CN114386626A - Equipment state evaluation and operation and maintenance strategy formulation realization system based on digital twinning - Google Patents
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Abstract
The invention discloses a device state evaluation and operation and maintenance strategy formulation and implementation system based on a digital twin, which comprises a station-level device digital twin and a data center, wherein the station-level device digital twin is connected with the data center through a network; the station-level equipment digital twin body is used for obtaining a first equipment state evaluation result of the equipment according to the obtained equipment information and sending the equipment information and the first equipment state evaluation result to the data center; the data center is used for obtaining a second equipment state evaluation result of each station level equipment digital twin according to the equipment information and the first equipment state evaluation result of each station level equipment digital twin, determining the operation and maintenance grade and the operation and maintenance strategy of each station level equipment digital twin, and sending the operation and maintenance strategy to each station level equipment digital twin so that each station level equipment digital twin adjusts the operation and maintenance scheme. The method and the device do not need to consume a large amount of human resources and time, can improve the accuracy of equipment state evaluation and operation and maintenance strategy formulation on the power equipment, and improve the state evaluation efficiency of the power equipment.
Description
Technical Field
The invention relates to the technical field of digital twins, in particular to a system for evaluating equipment states and formulating and realizing operation and maintenance strategies based on the digital twins.
Background
In order to ensure the normal operation of the power equipment, the equipment operation and maintenance department needs to periodically evaluate the equipment state of the power equipment, and formulate an operation and maintenance strategy of the power equipment according to the evaluation result to adjust the operation and maintenance scheme of the power equipment. In the prior art, the equipment state of the power equipment is generally evaluated by a manual means, and then an operation and maintenance strategy of the power equipment is formulated. Therefore, it is necessary to research an implementation system for evaluating the state of the equipment and formulating an operation and maintenance policy, which can improve the accuracy of evaluating the state of the equipment and formulating the operation and maintenance policy for the electrical equipment, improve the efficiency of evaluating the state of the electrical equipment, and dynamically adjust the operation and maintenance period of the electrical equipment.
Disclosure of Invention
The invention provides a device state evaluation and operation and maintenance strategy formulation realization system based on digital twins, which aims to solve the technical problems of how to improve the accuracy of device state evaluation and operation and maintenance strategy formulation on power equipment and improve the state evaluation efficiency of the power equipment. The method comprises the steps of mapping the power equipment into a three-dimensional model based on a digital twin technology, evaluating the equipment state of the power equipment by using a knowledge base and an expert base which are arranged in a station-level equipment digital twin body, and formulating an operation and maintenance strategy of the power equipment according to an evaluation result of the station-level equipment digital twin body by using the knowledge base, a standard base and a risk base which are arranged in a data center, so that the station-level equipment digital twin body can adjust an operation and maintenance scheme of the power equipment according to the operation and maintenance strategy, a large amount of human resources and time are not required to be consumed, the accuracy of evaluating the equipment state of the power equipment and formulating the operation and maintenance strategy is improved, the state evaluation efficiency of the power equipment is improved, and the dynamic adjustment of the operation and maintenance period of the power equipment is realized.
In order to solve the technical problem, an embodiment of the present invention provides an apparatus state evaluation and operation and maintenance strategy formulation implementation system based on a digital twin, including a station-level apparatus digital twin and a data center;
the station-level equipment digital twin is used for acquiring equipment information of equipment with a mapping relation, acquiring a first equipment state evaluation result of the equipment according to the equipment information, and sending the equipment information and the first equipment state evaluation result to the data center;
the data center is used for respectively obtaining a second equipment state evaluation result of at least one station-level equipment digital twin according to equipment information and a first equipment state evaluation result of the at least one station-level equipment digital twin, respectively determining an operation and maintenance grade and an operation and maintenance strategy of the at least one station-level equipment digital twin according to the second equipment state evaluation result, and sending the operation and maintenance strategy to the at least one station-level equipment digital twin, so that the at least one station-level equipment digital twin adjusts an operation and maintenance scheme of equipment with a mapping relation with the station-level equipment digital twin according to the operation and maintenance strategy.
