Intelligent management system used for insulating oil routine test handover

Abstract

The invention discloses an intelligent management system for insulating oil routine test handover. According to the invention, by constructing a collaborative system composed of the unique identity identification code, the intelligent code scanning terminal and the cloud data platform, digitization and intelligentization of the insulating oil handover process are realized, and the risk of wrong handover caused by information islands and unknown states is fundamentally eradicated; real-time verification and interaction of the dynamic state of the oil product are automatically triggered through code scanning, the accuracy and efficiency of handover operation are remarkably improved, meanwhile, a full-process traceable digital file is established, and reliable guarantee is provided for safe and stable operation of equipment.

Description

Technical Field

[0001] This invention relates to the technical field of routine testing of insulating oil, and more specifically to an intelligent management system for the handover of routine testing of insulating oil. Background Technology

[0002] As the core functional medium in oil-filled equipment such as transformers and instrument transformers, insulating oil simultaneously undertakes three key tasks: insulation barrier, heat dissipation carrier, and arc suppression. Therefore, regularly testing the performance of insulating oil to ensure it meets the requirements of the equipment is an important task in the operation and maintenance of power systems.

[0003] Currently, the handover process for insulating oil testing mainly relies on manual recording and paper-based document management. This traditional method has the following significant drawbacks:

[0004] Information is prone to errors: Manually recording oil information (such as station name, equipment name, sampling time, etc.) is prone to typos and omissions, and illegible handwriting may lead to misreading.

[0005] Inefficient: The handover process requires repeated verification of paper reports and physical labels, which is cumbersome, time-consuming, and affects the efficiency of experimental personnel and the time required for equipment to be put into operation.

[0006] Traceability difficulties: Paper documents are difficult to preserve for a long time and retrieve quickly. When oil quality problems occur or it is necessary to trace the flow of the same batch of oil, the query is difficult and the responsibility is not clearly defined.

[0007] Information silos: The updating of oil product status (such as test date, test results, test cycle, and defect status) relies on manual recording, which leads to information delays and the inability to synchronize with the management system in real time. This can easily cause equipment to operate with defects for a long time, endangering the safe and stable operation of the power grid.

[0008] In related technologies, there is a technical problem in the case of handover of insulating oil that may lead to erroneous handover due to the inability of the barcode scanning device to obtain and verify the dynamic status of the oil in real time. Summary of the Invention

[0009] The technical problem this invention aims to solve is the safety hazard of erroneous handover in insulating oil handover scenarios, caused by the inability of scanning devices to acquire and verify the dynamic state of the oil in real time. The purpose is to provide an intelligent management system for routine testing and handover of insulating oil, thereby resolving the safety hazard caused by the inability to acquire and verify the dynamic state of the oil in real time.

[0010] This invention is achieved through the following technical solution:

[0011] In a first aspect, the present invention provides an intelligent management system for routine testing and handover of insulating oil, comprising:

[0012] A unique identification code is configured to be attached to the insulating oil container and stores the static identification information of the insulating oil container;

[0013] The intelligent QR code scanning terminal includes a scanning module, a communication module, and a processing module; wherein, the scanning module is configured to read the unique identification code; the communication module is configured to interact with a cloud data platform; and the processing module is configured to execute a preset handover logic operation based on information obtained from the cloud data platform.

[0014] The cloud data platform is configured to maintain the dynamic status information of the insulating oil container associated with the static identification information, and in response to a query request from the smart barcode scanning terminal, return the corresponding dynamic status information to the smart barcode scanning terminal.

[0015] Furthermore, the processing module is configured to perform preset handover logic operations based on information obtained from the cloud data platform, including:

[0016] Verification is performed based on the dynamic status information obtained from the cloud data platform;

[0017] If the verification is successful, a handover confirmation command is generated and sent to the cloud data platform through the communication module to trigger the cloud data platform to update the dynamic status information of the insulating oil container;

[0018] If the verification fails, an alarm message will be generated and output.

[0019] Furthermore, the dynamic status information maintained by the cloud data platform includes the test status information and / or equipment association information of the insulating oil container; wherein, the test status information is used to indicate whether the insulating oil container is in a state that allows handover, and the equipment association information is used to indicate the matching relationship between the insulating oil container and the target power equipment.

[0020] Furthermore, the operation of verifying based on the dynamic status information obtained from the cloud data platform includes:

[0021] Verify whether the test status information indicates that handover is permitted and / or verify whether the equipment association information matches the target power equipment;

[0022] When the test status information indicates that handover is allowed and the equipment association information matches, the verification is deemed to have passed; otherwise, the verification is deemed to have failed.

[0023] Furthermore, the intelligent scanning terminal also includes a human-computer interaction interface module, which is communicatively connected to the processing module;

[0024] The human-computer interaction interface module is configured as follows:

[0025] Display the dynamic status information obtained from the cloud data platform;

[0026] And / or receive confirmation commands from the user;

[0027] And / or output the alarm information.

[0028] Furthermore, the intelligent barcode scanning terminal also includes an identity recognition module and a tag management module; the identity recognition module is configured to receive and record oil sample information of the insulating oil to be sampled, the oil sample information including equipment information and test properties; the tag management module is communicatively connected to the identity recognition module and is configured to generate and print the unique identification code based on the oil sample information, wherein the oil sample information represents information that constitutes at least a part of the static identification information.

[0029] Secondly, the present invention provides an intelligent management method for routine testing and handover of insulating oil, employing the intelligent management system described above, the method comprising the following steps:

[0030] The unique identification code attached to the insulating oil container is read through the scanning module of the intelligent scanning terminal.

[0031] In response to reading the identification code, the smart scanning terminal sends a query request to the cloud data platform;

[0032] In response to the query request, the cloud data platform executes a preset dynamic status information generation and update strategy to generate or update dynamic status information.

[0033] The cloud data platform returns the dynamic status information to the smart scanning terminal;

[0034] Based on the received dynamic status information, the intelligent scanning terminal executes a preset handover logic operation to control the handover process of the insulating oil container.

