Method, device and equipment for controlling remote power box of charged cleaning and storage medium

Abstract

The present application relates to the technical field of power supply box, and particularly relates to a control method, device and equipment of a remote control power supply box and a storage medium, wherein remote control signals are respectively sent to multiple sockets of the power supply box, so that the sockets control corresponding cleaning equipment to be powered on or off based on the remote control signals, one person controls multiple sockets, human resource allocation is optimized, work efficiency is improved, circuit overload or short circuit information fed back by a circuit breaker and leakage information fed back by a leakage protector are acquired in real time, circuit abnormality analysis is performed according to the circuit overload or short circuit information and the leakage information, a power supply cut-off instruction is generated when the abnormality analysis result is that the circuit is abnormal, multiple electrical protection mechanisms are integrated to ensure operation safety, the power supply box is diagnosed by using a Bayesian network, protection measure information is generated according to a diagnosis result, the intelligent degree is improved, the accuracy of fault cause diagnosis is improved, the reliability and stability of the equipment are improved, maintenance convenience is improved, and maintenance cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power supply boxes, and particularly relates to a control method and device of a remote control power supply box for live cleaning, equipment and a storage medium. BACKGROUND

[0002] As the core node of the power system, the safe and stable operation of the substation has a decisive significance for the entire power grid. The electrical equipment of the substation is easily affected by environmental factors (dust, dirt, salt mist, etc.) during operation, and gradually accumulates contamination, which not only reduces the insulation performance and increases the risk of short circuit and failure, but also may affect heat dissipation, leading to overheating and even fire accidents. Therefore, regular implementation of live cleaning and maintenance of electrical equipment in substations is a necessary measure to ensure the safe operation of the power grid. Live cleaning technology can maintain electrical equipment under non-power conditions, significantly improving work efficiency and safety.

[0003] In the practice process of the live cleaning operation team, it is found that the traditional power supply box is generally single in function, cumbersome in operation and insufficient in safety, and it is difficult to meet the actual operation needs of the live cleaning of the substation, cannot realize one-man multi-control, cannot optimize the allocation of human resources, reduces the work efficiency, and the current power supply box does not integrate overload, short circuit and leakage protection functions, cannot ensure the operation safety, when the power supply box fails, the manual troubleshooting of the failure cause is needed, reduces the maintenance convenience of the power supply box and increases the maintenance cost, cannot automatically diagnose the failure cause, has low intelligent degree and reduces the failure cause diagnosis accuracy, reduces the reliability and stability of the power supply box. SUMMARY

[0004] In order to overcome the shortcomings of the prior art, the purpose of the present application is to provide a control method, device, equipment and storage medium of a remote control power supply box for live cleaning, which realizes one-man multi-control effect, optimizes the allocation of human resources, improves work efficiency, integrates multiple electrical protection mechanisms, ensures operation safety, improves intelligent degree, improves failure cause diagnosis accuracy, improves the reliability and stability of the equipment, improves maintenance convenience and reduces maintenance cost.

[0005] The first aspect of the present application provides a control method for a remote power box for electrically charged cleaning, comprising: sending remote control signals to a plurality of sockets of the power box to control the on-off of cleaning equipment based on the remote control signals, each socket being connected to different cleaning equipment; acquiring circuit overload or short circuit information fed back by a circuit breaker connected to the socket in real time, and acquiring leakage information fed back by a leakage protector connected to the socket in real time; performing circuit anomaly analysis according to the circuit overload or short circuit information and the leakage information to obtain an anomaly analysis result, and generating a power cut-off instruction when the anomaly analysis result determines that there is an anomaly in the circuit; constructing a Bayesian network, performing fault diagnosis on the power box by using the Bayesian network to obtain a diagnosis result; generating protection measure information according to the diagnosis result, and sending the protection measure information to a management terminal.

[0006] Optionally, in the first implementation manner of the first aspect of the present application, the sending of the remote control signals to the plurality of sockets of the power box to control the on-off of the cleaning equipment based on the remote control signals, each socket being connected to different cleaning equipment, comprises: sending remote control signals to the plurality of sockets of the power box to make the corresponding sockets convert the remote control signals into electrical signals, each socket being connected to different cleaning equipment; and generating cleaning equipment on-off control instructions according to the electrical signals.

[0007] Optionally, in the second implementation manner of the first aspect of the present application, the real-time acquisition of the circuit overload or short circuit information fed back by the circuit breaker connected to the socket, and the real-time acquisition of the leakage information fed back by the leakage protector connected to the socket, comprises: real-time acquisition of the circuit overload or short circuit information fed back by the circuit breaker connected to the socket; data cleaning of the circuit overload or short circuit information, and conversion of the circuit overload or short circuit information into a standard format for model input; real-time acquisition of the leakage information fed back by the leakage protector connected to the socket; data cleaning of the leakage information, and conversion of the leakage information into a standard format for model input.

[0008] Optionally, in the third implementation manner of the first aspect of the present application, the circuit anomaly analysis according to the circuit overload or short circuit information and the leakage information to obtain an anomaly analysis result, and the generation of a power cut-off instruction when the anomaly analysis result determines that there is an anomaly in the circuit, comprises: calling a preset circuit analysis model; inputting the circuit overload or short circuit information and the leakage information into the circuit analysis model for circuit anomaly analysis, and outputting an anomaly analysis result; determining whether the anomaly analysis result is an anomaly in the circuit; and if yes, generating a power cut-off instruction.

