CN111338275B - Method and system for monitoring running state of electrical equipment - Google Patents
Method and system for monitoring running state of electrical equipment Download PDFInfo
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Abstract
The embodiment of the invention provides an electrical equipment running state monitoring method and system, which are used for acquiring a monitoring node configuration file for monitoring electrical equipment to be controlled, generating information of a predicted monitoring node according to the monitoring node configuration file and information of a monitored node contained in the electrical equipment to be controlled, determining a monitoring area of the monitored node type corresponding to the electrical equipment to be controlled according to the information of the monitored node, and determining a monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled according to the information of the predicted monitoring node, so that a target monitoring area is determined according to the monitoring area of the monitored node type corresponding to the electrical equipment to be controlled and the monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled. Therefore, each monitoring node is not required to be manually configured to the preset template, the labor cost is reduced, and the monitoring effect is improved.
Description
Technical Field
The invention relates to the technical field of electrical control, in particular to a method and a system for monitoring the running state of electrical equipment.
Background
At present, the running state monitoring of electrical equipment mainly realizes automatic monitoring by continuously configuring each monitoring node to a preset template through manual work, but the mode needs to consume higher human cost, and the preset template and the monitoring nodes can not be well fused under some conditions, so that the monitoring effect is poor.
Disclosure of Invention
In view of this, an object of the embodiments of the present invention is to provide a method and a system for monitoring an operating state of an electrical device, which do not require manual configuration of each monitoring node to a preset template, reduce labor cost, and improve monitoring effect.
According to an aspect of an embodiment of the present invention, there is provided an electrical device operation state monitoring method, applied to a server, where the server is in communication connection with an electrical device to be controlled, the method including:
acquiring a monitoring node configuration file for monitoring the electrical equipment to be controlled;
generating information for predicting the monitoring nodes according to the configuration files of the monitoring nodes and the information of the monitored nodes contained in the electrical equipment to be controlled; the information of the monitored node comprises a monitored node type and a corresponding monitoring area, and the information of the predicted monitoring node comprises a predicted monitoring node type and a corresponding monitoring area;
determining a monitoring area of the monitored node type corresponding to the electrical equipment to be controlled according to the information of the monitored node, and determining a monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled according to the information of the predicted monitoring node;
and determining a target monitoring area according to the monitoring area of the monitored node type corresponding to the electrical equipment to be controlled and the monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled.
In a possible example, the step of generating information of a predictive monitoring node according to the monitoring node profile and information of a monitored node contained in the electrical device to be controlled includes:
performing feature extraction on feature information of the monitoring nodes in the monitoring node configuration file to obtain monitoring node features;
performing feature extraction on the information of the monitored node to obtain the node feature of the monitored node;
and inputting the monitoring node characteristics and the monitored node characteristics into a pre-trained prediction model to obtain the information of the predicted monitoring node.
In a possible example, the step of generating information of a predictive monitoring node according to the monitoring node profile and information of a monitored node included in the electrical device to be controlled further includes:
and circularly executing node characteristics obtained by performing characteristic extraction on the information of the prediction monitoring node output by the prediction model last time, and inputting the monitoring node characteristics into the prediction model to obtain the information of the prediction monitoring node output by the prediction model this time until the prediction model outputs the information of the preset end monitoring node.
In a possible example, the step of generating information of a predictive monitoring node according to the monitoring node profile and information of a monitored node included in the electrical device to be controlled further includes:
acquiring a monitoring sample set for monitoring target electrical equipment and each monitoring node contained in the target electrical equipment;
generating information of each monitoring node according to the monitoring area of the target electrical equipment corresponding to each monitoring node and the content of each monitoring node;
sequentially arranging node characteristics extracted from the information of each monitoring node to obtain a training sequence; the node features extracted from the information of the preset starting element are positioned at the head of the training sequence, and the node features extracted from the information of the preset ending element are positioned at the tail of the training sequence;
and training the prediction model according to the monitoring node characteristics extracted from the monitoring sample set and the characteristics of each node in the training sequence so as to learn to obtain the corresponding relation between the monitoring node characteristics, the combination of the characteristics of the nodes in the training sequence and the information of the monitoring node.
In a possible example, the step of performing feature extraction on feature information of a monitoring node in the monitoring node configuration file to obtain a monitoring node feature includes:
generating a monitoring node matrix according to each monitoring node in the monitoring node configuration file, wherein the monitoring nodes in the monitoring node matrix are used for indicating the monitoring range of the corresponding monitoring node in the monitoring node configuration file;
and extracting the characteristics of the monitoring node matrix to obtain the characteristics of the monitoring nodes.
