CN117220402A - Online fault monitoring device and system for electric power - Google Patents
Online fault monitoring device and system for electric power Download PDFInfo
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Abstract
The invention discloses an electric power on-line fault monitoring device and system utilizing quantum communication, nano materials and virtual reality technology. According to the invention, the quantum signal transmitter and the quantum signal receiver are arranged, the power equipment operation state information represented by the quantum state is sent and received through the quantum channel, and the quantum key is distributed through the quantum key distributor and used for carrying out quantum encryption and decryption on the power equipment operation state information, so that the safe transmission of data is ensured, and eavesdropping or tampering is prevented; through setting up the nano material layer to cover at power equipment surface or inside, and link to each other with power equipment, have self-repairing function, can carry out automated inspection and restoration to the trouble that power equipment produced, and through the change of sensor perception nano material layer, and change into the electrical signal. The invention is suitable for the scene of on-line fault monitoring of various power equipment of transformers, transmission lines, distribution networks and wind driven generators.
Description
Technical Field
The invention relates to the technical field of power online fault monitoring, in particular to a power online fault monitoring device and system.
Background
Power equipment is an important component of an electrical power system, and its operating state directly affects the safety and stability of the electrical power system. Therefore, on-line fault monitoring of the power equipment is an important means for ensuring normal operation of the power system. At present, the common online power fault monitoring methods mainly comprise the following steps:
the method based on the traditional communication technology comprises the following steps: the method transmits the operation state information of the power equipment 101 to a monitoring center in a wired or wireless mode for data analysis and processing. The method has the advantages of maturity, reliability and easy realization, but has the following disadvantages: firstly, the data is easy to be disturbed or attacked in the transmission process, so that the data is lost or tampered; secondly, the transmission speed and the bandwidth are limited, and the real-time performance and the integrity of the data are affected; and thirdly, the transmission cost is higher, and the operation and maintenance burden is increased.
The method based on the technology of the Internet of things comprises the following steps: according to the method, the power equipment is connected with the Internet, so that remote collection, storage, management and analysis of data are realized. The method has the advantages of intelligence, high efficiency and flexibility, but also has the following disadvantages: firstly, the network security risk is high, and the network security risk is easy to be invaded or attacked by hackers or malicious software; secondly, the network dependence is strong, and once the network fails or breaks down, the normal transmission and processing of data can be affected; third, network resources consume a lot of servers, storage space and bandwidth.
The method based on the artificial intelligence technology comprises the following steps: the method performs characteristic extraction, classification and regression operation on the operation data of the power equipment by utilizing artificial intelligence, machine learning and data mining methods, and outputs fault type, fault level, fault reason, processing advice and measure information. The method has the advantages of being accurate, efficient and intelligent, but also has the following disadvantages: firstly, the algorithm complexity is high, and a large amount of computing resources and time are needed; secondly, the generalization of the algorithm is poor, and a large amount of training data and labeling data are needed; thirdly, the algorithm has low interpretability, and the internal logic and principle of the algorithm are difficult to understand.
In order to improve the security of data transmission, some researchers and enterprises begin to explore communication technologies based on quantum physics principles, namely quantum communication technologies. Quantum communication technology uses quantum states, such as single photons or entangled photons, to represent and transmit information, and uses the unclonability and indistinguishability of quantum states to ensure the safety of information. Currently, there are some laboratory or engineering implementations and applications such as ink-number satellites, quantum communications and networking projects of the National Institute of Standards and Technology (NIST). However, quantum communication technologies also face challenges and problems such as loss of quantum channels, noise, interference, resulting in limited distances and rates of data transmission; and the complexity, cost, stability of the quantum device, affecting the reliability and efficiency of data transmission
Therefore, we propose an on-line power failure monitoring device and system.