Preferably, the system further comprises a manufacturer end;
the data center is further used for sending the equipment information of the at least one station-level equipment digital twin body and a first equipment state evaluation result to the manufacturer end;
the manufacturer end is used for respectively generating operation and maintenance suggestions of the at least one station-level device digital twin according to the device information of the at least one station-level device digital twin and the first device state evaluation result, and sending the operation and maintenance suggestions to the data center.
Preferably, the data center is further configured to obtain a second device state evaluation result of the at least one station-level device digital twin according to the device information and the first device state evaluation result of the at least one station-level device digital twin and the operation and maintenance suggestion sent by the manufacturer.
Preferably, the station-level device digital twin is configured to obtain a first device state evaluation result of the device according to the device information, and specifically includes:
and comparing and analyzing the equipment information, the data of the station-level equipment knowledge base and the data of the station-level equipment expert base based on the station-level equipment knowledge base and the station-level equipment expert base which are preset in the station-level equipment digital twin to obtain a first equipment state evaluation result of the equipment.
Preferably, the data center is configured to obtain a second device status evaluation result of the at least one station-level device digital twin according to the device information and the first device status evaluation result of the at least one station-level device digital twin, specifically:
analyzing the equipment information and the first equipment state evaluation result of the at least one station-level equipment digital twin based on a data center knowledge base, a data center standard base and a data center risk base which are preset in the data center, and respectively obtaining a second equipment state evaluation result of the at least one station-level equipment digital twin.
Preferably, the manufacturer side is configured to generate operation and maintenance suggestions of the at least one station-level device digital twin according to the device information of the at least one station-level device digital twin and the first device state evaluation result, specifically:
analyzing the equipment information and the first equipment state evaluation result of the at least one station-level equipment digital twin body based on an equipment defect library and a manufacturer knowledge library which are preset at the manufacturer end, and respectively generating operation and maintenance suggestions of the at least one station-level equipment digital twin body.
Preferably, the station-level device digital twin body is further configured to send the device information and the first device state evaluation result to the manufacturer side;
the manufacturer side is further configured to obtain a defect condition of the device having a mapping relation with the station-level device digital twin by using the device defect library and the manufacturer knowledge library according to the device information and the first device state evaluation result, generate a defect processing strategy according to the defect condition, and send the defect processing strategy to the station-level device digital twin, so that the station-level device digital twin processes the defect condition according to the defect processing strategy.
Preferably, the data center is further configured to adjust an evaluation criterion of the equipment according to an equipment operating condition, generate an evaluation criterion adjustment result, and send the evaluation criterion adjustment result to the station-level equipment digital twin body, so that the station-level equipment digital twin body updates the data of the station-level equipment knowledge base and the data of the station-level equipment expert base according to the evaluation criterion adjustment result.
Preferably, the device information includes static information, dynamic information, configuration information, and control signal information.
Preferably, the static information includes at least a device name, a device serial number, and a manufacturer name;
the dynamic information at least comprises a temperature value, a pressure value, a speed value and a current value;
the configuration information at least comprises an equipment installation position, accumulated fault time and accumulated running time;
the control signal information includes at least a device status signal and a device alarm signal.
Compared with the prior art, the method and the device have the advantages that the power equipment is mapped into the three-dimensional model based on the digital twin technology, the equipment state of the power equipment is evaluated by the knowledge base and the expert base which are arranged in the station-level equipment digital twin, the operation and maintenance strategy of the power equipment is formulated by the knowledge base, the standard base and the risk base which are arranged in the data center according to the evaluation result of the station-level equipment digital twin, so that the station-level equipment digital twin adjusts the operation and maintenance scheme of the power equipment according to the operation and maintenance strategy, a large amount of manpower resources and time are not consumed, the accuracy of the equipment state evaluation and the operation and maintenance strategy formulation of the power equipment is improved, the state evaluation efficiency of the power equipment is improved, and the dynamic adjustment of the operation and maintenance period of the power equipment is realized.
