Electrical equipment autonomous controllability evaluation method and device, computer equipment, medium and product

Abstract

The invention relates to an electrical equipment autonomous controllability evaluation method and device, computer equipment, a medium and a product. The method comprises the steps of obtaining current life cycle data of the electrical equipment in a production process of the electrical equipment, storing the current life cycle data to a block chain under the condition that node permission verification of a current node is passed, reading the current life cycle data and historical life cycle data of the electrical equipment from the block chain, and sending the current life cycle data and historical life cycle data to the block chain; and according to the current life cycle data and the historical life cycle data, performing autonomous controllability evaluation on the electrical equipment, and when it is determined that the electrical equipment has a fault according to the autonomous controllability evaluation, sending out a prompt message for performing maintenance processing on the electrical equipment. And storing maintenance data formed after the electrical equipment is maintained to the block chain, so as to update the autonomous controllability evaluation result according to the maintenance data. By adopting the method, the safety of the electrical equipment can be improved.

Description

Technical Field

[0001] The present application relates to the field of electrical equipment safety technology, and in particular to a method, device, computer equipment, medium and product for evaluating the autonomous controllability of electrical equipment. Background Art

[0002] With the increasing complexity and diverse usage environments of electrical equipment, its autonomous controllability is becoming increasingly important. Current assessment systems rely primarily on manual review and centralized database records, making them vulnerable to human manipulation and data tampering. Furthermore, they lack sufficient transparency and credibility when tracing equipment failures. Therefore, a method for assessing the autonomous controllability of electrical equipment that provides transparent, tamper-proof data is urgently needed. Summary of the Invention

[0003] Based on this, it is necessary to provide an electrical equipment autonomous controllability evaluation method, device, computer equipment, medium and product that can improve the safety of electrical equipment in response to the above technical problems.

[0004] In a first aspect, the present application provides a method for evaluating the autonomous controllability of electrical equipment, comprising:

[0005] During the production process of electrical equipment, obtain the current life cycle data of the electrical equipment; the current life cycle data includes the operation data of the electrical equipment at each life cycle node;

[0006] When the node authority verification of the current node is passed, the current life cycle data is saved to the blockchain;

[0007] Read the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and conduct an autonomous controllability assessment of the electrical equipment based on the current life cycle data and historical life cycle data;

[0008] When it is determined that the electrical equipment has a fault based on the autonomous controllability assessment, a prompt message is issued to the outside to perform maintenance on the electrical equipment, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain to update the autonomous controllability assessment results based on the maintenance data.

[0009] In one embodiment, before saving the current lifecycle data to the blockchain, the process includes:

[0010] Through the consensus mechanism of the blockchain, the consistency of the current life cycle data is verified;

[0011] If the consistency check passes, the integrity of the current life cycle data will be verified through the blockchain's smart contract.

[0012] In one embodiment, the step of evaluating the autonomous controllability of electrical equipment based on current life cycle data and historical life cycle data includes:

[0013] Obtain parameter change trends of electrical equipment based on current life cycle data and historical life cycle data, and identify potential risk types of electrical equipment during operation based on parameter change trends;

[0014] Based on the potential risk type, the autonomous controllability score of electrical equipment is obtained through machine learning models.

[0015] In one embodiment, the method further comprises:

[0016] Based on the maintenance data, the maintenance quality score of the electrical equipment is obtained, and based on the maintenance quality score, the autonomous controllability score of the electrical equipment is updated.

[0017] In one embodiment, the method further comprises:

[0018] Determine the operation permissions corresponding to the current node based on the node permissions of the current node;

[0019] In response to the traceability query request triggered by the administrator, the query operation corresponding to the operation authority is executed according to the traceability query request.

[0020] In one embodiment, the step of executing a query operation corresponding to the operation authority according to the traceability query request includes:

[0021] Get the device identifier triggered by the administrator;

[0022] Obtain the full life cycle data of the traceable device corresponding to the device identifier from the blockchain; the full life cycle data includes the traceable device's production information, transportation records, installation status, operating parameters, and maintenance history;

[0023] In the event of a fault in the traceability device, the fault location of the traceability device is obtained based on the full life cycle data.