Disclosure of Invention
The invention aims to provide an electric power on-line fault monitoring device and system, which have the advantages of safe transmission, automatic detection and repair, intelligent analysis and processing, remote control and visual operation, and solve the problems of data safety, real-time performance, integrity, transmission cost, network safety risk, network dependence, network resource consumption, algorithm complexity, generalization and interpretability in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions: the utility model provides an online fault monitoring device of electric power, includes quantum signal transmitter, quantum signal receiver, quantum key distributor, quantum encryptor, quantum decryptor, nanometer material layer, sensor, data acquisition ware, data transmission ware and controller, its characterized in that:
the quantum signal transmitter and the quantum signal receiver are respectively arranged at two ends of at least one piece of power equipment, are connected through a quantum channel and are used for transmitting and receiving the running state information of the power equipment represented by the quantum state;
the nano material layer covers the surface or the inside of at least one piece of power equipment and is connected with the power equipment, so that the self-repairing function is realized;
the sensor is arranged on or in the nano material layer and connected with the nano material layer, can sense the change of the nano material layer and convert the change into an electric signal;
the data transmitter is arranged at the output end of the data collector and connected with the data collector, and can transmit digital signals to the controller in a wireless or wired mode;
the controller is arranged at the receiving end of the data transmitter and connected with the data transmitter, and is used for sending a control instruction to at least one electric device according to the received digital signal and the operation instruction of a worker, so as to realize remote control of the at least one electric device.
Preferably, the power equipment operation state information includes temperature, voltage, current and power parameters of the power equipment.
Preferably, the quantum channel uses single photons or entangled photons as a carrier and is transmitted through an optical fiber or free space.
Preferably, the nanomaterial layer is made of carbon nanotubes, graphene, nano metal or nano oxide materials and covers the surface or the inside of at least one electric device.
The utility model provides an electric power on-line fault monitoring system, includes data processor, cloud platform, virtual reality helmet, virtual reality handle and virtual reality camera, its characterized in that:
the data processor is connected with the controller, receives the digital signals from the controller, is used for analyzing and processing the digital signals by artificial intelligence, machine learning and data mining methods, and displays the digital signals on the virtual reality helmet;
the cloud platform is connected with the data processor and is responsible for storing, managing and updating at least one power equipment operation data and an intelligent model and providing remote access and cooperation functions;
the virtual reality helmet is arranged on the head of a worker and connected with the data processor, so that the visualization of a three-dimensional simulation model of at least one piece of power equipment can be realized, and the three-dimensional simulation model is synchronously updated with three-dimensional image signals captured by the virtual reality camera;
the virtual reality handle is arranged on the hand of a worker and connected with the controller, so that the operation of the three-dimensional simulation model of at least one piece of electric equipment can be realized;
the virtual reality camera is arranged at each position of at least one piece of power equipment and is connected with the virtual reality helmet, so that the running state information of the at least one piece of power equipment can be captured in real time and converted into three-dimensional image signals.
Preferably, the cloud platform is responsible for storing, managing and updating at least one power equipment operation data and an intelligent model, and providing remote access and cooperation functions, and comprises a deep learning algorithm module and an intelligent model module, wherein the deep learning algorithm module adopts a Convolutional Neural Network (CNN) or a cyclic neural network (RNN) or a long-short-term memory network (LSTM) or other deep learning algorithms to perform feature extraction, classification and regression operation on the at least one power equipment operation data, so that the accuracy and generalization of the intelligent model are improved; the intelligent model module adopts Decision Tree (DT) or Support Vector Machine (SVM) or Random Forest (RF) or other machine learning algorithm, and outputs fault type, fault level, fault cause, processing proposal and measure information according to the input at least one power equipment operation data.
Preferably, the virtual reality camera is arranged at each position of at least one power device and is connected with the virtual reality helmet, so that the running state information of the at least one power device can be captured in real time and converted into three-dimensional image signals, and the three-dimensional image signals comprise the appearance, the internal structure and the temperature distribution information of the power device and can reflect the omnibearing condition of the power device.
Preferably, the virtual reality helmet and virtual reality handle enable interactive manipulation of a three-dimensional simulation model of at least one electrical device, the interactive manipulation comprising touching, dragging, rotating, zooming actions.