[0035] Furthermore, the step of executing a preset dynamic state information generation and update strategy to generate or update dynamic state information includes:

[0036] Intelligent diagnostic algorithms based on multi-parameter interlocking feedback are used to generate or update dynamic status information.

[0037] Furthermore, the intelligent diagnostic algorithm based on multi-parameter interlocking feedback, in the step of generating or updating dynamic state information, includes:

[0038] Obtain test result data associated with the insulating oil container, including dissolved gas content, trace water content, and breakdown voltage value;

[0039] Cross-validation analysis was performed on at least two items of the experimental results data;

[0040] Based on the results of the cross-validation analysis, a comprehensive equipment health status diagnosis conclusion is generated.

[0041] Based on the comprehensive diagnostic conclusions, the test status information in the dynamic status information is generated or updated.

[0042] Furthermore, the step of performing cross-validation analysis on at least two items in the experimental result data includes at least one of the following analysis logics:

[0043] The first analysis logic is configured to, when the concentration of any gas component in the dissolved gas content exceeds its preset attention threshold and the relative gas production rate of that gas component exceeds its preset rate threshold, upgrade the single-parameter state judgment result based on the concentration of that gas component from a first preset level to a more severe second preset level; or, when the concentration of the first gas component in the dissolved gas content exceeds its preset attention threshold and the concentration of the second gas component also exceeds its preset attention threshold, upgrade the single-parameter state judgment result based on the concentrations of the two gas components from the first preset level to the second preset level.

[0044] The second analysis logic is configured to upgrade the single-parameter state judgment result based on the breakdown voltage value from the first preset level to the second preset level when the breakdown voltage value is higher than its preset attention threshold but lower than its preset severity threshold, and the micro-moisture content exceeds its preset attention threshold.

[0045] The third analysis logic is configured to strengthen the diagnostic tendency of solid insulation moisture degradation when the equipment is determined to have fault characteristics of low temperature overheating or partial discharge based on the dissolved gas content using the three ratio method or the David triangle method, and the trace moisture content exceeds its preset attention threshold; conversely, when the fault characteristics are present and the trace moisture content is lower than its preset low threshold, the diagnostic tendency of bare metal overheating is strengthened.

[0046] The fourth analysis logic is configured to, when the equipment is determined to have arc discharge fault characteristics based on the dissolved gas content using the three-ratio method or the David's triangle method, and the breakdown voltage value is lower than its preset severity threshold, upgrade the status level corresponding to the fault diagnosis conclusion based on the dissolved gas content from the second preset level to a more severe third preset level.

[0047] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0048] This invention provides an intelligent management system for routine testing and handover of insulating oil. By constructing a collaborative system consisting of a unique identification code, an intelligent barcode scanning terminal, and a cloud data platform, it realizes the digitalization and intelligentization of the insulating oil handover process. This invention fundamentally eliminates the risk of erroneous handover caused by information silos and unclear status. Through barcode scanning, it automatically triggers real-time verification and interaction of the dynamic status of the oil, significantly improving the accuracy and efficiency of the handover operation. At the same time, it establishes a fully traceable digital archive, providing a reliable guarantee for the safe and stable operation of the equipment. Attached Figure Description

[0049] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0050] Figure 1 This is an architecture diagram of an intelligent management system for routine testing and handover of insulating oil, provided in the embodiments of this specification.

[0051] Figure 2 This is one of the flowcharts for an intelligent management method for routine test handover of insulating oil provided in the embodiments of this specification;

[0052] Figure 3 This is the second flowchart of an intelligent management method for routine testing and handover of insulating oil, provided in the embodiments of this specification. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0054] In related technologies, during the operation and maintenance of power systems, the insulating oil inside oil-filled equipment such as transformers and instrument transformers plays a crucial role in insulation, heat dissipation, and arc suppression. To ensure the safe and stable operation of equipment, it is necessary to periodically sample the insulating oil and send it to the laboratory for routine testing. This process involves multiple stages, including on-site sampling, sample handover, laboratory testing, and data management. Currently, the insulating oil handover management method adopted in related technologies mainly relies on traditional paper documents and manual records, combined with basic barcode scanning equipment for identification. Specifically, the relevant technology involves operators sampling the insulating oil on-site and manually filling in the oil sample information (e.g., substation name, equipment number, sampling time, etc.) on a paper label and affixing it to the container, or generating a barcode / QR code containing only this static information. During the handover process, operators use ordinary barcode scanning equipment to read the identification information on the container. However, the function of such barcode scanning devices is limited to decoding and displaying the static content embedded in the identification code, or recording it into the local storage unit. They cannot communicate with the back-end management system (e.g., equipment asset management system, PMS) in real time, nor can they obtain and verify the latest dynamic status of the oil sample in the cloud, such as "whether the oil sample has been tested", "whether the corresponding equipment has any unresolved defects", "whether the oil sample has been designated for the current operation task" and other key information.

[0055] The difficulties and pain points of the aforementioned technologies lie in their inherent creation of information silos. The static information carried by the identification code is severely disconnected from the dynamic status information in the cloud management system, meaning that scanning only identifies the user but fails to verify the status. This directly leads to difficulties for operators in accurately and in real-time determining the compliance and compatibility of the oil's status during handover, easily resulting in erroneous handover operations. For example, incorrectly receiving substandard oil samples or associating oil samples with the wrong electrical equipment. Such errors not only reduce work efficiency but may also pose potential insulation failures and operational safety risks to electrical equipment due to the use of insulating oil in an unknown state.

[0056] In-depth analysis reveals that the root cause of this technical problem lies in the fact that the barcode scanning devices in the relevant technologies are designed as isolated data acquisition units within the system architecture. Their functional boundaries are limited to "reading-display / storage," lacking the ability to collaborate with cloud platforms and execute automated verification logic based on real-time dynamic information. In other words, existing technologies cannot use barcode scanning as the starting point to trigger an intelligent closed-loop process encompassing status query, real-time verification, and business-linked control.

