strategy and the maintenance strategy after the information associated node is updated.

In a possible design, for the sub-step S127, node position information corresponding to each preset associated node in the state associated region passing through the set region around each intersecting node may be obtained specifically according to the associated characteristic curve of the associated information. Then, according to the corresponding relationship between the node position information and the effective association attribute configured by the node position information corresponding to each preset association node in the state association area of the setting area around each intersection node, and in the corresponding relationship between the configured node position information and the effective association attribute, determining that the corresponding association attribute in the obtained node position information is the target node position information of the effective association attribute, wherein the association attribute comprises the effective association attribute corresponding to the node position information of at least part of adjustable parts of the power distribution process obtained by dividing the whole power distribution process of the PLC intelligent electric cabinet 200, and the effective association attribute corresponding to the node position information of at least part of adjustable parts of the working state process obtained by dividing the whole working state process of the electric equipment 300.

The corresponding relation between the node position information and the effective correlation attributes is configured in the following mode: in at least part of the power distribution process obtained by dividing the whole power distribution process of the PLC intelligent electric cabinet 200, the power distribution process identifier of the power distribution process in which the state association area corresponding to each intersection node is located is determined, and in at least part of the working state process obtained by dividing the whole working state process of the electric device 300, the working state process identifier of the working state process in which the state association area corresponding to each intersection node is located is determined. And then, acquiring first state associated coordinate information of at least part of the power distribution process in the power distribution process corresponding to the power distribution process identifier and second state associated coordinate information of at least part of the working state process in the working state process corresponding to the working state process identifier. And traversing each power distribution process according to the power distribution process identification, setting the node position information contained in the enclosed area defined by the first state associated coordinate information as an effective value to obtain an effective associated attribute, traversing each working state process according to the working state process identification, and setting the node position information contained in the enclosed area defined by the second state associated coordinate information as an effective value to obtain an effective associated attribute. On the basis, the corresponding relation between the node position information and the effective correlation attribute contained in at least part of the power distribution process and at least part of the working state process is established.

Based on the above description, the state association information between the PLC intelligent electric cabinet 200 and the electric device 300 in each preset power-on time period may be determined according to the target node position information in which the corresponding association attribute in the obtained node position information is the valid association attribute.

In one possible design, according to the target node position information that the corresponding correlation attribute in the obtained node position information is a valid correlation attribute, determining the state correlation information between the PLC intelligent electric cabinet 200 and the electric device 300 in each preset power-on time period may specifically be implemented as follows:

firstly, according to target node position information, determining that a corresponding association attribute in the obtained node position information is an effective association attribute, performing position simulation on each target node position of the target node position information to obtain a first position simulation result and a second position simulation result, wherein the first position simulation result position is an association behavior confidence result of each target node position, and the second position simulation result position is a non-association behavior confidence result of each target node position.

And secondly, generating corresponding association behaviors of the positions of the target nodes according to the first position simulation result and the second position simulation result, and determining an association data area according to the association behaviors of the positions of the target nodes.

And thirdly, extracting past associated data of the associated behaviors of the positions of the target nodes, taking a set threshold value as an associated window, and extracting an associated data sequence of which the associated region of the past associated data is overlapped with the associated data region.

Fourthly, processing the associated behaviors in the associated data sets according to a generating sequence according to any two adjacent associated data sets in the associated data sequence to form a plurality of associated behavior intervals, calculating the associated behavior intervals between all the associated behaviors in the next associated data set and all the associated behaviors in the last associated data set as the designated associated behaviors, identifying whether the associated behavior interval between only one associated behavior and one designated associated behavior meets the maximum associated behavior interval threshold value, if so, connecting the associated behaviors and the corresponding designated associated behaviors to form the associated behavior interval, updating the associated behavior interval to be the designated associated behavior, otherwise, expanding the associated behaviors to be the designated associated behavior interval, identifying whether the number of the associated behaviors contained in each associated behavior interval is larger than or equal to the number of the set associated behaviors, if so, calculating the association indication value of each target association behavior position by using the assigned association behavior in the association behavior interval, the last association behavior of the assigned association behavior and the association section of the association behavior in the next association data set, and otherwise, returning to execute the operation of calculating the association behavior interval between all association behaviors in the next association data set and all association behaviors in the last association data set as the assigned association behavior. And adopting the specified association behaviors in the association behavior interval, the last association behavior of the specified association behaviors and the association section of the association behaviors in the next association data set to calculate the association marking value of each target association behavior position, and adopting the association marking value of each target association behavior position to identify whether at most one association behavior exists in the next association data set so that the association marking value meets a preset threshold value. And if the association behavior exists, connecting the association behavior with the corresponding designated association behavior to form an association behavior interval, updating the association behavior to be the designated association behavior, and otherwise, expanding the association behavior to be the designated association behavior as a new association behavior interval.