Preferably, the virtual reality helmet and the virtual reality handle enable voice control of a three-dimensional simulation model of at least one electrical device, the voice control comprising voice recognition, voice synthesis, voice command functions.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, the quantum signal transmitter and the quantum signal receiver are arranged, the power equipment operation state information represented by the quantum state is sent and received through the quantum channel, and the quantum key is distributed through the quantum key distributor and used for carrying out quantum encryption and decryption on the power equipment operation state information, so that the effects of ensuring the safe transmission of data and preventing eavesdropping or tampering are achieved;
2. according to the invention, the nano material layer is arranged and covered on the surface or inside of the power equipment and is connected with the power equipment, so that the self-repairing function is realized, faults generated by the power equipment can be automatically detected and repaired, the change of the nano material layer is sensed through the sensor and converted into an electric signal, and the effects of improving the operation efficiency and safety of the power equipment and reducing the maintenance cost and risk are achieved;
3. according to the invention, the data processor is arranged, the digital signals are received from the controller, and the digital signals are used for carrying out analysis and processing of artificial intelligence, machine learning and data mining methods and are displayed on the virtual reality helmet, so that the effects of improving the accuracy, the high efficiency and the intelligence of the analysis and the processing of the data are achieved;
4. according to the invention, the virtual reality helmet and the virtual reality handle are arranged, so that the visualization and operation of the three-dimensional simulation model of the power equipment can be realized, and an operation instruction is sent to the controller according to the fault type, the fault level, the fault reason, the processing proposal and the measure information displayed by the data processor, thereby achieving the effects of improving the operation efficiency and the safety of the staff and increasing the operation convenience and the comfort of the staff;
5. according to the invention, the virtual reality camera is arranged at each position of the power equipment and is connected with the virtual reality helmet, so that the running state information of the power equipment can be captured in real time and converted into the three-dimensional image signal, and the effects of improving the real-time performance and the integrity of the running state information of the power equipment and reflecting the omnibearing condition of the power equipment are achieved.
Drawings
FIG. 1 is a schematic diagram of an on-line power failure monitoring device according to the present invention;
FIG. 2 is a schematic diagram of an on-line fault monitoring system for power according to the present invention;
FIG. 3 is a flow chart of the operation of the power on-line fault monitoring system of the present invention;
FIG. 4 is a schematic diagram of virtual reality interactions of the power online fault monitoring system of the present invention;
fig. 5 is a schematic diagram of an application of the device and system for monitoring power failure in a transformer scenario.
In the figure: 1. a quantum signal emitter; 2. a quantum signal receiver; 3. a quantum key distributor; 4. a quantum encryptor; 5. a quantum decryptor; 7. a sensor; 8. a data collector; 9. a data transmitter; 10. a controller; 11. a data processor; 12. a cloud platform; 13. a virtual reality helmet; 14. a virtual reality handle; 101. an electrical apparatus.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment is suitable for the scene of on-line fault monitoring of a transformer, as shown in fig. 1, the device for on-line fault monitoring of electric power of the present invention comprises a quantum signal emitter 1, a quantum signal receiver 2, a quantum key distributor 3, a quantum encryptor 4, a quantum decryptor 5, a nano material layer, a sensor 7, a data collector 8, a data transmitter 9 and a controller 10, and is characterized in that:
the quantum signal transmitter 1 and the quantum signal receiver 2 are respectively arranged at two ends of the transformer and are connected through a quantum channel, and are used for transmitting and receiving the running state information of the transformer represented by the quantum state;
the running state information of the transformer comprises temperature, voltage, current and power parameters of the transformer, and can reflect the running state and fault condition of the transformer;
the quantum channel adopts single photon or entangled photon as carrier, and transmits through optical fiber or free space, and utilizes the unclonability and indistinguishability of quantum state to ensure the safe transmission of quantum signal and prevent eavesdropping or tampering;
the quantum key distributor 3 is connected with the quantum signal emitter 1 and the quantum signal receiver 2 and is used for distributing quantum keys between the quantum signal emitter 1 and the quantum signal receiver 2 through quantum channels and carrying out quantum encryption and decryption on the operation state information of the transformer;