[0057] The inventive concept of this invention lies in: by constructing an intelligent management system that coordinates the work of an intelligent scanning terminal, a cloud data platform, and a unique identification code, the scanning terminal can automatically query and obtain the corresponding dynamic status information from the cloud platform after reading the static identification information, and then execute a preset handover logic operation based on the dynamic status information, thereby solving the safety hazard of mishandling caused by the inability of the scanning device to obtain and verify the dynamic status of the oil in real time.

[0058] like Figure 1 As shown, this embodiment provides an intelligent management system for routine testing and handover of insulating oil, including:

[0059] A unique identification code is configured to be attached to the insulating oil container and stores the static identification information of the insulating oil container.

[0060] In this embodiment, the unique identification code can represent a globally unique and machine-readable identity credential for each insulating oil container. This identification code can be physically affixed to an easily scannable location on the surface of the insulating oil container, such as the side or top of the container. Specifically, the unique identification code can store static identification information bound to the insulating oil container. This static identification information can be the most basic identity attributes of the oil sample, and may include, but is not limited to: oil sample number, name of the source substation, type of specific power equipment (main transformer, instrument transformer), sampling date and time, etc.

[0061] In this embodiment, the unique identification code can be a QR code or a one-dimensional barcode. Alternatively, it can be an RFID tag, which allows for contactless reading and is suitable for complex environments or scenarios where direct alignment is inconvenient. The carrier of the identification code can be an oil-resistant, wear-resistant self-adhesive label, or a permanent mark directly sprayed or engraved on the container.

[0062] The intelligent QR code scanning terminal includes a scanning module, a communication module, and a processing module; wherein, the scanning module is configured to read the unique identification code; the communication module is configured to interact with a cloud data platform; and the processing module is configured to execute a preset handover logic operation based on information obtained from the cloud data platform.

[0063] In this embodiment, the intelligent scanning terminal can be represented as a portable electronic device integrating data acquisition, processing, communication, and interaction functions. Specifically, it can be a direct tool for on-site operators to interact with the entire intelligent management system, responsible for triggering business processes and executing local intelligent decisions.

[0064] The scanning module can be a hardware unit used for optically sensing and parsing the information encoded in the unique identification code. Specifically, it can be a combination of different types of image sensors and decoding chips. For example, it can be a QR code scanning engine with an integrated CMOS image sensor, capable of quickly capturing and parsing QR code images, or it can be a laser scanning head.

[0065] The communication module can be defined as a hardware and software combination that establishes a data transmission link between the smart scanning terminal and a remote cloud data platform. It can support multiple wireless communication protocols. For example, it can be a cellular mobile communication module supporting 4G or 5G networks, ensuring internet access across a wide range of outdoor substation areas. It can also integrate a Wi-Fi module for use in indoor areas with local area network coverage, saving data usage. Furthermore, it may include a Bluetooth module for short-range communication with other peripheral devices.

[0066] The processing module is the terminal's data processing and control center. Its core function is to execute preset logical operations related to the handover process. It can be implemented by a microprocessor, memory, and firmware or application programs stored in the memory. For example, this module can be an embedded microprocessor based on an ARM architecture, running a dedicated Android or Linux operating system. The execution of preset handover logical operations based on information obtained from the cloud data platform can specifically mean that after receiving data returned from the cloud, the processing module can make judgments according to pre-programmed logic. For example, it can compare the returned oil status with preset qualification standards or verify whether the oil matches the power equipment specified in the current work order.

[0067] The cloud data platform is configured to maintain the dynamic status information of the insulating oil container associated with the static identification information, and in response to a query request from the smart barcode scanning terminal, return the corresponding dynamic status information to the smart barcode scanning terminal.

[0068] In this embodiment, the cloud data platform can be a software service system deployed on a remote server cluster.

[0069] The dynamic status information of the insulating oil container associated with the static identification information can be represented by a cloud data platform establishing a data record for each unique identifier in its database and continuously updating the dynamic status information related to the oil container represented by the identifier, which changes over time or with operation. This dynamic status information includes, but is not limited to: the current test status information of the oil sample (e.g., pending test, under test, test passed, test failed), the latest test parameter values ​​(e.g., trace water content, breakdown voltage value), and equipment association information (e.g., which specific transformer this oil sample is planned to be used for backfilling).

[0070] The statement that in response to a query request from the smart barcode scanning terminal, returning the corresponding dynamic status information to the smart barcode scanning terminal can be expressed as follows: when the network interface of the cloud data platform receives a query request initiated by the terminal that includes a specific identifier code, the business logic processing unit (e.g., a microservice written in Java or Python) inside the cloud data platform can query the database, retrieve the latest dynamic status information associated with the identifier code, and return the result data packet to the smart barcode scanning terminal via the network.

[0071] This embodiment provides an intelligent management system for routine testing and handover of insulating oil. By constructing a collaborative system consisting of a unique identification code, an intelligent barcode scanning terminal, and a cloud data platform, it realizes the digitalization and intelligentization of the insulating oil handover process. This embodiment fundamentally eliminates the risk of erroneous handover caused by information silos and unclear status. Through barcode scanning, it automatically triggers real-time verification and interaction of the dynamic status of the oil, significantly improving the accuracy and efficiency of the handover operation. At the same time, it establishes a fully traceable digital archive, providing a reliable guarantee for the safe and stable operation of the equipment.

[0072] In some embodiments, the processing module is configured to perform preset handover logic operations based on information obtained from the cloud data platform, including:

[0073] Verification is performed based on the dynamic status information obtained from the cloud data platform.

[0074] In this embodiment, the verification can be represented as the processing module running a preset judgment logic to compare the acquired dynamic status information with the built-in or cloud-synchronized allowed handover conditions.

[0075] In one possible and specific implementation, the verification may involve determining whether the test status information in the dynamic status information indicates that the test is qualified or that handover is permitted. If the status information indicates that the test is unqualified or that use is prohibited, the verification fails.