Drawings
Fig. 1 is a schematic structural diagram of an implementation system for evaluating a device state and making an operation and maintenance strategy based on a digital twin according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a station-level device digital twin body provided by an embodiment of the present invention;
fig. 3 is a schematic structural diagram of another preferred embodiment of a system for implementing the device state evaluation and operation and maintenance strategy formulation based on the digital twin according to an embodiment of the present invention.
Detailed Description
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, and 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.
Referring to fig. 1, an embodiment of the present invention provides an apparatus state evaluation and operation and maintenance strategy formulation implementation system based on a digital twin, including a station-level apparatus digital twin 101 and a data center 102;
the station-level device digital twin 101 is configured to acquire device information of a device having a mapping relationship with the station-level device digital twin 101, acquire a first device state evaluation result of the device according to the device information, and send the device information and the first device state evaluation result to the data center 102.
Preferably, the device information includes static information, dynamic information, configuration information, and control signal information.
Preferably, the static information includes at least a device name, a device serial number, and a manufacturer name;
the dynamic information at least comprises a temperature value, a pressure value, a speed value and a current value;
the configuration information at least comprises an equipment installation position, accumulated fault time and accumulated running time;
the control signal information includes at least a device status signal and a device alarm signal.
Specifically, the static information is data that reflects the inherent properties of the device and is relatively invariant, such as a device name, a device serial number, a manufacturer name (data at a vendor level). The dynamic information is data that reflects time-variable and usually measurable data during the operation of the device, such as temperature values, pressure values, speed values, current values, etc., and includes, in addition, dynamic measurement data that can be obtained by measurement and dynamic calculation data that can be obtained by calculation. The configuration information is settings and parameters related to the equipment operating conditions and operating environment, such as equipment installation location, accumulated time to failure, accumulated time to run, and the like. The control signal information is various equipment state signals and equipment alarm signals generated or received in the equipment production, operation and maintenance, such as low-pressure alarm, protection trip signals and the like.
Static information and configuration information are recorded by various service data systems to form an equipment ledger, the station-level equipment digital twin body 101 refers to the equipment ledger in the various service data systems, physical and virtual association is carried out by using a unique equipment scheduling number, an equipment installation space position and the like, one-to-one mapping is formed with corresponding physical equipment, the same static data and configuration digital twin virtual equipment are generated, and an entity-data-virtual digital twin basic structure is established.
Measurable dynamic data is collected and uploaded by devices such as a sensor, an instrument and meter and an intelligent patrol terminal (for example, temperature is collected through a temperature sensor or an infrared imager arranged on a device body, pressure is collected through remote transmission of a device pressure meter or visual identification of a dial plate, speed is collected through a device action sensor and a timer, current and voltage are collected through a current transformer and a voltage transformer, and sound is collected through an ultrasonic sensor arranged on the device body), and the dynamic data is updated on the digital twin virtual device in real time, so that the digital twin virtual device has the capability of showing the state of physical devices in real time.
The control signal data is provided by SCADA real-time synchronization, data in the SCADA needs to be converted into a format and a protocol which can be accepted by a digital twin, the SCADA and the digital twin are connected through an optical fiber or an RJ45 interface, and data interaction is carried out by adopting a TCP/IP protocol. Meanwhile, as the SCADA belongs to a production control large area, the data acquired by the digital twin body must pass through a forward and reverse isolation device, so that network safety accidents are avoided. The SCADA controls the physical equipment or receives various state signals of the physical equipment and simultaneously sends the signals to the station-level equipment digital twin body 101, and the station-level equipment digital twin body 101 synchronously updates the state of the digital twin virtual equipment according to the signals.
Since interfaces and protocols of devices and systems such as sensors, instruments and meters, intelligent patrol terminals, SCADA, service data systems and the like are different, the interfaces and protocols of various data sources must be converted and unified before entering the station-level device digital twin 101 for simulation and demonstration, and data preprocessing is performed to structure and normalize the data.