the quantum encryptor 4 is arranged at the output end of the quantum signal emitter 1, is connected with the quantum key distributor 3 and is used for carrying out quantum encryption on the running state information of the transformer;
the quantum decryptor 5 is arranged at the input end of the quantum signal receiver 2 and connected with the quantum key distributor 3 for carrying out quantum decryption on the running state information of the transformer;
the nano material layer covers the surface or the inside of the transformer and is connected with the transformer, so that the transformer has a self-repairing function;
the nanometer material layer is made of carbon nano tubes, graphene, nano metal or nano oxide materials, and covers the surface or the inside of the transformer, and the high conductivity and the high strength of the nanometer material are utilized to realize automatic detection and repair of faults generated by the transformer;
the sensor 7 is arranged on or in the nano material layer and connected with the nano material layer, and can sense the change of the nano material layer and convert the change into an electric signal;
the sensor 7 is of a piezoelectric sensor, a pyroelectric sensor, a photoelectric sensor or a chemical sensor type, is arranged on or in the nano material layer, can sense the change of the nano material layer, and converts the change into an electric signal, wherein the change comprises the shape, thickness and temperature attribute of the nano material layer, and can reflect the self-repairing effect and the fault degree of the nano material layer;
the data collector 8 is arranged at the output end of the sensor 7 and is connected with the sensor 7, and can collect and convert the electric signals output by the sensor 7 into digital signals;
the data transmitter 9 is arranged at the output end of the data collector 8 and is connected with the data collector 8, and can transmit digital signals to the controller 10 in a wireless or wired mode;
the data transmission between the data transmitter 9 and the controller 10 adopts encryption or compression or other technologies, and is performed in a wireless or wired mode, so that the safety and the transmission efficiency of the data are ensured;
the controller 10 is disposed at a receiving end of the data transmitter 9 and connected to the data transmitter 9, and is configured to send a control instruction to the transformer according to the received digital signal and an operation instruction of a worker, so as to implement remote control of the transformer, where the control instruction includes adjustment, repair or replacement operations, so that a fault problem of the transformer can be effectively solved.
As shown in fig. 2, the power online fault monitoring system of the present invention includes a data processor 11, a cloud platform 12, a virtual reality helmet 13, a virtual reality handle 14 and a virtual reality camera, and is characterized in that:
the data processor 11 is connected with the controller 10, and receives digital signals from the controller 10, and is used for analyzing and processing the digital signals through artificial intelligence, machine learning and data mining methods, and displaying the digital signals on the virtual reality helmet 13;
the cloud platform 12 is connected with the data processor 11 and is responsible for storing, managing and updating transformer operation data and intelligent models and providing remote access and cooperation functions;
the cloud platform 12 includes a deep learning algorithm module and an intelligent model module, wherein the deep learning algorithm module adopts a Convolutional Neural Network (CNN) or a cyclic neural network (RNN) or a long-short-term memory network (LSTM) or other deep learning algorithms to perform feature extraction, classification and regression operations on the transformer operation data, so as to improve the accuracy and generalization of the intelligent model; while embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, as defined by the appended claims and their equivalents, based on input transformer operating data, output fault types, fault levels, fault causes, process recommendations and action information, using Decision Trees (DT) or Support Vector Machines (SVM) or Random Forests (RF) or other machine learning algorithms. The virtual reality helmet 13 is arranged on the head of a worker and connected with the data processor 11, so that the visualization of a three-dimensional simulation model of the transformer can be realized, and the three-dimensional simulation model is synchronously updated with three-dimensional image signals captured by the virtual reality camera;
the virtual reality handle 14 is arranged on the hand of a worker and connected with the controller 10, so that the operation of the three-dimensional simulation model of the transformer can be realized;
the virtual reality camera is arranged at each position of the transformer and is connected with the virtual reality helmet 13, so that the running state information of the transformer can be captured in real time and converted into three-dimensional image signals, and the three-dimensional image signals comprise the appearance, the internal structure and the temperature distribution information of the transformer and can reflect the omnibearing condition of the transformer.