[0076] In one possible and specific implementation, the verification may involve determining whether the device association information in the dynamic status information is consistent with the target power device specified in the operation task instruction received by the current scanning terminal. For example, if the operation task requires the oil sample to be handed over to "#1 main transformer", but the scanned oil sample's device association information indicates that it is planned to be used for "#2 main transformer", then the verification will fail to prevent the oil sample from being misused.

[0077] If the verification passes, a handover confirmation command is generated and sent to the cloud data platform via the communication module to trigger the cloud data platform to update the dynamic status information of the insulating oil container.

[0078] In this embodiment, the handover confirmation instruction can be represented as a digital signal or data packet with a preset format generated by the processing module, used to confirm to the cloud data platform that the handover operation has been approved for completion.

[0079] In this embodiment, the handover confirmation instruction can be sent to the network interface specified by the cloud data platform via the communication module (e.g., a 4G / 5G module or a Wi-Fi module). Specifically, after receiving the instruction, the cloud data platform's background service can perform corresponding data update operations, such as updating the status of the insulating oil container in the database from pending handover to completed handover, and recording information such as the handover time and operator, thereby completing the business loop.

[0080] If the verification fails, an alarm message will be generated and output.

[0081] In this embodiment, the alarm information can be represented as a notification signal used to alert operators that there is an anomaly or risk.

[0082] In one possible and specific implementation, an alarm can be triggered by an optical indicator (LED light) on the control terminal emitting light of a specific color (flashing red light).

[0083] In one possible and specific implementation, a continuous or intermittent alarm sound can be emitted via a built-in audio generator (speaker or buzzer) on the terminal. Furthermore, alarm information can also be displayed visually via a graphical user interface on the terminal screen, in the form of text, pop-ups, or icons.

[0084] In some embodiments, the dynamic status information maintained by the cloud data platform includes the test status information and / or equipment association information of the insulating oil container; wherein, the test status information is used to indicate whether the insulating oil container is in a state that allows handover, and the equipment association information is used to indicate the matching relationship between the insulating oil container and the target power equipment.

[0085] In this embodiment, the test status information can be represented as the latest and most crucial judgment on whether the oil in the insulating oil container meets the handover conditions.

[0086] In one possible and specific implementation, the test status information can be a status flag. Specifically, it can include: "Qualified" or "Permitted for Handover," indicating that all key performance indicators of the oil (e.g., breakdown voltage, trace water content, dielectric loss factor) meet the requirements of the specifications and are permitted for use in equipment backfilling. It can also include: "Unqualified" or "Prohibited for Handover," indicating that one or more indicators of the oil exceed the limits and are prohibited from use in equipment operation.

[0087] It may also include "under testing" or "pending judgment". This status indicates that the oil has been sent to the laboratory, the testing process has not yet been completed, the final conclusion has not been reached, and therefore handover is not allowed at this time.

[0088] The cloud-based data platform can receive test result data from the Laboratory Information Management System (LIMS) and automatically update the test status information according to a preset judgment rule library. For example, after receiving a breakdown voltage of 40kV for an oil sample, the platform will compare it with a preset threshold (e.g., 35kV). If the result is better than the threshold, the status of the oil sample may be updated to qualified.

[0089] In this embodiment, the equipment association information can be used to define the mapping relationship between the insulating oil container and the target power equipment in the context of the work task. This ensures that the oil can be accurately delivered to the designated equipment and prevents misuse.

[0090] In one possible and specific implementation, the equipment association information can be one or more data fields. For example, it could be a target equipment code, which uniquely corresponds to the equipment ledger in the Production Management System (PMS), such as "Bayshan_Substation_#1_MainTransformer". It could also be a work order number, which clearly specifies the task content of the operation and the specific equipment to which the planned oil sample should be backfilled. When the on-site operator receives the task, their smart barcode scanning terminal can already load the context of the current work order. After obtaining the equipment association information returned from the cloud, the processing module can compare it with the work order information stored locally on the terminal. If they match, it indicates a match; if they do not match, it indicates a mismatch, thereby triggering the error prevention mechanism.

[0091] The test status information and equipment association information can function independently or work together. For example, the system can be configured to require both "test status information is qualified" and "equipment association information matches the current task" to be met simultaneously for the verification to pass.

[0092] In some embodiments, the operation of verifying based on the dynamic status information obtained from the cloud data platform includes:

[0093] Verify whether the test status information indicates that handover is permitted and / or verify whether the equipment association information matches the target power equipment;

[0094] When the test status information indicates that handover is allowed and the equipment association information matches, the verification is deemed to have passed; otherwise, the verification is deemed to have failed.

[0095] In this embodiment, the target power equipment may be a power transformer, voltage transformer, current transformer, high-voltage bushing, or circuit breaker, etc.

[0096] In this embodiment, the verification operation includes checking the test status information. Specifically, the processing module can parse the data fields in the received dynamic status information and extract the identifier representing the test status. This identifier can exist in the form of an enumeration value, such as "transfer allowed" or "transfer prohibited". The processing module can have preset rules that compare the obtained status identifier with the transfer-allowed conditions defined in the rules. For example, if the test status information is "qualified" or "test completed", it can be considered as indicating that transfer is allowed.

[0097] If the test result is unqualified, or if the test has failed, it can be considered that handover is not permitted.

[0098] In this embodiment, the verification operation may further include matching and verifying the device association information. The processing module can parse the target power equipment identifier associated with the insulating oil container from the dynamic status information, for example, the device code: BaySub_#1_MainTransformer. Simultaneously, the processing module can obtain the target device identifier specified by the task from the locally stored current operation task context. Then, the processing module can execute matching logic, which may involve comparing whether the two device identifiers are completely identical. A successful match indicates that the oil is intended for use with the device in the current operation.