Specifically, in order to realize conversion and unification of interfaces and protocols of various data sources, the data unifies and carries out conversion of the interfaces and the protocols through an intelligent gateway, wherein the intelligent gateway does not refer to a specific device, but is an integral concept of a device for processing the data interfaces and the protocols in a network link. Some data are collected and processed in an edge computing system and then converted into uniform interfaces and protocols, some data are directly accessed to the station level equipment digital twin 101 after being collected, interface and protocol conversion is needed, various network access modes such as LORA, WAPI, LTE230, network cables and optical fibers are converted into RJ-45 interfaces in the intelligent gateway, and various protocols such as 104 protocols and 61850 protocols are uniformly converted into 61850 protocols.
Data preprocessing includes data deduplication and data cleansing. The data deduplication refers to the data deduplication processing of the same size, naming, generation time and data format by using a bitmap algorithm, marking cannot be distinguished by the algorithm, and waiting for manual processing to ensure the uniqueness of the data. The data cleaning refers to analyzing and processing the legality, accuracy, integrity and consistency of data by using methods such as a clustering analysis algorithm, ARIMA model fitting, time sequence model fitting and the like, and the noise data is replaced and the empty gap value is filled by model fitting automatic filling or manual auxiliary modification.
Further, the station-level device digital twin 101 is mainly composed of physical devices and virtual devices, and the station-level device digital twin 101 includes a real-time database, a relational database, and a NoSQL database. The real-time database stores structured data of real-time sampling values such as voltage, current, temperature and pressure, the relational database stores structured data such as machine accounts, defects, important alarm information and report data of equipment, and the NoSQL database stores unstructured data such as pictures, audios and videos and documents. Data of different sources and different formats need to be classified, uniformly coded, and a data dictionary is formed by coding rules and corresponding contents, so that manual identification and butt joint with other systems are facilitated.
For the processing of the structured data, the data of each source is encoded through data preprocessing, and metadata such as the source, equipment number, equipment name, relative position of components, data type, generation time and the like of the data are encoded in a standard mode. The method is convenient for unifying the multi-element heterogeneous data to the digital twin body for use, and meanwhile, the method provides convenience for query, classification and data deepening application. The JSON format can be used for encoding, so as to avoid ambiguity caused by generating repeated data, the names should be unified during encoding, for example: the Pu ' er converter station and the Pu ' er station are unified into a Pu ' er converter station; the ACF1 and the first large ac filter set should be unified into the first large ac filter set.
For processing unstructured data, structured information in the unstructured data needs to be extracted and uniformly encoded, and the encoding principle is consistent with the type of the structured data.
It is worth to be noted that a three-dimensional model of the device in the station-level device digital twin 101 is built by using industrial simulation software (CAE), and different physical field simulation models (such as a conductor temperature field model, an internal current and voltage model, a contact wear model, a breaker arc extinguish chamber action model, a mechanism stress model, etc.) are built according to the physical principle of the device and according to different parameters concerned by different devices and different components. In order to shorten the calculation time of the working condition of the equipment, a reduction technology is adopted, and the analysis result of the 3D finite element is reduced into a ROM model which can be used for one-dimensional system simulation. Forming a simulation model training sample according to the equipment material parameters, the equipment action characteristics, the equipment experimental data, the equipment operation data and the equipment defect records, building a simulation model aiming at each equipment component and each physical field needing to be simulated, and carrying out model training through an intelligent deep learning technology and a recurrent neural network technology.
Measurable dynamic data such as equipment running state, external current and voltage quantity and the like can be directly displayed in a follow-up mode on digital twin three-dimensional modeling according to preset action animation and virtual instruments. And for the equipment state which cannot be measured in the operation process and needs to be simulated by means of CAE, real-time working condition data in the database are taken out by a simulation algorithm for calculation, and a simulation result is output. And for the prediction of the operation condition of the equipment, the simulation algorithm carries out trend prediction according to the actual condition, and early warning is carried out on the equipment or the parts which possibly reach the defect level.
And the reduced model can derive a three-dimensional space physical quantity distribution result file so as to be loaded on the 3D model for rendering and displaying. And simultaneously, carrying out visual description and real-time updating on the characteristics, behaviors, formation process, performance and the like of the digital twin body on three-dimensional modeling, and finishing the mapping from the physical equipment to the virtual equipment. A schematic structural diagram of a station-level device digital twin 101 is shown in fig. 2.