According to another aspect of the embodiments of the present invention, there is provided an electrical device operation state monitoring system, applied to a server, where the server is in communication connection with an electrical device to be controlled, the system including:
the acquisition module is used for acquiring a monitoring node configuration file for monitoring the electrical equipment to be controlled;
the generating module is used for generating information for predicting the monitoring nodes according to the configuration files of the monitoring nodes and the information of the monitored nodes contained in the electrical equipment to be controlled; the information of the monitored node comprises a monitored node type and a corresponding monitoring area, and the information of the predicted monitoring node comprises a predicted monitoring node type and a corresponding monitoring area;
the first determining module is used for determining a monitoring area of the monitored node type corresponding to the to-be-controlled electrical equipment according to the information of the monitored node, and determining a monitoring area of the predicted monitoring node type corresponding to the to-be-controlled electrical equipment according to the information of the predicted monitoring node;
and the second determining module is used for determining a target monitoring area according to the monitoring area of the monitored node type corresponding to the electrical equipment to be controlled and the monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled.
According to another aspect of the embodiments of the present invention, there is provided a readable storage medium, on which a computer program is stored, which, when being executed by a processor, can perform the steps of the electrical equipment operation state monitoring method described above.
Compared with the prior art, the method and the system for monitoring the running state of the electrical equipment provided by the embodiment of the invention have the advantages that the configuration file of the monitoring node for monitoring the electrical equipment to be controlled is obtained, the information of the predicted monitoring node is generated according to the configuration file of the monitoring node and the information of the monitored node contained in the electrical equipment to be controlled, the monitoring area of the electrical equipment to be controlled corresponding to the type of the monitored node is determined according to the information of the monitored node, the monitoring area of the electrical equipment to be controlled corresponding to the type of the predicted monitoring node is determined according to the information of the predicted monitoring node, and the target monitoring area is determined according to the monitoring area of the electrical equipment to be controlled corresponding to the type of the monitored node and the monitoring area of the electrical equipment to be controlled corresponding to the type of the predicted monitoring node. Therefore, each monitoring node is not required to be manually configured to the preset template, the labor cost is reduced, and the monitoring effect is improved.
In order to make the aforementioned objects, features and advantages of the embodiments of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed 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 invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 illustrates a component diagram of a server provided by an embodiment of the invention;
fig. 2 is a schematic flow chart illustrating a method for monitoring an operation state of an electrical device according to an embodiment of the present invention;
fig. 3 shows a functional block diagram of an electrical device operation state monitoring system according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood by the scholars in the technical field, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 shows an exemplary component schematic of a server 100. The server 100 may include one or more processors 104, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The server 100 may also include any storage media 106 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, storage medium 106 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage medium may use any technology to store information. Further, any storage medium may provide volatile or non-volatile retention of information. Further, any storage medium may represent a fixed or removable component of server 100. In one case, when the processor 104 executes the associated instructions stored in any storage medium or combination of storage media, the server 100 may perform any of the operations of the associated instructions. The server 100 further comprises one or more drive units 108 for interacting with any storage medium, such as a hard disk drive unit, an optical disk drive unit, etc.
The server 100 also includes input/output 110(I/O) for receiving various inputs (via input unit 112) and for providing various outputs (via output unit 114)). One particular output mechanism may include a presentation device 116 and an associated Graphical User Interface (GUI) 118. The server 100 may also include one or more network interfaces 120 for exchanging data with other devices via one or more communication units 122. One or more communication buses 124 couple the above-described components together.
The communication unit 122 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. The communication unit 122 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers 100, and so forth, governed by any protocol or combination of protocols.
Fig. 2 is a schematic flow chart illustrating an electrical device operation state monitoring method provided by an embodiment of the present invention, which can be executed by the server 100 shown in fig. 1, and the detailed steps of the electrical device operation state monitoring method are described as follows.