[0099] In this embodiment, the processing module can only determine that the verification has passed if and only if both of the above conditions are met simultaneously (the test status information indicates that the handover is allowed and the equipment association information is successfully matched). Conversely, if either of the above conditions is not met, for example, if the test status information indicates that the test is unqualified or the equipment association information shows that the oil is planned to be used for another piece of equipment (which does not match the current task), or if both of these situations occur simultaneously, the processing module will determine that the verification has failed.

[0100] In some embodiments, the intelligent scanning terminal further includes a human-computer interaction interface module, which is communicatively connected to the processing module;

[0101] The human-computer interaction interface module is configured as follows:

[0102] Displays the dynamic status information obtained from the cloud data platform.

[0103] In this embodiment, the displayed dynamic status information may specifically be:

[0104] Text information, for example, can directly display the test status.

[0105] Data lists can present more detailed experimental data in a structured format.

[0106] Status icons can use graphical elements to visually indicate the status. For example, a green checkmark indicates that the handover is allowed, and a red cross indicates that the handover is prohibited.

[0107] Color coding can use different background or font colors to convey status; for example, a green background indicates safety, yellow indicates caution, and red indicates warning.

[0108] And / or receive confirmation commands from the user.

[0109] In this embodiment, after reviewing the displayed information, the operator can proactively issue instructions to the system to perform the next operation.

[0110] In one possible and specific implementation, a virtual button can be rendered on the display screen; for example, it could be a touch area labeled "Confirm Handover." When a user's finger touches this area, the touch sensor detects the operation, generates an electrical signal, which is encoded as a confirmation command and sent to the processing module.

[0111] In one possible and specific implementation, one or more physical buttons can be provided on the terminal casing. When the user presses a designated confirmation button, the electrical signal generated by the button is recognized by the processing module as a confirmation command.

[0112] And / or output the alarm information.

[0113] In this embodiment, the alarm information can be output via visual alerts. For example, the smart scanning terminal can be equipped with an independent light-emitting diode that emits a preset pattern of flashing red light or controls the entire screen to flash at high brightness and high frequency, effectively providing a warning even when the ambient light is strong or the user is not looking directly at the screen.

[0114] In this embodiment, the alarm information can also be output via auditory or tactile alarms.

[0115] In some embodiments, the intelligent barcode scanning terminal further includes an identity recognition module and a tag management module; the identity recognition module is configured to receive and record oil sample information of the insulating oil to be sampled, the oil sample information including equipment information and test properties.

[0116] In this embodiment, the identity recognition module is used to receive various oil sample information related to the insulating oil to be sampled, input by the operator, and to electronically record and temporarily store the above information.

[0117] In one possible and specific implementation, a standardized information input interface can be presented through the touch screen of the smart scanning terminal itself, through which operators can manually input or select various items from the drop-down menu.

[0118] In one possible and specific implementation, the sampling task order pre-issued by other business systems (e.g., production management system PMS) can be received through the external data interface of the smart barcode scanning terminal, thereby automatically filling in part of the oil sample information.

[0119] In this embodiment, the oil sample information may include equipment information for uniquely identifying the sampling object and test properties describing the test type. Specifically, the equipment information may include: substation name, voltage level, specific equipment number (e.g., "#1 main transformer"), or phase information, etc. The test properties can be used to distinguish different testing requirements; for example, it may be a predefined test type code such as routine test, diagnostic test, new oil acceptance, or fault diagnosis.

[0120] The label management module is communicatively connected to the identity recognition module and is configured to generate and print the unique identification code based on the oil sample information, wherein the oil sample information represents information that constitutes at least a part of the static identification information.

[0121] In this embodiment, the label management module is used to automatically generate a visual, machine-readable unique identification code based on the oil sample information recorded by the identification module, and drive the printing device to physically print it out. Specifically, the label management module can call its internal encoding generation algorithm. This algorithm can take structured oil sample information as input. More specifically, firstly, it can combine various data fields into a string according to a predetermined order and separators. Then, it can perform verification and calculation on the string to improve data integrity. Finally, it can call a QR code generation library to convert the string into a QR code image data that conforms to the QR Code standard. The printing operation can be completed by a portable label printer connected to a smart scanning terminal. The printer can be a model using thermal printing technology or thermal transfer technology, which can print the generated QR code image and optional plaintext information (e.g., station name, equipment name) on self-adhesive label paper of preset specifications according to instructions. In this process, all or key parts of the oil sample information collected by the identification module are encoded into the identification code, thus constituting the core content of the static identification information at the information level.

[0122] In this embodiment, the printer can also be directly integrated into the smart barcode scanning terminal. Specifically, the printing function described above can also be implemented through a printing module, which can be directly integrated inside the device housing of the smart barcode scanning terminal. The printing module can establish electrical connections and data communication with the processing module and label management function unit via an internal system bus or a dedicated parallel / serial interface. Under the unified scheduling of the processing module, the identification code image data generated by the label management function unit can be transmitted to the drive circuit of the printing module. More specifically, a micro thermal printing engine or a micro thermal transfer printing engine can be selected. The thermal printing engine completes printing by controlling the print head to heat and develop the printing area of ​​the thermal paper. The thermal transfer printing engine, on the other hand, transfers the toner on the ribbon to the label paper by heating. The printing module can include a paper tray for loading the label paper roll, a paper feeding mechanism driven by a stepper motor, and the aforementioned print head. When printing is required, the operation command can be issued by the processing module, the paper feeding mechanism accurately delivers the label paper to the printing position, and the print head forms the corresponding QR code graphic and necessary plaintext information on the label paper based on the received image data. After printing is complete, the label paper is separated by a cutting mechanism or manually to generate the unique identification code that can be pasted.

[0123] It is understood that the static identification information stored in the unique identification code (e.g., QR code) directly originates from or is entirely composed of the oil sample information. For example, the data string included in the encoded QR code is the result of formatting (e.g., JSON or XML serialization) the oil sample information such as equipment information and test properties. That is, by scanning the static identification information parsed from the identification code, the initially entered oil sample information can be directly reconstructed.