Preferably, the station-level device digital twin 101 is configured to obtain a first device state evaluation result of the device according to the device information, specifically:
and comparing and analyzing the equipment information, the data of the station-level equipment knowledge base and the data of the station-level equipment expert base based on the station-level equipment knowledge base and the station-level equipment expert base which are preset in the station-level equipment digital twin body 101 to obtain a first equipment state evaluation result of the equipment.
Specifically, the station-level device digital twin 101 generates a station-level device knowledge base and a station-level device expert base according to the device operation and maintenance experience, the device defect base, the supplier technical support, and the device management strategy. The station-level equipment digital twin 101 periodically and automatically uses the station-level equipment knowledge base and the station-level equipment expert base to analyze and judge the equipment operation and maintenance data, the simulation result and the prediction trend in real time, carries out the statistics of the action times of the equipment, the evaluation of the equipment loss, the evaluation of the environmental impact and the identification of the defect abnormity, and scores the equipment according to the importance degree and the health degree of the equipment to evaluate the state of the station-level equipment. In one embodiment, the evaluation result of the device status generated by the station-level device digital twin 101 according to the device information is shown in the following table:
TABLE 1 evaluation results of device states
The station-level equipment digital twin 101 determines an equipment state evaluation result according to the evaluation deduction value, different score sections correspond to different evaluation results and can be divided into four grades of normal, attention, abnormal and severe, and the more the deduction is, the worse the equipment state is, and the evaluation grade score sections of different equipment and different parts are different.
The data center 102 is configured to obtain a second device state evaluation result of the at least one station-level device digital twin 101 according to the device information and the first device state evaluation result of the at least one station-level device digital twin 101, determine an operation and maintenance level and an operation and maintenance policy of the at least one station-level device digital twin 101 according to the second device state evaluation result, and send the operation and maintenance policy to the at least one station-level device digital twin 101, so that the at least one station-level device digital twin 101 adjusts an operation and maintenance scheme of a device having a mapping relationship with the at least one station-level device digital twin 101 according to the operation and maintenance policy.
Specifically, each station-level device digital twin 101 provides an access interface to the data center 102 through the cloud server, so that the data center 102 can invoke the data of the station-level device digital twin 101 as needed. The data center 102 uses geographic information for modeling, and shares map service through the cloud server, inputs accurate three-dimensional geographic information of each site and line, can display the spatial positions of the sites and lines of the whole network on a whole disc, and can also enter a single site to look up the operation and maintenance conditions of the equipment level digital twin for real-time dynamic interaction. The service system data is accessed to the data center 102 through the cloud server, such as network level production monitoring command, major risk management and control, major defect tracking, natural disaster early warning, equipment management and control grading decision and other services. And modeling according to geographic information, performing service content grading display on corresponding dimensions on a map according to different dimensions of provinces, cities, regions, stations or lines, designing a corresponding real-time visualization instrument panel according to the service content, reflecting the operation situation, major risks, natural disasters, equipment control conditions and other contents of each dimension in real time, and realizing service visualization of the network-level digital twin body consisting of each station-level equipment digital twin body 101 and the data center 102.
Preferably, the data center 102 is configured to obtain a second device state evaluation result of the at least one station-level device digital twin 101 according to the device information and the first device state evaluation result of the at least one station-level device digital twin 101, specifically:
analyzing the equipment information and the first equipment state evaluation result of the at least one station-level equipment digital twin 101 based on a data center knowledge base, a data center standard base and a data center risk base which are preset in the data center 102, and respectively obtaining a second equipment state evaluation result of the at least one station-level equipment digital twin 101.
Specifically, after receiving the device information and the first device state evaluation result sent by each station-level device digital twin 101, the data center 102 generates a report of the initial evaluation results of various devices, and further analyzes and judges the device operation and maintenance data with a low initial evaluation score or a large influence on the system based on a data center knowledge base, a data center standard base and a data center risk base which are preset in the data center 102, thereby generating a second device state evaluation result. The data center 102 performs big data analysis on the initial evaluation result of the equipment: the trend of the state change of various equipment along with time can be mined from the time dimension, so that the operation and maintenance period and the maintenance plan are guided to be made; regional defect conditions of various devices can be mined from the spatial dimension, so that differential operation and maintenance strategies under different environments are guided to be formulated; the operation conditions of equipment of various models can be mined from the class dimension, so that batch defects can be found, and targeted operation and maintenance measures can be made.