[0024] In a second aspect, the present application further provides an electrical equipment autonomous controllability assessment device, comprising:

[0025] The data acquisition module is used to obtain the current life cycle data of the electrical equipment during the production process of the electrical equipment; the current life cycle data includes the operation data of the electrical equipment at each life cycle node;

[0026] The data storage module is used to save the current life cycle data to the blockchain when the node authority verification of the current node is passed;

[0027] The controllability assessment module reads the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and conducts an autonomous controllability assessment of the electrical equipment based on the current life cycle data and historical life cycle data;

[0028] The evaluation and optimization module is used to issue a reminder message to perform maintenance on the electrical equipment when it is determined that the electrical equipment has a fault based on the autonomous controllability evaluation, and save the maintenance data generated after the electrical equipment is maintained to the blockchain to update the autonomous controllability evaluation results based on the maintenance data.

[0029] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements any one of the method steps in the first aspect when executing the computer program.

[0030] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements any one of the method steps in the first aspect when the computer program is executed by a processor.

[0031] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which implements any one of the method steps in the first aspect when executed by a processor.

[0032] The above-mentioned method, device, computer equipment, medium and product for evaluating the autonomous controllability of electrical equipment obtain the current life cycle data of the electrical equipment during the production process of the electrical equipment, save the current life cycle data to the blockchain when the node authority verification of the current node is passed, read the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and perform autonomous controllability evaluation on the electrical equipment based on the current life cycle data and historical life cycle data. When it is determined that the electrical equipment has a fault according to the autonomous controllability evaluation, a prompt message for maintenance of the electrical equipment is sent to the outside, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain to update the autonomous controllability evaluation result according to the maintenance data. This can realize closed-loop management from data collection, storage to analysis and evaluation, accurately evaluate the autonomous controllability of the electrical equipment, and thus improve the safety and operation efficiency of the electrical equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 This is a diagram of an application environment of a method for evaluating the autonomous controllability of electrical equipment in one embodiment;

[0035] Figure 2 1 is a flow chart of a method for evaluating autonomous controllability of electrical equipment in one embodiment;

[0036] Figure 3 A schematic diagram of collecting lifecycle data in one embodiment;

[0037] Figure 4 1 is a flow chart of a method for evaluating autonomous controllability of electrical equipment according to another embodiment;

[0038] Figure 5 1 is a structural block diagram of an apparatus for evaluating autonomous controllability of electrical equipment in one embodiment;

[0039] Figure 6 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0041] The electrical equipment autonomous controllability evaluation method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store data that server 104 needs to process. The data storage system can be integrated with server 104, or located in the cloud or on other network servers. Terminal 102 is used to obtain the current lifecycle data of the electrical equipment during its production process. If the node authority verification of the current node is passed, the current lifecycle data is saved to the blockchain. The current lifecycle data and historical lifecycle data of the electrical equipment are read from the blockchain. Based on the current lifecycle data and historical lifecycle data, an autonomous controllability assessment is performed on the electrical equipment. If the autonomous controllability assessment determines that the electrical equipment is faulty, a prompt message is issued to the public to perform maintenance on the electrical equipment. Maintenance data generated after the electrical equipment is maintained is saved to the blockchain, and the autonomous controllability assessment results are updated based on the maintenance data. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart car devices, projectors, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. Head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. Server 104 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0042] In an exemplary embodiment, Figure 2 As shown in the figure, a method for evaluating the autonomous controllability of electrical equipment is provided. Figure 1 The terminal 102 in the example is used as an example to illustrate the process, including the following steps S202 to S208.

[0043] Step S202 : during the production process of the electrical equipment, obtaining the current life cycle data of the electrical equipment; the current life cycle data includes the operation data of the electrical equipment at each life cycle node.

[0044] Optionally, during the production phase of electrical equipment, key operating parameters of the equipment can be collected in real time as current lifecycle data. For example, temperature sensors can be used to collect temperature information during the production and assembly process, while vibration and pressure sensors can be used to collect vibration and pressure information. Sensors can be installed on core components of the electrical equipment, such as electrical control cabinets or transformers.