[0124] In one possible and specific implementation, the static identification information is directly the complete oil sample information after serialization (e.g., conversion to a JSON string, XML format, or a custom binary format). In this case, scanning and decoding the identification code allows for the reconstruction of all original oil sample information, such as equipment information and test characteristics.

[0125] like Figure 2 and Figure 3 As shown, this embodiment provides an intelligent management method for routine testing and handover of insulating oil, employing the intelligent management system described above. The method includes the following steps:

[0126] Step S10: Read the unique identification code attached to the insulating oil container through the scanning module of the intelligent scanning terminal.

[0127] In this embodiment, the operator can hold a smart barcode scanning terminal and align and focus its scanning module (e.g., a camera or laser scanner) on the unique identification code (e.g., a QR code) affixed to the insulating oil container. The optical sensor of the scanning module can capture the image or reflected light signal of the identification code. Then, the decoding chip or decoding software running in the processing module inside the smart barcode scanning terminal analyzes the captured signal, converting the graphical identification code into a digital string or data packet that can be used for subsequent processing. This data packet is the static identification information extracted from the identification code. If the reading fails, the smart barcode scanning terminal can display an error message through the human-machine interface, requesting the operator to try again.

[0128] Step S12: In response to reading the identification code, the smart scanning terminal sends a query request to the cloud data platform.

[0129] In this embodiment, after successfully completing the decoding in step S10, the processing module of the smart barcode scanning terminal can generate a network request. Specifically, the processing module can use the decoded static identification information as core parameters and encapsulate it into a query request data packet conforming to a predetermined communication protocol (e.g., HTTP / HTTPS protocol). This data packet can be sent via the communication module of the smart barcode scanning terminal (e.g., 4G / 5G module or Wi-Fi module) to the network address (API interface) specified by the cloud data platform through a wireless network.

[0130] Step S14: In response to the query request, the cloud data platform executes a preset dynamic status information generation and update strategy to generate or update dynamic status information.

[0131] In this embodiment, after receiving the query request from step S12, the cloud data platform can trigger the background business logic processing unit to execute a preset operation. Specifically, firstly, the cloud data platform can parse static identification information from the request data packet and use it as a keyword to query its background database to retrieve the latest record associated with the insulating oil container. The execution of the preset dynamic status information generation and update strategy may specifically include: directly returning the latest status currently stored in the database. The execution of the preset dynamic status information generation and update strategy may also specifically include: before returning the information, the cloud data platform can first call an intelligent diagnostic algorithm (e.g., a multi-parameter interlocking feedback algorithm) to recalculate and update the health status level of the oil based on the latest test result data, and then use the updated status information as the return result of this query.

[0132] Step S16: The cloud data platform returns the dynamic status information to the smart scanning terminal.

[0133] In this embodiment, the cloud data platform can encapsulate the dynamic status information generated or retrieved in step S14 into a response data packet, and then send it back to the smart scanning terminal that initiated the request via the network.

[0134] Step S18: The intelligent scanning terminal executes a preset handover logic operation based on the received dynamic status information to control the handover process of the insulating oil container.

[0135] In this embodiment, the processing module of the intelligent barcode scanning terminal can parse the dynamic status information received in step S16 and run preset verification logic. Specifically, it can verify whether the test status allows handover, and whether the device association information matches, etc. Based on the verification results, the processing module can execute different branches to control the handover process. Specifically, if the verification passes, a handover confirmation command can be generated and sent to the cloud to complete the digital handover process. If the verification fails, alarm information (e.g., sound, light, vibration) can be generated and output to forcibly interrupt the physical handover operation and wait for personnel intervention.

[0136] In some implementations, the step of executing a preset dynamic state information generation and update strategy to generate or update dynamic state information includes:

[0137] Step S142: Use an intelligent diagnostic algorithm based on multi-parameter interlocking feedback to generate or update dynamic status information.

[0138] In this embodiment, step S14 executes a preset dynamic status information generation and update strategy, the purpose of which is to execute an intelligent diagnostic algorithm based on multi-parameter interlocking feedback. This algorithm does not perform isolated threshold judgments on individual test parameters of the insulating oil, but rather analyzes the physical correlation and mutual influence between multiple key parameters, performs comprehensive cross-validation and weight correction, thereby deriving a more accurate and reliable equipment health status diagnosis conclusion, and generating or updating the core status data in the dynamic status information accordingly.

[0139] In some implementations, the intelligent diagnostic algorithm based on multi-parameter interlocking feedback, in the step of generating or updating dynamic state information, includes:

[0140] Step S1422: Obtain test result data associated with the insulating oil container, the test result data including dissolved gas content, trace water content and breakdown voltage value.

[0141] In this embodiment, the cloud data platform can retrieve and call upon its associated database based on the static identification information (e.g., a unique oil sample number) carried in the currently processed query request. The test result data can be represented as a quantitative indicator obtained after testing the oil sample in the insulating oil container using standard chemical analysis methods. This data can be entered by the test personnel or automatically uploaded to the cloud data platform through the experimental equipment interface, and stored in association with the identity information of the insulating oil container.

[0142] Specifically, the dissolved gas content can be expressed as the volume concentration values ​​of various characteristic gases dissolved in the insulating oil, as measured by gas chromatography. These may include hydrogen, methane, ethane, ethylene, acetylene, etc.

[0143] The trace water content can be expressed as the mass concentration of water in insulating oil measured using standard methods such as coulometric method or Karl Fischer method.

[0144] The breakdown voltage value can be expressed as the voltage value at which an insulating oil sample is electrically broken down under standard test electrodes and a specified voltage ramp rate.

[0145] Step S1424: Perform cross-validation analysis on at least two items in the experimental result data.

[0146] In this implementation, the algorithm does not judge each parameter in isolation, but establishes logical relationships between parameters. It uses the status of one parameter to verify or correct the preliminary diagnostic conclusions drawn from another parameter in order to discover potential, complex failure modes.