Step S110, acquiring a monitoring node configuration file for monitoring the electrical equipment to be controlled;
step S120, generating information for predicting the monitoring node according to the configuration file of the monitoring node and the information of the monitored node contained in the electrical equipment to be controlled; the information of the monitored node comprises a monitored node type and a corresponding monitoring area, and the information of the predicted monitoring node comprises a predicted monitoring node type and a corresponding monitoring area;
step S130, determining a monitoring area of the monitored node type corresponding to the electrical equipment to be controlled according to the information of the monitored node, and determining a monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled according to the information of the predicted monitoring node;
step S140, determining a target monitoring area according to the monitoring area of the to-be-controlled electrical equipment corresponding to the type of the monitored node and the monitoring area of the to-be-controlled electrical equipment corresponding to the type of the predicted monitoring node.
Based on the above steps, in this embodiment, a monitoring node configuration file for monitoring the electrical device to be controlled is obtained, information of a predicted monitoring node is generated according to the monitoring node configuration file and information of a monitored node included in the electrical device to be controlled, a monitoring area where the type of the monitored node corresponds to the electrical device to be controlled is determined according to the information of the monitored node, and a monitoring area where the type of the predicted monitoring node corresponds to the electrical device to be controlled is determined according to the information of the predicted monitoring node, so that a target monitoring area is determined according to the monitoring area where the type of the monitored node corresponds to the electrical device to be controlled and the monitoring area where the type of the predicted monitoring node corresponds to the electrical device to be controlled. Therefore, each monitoring node is not required to be manually configured to the preset template, the labor cost is reduced, and the monitoring effect is improved.
In a possible example, for step S120, the embodiment may perform feature extraction on feature information of the monitoring node in the monitoring node configuration file to obtain a monitoring node feature;
performing feature extraction on the information of the monitored node to obtain the node feature of the monitored node;
and inputting the monitoring node characteristics and the monitored node characteristics into a pre-trained prediction model to obtain the information of the predicted monitoring node.
In a possible example, the embodiment cyclically executes the node feature obtained by performing feature extraction on the information of the predicted monitoring node output by the prediction model last time, and inputs the monitoring node feature into the prediction model to obtain the information of the predicted monitoring node output by the prediction model this time until the prediction model outputs the information of the preset end monitoring node.
In a possible example, the embodiment may obtain a monitoring sample set for monitoring a target electrical device and each monitoring node included in the target electrical device, then generate information of each monitoring node according to a monitoring area of the target electrical device corresponding to each monitoring node and the content of each monitoring node, and then sequentially arrange node features extracted from the information of each monitoring node to obtain a training sequence; the node features extracted from the information of the preset starting element are located at the head of the training sequence, and the node features extracted from the information of the preset ending element are located at the tail of the training sequence. Therefore, the prediction model can be trained according to the monitoring node features extracted from the monitoring sample set and the node features in the training sequence, so that the corresponding relation between the monitoring node features, the node feature combination in the training sequence and the information of the monitoring node can be obtained through learning.
In a possible example, in this embodiment, a monitoring node matrix may be generated according to each monitoring node in the monitoring node configuration file, where a monitoring node in the monitoring node matrix is used to indicate a monitoring range of a corresponding monitoring node in the monitoring node configuration file, and then the monitoring node matrix is subjected to feature extraction to obtain the monitoring node feature.
Fig. 3 is a functional block diagram of an electrical device operation state monitoring system 200 according to an embodiment of the present invention, where functions implemented by the electrical device operation state monitoring system 200 may correspond to steps executed by the foregoing method. The electrical device operation state monitoring system 200 may be understood as the server 100 or a processor of the server 100, or may be understood as a component that is independent from the server 100 or the processor and implements the functions of the present invention under the control of the server 100, as shown in fig. 3, and the functions of each functional module of the electrical device operation state monitoring system 200 are described in detail below.
An obtaining module 210, configured to obtain a monitoring node configuration file for monitoring an electrical device to be controlled;
a generating module 220, configured to generate information for predicting the monitoring node according to the monitoring node configuration file and information of the monitored node included in the electrical device to be controlled; the information of the monitored node comprises a monitored node type and a corresponding monitoring area, and the information of the predicted monitoring node comprises a predicted monitoring node type and a corresponding monitoring area;
a first determining module 230, configured to determine, according to the information of the monitored node, a monitoring area where the monitored node type corresponds to the electrical device to be controlled, and determine, according to the information of the predicted monitoring node, a monitoring area where the predicted monitoring node type corresponds to the electrical device to be controlled;
the second determining module 240 is configured to determine a target monitoring area according to the monitoring area where the monitored node type corresponds to the electrical device to be controlled and the monitoring area where the predicted monitoring node type corresponds to the electrical device to be controlled.