Preferably, the system further comprises a manufacturer end;
the data center 102 is further configured to send the device information of the at least one station-level device digital twin 101 and a first device state evaluation result to the manufacturer;
the manufacturer side is configured to generate operation and maintenance suggestions of the at least one station-level device digital twin 101 according to the device information of the at least one station-level device digital twin 101 and the first device state evaluation result, and send the operation and maintenance suggestions to the data center 102.
Preferably, the manufacturer side is configured to generate operation and maintenance suggestions of the at least one station-level device digital twin 101 according to the device information of the at least one station-level device digital twin 101 and the first device state evaluation result, specifically:
analyzing the equipment information and the first equipment state evaluation result of the at least one station-level equipment digital twin 101 based on an equipment defect library and a manufacturer knowledge library which are preset at the manufacturer end, and respectively generating operation and maintenance suggestions of the at least one station-level equipment digital twin 101.
It should be noted that, since a large amount of device design files and three-dimensional drawings are mastered by the manufacturer, the manufacturer is added and participates in the operation and maintenance process of the device. The manufacturer side communicates with the data center 102 through an encryption channel, and the data center 102 classifies data sent by the digital twin 101 of each station-level device according to the manufacturer of the device after being checked, encrypts and sends the data to the manufacturer side corresponding to each device. The manufacturer judges the operation and maintenance condition of the equipment based on the equipment defect library and the manufacturer knowledge library which are preset at the manufacturer, generates an operation and maintenance suggestion, encrypts the operation and maintenance suggestion and sends the operation and maintenance suggestion to the data center 102.
Preferably, the data center 102 is further configured to obtain a second device state evaluation result of the at least one station-level device digital twin 101 according to the device information and the first device state evaluation result of the at least one station-level device digital twin 101 and the operation and maintenance suggestion sent by the manufacturer.
Preferably, the station-level device digital twin 101 is further configured to send the device information and the first device state evaluation result to the manufacturer side;
the manufacturer side is further configured to obtain, according to the device information and the first device state evaluation result, a defect condition of a device having a mapping relationship with the station-level device digital twin 101 by using the device defect library and the manufacturer knowledge library, generate a defect handling policy according to the defect condition, and send the defect handling policy to the station-level device digital twin 101, so that the station-level device digital twin 101 handles the defect condition according to the defect handling policy.
Specifically, when an emergency defect situation occurs in a station-level device, a manufacturer side assistance right is opened by a station where the device is located, the station-level device digital twin 101 sends the device information and the first device state evaluation result to the manufacturer side, the manufacturer side obtains the device information and the first device state evaluation result through a digital twin real-time mapping function, obtains a defect situation of a device having a mapping relationship with the station-level device digital twin 101 by using the device defect library and the manufacturer knowledge library, generates a defect handling policy according to the defect situation, and sends the defect handling policy to the station-level device digital twin 101, so that the station-level device digital twin 101 handles the defect situation according to the defect handling policy. The method and the device realize more intuitive point-to-point technical support for the station, quickly position the fault and accelerate the defect processing speed.
Preferably, the data center 102 is further configured to adjust an evaluation criterion of the equipment according to an equipment operating condition, generate an evaluation criterion adjustment result, and send the evaluation criterion adjustment result to the station-level equipment digital twin body 101, so that the station-level equipment digital twin body 101 updates data of the station-level equipment knowledge base and data of the station-level equipment expert base according to the evaluation criterion adjustment result.
Specifically, after the data center 102 generates a second device state evaluation result and formulates a device operation and maintenance strategy, the evaluation criteria of the device are adjusted according to device operation conditions, such as device batch quality conditions, external risk dynamic changes, operation and maintenance technology promotion conditions, environmental influences and the like, so as to generate an evaluation criteria adjustment result, so as to achieve timeliness of the evaluation criteria, and the data center 102 sends the evaluation criteria adjustment result to the station-level device digital twin 101, so that the station-level device digital twin 101 updates the data of the station-level device knowledge base and the data of the station-level device expert base according to the evaluation criteria adjustment result, executes a new scoring criterion, and ensures accuracy, timeliness and compliance of the device initial result.