[0147] In this embodiment, the cross-validation analysis of at least two items in the test results data can specifically include cross-validation of gas analysis and trace moisture content. More specifically, when the analysis results of dissolved gas content (e.g., determined by the three-ratio method) indicate that the equipment has fault characteristics such as low-temperature overheating or partial discharge, if the measured value of trace moisture content also significantly exceeds its preset attention threshold, the analysis logic can determine that: the increase in moisture may have aggravated the thermal degradation process of the solid insulation material (e.g., insulating paperboard) or reflected moisture intrusion caused by poor sealing.

[0148] Understandably, the aforementioned correlation can strengthen the reliability of the diagnostic tendency for moisture-induced thermal degradation of solid insulation. Conversely, if gas analysis indicates abnormalities but the moisture content is extremely low, the analytical logic may be more inclined to diagnose an overheating fault involving bare metal.

[0149] In this embodiment, the cross-validation analysis of at least two items in the test results data can specifically include performing cross-validation of breakdown voltage and trace moisture content. More specifically, when the breakdown voltage value is slightly higher than its preset attention threshold but not reaching the severity threshold, if the trace moisture content is also severely exceeded, the analysis logic can determine that although the absolute value of the breakdown voltage has not deteriorated drastically, the presence of moisture poses a substantial and urgent threat to the insulation strength of the oil. At this time, the analysis process can dynamically increase the weight of the breakdown voltage parameter in the comprehensive diagnosis, and may, based on this strong correlation, upgrade the equipment status judgment from a single-parameter attention level to a severity level.

[0150] In this embodiment, the cross-validation analysis of at least two items in the test results data can specifically include mutual corroboration between gas analysis and breakdown voltage. More specifically, when dissolved gas analysis indicates the presence of a high-energy discharge fault such as arc discharge, if the breakdown voltage also drops significantly and falls below its severity threshold, the analysis logic can confirm that the internal insulation medium of the equipment has been severely damaged due to the discharge process. In this case, the degradation of the breakdown voltage provides strong corroboration for the gas analysis conclusion, which can lead to the diagnostic conclusion being upgraded from severe to the highest critical level.

[0151] Step S1426: Based on the results of the cross-validation analysis, generate a comprehensive equipment health status diagnosis conclusion.

[0152] In this embodiment, the diagnostic conclusion of the device health status may include:

[0153] Status levels can be classification markers used to quickly characterize the health status of equipment. Multi-level classification systems can be used, such as Normal, Caution, Abnormal, Severe, and Critical.

[0154] The diagnostic criteria can be a textual description that concisely explains the origin of the condition level and the potential fault type it reflects. For example, the output could be: "Diagnosed as moderate overheating with risk of insulation dampness" or "Diagnosed as high-energy discharge has caused a severe decrease in insulation strength."

[0155] Step S1428: Based on the comprehensive diagnostic conclusion, generate or update the test status information in the dynamic status information.

[0156] In this embodiment, generating or updating the test status information in the dynamic status information can be represented as converting the comprehensive diagnostic conclusion obtained in step S1426 into a status identifier that the intelligent management system can directly understand and use for process control.

[0157] Specifically, the cloud data platform can map the status level in the comprehensive diagnostic conclusion to an operable status identifier defined in the business logic.

[0158] When the comprehensive diagnostic conclusion is normal or warning, the test status information can be updated to allow handover. When the comprehensive diagnostic conclusion is severe, the test status information can be updated to prohibit handover - severe status, requiring retesting. When the comprehensive diagnostic conclusion is critical, the test status information can be updated to prohibit handover - critical status, requiring emergency handling. This newly generated or updated test status information can be written into the dynamic status record of the insulating oil container in the cloud database and used as the content returned to the intelligent barcode scanning terminal in step S16, directly guiding subsequent handover logic operations.

[0159] In some embodiments, the step of performing cross-validation analysis on at least two items of the experimental result data includes at least one of the following analysis logics:

[0160] The first analysis logic is configured to, when the concentration of any gas component in the dissolved gas content exceeds its preset attention threshold and the relative gas production rate of that gas component exceeds its preset rate threshold, upgrade the single-parameter state judgment result based on the concentration of that gas component from a first preset level to a more severe second preset level; or, when the concentration of the first gas component in the dissolved gas content exceeds its preset attention threshold and the concentration of the second gas component also exceeds its preset attention threshold, upgrade the single-parameter state judgment result based on the concentrations of the two gas components from the first preset level to the second preset level.

[0161] In this embodiment, the preset attention threshold can be a concentration critical value set individually for each gas component. This threshold can be a value preset and stored in the system based on a large amount of historical operating data, industry standards, and equipment manufacturer recommendations. For example, for acetylene, the attention threshold can be set to 5 μL / L, and for hydrogen, it can be set to 150 μL / L. When the measured concentration of a gas component exceeds its corresponding attention threshold, the system can initially mark that the parameter is abnormal.

[0162] The relative gas production rate can be a dynamic indicator characterizing the development trend of a fault, defined as the percentage increase in the average concentration of a certain gas component relative to the oil weight of the equipment over a certain time interval. The preset rate threshold can be a critical value set for this relative gas production rate to judge the speed of fault development; for example, it can be set to 10% per month. If the gas production rate exceeds this threshold, it indicates that the fault is developing rapidly.

[0163] The first preset level and the second preset level can be two categories used to describe the severity of the equipment's health status. The first preset level corresponds to a lower severity level of attention. This level indicates that the parameters have exceeded the normal range and require attention, but may not necessarily require immediate emergency measures. The second preset level corresponds to a higher severity level of severe status. This level indicates that the equipment has a clear fault, which may be developing, and requires diagnosis and repair as soon as possible.

[0164] The second analysis logic is configured to upgrade the single-parameter state judgment result based on the breakdown voltage value from the first preset level to the second preset level when the breakdown voltage value is higher than its preset attention threshold but lower than its preset severity threshold, and the micro-moisture content exceeds its preset attention threshold.