[0045] For example, the schematic diagram of operation data collection at each life cycle node in the production process of electrical equipment is as follows: Figure 3 As shown, Figure 3 In the production process of electrical equipment, the production, transportation, installation, operation and scrapping include production, transportation, installation, operation and scrapping. At the production node, the temperature and pressure parameters of the core components are collected by temperature sensors and pressure sensors arranged on the electronic controller or transformer. At the transportation node, the vibration and collision parameters of the vehicle are collected by vibration sensors and collision sensors installed on the chassis or cargo box of the transport vehicle. At the installation node, the on-site operation parameters are collected by the operation parameter sensors installed on the tower pole and cabinet interface. At the operation node, the operation parameters of the equipment are monitored in real time by sensors installed on the terminal device or distributed node. At the scrapping node, the scrapping registration is carried out through the recycling of special registration devices.

[0046] Step S204: If the node authority verification of the current node is passed, the current life cycle data is saved to the blockchain.

[0047] Optionally, before data is uploaded to the blockchain, the access rights of the current operating node must be verified to prevent unauthorized data tampering or leakage. Using blockchain's distributed ledger technology, data is encrypted and stored on the chain. Each data block contains a timestamp, device identification, operating node information, etc., ensuring that the data cannot be tampered with and is traceable.

[0048] Step S206: read the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and perform an autonomous controllability assessment on the electrical equipment based on the current life cycle data and historical life cycle data.

[0049] Optionally, when conducting an autonomous controllability assessment, the historical life cycle data and current data of the equipment are read from the blockchain. By comparing the historical data and real-time data, the autonomous controllability of the electrical equipment is evaluated, that is, whether the equipment can work stably and reliably during operation, and whether there are any failure risks caused by design defects, component aging or external interference.

[0050] Step S208: When it is determined that the electrical equipment has a fault according to the autonomous controllability assessment, a prompt message is sent to the outside to perform maintenance on the electrical equipment, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain to update the autonomous controllability assessment result according to the maintenance data.

[0051] Optionally, if the assessment identifies a fault or anomaly in the equipment, a maintenance reminder message is automatically issued to alert relevant personnel to perform repairs. The maintenance data generated after the electrical equipment is maintained is saved to the blockchain, updating the equipment's lifecycle data. Based on this new lifecycle data, the autonomous controllability of the electrical equipment is reassessed, ensuring that the assessment results reflect the latest status of the equipment in real time. The autonomous controllability assessment results are used to characterize the operating status of the electrical equipment, for example, whether the electrical equipment is operating normally and stably.

[0052] In the above-mentioned method for evaluating the autonomous controllability of electrical equipment, the current life cycle data of the electrical equipment is obtained during the production process of the electrical equipment. When the node authority verification of the current node is passed, the current life cycle data is saved to the blockchain, the current life cycle data and historical life cycle data of the electrical equipment are read from the blockchain, and the autonomous controllability of the electrical equipment is evaluated based on the current life cycle data and the historical life cycle data. When it is determined that the electrical equipment has a fault according to the autonomous controllability evaluation, a prompt message for maintenance of the electrical equipment is sent to the outside, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain, so as to update the autonomous controllability evaluation result according to the maintenance data. This can realize closed-loop management from data collection, storage to analysis and evaluation, accurately evaluate the autonomous controllability of the electrical equipment, and thus improve the safety and operation efficiency of the electrical equipment.

[0053] In an exemplary embodiment, before saving the current lifecycle data to the blockchain, it includes: verifying the consistency of the current lifecycle data through the consensus mechanism of the blockchain; if the consistency check passes, verifying the integrity of the current lifecycle data through the smart contract of the blockchain.

[0054] Optionally, before writing the current lifecycle data of an electrical device to the blockchain, nodes in the network must verify data consistency using a consensus algorithm. This ensures that data collected or transmitted from different nodes for the same device is fully consistent, preventing data inconsistencies caused by network delays, transmission errors, or human tampering. Each node independently verifies the legitimacy of the data source and the rationality of the data content. A consensus algorithm is used to vote or calculate the data. Only when a majority of nodes confirm the data is consistent is the data allowed to proceed to the next verification stage. After the consistency check passes, the data integrity is verified using a smart contract. Smart contracts are pre-programmed, automated programs deployed on the blockchain that automatically enforce data verification rules. For example, a unique hash value is generated for the original data and compared with the hash value of the data transmitted to the blockchain. If the hash value matches, the data has not been tampered with or lost during transmission. If the integrity check passes, the data is encrypted and written to a new block on the blockchain. If it fails, the data is rejected and an exception notification is triggered.