As shown in fig. 3, the working flow of the power online fault monitoring system of the invention is as follows:
step 1: the quantum signal transmitter 1 and the quantum signal receiver 2 send and receive the transformer running state information represented by the quantum state through a quantum channel, and distribute a quantum key through the quantum key distributor 3 for carrying out quantum encryption and decryption on the transformer running state information;
step 2: the nanometer material layer is covered on the surface or inside of the transformer and is connected with the transformer, so that the transformer has a self-repairing function, faults generated by the transformer can be automatically detected and repaired, the change of the nanometer material layer is sensed through the sensor 7, and the change is converted into an electric signal;
step 3: the data collector 8 collects the electric signal output by the sensor 7, converts the electric signal into a digital signal, and transmits the digital signal to the controller 10 in a wireless or wired mode through the data transmitter 9;
step 4: the controller 10 receives the digital signal and transmits it to the data processor 11 by wireless or wired means;
step 5: the data processor 11 receives the intelligent model from the cloud platform 12, performs analysis and processing of artificial intelligence, machine learning and data mining methods on the digital signal, and displays the digital signal on the virtual reality helmet 13;
step 6: the staff wears the virtual reality helmet 13 and the virtual reality handle 14, can realize the visualization and operation of the three-dimensional simulation model of the transformer, and sends an operation instruction to the controller 10 according to the fault type, fault level, fault reason, processing advice and measure information displayed by the data processor 11;
step 7: the controller 10 sends a control command to the transformer according to the received operation command, so as to realize remote control of the transformer, wherein the control command comprises adjustment, repair or replacement operation, and the fault problem of the transformer can be effectively solved.
Having example 2:
compared with embodiment 1, in this embodiment, the power equipment 101 is a power transmission line, and other structural and functional features are the same or similar, and will not be described again.
In this embodiment, the quantum signal transmitter 1 and the quantum signal receiver 2 are respectively disposed at two ends of the power transmission line, and send and receive, through a quantum channel, information of an operation state of the power transmission line, where the information includes temperature, voltage, current and power parameters of the power transmission line, and can reflect an operation condition and a fault condition of the power transmission line. For example, when the power transmission line is overheated, overloaded, and short-circuited, the information is changed accordingly, so that the information is perceived and transmitted by the quantum signal emitter 1 and the quantum signal receiver 2.
In this embodiment, the nanomaterial layer covers the surface or the inside of the power transmission line and is connected to the power transmission line, so that the self-repairing function is provided, faults generated by the power transmission line can be automatically detected and repaired, the change of the nanomaterial layer is sensed by the sensor 7, and the change is converted into an electrical signal. For example, when the power transmission line breaks, corrodes and ages, the damaged part can be automatically filled or repaired by utilizing the high conductivity and high strength of the nano material layer, and corresponding electric signals are output through the sensor 7 to reflect the self-repairing effect and the failure degree of the nano material layer.
In this embodiment, the virtual reality helmet 13 and the virtual reality handle 14 can realize visualization and operation of the three-dimensional simulation model of the transmission line, and send an operation instruction to the controller 10 according to the fault type, fault level, fault cause, processing protocol and measure information displayed by the data processor 11. For example, when the worker wears the virtual reality helmet 13 and the virtual reality handle 14, they can see the three-dimensional simulation model of the transmission line on the virtual reality helmet 13 and touch, drag, rotate it through the virtual reality handle 14, simulating the actual operation of the transmission line. At the same time, they can also see the fault information displayed by the data processor 11 on the virtual reality helmet 13 and send operating instructions to the controller 10 according to the processing recommendations and measures provided by them. For example, when the data processor 11 shows that an overheat fault occurs in the power transmission line, the worker may send an operation instruction to adjust the temperature of the power transmission line to the controller 10; when the data processor 11 shows that the transmission line breaks down, the worker may send an operation instruction to repair or replace the transmission line to the controller 10.