In one possible example, the generating module 220 generates the information of the predictive monitoring node by:
performing feature extraction on feature information of the monitoring nodes in the monitoring node configuration file to obtain monitoring node features;
performing feature extraction on the information of the monitored node to obtain the node feature of the monitored node;
and inputting the monitoring node characteristics and the monitored node characteristics into a pre-trained prediction model to obtain the information of the predicted monitoring node.
In one possible example, the generating module 220 generates the information of the predictive monitoring node by:
and circularly executing node characteristics obtained by performing characteristic extraction on the information of the prediction monitoring node output by the prediction model last time, and inputting the monitoring node characteristics into the prediction model to obtain the information of the prediction monitoring node output by the prediction model this time until the prediction model outputs the information of the preset end monitoring node.
In one possible example, the generating module 220 generates the information of the predictive monitoring node by:
acquiring a monitoring sample set for monitoring target electrical equipment and each monitoring node contained in the target electrical equipment;
generating information of each monitoring node according to the monitoring area of the target electrical equipment corresponding to each monitoring node and the content of each monitoring node;
sequentially arranging node characteristics extracted from the information of each monitoring node to obtain a training sequence; the node features extracted from the information of the preset starting element are positioned at the head of the training sequence, and the node features extracted from the information of the preset ending element are positioned at the tail of the training sequence;
and training the prediction model according to the monitoring node characteristics extracted from the monitoring sample set and the characteristics of each node in the training sequence so as to learn to obtain the corresponding relation between the monitoring node characteristics, the combination of the characteristics of the nodes in the training sequence and the information of the monitoring node.
In a possible example, the generating module 220 performs feature extraction on feature information of the monitoring node in the monitoring node configuration file to obtain a monitoring node feature by:
generating a monitoring node matrix according to each monitoring node in the monitoring node configuration file, wherein the monitoring nodes in the monitoring node matrix are used for indicating the monitoring range of the corresponding monitoring node in the monitoring node configuration file;
and extracting the characteristics of the monitoring node matrix to obtain the characteristics of the monitoring nodes.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
Alternatively, all or part of the implementation may be in 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 invention 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.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any drawing credit or debit acknowledgement in the claims should not be construed as limiting the claim concerned.
Claims (2)
1. The method for monitoring the running state of the electrical equipment is applied to a server, wherein the server is in communication connection with the electrical equipment to be controlled, and the method comprises the following steps:
acquiring a monitoring node configuration file for monitoring the electrical equipment to be controlled;
generating information for predicting the monitoring nodes according to the configuration files of the monitoring nodes and the information of the monitored nodes contained in the electrical equipment to be controlled; the information of the monitored node comprises a monitored node type and a corresponding monitoring area, and the information of the predicted monitoring node comprises a predicted monitoring node type and a corresponding monitoring area;
determining a monitoring area of the monitored node type corresponding to the electrical equipment to be controlled according to the information of the monitored node, and determining a monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled according to the information of the predicted monitoring node;
determining a target monitoring area according to the monitoring area of the monitored node type corresponding to the electrical equipment to be controlled and the monitoring area of the predicted monitoring node type corresponding to the electrical equipment to be controlled;
the step of generating information of the predicted monitoring node according to the configuration file of the monitoring node and the information of the monitored node contained in the electrical equipment to be controlled comprises the following steps:
performing feature extraction on feature information of the monitoring nodes in the monitoring node configuration file to obtain monitoring node features;
performing feature extraction on the information of the monitored node to obtain the node feature of the monitored node;
inputting the monitoring node characteristics and the monitored node characteristics into a pre-trained prediction model to obtain information of the predicted monitoring node;
the step of generating information of the predicted monitoring node according to the configuration file of the monitoring node and the information of the monitored node contained in the electrical device to be controlled further includes:
circularly executing node characteristics obtained by performing characteristic extraction on the information of the prediction monitoring node output by the prediction model last time, and inputting the monitoring node characteristics into the prediction model to obtain the information of the prediction monitoring node output by the prediction model this time until the prediction model outputs the information of the preset monitoring node;
the step of generating information of the predicted monitoring node according to the configuration file of the monitoring node and the information of the monitored node contained in the electrical device to be controlled further includes:
acquiring a monitoring sample set for monitoring target electrical equipment and each monitoring node contained in the target electrical equipment;
generating information of each monitoring node according to the monitoring area of the target electrical equipment corresponding to each monitoring node and the content of each monitoring node;
sequentially arranging node characteristics extracted from the information of each monitoring node to obtain a training sequence; the node features extracted from the information of the preset starting element are positioned at the head of the training sequence, and the node features extracted from the information of the preset ending element are positioned at the tail of the training sequence;
training the prediction model according to the monitoring node features extracted from the monitoring sample set and the node features in the training sequence to learn a corresponding relation between the monitoring node features, the node feature combination in the training sequence and the information of the monitoring nodes;
the step of extracting the characteristics of the characteristic information of the monitoring node in the configuration file of the monitoring node to obtain the characteristics of the monitoring node comprises the following steps:
generating a monitoring node matrix according to each monitoring node in the monitoring node configuration file, wherein the monitoring nodes in the monitoring node matrix are used for indicating the monitoring range of the corresponding monitoring node in the monitoring node configuration file;
and extracting the characteristics of the monitoring node matrix to obtain the characteristics of the monitoring nodes.