[0055] In this embodiment, the consistency of the current life cycle data is verified through the consensus mechanism of the blockchain; if the consistency verification passes, the integrity of the current life cycle data is verified through the smart contract of the blockchain, which can ensure the security and integrity of the current life cycle, thereby ensuring the accuracy of the subsequent autonomous controllability assessment.

[0056] In an exemplary embodiment, the steps of evaluating the autonomous controllability of electrical equipment based on current life cycle data and historical life cycle data include: obtaining parameter change trends of the electrical equipment based on the current life cycle data and historical life cycle data, and identifying potential risk types of the electrical equipment during operation based on the parameter change trends; and obtaining an autonomous controllability score of the electrical equipment through a machine learning model based on the potential risk type.

[0057] Optionally, by comparing historical data with real-time data, the potential risk types of electrical equipment during operation can be identified. For example, if an upward trend is found in the temperature data and it continues to be above the safety threshold, it means that the electrical equipment may have a temperature anomaly risk, and an alarm will be generated and the relevant maintenance personnel will be notified to take measures. It should be noted that the autonomous controllability score is used to characterize the current risk level of the electrical equipment. In actual applications, the corresponding alarm information can be triggered directly based on the parameter change trend, or the autonomous controllability score of the electrical equipment can be obtained through a machine learning model. The higher the score, the higher the autonomous controllability of the electrical equipment, that is, the electrical equipment always maintains a safe and controllable operating state.

[0058] In this embodiment, by evaluating the autonomous controllability of electrical equipment based on current life cycle data and historical life cycle data, the autonomous controllability of the electrical equipment can be accurately evaluated, thereby improving the safety and operating efficiency of the electrical equipment.

[0059] In an exemplary embodiment, the method further includes: obtaining a maintenance quality score of the electrical equipment based on the maintenance data, and updating an autonomous controllability score of the electrical equipment based on the maintenance quality score.

[0060] Maintenance data can optionally include the type of replaced parts, the specific time of maintenance, and the maintenance personnel's information. Before being saved to the blockchain, maintenance data is also verified by the consensus mechanism and smart contracts. Only after passing verification can it be saved. Through smart contracts, the autonomous controllability score of the electrical equipment is updated based on the maintenance data saved to the blockchain. A higher maintenance quality score indicates higher maintenance quality, and the corresponding updated autonomous controllability score is higher, indicating safer electrical equipment.

[0061] In this embodiment, by obtaining the maintenance quality score of the electrical equipment based on the maintenance data and updating the autonomous controllability score of the electrical equipment based on the maintenance quality score, the autonomous controllability score can be updated in a timely manner, thereby improving the accuracy and real-time performance of the autonomous controllability score.

[0062] In an exemplary embodiment, the method further includes: determining the operation authority corresponding to the current node based on the node authority of the current node; and in response to a traceability query request triggered by the administrator, executing a query operation corresponding to the operation authority based on the traceability query request.

[0063] Optionally, in the event of a device failure or a need for a traceability query, the node's permissions can be used to determine the corresponding operational permissions for the current node. This means the scope and content of queries allowed for the current node can be determined, ensuring the security of data on the blockchain. A traceability query request triggered by an administrator executes the query operation corresponding to the operational permissions.

[0064] In this embodiment, by determining the operation authority corresponding to the current node based on the node authority of the current node, responding to the traceability query request triggered by the management personnel, and executing the query operation corresponding to the operation authority according to the traceability query request, the management efficiency of electrical equipment can be improved.

[0065] In an exemplary embodiment, according to the traceability query request, the steps of executing the query operation corresponding to the operation authority include: obtaining the device identifier triggered by the administrator; obtaining the full life cycle data of the traceability device corresponding to the device identifier from the blockchain; the full life cycle data includes the production information, transportation records, installation status, operating parameters and maintenance history records of the traceability device; in the event that there is a fault in the traceability device, the fault location of the traceability device is obtained based on the full life cycle data.