Example 3:
the embodiment is suitable for a scenario of performing online fault monitoring on a power distribution network, and compared with the embodiment 1, in this embodiment, the power equipment 101 is the power distribution network, and other structural and functional features are the same or similar, and are not described again.
In this embodiment, the quantum signal transmitter 1 and the quantum signal receiver 2 are respectively disposed at each node of the power distribution network, and send and receive, through a quantum channel, information of an operation state of the power distribution network, where the information includes load, voltage, current and power parameters of the power distribution network, and can reflect an operation condition and a fault condition of the power distribution network. For example, when the power distribution network has load imbalance, voltage fluctuation and abnormal current faults, the information changes correspondingly, so that the information is perceived and transmitted by the quantum signal emitter 1 and the quantum signal receiver 2.
In this embodiment, the nanomaterial layer covers the surface or the inside of the power distribution network, is connected to the power distribution network, has a self-repairing function, can automatically detect and repair faults generated by the power distribution network, senses the change of the nanomaterial layer through the sensor 7, and converts the change into an electrical signal. For example, when the power distribution network has open circuit, short circuit and ground fault, the nano material layer can automatically fill or repair the damaged part by utilizing the high conductivity and high strength of the nano material layer, and the corresponding electric signal is output through the sensor 7 to reflect the self-repairing effect and the fault degree of the nano material layer.
In this embodiment, the virtual reality helmet 13 and the virtual reality handle 14 can realize visualization and operation of the three-dimensional simulation model of the power distribution network, and send an operation instruction to the controller 10 according to the fault type, the fault level, the fault cause, the processing protocol and the measure information displayed by the data processor 11. For example, when the worker wears the virtual reality helmet 13 and the virtual reality handle 14, they can see the three-dimensional simulation model of the power distribution network on the virtual reality helmet 13 and touch, drag, rotate the virtual reality helmet through the virtual reality handle 14, simulating the actual operation of the power distribution network. At the same time, they can also see the fault information displayed by the data processor 11 on the virtual reality helmet 13 and send operating instructions to the controller 10 according to the processing recommendations and measures provided by them. For example, when the data processor 11 shows that the power distribution network has a load imbalance fault, the worker may send an operation instruction to the controller 10 to adjust the load distribution of the power distribution network; when the data processor 11 shows that the distribution network has a broken circuit, the operator may send an operation instruction to repair or replace the distribution network line to the controller 10.
Example 4:
in this embodiment, the nano material layer covers the surface or the inside of the wind driven generator, is connected with the wind driven generator, has a self-repairing function, can automatically detect and repair faults generated by the wind driven generator, senses the change of the nano material layer through the sensor 7, and converts the change into an electric signal. For example, when the wind driven generator has blade fracture, bearing abrasion and generator failure, the nano material layer can automatically fill or repair the damaged part by utilizing the high conductivity and high strength of the nano material layer, and the sensor 7 outputs corresponding electric signals to reflect the self-repairing effect and the failure degree of the nano material layer.