[0009] Optionally, in a fourth implementation form of the first aspect of the present application, the constructing the Bayesian network and performing fault diagnosis on the power cabinet based on the Bayesian network to obtain a diagnosis result comprises: collecting historical fault features, and constructing a fault database based on the historical fault features; training the Bayesian network based on the fault database; collecting real-time operation signal samples that can reflect the health status of the power cabinet, pre-processing the operation signal samples by using wavelet analysis to obtain pre-processed signal samples; extracting real-time fault features of the pre-processed signal samples; inputting the real-time fault features into the Bayesian network to perform fault diagnosis on the power cabinet, and outputting a diagnosis result, wherein the diagnosis result is one of mechanical failure, circuit failure, improper operation failure, aging and wear failure, software failure and no failure.

[0010] Optionally, in a fifth implementation form of the first aspect of the present application, the generating protection measure information according to the diagnosis result and sending the protection measure information to the management terminal comprises: calling a preset fault handling scheme library; matching a fault specific handling scheme having a mapping relationship with the diagnosis result in the fault handling scheme library; generating protection measure information according to the fault specific handling scheme; and sending the protection measure information to the management terminal, so that the management terminal generates and displays a protection measure page based on the protection measure information.

[0011] Optionally, in a sixth implementation form of the first aspect of the present application, after the generating protection measure information according to the diagnosis result and sending the protection measure information to the management terminal, the method further comprises: obtaining a time stamp from a time stamp service platform based on a diagnosis time, and inserting the time stamp into the diagnosis result; recording fault handling result information fed back by the management terminal, combining the diagnosis result and the fault handling result information to obtain fault diagnosis and handling information; encrypting the fault diagnosis and handling information to obtain fault diagnosis and handling encrypted information; and uploading the fault diagnosis and handling encrypted information to a block chain.

[0012] The second aspect of the present application provides a control device for remotely controlling a power supply box for electrically charged cleaning, comprising: a sending module configured to send remote control signals to a plurality of sockets of the power supply box respectively, so that the sockets control the on-off of cleaning equipment based on the remote control signals, each of the sockets being connected to different cleaning equipment; an acquisition module configured to acquire circuit overload or short circuit information fed back by a circuit breaker connected to the sockets in real time, and to acquire leakage information fed back by a leakage protector connected to the sockets in real time; an analysis and generation module configured to perform circuit anomaly analysis according to the circuit overload or short circuit information and the leakage information, and to obtain an anomaly analysis result, and to generate a power supply cut-off instruction if the anomaly analysis result determines that there is an anomaly in the circuit; a diagnosis module configured to construct a Bayesian network, perform fault diagnosis on the power supply box by using the Bayesian network, and obtain a diagnosis result; and a generation and sending module configured to generate protection measure information according to the diagnosis result, and send the protection measure information to a management terminal.

[0013] Optionally, in the first implementation manner of the second aspect of the present application, the sending module comprises: a first sending unit configured to send remote control signals to a plurality of sockets of the power supply box respectively, so that the corresponding sockets convert the remote control signals into electrical signals, each of the sockets being connected to different cleaning equipment; and a first generation unit configured to generate cleaning equipment on-off control instructions according to the electrical signals.

[0014] Optionally, in the second implementation manner of the second aspect of the present application, the acquisition module comprises: a first acquisition unit configured to acquire circuit overload or short circuit information fed back by a circuit breaker connected to the sockets in real time; a first cleaning and conversion unit configured to clean the circuit overload or short circuit information and convert the circuit overload or short circuit information into a standard format for model input; a second acquisition unit configured to acquire leakage information fed back by a leakage protector connected to the sockets in real time; and a second cleaning and conversion unit configured to clean the leakage information and convert the leakage information into a standard format for model input.

[0015] Optionally, in the third implementation manner of the second aspect of the present application, the analysis and generation module comprises: a first calling unit configured to call a preset circuit analysis model; an analysis unit configured to input the circuit overload or short circuit information and the leakage information into the circuit analysis model to perform circuit anomaly analysis, and output an anomaly analysis result; a judgment unit configured to judge whether the anomaly analysis result is that there is an anomaly in the circuit; and a second generation unit configured to generate a power supply cut-off instruction if the judgment result is that there is an anomaly in the circuit.

[0016] Optionally, in a fourth implementation of the second aspect of the present invention, the diagnosis module is constructed including: a collection and construction unit for collecting historical fault features and constructing a fault database based on the historical fault features; a training unit for using the fault database to train a Bayesian network; an acquisition and preprocessing unit for real-time collection of operating signal samples in the power box that can reflect its health status, and preprocessing the operating signal samples using wavelet analysis to obtain preprocessed signal samples; an extraction unit for extracting real-time fault features of the preprocessed signal samples; a diagnosis unit for inputting the real-time fault features into the Bayesian network to perform fault diagnosis on the power box, and outputting a diagnosis result, which is one of mechanical fault, circuit fault, improper operation fault, aging and wear fault, software fault and no fault.

[0017] Optionally, in a fifth implementation of the second aspect of the present invention, the generation and sending module includes: a second calling unit, used to call a preset fault handling solution library; a matching unit, used to match a specific fault handling solution that has a mapping relationship with the diagnosis result in the fault handling solution library; a third generating unit, used to generate protection measures information according to the specific fault handling solution; and a second sending unit, used to send the protection measures information to the management terminal, so that the management terminal generates and displays a protection measures page based on the protection measures information.