[0066] Optionally, managers can retrieve data on the entire lifecycle of electrical equipment by entering its unique identifier, including production information, shipping records, installation status, operating parameters, and maintenance history. Due to the immutability of blockchain, all retrieved information is trusted, ensuring the accuracy and integrity of the traceability process. For example, if a device problem occurs, a query can trace back detailed information about the device at a specific stage, allowing rapid problem identification and appropriate action.

[0067] In this embodiment, by executing the query operation corresponding to the operation authority according to the traceability query request, the fault location can be quickly located, and closed-loop management from data collection, storage to analysis and evaluation can be achieved, thereby improving the safety and operation efficiency of electrical equipment.

[0068] In an exemplary embodiment, Figure 4As shown, a method for evaluating the autonomous controllability of electrical equipment is provided, the method comprising the following steps:

[0069] S402: During the production process of the electrical equipment, current life cycle data of the electrical equipment is obtained; the current life cycle data includes operation data of the electrical equipment at each life cycle node.

[0070] S404: Verify the consistency of the current lifecycle data through the consensus mechanism of the blockchain; if the consistency check passes, verify the integrity of the current lifecycle data through the smart contract of the blockchain.

[0071] S406: When the node authority verification of the current node is passed, the current life cycle data is saved to the blockchain.

[0072] S408: Read the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, obtain the parameter change trend of the electrical equipment based on the current life cycle data and the historical life cycle data, and identify the potential risk type of the electrical equipment during operation based on the parameter change trend; based on the potential risk type, obtain the autonomous controllability score of the electrical equipment through the machine learning model.

[0073] S410: Obtain a maintenance quality score of the electrical equipment based on the maintenance data, and update an autonomous controllability score of the electrical equipment based on the maintenance quality score.

[0074] S412: When it is determined that the electrical equipment has a fault according to the autonomous controllability assessment, a prompt message is issued to the outside to perform maintenance on the electrical equipment, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain to update the autonomous controllability assessment result according to the maintenance data.

[0075] S414: Determine the operation authority corresponding to the current node based on the node authority of the current node; obtain the device identifier triggered by the manager in response to the traceability query request triggered by the manager; obtain the full life cycle data of the traceability device corresponding to the device identifier from the blockchain; the full life cycle data includes the production information, transportation records, installation status, operating parameters and maintenance history records of the traceability device; in the event of a fault in the traceability device, obtain the fault location of the traceability device based on the full life cycle data.

[0076] In this embodiment, during the production process of the electrical equipment, the current life cycle data of the electrical equipment is obtained. When the node authority verification of the current node is passed, the current life cycle data is saved to the blockchain, the current life cycle data and historical life cycle data of the electrical equipment are read from the blockchain, and the autonomous controllability of the electrical equipment is evaluated based on the current life cycle data and the historical life cycle data. When it is determined that the electrical equipment has a fault according to the autonomous controllability evaluation, a prompt message for maintenance of the electrical equipment is sent to the outside, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain, so as to update the autonomous controllability evaluation result according to the maintenance data. This can realize closed-loop management from data collection, storage to analysis and evaluation, accurately evaluate the autonomous controllability of the electrical equipment, and thus improve the safety and operation efficiency of the electrical equipment.

[0077] It should be understood that, although the various steps in the flowcharts involved in the above embodiments are displayed in sequence according to the instructions of the arrows, these steps are not necessarily performed in sequence in the order indicated by the arrows. Unless clearly stated herein, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of the steps or stages in other steps or other steps. It is understandable that the various steps in different embodiments can be freely combined as needed, and the various non-contradictory schemes formed by the combination all fall within the scope of protection of this application.

[0078] Based on the same inventive concept, embodiments of the present application also provide an electrical equipment autonomous controllability assessment device for implementing the aforementioned electrical equipment autonomous controllability assessment method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the electrical equipment autonomous controllability assessment device provided below can be found in the limitations of the electrical equipment autonomous controllability assessment method described above and will not be repeated here.

[0079] In an exemplary embodiment, Figure 5 As shown, an electrical equipment autonomous controllability evaluation device is provided, comprising: a data acquisition module 10, a data storage module 20, a controllability evaluation module 30 and an evaluation optimization module 40, wherein:

[0080] The data acquisition module 10 is used to acquire the current life cycle data of the electrical equipment during the production process of the electrical equipment; the current life cycle data includes the operation data of the electrical equipment at each life cycle node.