In this embodiment, the virtual reality helmet 13 and the virtual reality handle 14 can realize visualization and operation of the three-dimensional simulation model of the wind turbine, and send an operation instruction to the controller 10 according to the fault type, fault level, fault cause, processing protocol and measure information displayed by the data processor 11. For example, when the worker wears the virtual reality helmet 13 and the virtual reality handle 14, they can see the three-dimensional simulation model of the wind power generator on the virtual reality helmet 13 and touch, drag, rotate it through the virtual reality handle 14, simulating the actual operation of the wind power generator. At the same time, they can also see the fault information displayed by the data processor 11 on the virtual reality helmet 13 and send operating instructions to the controller 10 according to the processing recommendations and measures provided by them. For example, when the data processor 11 shows that the wind turbine fails at an overspeed, the worker may send an operation instruction to the controller 10 to adjust the rotational speed of the wind turbine; when the data processor 11 shows that the wind driven generator has blade fracture fault, the staff can send an operation instruction for repairing or replacing the wind driven generator blade to the controller 10;
in the scheme, the system realizes the functions of safe transmission, automatic detection and repair, intelligent analysis and processing, remote control and visual operation of the running state information of the power equipment 101 through quantum communication, nano materials and virtual reality technology. Some of the algorithms run are as follows:
quantum communication algorithm: the system adopts a Quantum Key Distribution (QKD) algorithm to realize the quantum key distribution between the quantum signal emitter 1 and the quantum signal receiver 2, and is used for carrying out quantum encryption and decryption on the operation state information of the power equipment 101. The QKD algorithm is an algorithm that uses the unclonability and indistinguishability of quantum states to ensure secure distribution of keys. There are various specific implementations of QKD algorithms, such as single-photon or entangled-photon based BB84 protocol, E91 protocol. The system can select a proper QKD algorithm to carry out quantum communication according to different quantum channels and quantum carriers.
Nanomaterial self-repair algorithm: the system adopts a self-repairing algorithm based on the characteristics of the nano materials to realize automatic detection and repair of faults generated by the power equipment 101. The algorithm is an algorithm for automatically filling or repairing damaged parts by utilizing the high conductivity and high strength of the nano material layer according to the change of the operation state information of the power equipment 101 perceived by the nano material layer. There are various specific implementations of the algorithm, such as a conductive bridge formation mechanism based on carbon nanotubes or graphene materials, a surface adsorption or catalytic reaction mechanism based on nano-metal or nano-oxide materials. The system can select proper nanomaterial self-repairing algorithm to process faults according to different power equipment 101 and fault types.
Intelligent analysis processing algorithm: the system adopts an intelligent analysis processing algorithm based on artificial intelligence, machine learning and data mining methods to realize the algorithms of extracting, classifying and regressing the operation data of the power equipment 101 and outputting fault types, fault levels, fault reasons, processing suggestions and measure information. The algorithm is an algorithm for analyzing and processing digital signals received by a data processor by utilizing the cloud platform to store, manage and update the power equipment 101 operation data and the intelligent model. The algorithm has various specific implementation modes, for example, the feature extraction, classification and regression operation are performed on the operation data of the power equipment 101 based on a Convolutional Neural Network (CNN) or a cyclic neural network (RNN) or a long-short-term memory network (LSTM) deep learning algorithm, so that the accuracy and generalization of an intelligent model are improved; based on Decision Tree (DT) or Support Vector Machine (SVM) or Random Forest (RF) machine learning algorithms, fault type, fault level, fault cause, process recommendation and action information are output from the input power device 101 operation data. The system can select a proper intelligent analysis processing algorithm for data analysis and processing according to different power equipment 101 and data characteristics.
Claims (9)
1. The utility model provides an online fault monitoring device of electric power, includes quantum signal transmitter (1), quantum signal receiver (2), quantum key distributor (3), quantum encryptor (4), quantum decryptor (5), nanometer material layer, sensor (7), data acquisition ware (8), data transmission ware (9) and controller (10), its characterized in that:
the quantum signal transmitter (1) and the quantum signal receiver (2) are respectively arranged at two ends of at least one power device (101) and are connected through a quantum channel, and are used for transmitting and receiving the running state information of the power device (101) represented by a quantum state;
the nano material layer covers the surface or the inside of at least one electric device (101) and is connected with the electric device (101) to have a self-repairing function;
the sensor (7) is arranged on or in the nano material layer and connected with the nano material layer, can sense the change of the nano material layer and convert the change into an electric signal;
the data transmitter (9) is arranged at the output end of the data collector (8) and is connected with the data collector (8) and can transmit digital signals to the controller (10) in a wireless or wired mode;
the controller (10) is arranged at the receiving end of the data transmitter (9) and is connected with the data transmitter (9) and is used for sending a control instruction to at least one electric device (101) according to the received digital signal and an operation instruction of a worker so as to realize remote control of the at least one electric device (101).