[0018] Optionally, in the sixth implementation method of the second aspect of the present invention, it also includes: an acquisition and insertion module, which is used to obtain a timestamp from the timestamp service platform based on the diagnosis time, and insert the timestamp into the diagnosis result; a record merging module, which is used to record the fault processing result information fed back by the management terminal, merge the diagnosis result and the fault processing result information, and obtain fault diagnosis and processing information; an encryption upload module, which is used to encrypt the fault diagnosis and processing information, obtain fault diagnosis and processing encrypted information, and upload the fault diagnosis and processing encrypted information to the blockchain.

[0019] The third aspect of the present invention provides a control device for a remote-controlled power box for live cleaning, the control device for the remote-controlled power box for live cleaning comprising: a memory and at least one processor, the memory storing instructions; at least one processor calling the instructions in the memory so that the control device for the remote-controlled power box for live cleaning executes each step of the control method for the remote-controlled power box for live cleaning described in any one of the above items.

[0020] A fourth aspect of the present invention provides a computer-readable storage medium having instructions stored thereon, which, when executed by a processor, implement the various steps of the control method for a remote-controlled power box for live cleaning as described in any one of the above items.

[0021] In the technical solution of the present application, by sending remote control signals to multiple sockets of the power box respectively, the sockets control the corresponding cleaning equipment to be powered on or off based on the remote control signals, one person controls multiple devices, optimizes the allocation of human resources, improves work efficiency, real-time acquisition of circuit overload or short circuit information feedback by the circuit breaker and leakage information feedback by the leakage protector, circuit abnormality analysis according to the circuit overload or short circuit information and the leakage information, generation of power-off instructions when the abnormality analysis result determines that the circuit is abnormal, integration of multiple electrical protection mechanisms to ensure job safety, construction of a Bayesian network for fault diagnosis of the power box, generation of protection measures information according to the diagnosis result, improvement of the intelligent degree, improvement of the accuracy of fault cause diagnosis, improvement of the reliability and stability of the equipment, improvement of the maintenance convenience and reduction of the maintenance cost. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The first flowchart of the control method of the live cleaning remote power box provided by the embodiment of the present application.

[0023] Figure 2 The second flowchart of the control method of the live cleaning remote power box provided by the embodiment of the present application.

[0024] Figure 3 The third flowchart of the control method of the live cleaning remote power box provided by the embodiment of the present application.

[0025] Figure 4 The fourth flowchart of the control method of the live cleaning remote power box provided by the embodiment of the present application.

[0026] Figure 5 The structure schematic diagram of the control device of the live cleaning remote power box provided by the embodiment of the present application.

[0027] Figure 6 Another structure schematic diagram of the control device of the live cleaning remote power box provided by the embodiment of the present application.

[0028] Figure 7 The structure schematic diagram of the control device of the live cleaning remote power box provided by the embodiment of the present application. DETAILED DESCRIPTION

[0029] The present application provides a control method, device and equipment of a live cleaning remote power box, which realizes one person controlling multiple devices, optimizes the allocation of human resources, improves work efficiency, integrates multiple electrical protection mechanisms to ensure job safety, improves the intelligent degree, improves the accuracy of fault cause diagnosis, improves the reliability and stability of the equipment, improves the maintenance convenience and reduces the maintenance cost.

[0030] The terms "first," "second," "third," "fourth," and so on (if any) in the description and claims of the present invention and in the accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that shown or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus that includes a series of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, product, or apparatus.

[0031] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 An embodiment of a control method for a live cleaning remote control power box according to an embodiment of the present invention includes:

[0032] 101. Sending remote control signals to multiple sockets of the power box respectively, so that the sockets control the power on and off of the cleaning equipment based on the remote control signals, and each socket is connected to a different cleaning equipment;

[0033] In this embodiment, the remote control signal is sent by the remote controller and then transmitted to each socket module. These socket modules receive the signal wirelessly and perform corresponding operations. Each socket module controls the power on and off of the connected cleaning equipment by receiving the remote control signal.

[0034] 102. Real-time acquisition of circuit overload or short circuit information fed back by the circuit breaker connected to the socket, and real-time acquisition of leakage information fed back by the leakage protector connected to the socket;

[0035] In this embodiment, through the cooperation of the circuit breaker and the leakage protector, each socket module will independently protect the connected cleaning equipment. The circuit breaker can quickly cut off the power supply when the cleaning equipment is overloaded or short-circuited to avoid equipment damage. The leakage protector can disconnect the power supply in time when the cleaning equipment leaks to protect the safety of equipment and personnel, and obtain in real time the circuit overload or short-circuit information fed back by the circuit breaker connected to the socket, and obtain in real time the leakage information fed back by the leakage protector connected to the socket.

[0036] 103. Perform circuit abnormality analysis based on circuit overload or short circuit information and leakage information to obtain abnormality analysis results. When the abnormality analysis results determine that the circuit is abnormal, generate a power cut-off instruction;

[0037] In the embodiment, by comparing the current, pressure and other data collected by the sensor with the preset threshold value, the system first judges whether overload or short circuit occurs, monitors the difference of the circuit in and out current through the differential current sensor, and if the difference exceeds the set threshold value, it is considered as leakage, and when the abnormal analysis result determines that the circuit is abnormal, a power cut-off instruction is generated.