[0081] The data storage module 20 is used to save the current life cycle data to the blockchain when the node authority verification of the current node is passed.

[0082] The controllability evaluation module 30 is used to read the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and perform autonomous controllability evaluation on the electrical equipment based on the current life cycle data and historical life cycle data.

[0083] The evaluation and optimization module 40 is used to send a prompt message to the outside to perform maintenance on the electrical equipment when it is determined that the electrical equipment has a fault based on the autonomous controllability evaluation, and save the maintenance data generated after the electrical equipment is maintained to the blockchain to update the autonomous controllability evaluation result based on the maintenance data.

[0084] In an exemplary embodiment, the data storage module 20 is also used to verify the consistency of the current life cycle data through the consensus mechanism of the blockchain; if the consistency check passes, the integrity of the current life cycle data is verified through the smart contract of the blockchain.

[0085] In an exemplary embodiment, the controllability assessment module 30 is also used to obtain parameter change trends of electrical equipment based on current life cycle data and historical life cycle data, and identify potential risk types of electrical equipment during operation based on parameter change trends; based on the potential risk types, the autonomous controllability score of the electrical equipment is obtained through a machine learning model.

[0086] In an exemplary embodiment, the controllability evaluation module 30 is further configured to obtain a maintenance quality score of the electrical equipment based on the maintenance data, and update the autonomous controllability score of the electrical equipment based on the maintenance quality score.

[0087] In an exemplary embodiment, the evaluation and optimization module 40 is also used to determine the operation permissions corresponding to the current node based on the node permissions of the current node; in response to the traceability query request triggered by the administrator, execute the query operation corresponding to the operation permissions according to the traceability query request.

[0088] In an exemplary embodiment, the evaluation and optimization module 40 is also used to obtain a device identifier triggered by a manager; obtain the full life cycle data of the traceability device corresponding to the device identifier from the blockchain; the full life cycle data includes the production information, transportation records, installation status, operating parameters and maintenance history records of the traceability device; in the event that a fault occurs in the traceability device, the fault location of the traceability device is obtained based on the full life cycle data.

[0089] Each module in the aforementioned electrical equipment autonomous controllability assessment device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.

[0090] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, mobile cellular networks, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for evaluating the autonomous controllability of electrical equipment. The display unit of the computer device is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0091] Those skilled in the art will understand that Figure 6The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0092] In an exemplary embodiment, a computer device is provided, comprising a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: during the production process of the electrical equipment, obtaining the current life cycle data of the electrical equipment; the current life cycle data includes the operating data of the electrical equipment at each life cycle node; if the node authority verification of the current node is passed, saving the current life cycle data to the blockchain; reading the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and performing an autonomous controllability assessment on the electrical equipment based on the current life cycle data and the historical life cycle data; if it is determined that the electrical equipment has a fault according to the autonomous controllability assessment, sending a prompt message to the outside to perform maintenance on the electrical equipment, and saving the maintenance data generated after the electrical equipment is maintained to the blockchain, so as to update the autonomous controllability assessment result according to the maintenance data.

[0093] In one embodiment, before saving the current lifecycle data to the blockchain when the processor executes the computer program, the steps include: verifying the consistency of the current lifecycle data through the consensus mechanism of the blockchain; and if the consistency check passes, verifying the integrity of the current lifecycle data through the smart contract of the blockchain.

[0094] In one embodiment, when a processor executes a computer program, it involves performing an autonomous controllability assessment on the electrical equipment based on current life cycle data and historical life cycle data, including: obtaining a parameter change trend of the electrical equipment based on the current life cycle data and the historical life cycle data, and identifying the potential risk type of the electrical equipment during operation based on the parameter change trend; and obtaining an autonomous controllability score of the electrical equipment through a machine learning model based on the potential risk type.

[0095] In one embodiment, when the processor executes the computer program, it further implements the following steps: obtaining a maintenance quality score of the electrical equipment according to the maintenance data, and updating an autonomous controllability score of the electrical equipment according to the maintenance quality score.