Further, after the data center 102 sends the operation and maintenance strategy to the station-level device digital twin 101, the station-level device digital twin 101 is linked with the intelligent patrol system according to the operation and maintenance strategy, dynamically adjusts the device acquisition cycle and the robot patrol task cycle according to the new device operation and maintenance strategy, and highlights and displays important device data on the station-level device digital twin 101 display interface.
The embodiment of the invention provides a system for evaluating equipment state and formulating operation and maintenance strategy based on digital twins, which is characterized in that power equipment is mapped into a three-dimensional model based on a digital twins technology, the equipment state of the power equipment is evaluated based on a knowledge base and an expert base which are arranged in a station-level equipment digital twins, an operation and maintenance suggestion is generated by a manufacturer end of the equipment according to the evaluation result of the station-level equipment digital twins, the operation and maintenance suggestion and the evaluation result of the station-level equipment digital twins are analyzed and researched based on the knowledge base, a standard base and a risk base which are arranged in a data center, the operation and maintenance strategy of the power equipment is formulated, so that the station-level equipment digital twins can adjust the operation and maintenance scheme of the power equipment according to the operation and maintenance strategy without consuming a large amount of human resources and time, the accuracy of evaluating the equipment state and formulating operation and maintenance strategy of the power equipment is improved, and the state evaluation efficiency of the power equipment is improved, and the dynamic adjustment of the operation and maintenance period of the power equipment is realized.
In order to better describe the operation flow of the device state evaluation and operation and maintenance strategy formulation implementation system based on the digital twin according to the embodiment of the present invention, the following description is made with reference to fig. 3.
(1) And the station-level equipment digital twin body judges the equipment defects according to the acquired equipment information and based on a knowledge base and an expert base of the station-level equipment digital twin body, determines the defect level, generates a first equipment state evaluation result and uploads the first equipment state evaluation result to a data center.
(2) The data center receives first equipment state evaluation results sent by a plurality of station-level equipment digital twin bodies, the first equipment state evaluation results are all same type equipment and same type defect information, and the data center sends the first equipment state evaluation results to a manufacturer side.
(3) And the manufacturer side determines the possibility of batch defects of the equipment of the model based on the equipment defect library and the knowledge base of the manufacturer side, and sends operation and maintenance suggestions to the data center.
(4) And the data center analyzes and judges by using a knowledge base, a standard base and a risk base according to a first equipment state evaluation result sent by the station-level equipment digital twin and an operation and maintenance suggestion sent by a manufacturer end to obtain a second equipment state evaluation result, generates an operation and maintenance strategy and sends the operation and maintenance strategy to each station-level equipment digital twin.
(5) And the digital twin of each station-level equipment adjusts the operation and maintenance scheme of the equipment according to the operation and maintenance strategy, and the defect condition of the equipment is processed.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (10)
1. A device state evaluation and operation and maintenance strategy formulation and implementation system based on digital twins is characterized by comprising a station-level device digital twins and a data center;
the station-level equipment digital twin is used for acquiring equipment information of equipment with a mapping relation, acquiring a first equipment state evaluation result of the equipment according to the equipment information, and sending the equipment information and the first equipment state evaluation result to the data center;
the data center is used for respectively obtaining a second equipment state evaluation result of at least one station-level equipment digital twin according to equipment information and a first equipment state evaluation result of the at least one station-level equipment digital twin, respectively determining an operation and maintenance grade and an operation and maintenance strategy of the at least one station-level equipment digital twin according to the second equipment state evaluation result, and sending the operation and maintenance strategy to the at least one station-level equipment digital twin, so that the at least one station-level equipment digital twin adjusts an operation and maintenance scheme of equipment with a mapping relation with the station-level equipment digital twin according to the operation and maintenance strategy.