[0038] 104. Constructing a Bayesian network, using the Bayesian network to perform fault diagnosis on the power box, and obtaining a diagnosis result;

[0039] In the embodiment, a Bayesian network is constructed, the Bayesian network is composed of nodes (representing random variables) and directed edges (representing conditional dependence relationships between variables), each node has a conditional dependence relationship with its parent node, the state of the parent node determines the probability distribution of the child node, and each node has a conditional probability table (CPT) representing the probability of the node given its parent node, for example, if the power box has a short circuit fault, the current value may increase sharply, the Bayesian network calculates this change through conditional probability, uses the Bayesian network to perform fault diagnosis on the power box, and obtains a diagnosis result.

[0040] 105. Generating protection measure information according to the diagnosis result, and sending the protection measure information to a management terminal;

[0041] In the embodiment, the diagnosis result is analyzed to determine the type of the diagnosis result, according to the set rule base, the system can generate corresponding protection measure information according to different fault types, the definition of the protection measure depends on the specific type and severity of the fault diagnosis, and the protection measure information is sent to the management terminal.

[0042] In the embodiment, the remote control signal is sent to the plurality of sockets of the power box respectively, so that the sockets control the corresponding cleaning equipment to be powered on and off based on the remote control signal, one-man multi-control is realized, human resource allocation is optimized, work efficiency is improved, circuit overload or short circuit information fed back by a circuit breaker and leakage information fed back by a leakage protector are acquired in real time, circuit abnormality analysis is performed according to the circuit overload or short circuit information and the leakage information, a power cut-off instruction is generated when the abnormality analysis result determines that the circuit is abnormal, multiple electrical protection mechanisms are integrated to ensure work safety, a Bayesian network is constructed, the Bayesian network is used to perform fault diagnosis on the power box, protection measure information is generated according to the diagnosis result, the intelligent degree is improved, the fault cause diagnosis accuracy is improved, the reliability and stability of the equipment are improved, the maintenance convenience is improved, and the maintenance cost is reduced.

[0043] Please refer to Figure 2 , the second embodiment of the control method of the live cleaning remote power box in the embodiment includes:

[0044] 201. Sending remote control signals to multiple sockets of the power box respectively, so that the corresponding sockets convert the remote control signals into electrical signals, and each socket is connected to a different cleaning device;

[0045] In this embodiment, remote control signals are sent to multiple sockets of the power box through a remote control using infrared remote control, radio frequency communication (RF) or Wi-Fi. The sockets have a wireless receiving function, can receive the remote control signal and identify its content, and then convert the remote control signal into an electrical signal.

[0046] 202. Generate a power on / off control instruction for the cleaning equipment according to the electrical signal;

[0047] In this embodiment, the socket controls the switch of the connected cleaning device according to the electrical signal, and each cleaning device is controlled independently to prevent the signal of one socket from interfering with the operation of other devices.

[0048] 203. Real-time acquisition of circuit overload or short circuit information fed back by a circuit breaker connected to the socket;

[0049] In this embodiment, circuit overload or short circuit information fed back by the circuit breaker connected to the socket is obtained in real time, current changes are detected in real time using a current sensor to monitor whether the current exceeds a preset safety range, and voltage sensors are used to monitor the voltage to determine whether a short circuit occurs.

[0050] 204. Clean the circuit overload or short circuit information and convert the circuit overload or short circuit information into a standard format for model input;

[0051] In this embodiment, duplicate items in the circuit overload or short circuit information are deleted, missing values ​​of the circuit overload or short circuit information are filled by an interpolation method, and abnormal values ​​of the circuit overload or short circuit information are corrected, and the circuit overload or short circuit information is converted into a standard format for model input.

[0052] 205. Real-time acquisition of leakage information fed back by the leakage protector connected to the socket;

[0053] In this embodiment, the leakage protector detects the current difference through a built-in leakage current sensor, and obtains leakage information fed back by the leakage protector connected to the socket in real time.

[0054] 206. Clean the leakage information and convert the leakage information into a standard format for model input;

[0055] In this embodiment, duplicate items in the leakage information are deleted, missing values ​​of the leakage information are filled by an interpolation method, and abnormal values ​​of the leakage information are corrected, so as to convert the leakage information into a standard format for model input.

[0056] In the embodiment of the present application, through the conversion of remote control signals and electrical signals, the system can remotely control multiple cleaning devices, realize efficient automatic management, obtain and process overload, short circuit, leakage and other information in real time, help to identify device faults or abnormalities in time, ensure the safe and stable operation of the system, through data cleaning and format conversion of feedback information, ensure the accuracy and consistency of the data, provide reliable input for subsequent analysis or model processing, monitor the overload, short circuit and leakage of the circuit in real time, effectively prevent safety hazards and improve the overall safety of the system.

[0057] Please refer to Figure 3 The third embodiment of the control method of the live cleaning remote power supply box in the embodiment of the present application comprises:

[0058] 301, calling a preset circuit analysis model;

[0059] In this embodiment, the preset circuit analysis model is called, and the circuit analysis model is a machine learning model trained by using decision tree, random forest, support vector machine (SVM) or neural network algorithm and a large amount of historical circuit data (including labeled normal state circuit data and abnormal state circuit data). The circuit analysis model will diagnose the circuit abnormality according to the actual state of the input circuit information.

[0060] 302, inputting the circuit overload or short circuit information and the leakage information into the circuit analysis model for circuit abnormality analysis, and outputting an abnormality analysis result;

[0061] In this embodiment, the circuit overload or short circuit information and the leakage information are input into the circuit analysis model. The circuit analysis model will calculate the key parameters such as current, voltage and power, and diagnose the circuit abnormality according to the actual state of the key parameters. For example, if the current exceeds the rated range, it is marked as overload, if the current increases sharply, it is marked as short circuit, and if the current leaks to the ground or non-normal channel, it is marked as leakage. Finally, the abnormality analysis result is output.