2. The power on-line fault monitoring device of claim 1, wherein: the operating state information of the power equipment (101) comprises temperature, voltage, current and power parameters of the power equipment (101).
3. The power on-line fault monitoring device of claim 1, wherein: the quantum channel adopts single photon or entangled photon as carrier and is transmitted via optical fiber or free space.
4. The power on-line fault monitoring device of claim 1, wherein: the nanomaterial layer is made of carbon nanotubes, graphene, nano metal or nano oxide materials and covers the surface or the inside of at least one electric device (101).
5. An electric power on-line fault monitoring system for use in claim 1, comprising a data processor (11), a cloud platform (12), a virtual reality helmet (13), a virtual reality handle (14) and a virtual reality camera, characterized in that:
the data processor (11) is connected with the controller (10) and receives digital signals from the controller (10) and is used for analyzing and processing the digital signals through artificial intelligence, machine learning and data mining methods and displaying the digital signals on the virtual reality helmet (13);
the cloud platform (12) is connected with the data processor (11) and is responsible for storing, managing and updating at least one power equipment (101) operation data and intelligent models and providing remote access and cooperation functions;
the virtual reality helmet (13) is arranged on the head of a worker and connected with the data processor (11), so that the visualization of a three-dimensional simulation model of at least one electric device (101) can be realized, and the three-dimensional simulation model is synchronously updated with three-dimensional image signals captured by the virtual reality camera;
the virtual reality handle (14) is arranged on the hand of a worker and connected with the controller (10) and can realize the operation of a three-dimensional simulation model of at least one electric device (101);
the virtual reality camera is arranged at each position of at least one power equipment (101) and is connected with the virtual reality helmet (13), so that the running state information of the at least one power equipment (101) can be captured in real time and converted into a three-dimensional image signal.
6. An on-line fault monitoring system for electrical power as claimed in claim 5, wherein: the cloud platform (12) is responsible for storing, managing and updating operation data and intelligent models of at least one electric device (101) and providing remote access and cooperation functions, the cloud platform (12) comprises a deep learning algorithm module and an intelligent model module, the deep learning algorithm module adopts a Convolutional Neural Network (CNN) or a cyclic neural network (RNN) or a long-short-term memory network (LSTM) or other deep learning algorithms to perform feature extraction, classification and regression operation on the operation data of the at least one electric device (101), and the accuracy and generalization of the intelligent model are improved; the intelligent model module adopts Decision Tree (DT) or Support Vector Machine (SVM) or Random Forest (RF) or other machine learning algorithm, and outputs fault type, fault level, fault cause, processing proposal and measure information according to the input operation data of at least one power equipment (101).
7. The power on-line fault monitoring system as claimed in any one of claims 6, wherein: the virtual reality camera is arranged at each position of at least one power equipment (101) and is connected with the virtual reality helmet (13), so that the running state information of the at least one power equipment (101) can be captured in real time and converted into three-dimensional image signals, and the three-dimensional image signals comprise the appearance, the internal structure and the temperature distribution information of the power equipment (101) and can reflect the omnibearing condition of the power equipment (101).
8. The power on-line fault monitoring system as claimed in any one of claims 7, wherein: the virtual reality helmet (13) and the virtual reality handle (14) enable interactive operation of a three-dimensional simulation model of at least one electrical device (101), the interactive operation comprising touching, dragging, rotating, zooming actions.
9. The power on-line fault monitoring system of any one of claim 8, wherein: the virtual reality helmet (13) and the virtual reality handle (14) enable voice control of a three-dimensional simulation model of at least one electrical device (101), the voice control comprising voice recognition, voice synthesis, voice command functions.
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