2. The system for implementing digital twin-based equipment status evaluation and operation and maintenance strategy formulation according to claim 1, further comprising a manufacturer end;
the data center is further used for sending the equipment information of the at least one station-level equipment digital twin body and a first equipment state evaluation result to the manufacturer end;
the manufacturer end is used for respectively generating operation and maintenance suggestions of the at least one station-level device digital twin according to the device information of the at least one station-level device digital twin and the first device state evaluation result, and sending the operation and maintenance suggestions to the data center.
3. The system according to claim 2, wherein the data center is further configured to obtain a second device status evaluation result of the at least one station-level device digital twin according to the device information and the first device status evaluation result of the at least one station-level device digital twin and the operation and maintenance advice sent by the manufacturer.
4. The system according to claim 3, wherein the station-level device digital twin is configured to obtain a first device state evaluation result of the device according to the device information, and specifically includes:
and comparing and analyzing the equipment information, the data of the station-level equipment knowledge base and the data of the station-level equipment expert base based on the station-level equipment knowledge base and the station-level equipment expert base which are preset in the station-level equipment digital twin to obtain a first equipment state evaluation result of the equipment.
5. The system according to claim 3, wherein the data center is configured to obtain a second device status evaluation result of the at least one station-level device digital twin according to the device information and the first device status evaluation result of the at least one station-level device digital twin, specifically:
analyzing the equipment information and the first equipment state evaluation result of the at least one station-level equipment digital twin based on a data center knowledge base, a data center standard base and a data center risk base which are preset in the data center, and respectively obtaining a second equipment state evaluation result of the at least one station-level equipment digital twin.
6. The system according to claim 3, wherein the manufacturer side is configured to generate operation and maintenance suggestions of the at least one station-level device digital twin according to the device information of the at least one station-level device digital twin and the first device state evaluation result, specifically:
analyzing the equipment information and the first equipment state evaluation result of the at least one station-level equipment digital twin body based on an equipment defect library and a manufacturer knowledge library which are preset at the manufacturer end, and respectively generating operation and maintenance suggestions of the at least one station-level equipment digital twin body.
7. The system for evaluating the equipment state and making the operation and maintenance strategy based on the digital twin of claim 6, wherein the station-level equipment digital twin is further configured to send the equipment information and the first equipment state evaluation result to the manufacturer;
the manufacturer side is further configured to obtain a defect condition of the device having a mapping relation with the station-level device digital twin by using the device defect library and the manufacturer knowledge library according to the device information and the first device state evaluation result, generate a defect processing strategy according to the defect condition, and send the defect processing strategy to the station-level device digital twin, so that the station-level device digital twin processes the defect condition according to the defect processing strategy.
8. The system according to claim 4, wherein the data center is further configured to adjust an evaluation criterion of the equipment according to an equipment operating condition, generate an evaluation criterion adjustment result, and send the evaluation criterion adjustment result to the station-level equipment digital twin, so that the station-level equipment digital twin updates the data of the station-level equipment knowledge base and the data of the station-level equipment expert base according to the evaluation criterion adjustment result.
9. The system of claim 3, wherein the device information includes static information, dynamic information, configuration information, and control signal information.
10. The system of claim 9, wherein the static information includes at least a device name, a device serial number, and a manufacturer name;
the dynamic information at least comprises a temperature value, a pressure value, a speed value and a current value;
the configuration information at least comprises an equipment installation position, accumulated fault time and accumulated running time;
the control signal information includes at least a device status signal and a device alarm signal.
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| CN116684303A (en) * | 2023-08-01 | 2023-09-01 | 聪育智能科技(苏州)有限公司 | Digital twinning-based data center operation and maintenance method and system |
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| CN115221708A (en) * | 2022-07-19 | 2022-10-21 | 贵州电网有限责任公司 | Isolating switch contact heating model construction method |
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| CN116029116A (en) * | 2022-12-28 | 2023-04-28 | 广东电网有限责任公司湛江供电局 | Intelligent substation wisdom management and control digital twin system |
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| CN116684303B (en) * | 2023-08-01 | 2023-10-27 | 聪育智能科技(苏州)有限公司 | Digital twinning-based data center operation and maintenance method and system |
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