[0062] 303, judging whether the abnormality analysis result is that the circuit has an abnormality;

[0063] In this embodiment, it is judged whether the abnormality analysis result is that the circuit has an abnormality. The current exceeding the rated range, the current increasing sharply or the current leaking are the circuit having an abnormality.

[0064] 304, if yes, generating a power cut-off instruction;

[0065] In this embodiment, if it is judged that the abnormality analysis result is that the circuit has an abnormality, a power cut-off instruction is generated, and the automatic execution of power cut-off is realized through a circuit breaker or a leakage protector.

[0066] 305. Collect historical fault features and build a fault database based on the historical fault features;

[0067] In this embodiment, all fault data that has occurred in the past are collected, and historical fault features are extracted from all fault data. The historical fault features are sorted and classified and stored in a fault database that can be queried and analyzed. The fault database has the ability to be updated in real time, and new fault data can be continuously added to the database to ensure that the fault information in the database is up to date.

[0068] 306. Using the fault database to train a Bayesian network;

[0069] In this embodiment, the structure of the Bayesian network is defined, which describes the dependency relationship between different variables. Appropriate prior probabilities are selected and conditional probabilities are determined. The Bayesian network is trained using the maximum likelihood estimation method. After the training is completed, the Bayesian network is evaluated. Once the Bayesian network training is completed, it can be applied to actual fault prediction tasks.

[0070] 307. Collecting operation signal samples from the power box in real time that can reflect its health status, and preprocessing the operation signal samples using wavelet analysis to obtain preprocessed signal samples;

[0071] In this embodiment, the operation signal samples that can reflect the health status of the power box are collected in real time, and the operation signal samples are preprocessed using wavelet analysis. The specific process is shown in formula (1):

[0072] (1)

[0073] Where, and Indicates a non-negative constant, the collected signal The expression after preprocessing is shown in formula (2):

[0074] (2)

[0075] In the formula Indicates the acquisition signal The wavelet transform function of represents the scale factor, represents time shift, represents the wavelet basis.

[0076] 308. Extracting real-time fault features of the preprocessed signal samples;

[0077] In this embodiment, the real-time fault features of the preprocessed signal samples are extracted. The specific process is shown in formula (3):

[0078] (3)

[0079] wherein, represents a fault feature of a power box equipment operation signal, represents a signal value in each sample, represents a mean value of each signal, represents a sample number of each signal.

[0080] 309, inputting the real-time fault feature into the Bayesian network to perform fault diagnosis on the power box, and outputting a diagnosis result, the diagnosis result being one of mechanical fault, circuit fault, improper operation fault, aging wear fault, software fault and no fault;

[0081] In the embodiment, the real-time fault feature is inputted into the Bayesian network to perform fault diagnosis on the power box, the Bayesian network is composed of a group of nodes and directed edges, each node represents a variable (such as a certain fault feature or a fault type), and the edges represent the conditional dependence relationship between the variables, in the embodiment, the nodes can be the inputted fault features, and the outputted diagnosis result is the type of the power box fault, the diagnosis result being one of mechanical fault, circuit fault, improper operation fault, aging wear fault, software fault and no fault.

[0082] In the embodiment, by calling the circuit analysis model and the Bayesian network, the system can intelligently identify and diagnose faults based on real-time and historical data, avoid manual intervention, improve diagnosis efficiency, early discover potential faults by real-time collection and analysis of operation signal samples, provide early warning, help prevent major faults, reduce downtime and maintenance costs, accurately classify faults into different types by extracting fault features and applying the Bayesian network, and thus take corresponding processing measures to improve system stability, and the collection of historical fault features and the construction of a fault database enable the system to continuously learn and optimize, and improve the accuracy and reliability of future diagnosis.

[0083] Please refer to Figure 4 , the fourth embodiment of the control method of the remote power box for live cleaning in the embodiment includes:

[0084] 401, calling a preset fault handling scheme library;

[0085] In the embodiment, the preset fault handling scheme library is called, and the preset fault handling scheme library is a database containing various fault types and corresponding processing steps.

[0086] 402, matching a fault specific handling scheme having a mapping relationship with the diagnosis result in the fault handling scheme library;

[0087] In the embodiment, the diagnosis result is the type of power box failure, and a relevant specific failure handling scheme is found from the failure handling scheme library according to the type.

[0088] 403, generating protection measure information according to the specific failure handling scheme;

[0089] In the embodiment, the protection measure information is generated after the specific failure handling scheme is executed.

[0090] 404, sending the protection measure information to the management terminal to enable the management terminal to generate and display a protection measure page based on the protection measure information;

[0091] In the embodiment, the protection measure information is sent to the management terminal through a data transmission mode such as an API interface, a data stream, or a message queue. Once the management terminal receives the protection measure information, the management terminal will start to analyze the protection measure information, and then generate and display a protection measure page.

[0092] 405, obtaining a timestamp from a timestamp service platform based on a diagnosis time, and inserting the timestamp into the diagnosis result;

[0093] In the embodiment, the interface form provided by the timestamp service platform (such as HTTP API, RPC, etc.) is determined, and an accurate timestamp is obtained from the interface based on the diagnosis time, to ensure that the data format of the timestamp is consistent with the format of the position to be inserted in the diagnosis result, and the obtained timestamp is added to the appropriate position in the diagnosis result.