And fifthly, according to the generation sequence, forming the associated data set characteristic by the associated behavior interval, wherein the connection sequence is adjacent, and the associated behavior interval between the initial associated behavior and the tail associated behavior of the two associated behavior intervals is smaller than the maximum continuous associated behavior interval of the associated behavior at the position of each target associated behavior in the associated behavior interval.

And sixthly, substituting the associated behaviors in each associated data set characteristic into a hidden Mark matrix to obtain an associated section of state associated designated information of each associated data set characteristic, obtaining the associated behavior characteristic of each target associated behavior position according to the past associated data, and processing the associated behavior characteristic of each target associated behavior position at set intervals to obtain a plurality of associated sections for identifying associated points.

And seventhly, matching according to the state association designated information on the association data set characteristics and the association sections of the identification association points on the association behavior characteristics of the target association behavior positions to obtain the accumulated association behavior interval value.

And eighthly, selecting the associated data set characteristic with the minimum accumulated associated behavior interval value of the associated behavior characteristics of the associated behavior positions of all the associated data set characteristics as the state associated information between the PLC intelligent electric cabinet 200 and the electric equipment 300 in each preset power-on time period.

In one possible design, referring to fig. 4 in conjunction with step S130, the following steps may be further implemented:

and a substep S131 of determining target specific information matched with the state related specific information characteristics of the previous control task of the PLC intelligent electric cabinet 200 by taking the next preset power-on time period as a reference from each state related specific information of the state related information.

And a substep S132 of determining a control task corresponding to each designated control node in the target designation information according to the designated control node in the target designation information and the state-associated designated control node matched with the designated control node in the previous control task.

And a substep S133, generating a control task set for the PLC intelligent electric cabinet 200 based on the control task corresponding to each designated control node in the target designation information, and sending the control task set to the PLC intelligent electric cabinet 200.

In one possible design, for sub-step S133, the node control parameter of each designated control node may be specifically determined according to the designated control node in the target designation information and the designated control node associated with the state matching the designated control node feature in the previous control task.

Then, for each designated control node, the number of nodes having the same node control parameter as the designated control node among the other designated control nodes is determined.

And then, determining the node control parameter of the designated control node corresponding to the maximum value of the number of the nodes of the same node control parameter corresponding to each designated control node as the global node control parameter corresponding to the target designated information, and taking the node control parameters of the rest designated control nodes as the branch node control parameters corresponding to each designated control node.

Therefore, the control task corresponding to each designated control node in the target designated information can be determined according to the global node control parameters and the branch node control parameters corresponding to the global node control parameters and the branch node control parameters.

Fig. 5 is a schematic diagram of functional modules of the PLC intelligent electric cabinet control device 400 according to the embodiment of the present application, and in this embodiment, the PLC intelligent electric cabinet control device 400 may be divided into the functional modules according to the above method embodiment. For example, the functional blocks may be divided for the respective functions, or two or more functions may be integrated into one processing block. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. It should be noted that, the division of the modules in the present application is schematic, and is only a logical function division, and there may be another division manner in actual implementation. For example, in the case of dividing each function module according to each function, the PLC intelligent electric cabinet control device 400 shown in fig. 5 is only a schematic device diagram. The PLC intelligent electrical cabinet control apparatus 400 may include an obtaining module 410, a determining module 420, and a generating module 430, and the functions of the functional modules of the PLC intelligent electrical cabinet control apparatus 400 are described in detail below.

The obtaining module 410 is configured to obtain power distribution process information of the PLC intelligent electrical cabinet 200 in each preset power-on time period in the power-on process with the electrical device 300 and working state information of the electrical device 300.

The determining module 420 is configured to determine, according to the acquired power distribution process information and the acquired working state information in each preset power-on time period, state association information between the PLC intelligent electric cabinet 200 and the electric device 300 in each preset power-on time period.

The generating module 430 is configured to generate a control task set for the PLC intelligent electric cabinet 200 based on the following preset power-on time period according to the determined state association information between the PLC intelligent electric cabinet 200 and the electric device 300 in each preset power-on time period, and then send the control task set to the PLC intelligent electric cabinet 200, so that the PLC intelligent electric cabinet 200 adjusts a working state in a corresponding power distribution process in the next preset power-on time period according to the control task set.