2. An electrical equipment running state monitoring system is applied to a server, the server is in communication connection with electrical equipment to be controlled, and the system comprises:
the acquisition module is used for acquiring a monitoring node configuration file for monitoring the electrical equipment to be controlled;
the generating module is used for generating information for predicting the monitoring nodes according to the configuration files of the monitoring nodes and the information of the monitored nodes contained in the electrical equipment to be controlled; the information of the monitored node comprises a monitored node type and a corresponding monitoring area, and the information of the predicted monitoring node comprises a predicted monitoring node type and a corresponding monitoring area;
the first determining module is used for determining a monitoring area of the monitored node type corresponding to the to-be-controlled electrical equipment according to the information of the monitored node, and determining a monitoring area of the predicted monitoring node type corresponding to the to-be-controlled electrical equipment according to the information of the predicted monitoring node;
the second determination module is used for determining a target monitoring area according to the monitoring area of the to-be-controlled electrical equipment corresponding to the type of the monitored node and the monitoring area of the to-be-controlled electrical equipment corresponding to the type of the predicted monitoring node;
the generation module generates information of the predictive monitoring node by the following method:
performing feature extraction on feature information of the monitoring nodes in the monitoring node configuration file to obtain monitoring node features;
performing feature extraction on the information of the monitored node to obtain the node feature of the monitored node;
inputting the monitoring node characteristics and the monitored node characteristics into a pre-trained prediction model to obtain information of the predicted monitoring node;
the generation module generates information of the predictive monitoring node by the following method:
circularly executing node characteristics obtained by performing characteristic extraction on the information of the prediction monitoring node output by the prediction model last time, and inputting the monitoring node characteristics into the prediction model to obtain the information of the prediction monitoring node output by the prediction model this time until the prediction model outputs the information of the preset monitoring node;
the generation module generates information of the predictive monitoring node by the following method:
acquiring a monitoring sample set for monitoring target electrical equipment and each monitoring node contained in the target electrical equipment;
generating information of each monitoring node according to the monitoring area of the target electrical equipment corresponding to each monitoring node and the content of each monitoring node;
sequentially arranging node characteristics extracted from the information of each monitoring node to obtain a training sequence; the node features extracted from the information of the preset starting element are positioned at the head of the training sequence, and the node features extracted from the information of the preset ending element are positioned at the tail of the training sequence;
training the prediction model according to the monitoring node features extracted from the monitoring sample set and the node features in the training sequence to learn a corresponding relation between the monitoring node features, the node feature combination in the training sequence and the information of the monitoring nodes;
the generation module extracts the characteristics of the characteristic information of the monitoring nodes in the monitoring node configuration file in the following mode to obtain the characteristics of the monitoring nodes:
generating a monitoring node matrix according to each monitoring node in the monitoring node configuration file, wherein the monitoring nodes in the monitoring node matrix are used for indicating the monitoring range of the corresponding monitoring node in the monitoring node configuration file;
and extracting the characteristics of the monitoring node matrix to obtain the characteristics of the monitoring nodes.
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| JP7323541B2 (en) * | 2018-03-13 | 2023-08-08 | アプライド マテリアルズ インコーポレイテッド | Machine learning system for monitoring semiconductor processing |
| CN110175679A (en) * | 2019-05-29 | 2019-08-27 | 深圳前海微众银行股份有限公司 | A kind of method and device of monitoring model training |
| CN110781732B (en) * | 2019-09-17 | 2023-08-29 | 腾讯科技（深圳）有限公司 | Control method and device for intelligent equipment switch, storage medium and electronic device |
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