[0094] 406, recording the failure handling result information fed back by the management terminal, merging the diagnosis result and the failure handling result information, and obtaining failure diagnosis and handling information;

[0095] In the embodiment, the management terminal is responsible for receiving failure reports of each part of the system and returning handling results to obtain failure handling result information. The failure handling result information fed back by the management terminal is recorded, the diagnosis result and the handling result are associated through a failure ID, a device number, or an event time, the diagnosis result and the failure handling result information are merged, and failure diagnosis and handling information is obtained.

[0096] 407, encrypting the failure diagnosis and handling information to obtain failure diagnosis and handling encrypted information, and uploading the failure diagnosis and handling encrypted information to a blockchain;

[0097] In this embodiment, asymmetric encryption (such as RSA) is used to encrypt the fault diagnosis and processing information to obtain the fault diagnosis and processing encrypted information. The fault diagnosis and processing encrypted information is used as a block, including necessary metadata (such as block ID, timestamp, hash value of the previous block, etc.) to form a new block. The block is verified in the blockchain. After the verification is passed, the block is written into the blockchain and becomes part of the blockchain.

[0098] In the embodiment of the present invention, by calling a preset fault handling solution library and automatically matching the handling solution, manual intervention is reduced, and processing speed and accuracy are improved. By generating and sending protection measures information to the management terminal, real-time sharing and display of fault handling information is achieved, ensuring that relevant personnel can quickly obtain accurate information. Through the timestamp service platform and blockchain technology, the accurate recording and non-tamperability of diagnosis and processing information are ensured, and the reliability and transparency of the data are enhanced. The fault handling information is encrypted and uploaded to the blockchain, which improves the security and privacy protection of the information and prevents data leakage and tampering.

[0099] The above describes the control method of the live cleaning remote control power box in the embodiment of the present invention. The following describes the control device of the live cleaning remote control power box in the embodiment of the present invention. Figure 5 In one embodiment of the present invention, a control device for a remote control power box for live cleaning includes:

[0100] A sending module 501 is used to send remote control signals to multiple sockets of the power box respectively, so that the sockets control the power on and off of the cleaning equipment based on the remote control signals, and each socket is connected to a different cleaning equipment;

[0101] An acquisition module 502 is configured to acquire, in real time, circuit overload or short circuit information fed back by a circuit breaker connected to the socket, and leakage information fed back by a leakage protector connected to the socket;

[0102] Analysis and generation module 503, configured to perform circuit abnormality analysis based on circuit overload or short circuit information and leakage information to obtain abnormality analysis results, and generate a power cut-off instruction when the abnormality analysis results determine that the circuit is abnormal;

[0103] Constructing a diagnosis module 504 for constructing a Bayesian network, and using the Bayesian network to perform fault diagnosis on the power box to obtain a diagnosis result;

[0104] The generating and sending module 505 is configured to generate protection measure information according to the diagnosis result and send the protection measure information to the management terminal.

[0105] In the embodiment, the remote control signals are sent to the multiple sockets of the power box respectively, so that the sockets control the corresponding cleaning equipment to be powered on or off based on the remote control signals, one person controls multiple, optimizes the allocation of human resources, improves work efficiency, real-time circuit overload or short circuit information fed back by the circuit breaker and leakage information fed back by the leakage protector are obtained, circuit abnormality analysis is performed according to the circuit overload or short circuit information and the leakage information, when the abnormality analysis result is determined as the circuit existing abnormality, a power cut-off instruction is generated, multiple electrical protection mechanisms are integrated to ensure the operation safety, a Bayesian network is constructed, fault diagnosis of the power box is performed by using the Bayesian network, protection measure information is generated according to the diagnosis result, the intelligent degree is improved, the fault cause diagnosis accuracy is improved, the reliability and stability of the equipment are improved, the maintenance convenience is improved and the maintenance cost is reduced.

[0106] Referring to Figure 6 Another embodiment of the control device of the live cleaning remote control power box in the embodiment of the application includes:

[0107] The sending module 501 is configured to send remote control signals to multiple sockets of the power box respectively, so that the sockets control the cleaning equipment to be powered on or off based on the remote control signals, and each socket is connected to different cleaning equipment.

[0108] The obtaining module 502 is configured to obtain circuit overload or short circuit information fed back by a circuit breaker connected to the socket in real time, and obtain leakage information fed back by a leakage protector connected to the socket in real time.

[0109] The analysis and generation module 503 is configured to perform circuit abnormality analysis according to the circuit overload or short circuit information and the leakage information, and obtain an abnormality analysis result, and generate a power cut-off instruction when the abnormality analysis result is determined as the circuit existing abnormality.

[0110] The construction and diagnosis module 504 is configured to construct a Bayesian network, perform fault diagnosis of the power box by using the Bayesian network, and obtain a diagnosis result.

[0111] The generation and sending module 505 is configured to generate protection measure information according to the diagnosis result, and send the protection measure information to a management terminal.

[0112] In the embodiment, the sending module 501 includes a first sending unit 5011 configured to send remote control signals to multiple sockets of the power box respectively, so that the corresponding sockets convert the remote control signals into electrical signals, and each socket is connected to different cleaning equipment, and a first generation unit 5012 configured to generate cleaning equipment on-off control instructions according to the electrical signals.