[0096] In one embodiment, when the processor executes the computer program, it also implements the following steps: determining the operation authority corresponding to the current node based on the node authority of the current node; and responding to the traceability query request triggered by the administrator, executing the query operation corresponding to the operation authority based on the traceability query request.

[0097] In one embodiment, when the processor executes a computer program, it performs a query operation corresponding to the operation authority based on the traceability query request, including: obtaining a device identifier triggered by a manager; obtaining the full life cycle data of the traceability device corresponding to the device identifier from the blockchain; the full life cycle data includes the production information, transportation records, installation status, operating parameters and maintenance history records of the traceability device; in the event that there is a fault in the traceability device, the fault location of the traceability device is obtained based on the full life cycle data.

[0098] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: during the production process of the electrical equipment, the current life cycle data of the electrical equipment is obtained; the current life cycle data includes the operating data of the electrical equipment at each life cycle node; when the node authority verification of the current node is passed, the current life cycle data is saved to the blockchain; the current life cycle data and historical life cycle data of the electrical equipment are read from the blockchain, and the autonomous controllability evaluation of the electrical equipment is performed based on the current life cycle data and the historical life cycle data; when it is determined that the electrical equipment has a fault according to the autonomous controllability evaluation, a prompt message for maintenance processing of the electrical equipment is issued to the outside, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain, so as to update the autonomous controllability evaluation result according to the maintenance data.

[0099] In one embodiment, before saving the current lifecycle data to the blockchain, the computer program executed by the processor includes: verifying the consistency of the current lifecycle data through the consensus mechanism of the blockchain; and if the consistency check passes, verifying the integrity of the current lifecycle data through the smart contract of the blockchain.

[0100] In one embodiment, when a computer program is executed by a processor, it involves performing an autonomous controllability assessment on electrical equipment based on current life cycle data and historical life cycle data, including: obtaining parameter change trends of the electrical equipment based on the current life cycle data and historical life cycle data, and identifying potential risk types of the electrical equipment during operation based on the parameter change trends; and obtaining an autonomous controllability score of the electrical equipment through a machine learning model based on the potential risk type.

[0101] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: obtaining a maintenance quality score of the electrical equipment according to the maintenance data, and updating an autonomous controllability score of the electrical equipment according to the maintenance quality score.

[0102] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the operation authority corresponding to the current node based on the node authority of the current node; and in response to a traceability query request triggered by the administrator, executing the query operation corresponding to the operation authority based on the traceability query request.

[0103] In one embodiment, when a computer program is executed by a processor, it involves performing query operations corresponding to operation permissions based on a traceability query request, including: obtaining a device identifier triggered by a manager; obtaining the full life cycle data of the traceability device corresponding to the device identifier from the blockchain; the full life cycle data includes the production information, transportation records, installation status, operating parameters and maintenance history records of the traceability device; in the event that a fault occurs in the traceability device, the fault location of the traceability device is obtained based on the full life cycle data.

[0104] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps: obtaining current life cycle data of the electrical equipment during the production process of the electrical equipment; the current life cycle data includes operating data of the electrical equipment at each life cycle node; saving the current life cycle data to a blockchain when the node authority verification of the current node passes; reading the current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and performing an autonomous controllability assessment on the electrical equipment based on the current life cycle data and the historical life cycle data; and, when it is determined that the electrical equipment has a fault based on the autonomous controllability assessment, issuing a prompt message to perform maintenance on the electrical equipment, and saving the maintenance data generated after the electrical equipment is maintained to the blockchain, so as to update the autonomous controllability assessment result based on the maintenance data.

[0105] In one embodiment, before saving the current lifecycle data to the blockchain, the computer program executed by the processor includes: verifying the consistency of the current lifecycle data through the consensus mechanism of the blockchain; and if the consistency check passes, verifying the integrity of the current lifecycle data through the smart contract of the blockchain.

[0106] In one embodiment, when a computer program is executed by a processor, it involves performing an autonomous controllability assessment on electrical equipment based on current life cycle data and historical life cycle data, including: obtaining parameter change trends of the electrical equipment based on the current life cycle data and historical life cycle data, and identifying potential risk types of the electrical equipment during operation based on the parameter change trends; and obtaining an autonomous controllability score of the electrical equipment through a machine learning model based on the potential risk type.