Further, fig. 6 is a schematic structural diagram of a PLC control server 100 for executing the above-mentioned PLC intelligent electric cabinet control method according to an embodiment of the present application. As shown in fig. 6, the PLC control server 100 may include a network interface 110, a machine-readable storage medium 120, a processor 130, and a bus 140. The simulation container data of the processor 130 may be one or more, and one processor 130 is taken as an example in fig. 6. The network interface 110, the machine-readable storage medium 120, and the processor 130 may be connected by a bus 140 or otherwise, as exemplified by the connection by the bus 140 in fig. 6.

The machine-readable storage medium 120 is a computer-readable storage medium, and can be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the PLC intelligent electric cabinet control method in the embodiment of the present application (for example, the acquiring module 410, the determining module 420, and the generating module 430 included in the PLC intelligent electric cabinet control apparatus 400 shown in fig. 5). The processor 130 executes various functional applications and data processing of the terminal device by detecting the software programs, instructions and modules stored in the machine-readable storage medium 120, that is, the above-mentioned PLC intelligent electric cabinet control method is implemented, and details are not repeated herein.

The machine-readable storage medium 120 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the machine-readable storage medium 120 may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile memory may be a Read-only memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of example, but not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double data rate Synchronous Dynamic random access memory (DDR SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchronous link SDRAM (SLDRAM), and direct memory bus RAM (DR RAM). It should be noted that the memories of the systems and methods described herein are intended to comprise, without being limited to, these and any other suitable memory of a publishing node. In some examples, the machine-readable storage medium 120 may further include memory located remotely from the processor 130, which may be connected to the terminal device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The processor 130 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method embodiments may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 130. The processor 130 may be a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor.

The PLC control server 100 may perform information interaction with other devices (e.g., the PLC intelligent electric cabinet 200 and the electric device 300) through the communication interface 110. Communication interface 110 may be a circuit, bus, transceiver, or any other device that may be used to exchange information. Processor 130 may send and receive information using communication interface 110.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

Embodiments of the present application are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

It will be apparent to those skilled in the art that various changes and modifications may be made in the embodiments of the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the embodiments of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to encompass such modifications and variations.

Claims

1. A PLC intelligent electric cabinet control method is applied to a PLC control server, the PLC control server is respectively in communication connection with a PLC intelligent electric cabinet and electric equipment electrically connected with the PLC intelligent electric cabinet, and the method comprises the following steps:

2. The PLC intelligent electric cabinet control method according to claim 1, wherein the step of determining the state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period according to the acquired power distribution process information and the acquired working state information in each preset power-on time period comprises the steps of:

3. The PLC intelligent electric cabinet control method according to claim 2, wherein the step of generating the associated characteristic curve of the associated information according to the first associated characteristic value and the second associated characteristic value of each information associated node of the associated information comprises:

4. The PLC intelligent electric cabinet control method according to claim 2, wherein the step of determining the state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period according to the association characteristic curve of the association information comprises the following steps:

5. The PLC intelligent electric cabinet control method according to claim 2, wherein the step of determining the state association information between the PLC intelligent electric cabinet and the electric equipment in each preset power-on time period according to the target node position information that the corresponding association attribute in the determined obtained node position information is a valid association attribute comprises:

6. The method according to claim 1, wherein the step of generating a set of control tasks for the PLC intelligent electric cabinet based on the following preset power-on period and sending the set of control tasks to the PLC intelligent electric cabinet according to the determined state association information between the PLC intelligent electric cabinet and the electric device in each preset power-on period includes:

7. The PLC intelligent electric cabinet control method according to claim 6, wherein the step of determining the control task corresponding to each designated control node in the target designation information by associating the designated control node according to the designated control node in the target designation information and the state matched with the designated control node in the previous control task in terms of characteristics comprises:

8. The utility model provides an electric cabinet controlling means of PLC intelligence which characterized in that is applied to PLC control server, PLC control server respectively with the electric cabinet of PLC intelligence and with the electric equipment communication connection of the electric cabinet electric connection of PLC intelligence, the device includes:

9. A PLC control server, comprising a processor, a memory and a network interface, wherein the memory, the network interface and the processor are connected through a bus system, the network interface is used for being communicatively connected with a PLC intelligent electrical cabinet, the memory is used for storing programs, instructions or codes, and the processor is used for executing the programs, instructions or codes in the memory to implement the PLC intelligent electrical cabinet control method according to any one of claims 1 to 7.

10. A readable storage medium, wherein instructions are stored in the readable storage medium, and when executed, the readable storage medium implements the PLC intelligent electric cabinet control method according to any one of claims 1 to 7.