[0113] In the embodiment, the acquisition module 502 comprises: a first acquisition unit 5021, configured to acquire circuit overload or short circuit information fed back by a circuit breaker connected to the socket in real time; a first cleaning and conversion unit 5022, configured to clean data of the circuit overload or short circuit information and convert the circuit overload or short circuit information into a standard format for model input; a second acquisition unit 5023, configured to acquire leakage information fed back by a leakage protector connected to the socket in real time; and a second cleaning and conversion unit 5024, configured to clean data of the leakage information and convert the leakage information into a standard format for model input.

[0114] In the embodiment, the analysis generation module 503 comprises: a first calling unit 5031, configured to call a preset circuit analysis model; an analysis unit 5032, configured to input the circuit overload or short circuit information and the leakage information into the circuit analysis model for circuit anomaly analysis and output an anomaly analysis result; a judgment unit 5033, configured to judge whether the anomaly analysis result is that the circuit is abnormal; and a second generation unit 5034, configured to generate a power cut-off instruction if the result is that the circuit is abnormal.

[0115] In the embodiment, the diagnosis module 504 comprises: a collection and construction unit 5041, configured to collect historical fault features and construct a fault database based on the historical fault features; a training unit 5042, configured to train a Bayesian network by using the fault database; a sample collection and preprocessing unit 5043, configured to collect running signal samples that can reflect a health state of the power box in real time, pre-process the running signal samples by using wavelet analysis, and obtain preprocessed signal samples; an extraction unit 5044, configured to extract real-time fault features of the preprocessed signal samples; and a diagnosis unit 5045, configured to input the real-time fault features into the Bayesian network to perform fault diagnosis on the power box, and output a diagnosis result, which is one of a mechanical fault, a circuit fault, an improper operation fault, an aging wear fault, a software fault and no fault.

[0116] In the embodiment, the generation and sending module 505 comprises: a second calling unit 5051, configured to call a preset fault handling scheme library; a matching unit 5052, configured to match a fault specific handling scheme having a mapping relationship with the diagnosis result in the fault handling scheme library; a third generation unit 5053, configured to generate protection measure information according to the fault specific handling scheme; and a second sending unit 5054, configured to send the protection measure information to a management terminal, so that the management terminal generates and displays a protection measure page based on the protection measure information.

[0117] In the embodiment, the method further includes: obtaining the time stamp from a time stamp service platform based on the diagnosis time, inserting the time stamp into the diagnosis result; recording the fault handling result information fed back by the management terminal, merging the diagnosis result and the fault handling result information to obtain fault diagnosis and handling information; and encrypting the fault diagnosis and handling information to obtain fault diagnosis and handling encrypted information, and uploading the fault diagnosis and handling encrypted information to a block chain.

[0118] The above Figure 5 And Figure 6 The control device of the live cleaning remote power supply box in the embodiment of the application is described in detail from the perspective of the modular functional entity, and the control device of the live cleaning remote power supply box in the embodiment of the application is described in detail from the perspective of hardware processing.

[0119] Figure 7 Fig. 1 is a structural schematic diagram of the control device of the live cleaning remote power supply box provided by the embodiment of the application. The control device 600 of the live cleaning remote power supply box can be quite different due to different configurations or performances, and can include one or more than one processor (central processing unit, CPU) 610 (for example, one or more than one processor) and a memory 620, and one or more than one storage medium 630 (for example, one or more than one mass storage device) storing an application program 633 or data 632. The memory 620 and the storage medium 630 can be temporary storage or persistent storage. The program stored in the storage medium 630 can include one or more than one module (not shown in the figure), and each module can include a series of instruction operations in the control device 600 of the live cleaning remote power supply box. Further, the processor 610 can be configured to communicate with the storage medium 630, execute a series of instruction operations in the storage medium 630 on the control device 600 of the live cleaning remote power supply box, so as to implement the steps of the control method of the live cleaning remote power supply box provided by each method embodiment.

[0120] The control device 600 of the live cleaning remote power supply box can further include one or more than one power supply 640, one or more than one wired or wireless network interface 650, one or more than one input and output interface 660, and / or one or more than one operating system 631, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. Those skilled in the art can understand that the control device 600 of the live cleaning remote power supply box can further include other components necessary for the operation of the control device 600 of the live cleaning remote power supply box, and the other components are not described in detail herein. Figure 7The structure of the control device for the live cleaning remote power box shown does not constitute a limitation on the control device for the live cleaning remote power box, and can include more or fewer components than shown, or combine certain components, or arrange different components.

[0121] The application also provides a computer readable storage medium, which can be a non-volatile computer readable storage medium, or a volatile computer readable storage medium. The computer readable storage medium stores instructions, which, when executed on a computer, cause the computer to perform the steps of the control method for the live cleaning remote power box.

[0122] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system or device, unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0123] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art, or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program code storage media.