[0107] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: obtaining a maintenance quality score of the electrical equipment according to the maintenance data, and updating an autonomous controllability score of the electrical equipment according to the maintenance quality score.

[0108] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the operation authority corresponding to the current node based on the node authority of the current node; and in response to a traceability query request triggered by the administrator, executing the query operation corresponding to the operation authority based on the traceability query request.

[0109] In one embodiment, when a computer program is executed by a processor, it involves performing query operations corresponding to operation permissions based on a traceability query request, including: obtaining a device identifier triggered by a manager; obtaining the full life cycle data of the traceability device corresponding to the device identifier from the blockchain; the full life cycle data includes the production information, transportation records, installation status, operating parameters and maintenance history records of the traceability device; in the event that a fault occurs in the traceability device, the fault location of the traceability device is obtained based on the full life cycle data.

[0110] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0111] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0112] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for evaluating the autonomous controllability of electrical equipment, characterized in that: The method comprises: During the production process of the electrical equipment, current life cycle data of the electrical equipment is obtained; the current life cycle data includes operation data of the electrical equipment at each life cycle node; If the node authority verification of the current node is passed, the current life cycle data is saved to the blockchain; reading current life cycle data and historical life cycle data of the electrical equipment from the blockchain, and performing an autonomous controllability assessment on the electrical equipment based on the current life cycle data and the historical life cycle data; When it is determined that the electrical equipment has a fault according to the autonomous controllability assessment, a prompt message is issued to the outside to perform maintenance on the electrical equipment, and the maintenance data generated after the electrical equipment is maintained is saved to the blockchain to update the autonomous controllability assessment result according to the maintenance data.

2. The method according to claim 1, characterized in that Before saving the current life cycle data to the blockchain, the process includes: Verify the consistency of the current lifecycle data through the consensus mechanism of the blockchain; When the consistency check passes, the integrity of the current lifecycle data is verified through the smart contract of the blockchain.

3. The method according to claim 1, characterized in that The performing autonomous controllability assessment on the electrical equipment based on the current life cycle data and the historical life cycle data includes: Obtaining a parameter change trend of the electrical equipment based on the current life cycle data and the historical life cycle data, and identifying a potential risk type of the electrical equipment during operation based on the parameter change trend; According to the potential risk type, an autonomous controllability score of the electrical equipment is obtained through a machine learning model.

4. The method according to claim 1, wherein The method further comprises: A maintenance quality score of the electrical equipment is obtained according to the maintenance data, and an autonomous controllability score of the electrical equipment is updated according to the maintenance quality score.

5. The method according to claim 1, wherein The method further comprises: Determine the operation permission corresponding to the current node according to the node permission of the current node; In response to a traceability query request triggered by a manager, a query operation corresponding to the operation authority is executed according to the traceability query request.

6. The method according to claim 5, characterized in that The step of executing the query operation corresponding to the operation authority according to the traceability query request includes: Obtaining a device identifier triggered by the administrator; Obtaining the full life cycle data of the traceable device corresponding to the device identifier from the blockchain; the full life cycle data includes the production information, transportation records, installation status, operating parameters and maintenance history of the traceable device; In the event that a fault occurs in the traceability device, the fault location of the traceability device is obtained based on the full life cycle data.

7. An electrical equipment autonomous controllability assessment device, characterized in that: The device comprises: A data acquisition module is used to acquire the current life cycle data of the electrical equipment during the production process of the electrical equipment; the current life cycle data includes the operation data of the electrical equipment at each life cycle node; A data storage module, configured to save the current lifecycle data to the blockchain if the node authority verification of the current node is passed; a controllability evaluation module, which reads the current life cycle data and the historical life cycle data of the electrical equipment from the blockchain, and performs an autonomous controllability evaluation on the electrical equipment based on the current life cycle data and the historical life cycle data; An evaluation and optimization module is configured to, when it is determined that the electrical equipment has a fault according to the autonomous controllability evaluation, issue a prompt message to perform maintenance on the electrical equipment, and save maintenance data generated after the electrical equipment has been maintained to the blockchain, so as to update the autonomous controllability evaluation result according to the maintenance data.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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