[0124] Finally, it should be noted that: the above only describes the preferred examples of the present application, and does not limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or equivalently replace some technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A control method of a live cleaning remote power supply box, characterized by, The method comprises the following steps: sending remote control signals to multiple sockets of a power box to control the on-off of cleaning equipment based on the remote control signals, each socket being connected to different cleaning equipment; real-time acquisition of circuit overload or short circuit information fed back by a circuit breaker connected to the socket, and real-time acquisition of leakage information fed back by a leakage protector connected to the socket; circuit anomaly analysis based on the circuit overload or short circuit information and the leakage information, to obtain an anomaly analysis result, and generation of a power cut-off instruction when the anomaly analysis result determines that there is an anomaly in the circuit; construction of a Bayesian network, fault diagnosis of the power box by using the Bayesian network, and obtaining of a diagnosis result; generation of protection measure information based on the diagnosis result, and sending of the protection measure information to a management terminal; the circuit anomaly analysis based on the circuit overload or short circuit information and the leakage information, to obtain an anomaly analysis result, and generation of a power cut-off instruction when the anomaly analysis result determines that there is an anomaly in the circuit, comprising: calling a preset circuit analysis model; inputting the circuit overload or short circuit information and the leakage information into the circuit analysis model for circuit anomaly analysis, and outputting an anomaly analysis result; determining whether the anomaly analysis result is an anomaly in the circuit; if yes, generating a power cut-off instruction; the construction of a Bayesian network, fault diagnosis of the power box by using the Bayesian network, and obtaining of a diagnosis result, comprising: collecting historical fault features, and constructing a fault database based on the historical fault features; training the Bayesian network by using the fault database; real-time acquisition of running signal samples that can reflect the health status of the power box, pre-processing of the running signal samples by using wavelet analysis to obtain pre-processed signal samples, and the specific process being as shown in formula (1): （1） In the formula, With represents a constant with non-negative value, the collected signal The expression after preprocessing is shown in formula (2): （2） wherein a wavelet transform function representing the acquisition signal a scale factor, a time shift, a wavelet basis;​ extracting real-time fault features of the pre-processed signal samples, and the specific process being as shown in formula (3): （3） wherein a fault feature representing the power box device operation signal, a signal value in each sample, a mean value of each signal, a number of samples of each signal; inputting the real-time fault features into the Bayesian network for fault diagnosis of the power box, and outputting a diagnosis result, the diagnosis result being one of mechanical fault, circuit fault, improper operation fault, aging and wear fault, software fault and no fault; the generation of protection measure information based on the diagnosis result, and the sending of the protection measure information to a management terminal, comprising: calling a preset fault handling scheme library; matching a fault specific handling scheme having a mapping relationship with the diagnosis result in the fault handling scheme library; generating protection measure information based on the fault specific handling scheme; sending the protection measure information to a management terminal, so that the management terminal generates and displays a protection measure page based on the protection measure information.

2. The control method of the charged cleaning remote power supply box according to claim 1, characterized by, The sending of remote control signals to multiple sockets of a power box to control the on-off of cleaning equipment based on the remote control signals, each socket being connected to different cleaning equipment, comprising: sending remote control signals to multiple sockets of a power box to control the on-off of cleaning equipment based on the remote control signals, each socket being connected to different cleaning equipment; generating cleaning equipment on-off control instructions based on the electrical signals.

3. The control method of the charged cleaning remote power supply box according to claim 1, characterized by, The circuit overload or short circuit information fed back by the circuit breaker connected with the socket is acquired in real time, the leakage information fed back by the leakage protector connected with the socket is acquired in real time, and the method comprises the following steps: The circuit overload or short circuit information fed back by the circuit breaker connected with the socket is acquired in real time; The circuit overload or short circuit information is data-cleaned, and the circuit overload or short circuit information is converted into a standard format for model input; The leakage information fed back by the leakage protector connected with the socket is acquired in real time; The leakage information is data-cleaned, and the leakage information is converted into a standard format for model input.

4. The control method of the charged cleaning remote power supply box according to claim 1, characterized by, After the protection measure information is generated according to the diagnostic result and the protection measure information is sent to the management terminal, the method further comprises the following steps: A timestamp is acquired from a timestamp service platform based on a diagnostic time, and the timestamp is inserted into the diagnostic result; The fault processing result information fed back by the management terminal is recorded, the diagnostic result and the fault processing result information are combined to obtain fault diagnosis and processing information; The fault diagnosis and processing information is encrypted to obtain fault diagnosis and processing encrypted information, and the fault diagnosis and processing encrypted information is uploaded to a blockchain.

5. A control device for controlling the method of claim 1 to 4, characterized in that The method comprises the following steps: The sending module is used for sending remote control signals to multiple sockets of the power box respectively, so that the sockets control the on-off power of the cleaning equipment based on the remote control signals, and each socket is connected with different cleaning equipment; The acquisition module is used for acquiring circuit overload or short circuit information fed back by a circuit breaker connected with the socket in real time, and acquiring leakage information fed back by a leakage protector connected with the socket in real time; The analysis and generation module is used for performing circuit abnormality analysis according to the circuit overload or short circuit information and the leakage information to obtain an abnormality analysis result, and generating a power cut-off instruction when the abnormality analysis result is determined to be abnormal; The construction diagnosis module is used for constructing a Bayesian network, performing fault diagnosis on the power box by using the Bayesian network, and obtaining a diagnostic result; The generation and sending module is used for generating protection measure information according to the diagnostic result, and sending the protection measure information to a management terminal.

6. A control device for a live cleaning remote power box, characterized by The control device of the live cleaning remote power box comprises a memory and at least one processor, and the memory stores instructions; The at least one processor invokes the instructions in the memory, so that the control device of the live cleaning remote power box executes the steps of the control method of the live cleaning remote power box according to any one of claims 1-4.

7. A computer-readable storage medium having stored thereon instructions, the computer-readable storage medium comprising: The instructions are executed by the processor to implement the steps of the control method of the live cleaning remote power box according to any one of claims 1-4.

Images