[0165] In this embodiment, the breakdown voltage value can be represented as a critical value for judging different levels of insulation performance degradation of the insulating oil. For example, for an oil of a certain voltage level, the attention threshold can be set to 40 kV, indicating that the insulation performance has begun to decline, and the severe threshold can be set to 30 kV, indicating that the insulation performance has severely deteriorated and the oil is unqualified. When the breakdown voltage value is between 40 kV and 30 kV, the single parameter judgment can be only for attention.

[0166] The third analysis logic is configured to strengthen the diagnostic tendency of solid insulation moisture degradation when the equipment is determined to have fault characteristics of low temperature overheating or partial discharge based on the dissolved gas content using the three ratio method or the David triangle method, and the trace moisture content exceeds its preset attention threshold; conversely, when the fault characteristics are present and the trace moisture content is lower than its preset low threshold, the diagnostic tendency of bare metal overheating is strengthened.

[0167] In this embodiment, the three-ratio method or David's triangle method can be represented as a method recommended by the International Electrotechnical Commission (IEC) standards and national standards, which uses the ratio relationship of dissolved gas component concentrations to diagnose the fault type of oil-filled electrical equipment.

[0168] In this embodiment, the preset low threshold can be expressed as an extremely low value for trace moisture content, indicating that the oil is very dry. For example, the low threshold can be set to 10 ppm. When the trace moisture content is below this value, the insulation system can be considered not to be damp.

[0169] The fourth analysis logic is configured to, when the equipment is determined to have arc discharge fault characteristics based on the dissolved gas content using the three-ratio method or the David's triangle method, and the breakdown voltage value is lower than its preset severity threshold, upgrade the status level corresponding to the fault diagnosis conclusion based on the dissolved gas content from the second preset level to a more severe third preset level.

[0170] In this embodiment, the third preset level can be represented as a more severe state level than the second preset level. Specifically, if the second preset level refers to severe, then the more severe third preset level can refer to a critical level, indicating that the equipment is at risk of immediate failure and needs to be dealt with as soon as possible.

[0171] In one specific implementation plan, an intelligent transfer device for insulating oil is provided. Its core lies in constructing a closed-loop management system consisting of an intelligent terminal, a cloud platform, and a coding system. Its working principle and connection relationships are as follows:

[0172] System Overall Architecture

[0173] The device system includes: a smart scanning terminal, a cloud data management platform, and a unique identification code (QR code label).

[0174] Intelligent scanning terminal: It has a built-in scanning module (such as a QR code / barcode scanner), communication module, human-computer interaction interface and data management module.

[0175] Cloud-based data management platform: Used to receive, store, and process data uploaded by barcode scanning terminals, and to interact with existing inventory management systems (PMS).

[0176] Unique Identification Code (QR Code Label): Affixed to a designated location on the insulating oil container, the code includes the station name, equipment name, sampling date, etc.

[0177] Intelligent handover process

[0178] Automatic information collection: Before sampling, the operator uses a mobile terminal to confirm the information of the insulating oil to be sampled and prints an identification code with a QR code label; after sampling, the intelligent scanning terminal scans the identification code on the insulating oil container. The terminal automatically parses the information within the code and displays it on the interactive interface.

[0179] Real-time status confirmation and updates: The terminal obtains the latest status (e.g., chromatographic or simplified) of the oil from the cloud platform via a wireless network. Operators can confirm the handover operation (e.g., "Confirm") on the terminal, which triggers the cloud platform to update the oil status in real time.

[0180] Anti-mishandling mechanism: If an oil product that does not match the equipment on the PMS is detected, the terminal will issue an audible and visual alarm and display a warning message on the interface, effectively preventing accidental handover.

[0181] Seamless data flow: Handover records (time, location, operator, oil information) are automatically uploaded to the cloud platform and synchronized to relevant management systems to achieve data closure.

[0182] Core component relationships

[0183] The cloud platform acts as the data hub, communicating bidirectionally with the PMS.

[0184] The identification code is the physical key that triggers the entire smart handover process.

[0185] Dissolved gas-micro water-pressure withstand interlocking feedback algorithm

[0186] By comprehensively analyzing key test parameters of insulating oil (dissolved gas, trace water content, breakdown voltage), we can achieve more accurate and reliable diagnosis and early warning of equipment status.

[0187] Data input: Receive three core parameters from the experimental results: dissolved gas content (e.g., ... , , , , , , ), moisture content, and breakdown voltage.

[0188] 1) Definition of device status threshold

[0189] The equipment status thresholds are defined in a tiered manner for several key parameters of the insulating oil. The thresholds for each level differ according to the equipment voltage level (e.g., 110kV and 220kV), as detailed below:

[0190] (1) Hydrogen

[0191] Normal: Hydrogen content is between 0 μL / L and 100 μL / L.

[0192] Note: The hydrogen content is between 100 μL / L and 150 μL / L.

[0193] Generally, the hydrogen content is between 150 μL / L and 300 μL / L.

[0194] Serious: Hydrogen content greater than or equal to 300 microliters per liter.

[0195] (2) Acetylene

[0196] For 110kV equipment:

[0197] Normal: Acetylene content is between 0 μL / L and 0.1 μL / L.

[0198] Note: Acetylene content ranges from 0.1 μL / L to 2 μL / L.

[0199] Generally: acetylene content ranges from 2 μL / L to 5 μL / L.

[0200] Serious: Acetylene content greater than or equal to 5 microliters per liter.

[0201] For 220kV equipment:

[0202] Normal: Acetylene content is between 0 μL / L and 0.1 μL / L.

[0203] Note: Acetylene content ranges from 0.1 μL / L to 1 μL / L.

[0204] Generally: acetylene content ranges from 1 μL / L to 2 μL / L.

[0205] Serious: Acetylene content greater than or equal to 2 μL / L.

[0206] (3) Total hydrocarbons

[0207] Normal: Total hydrocarbon content ranges from 0 μL / L to 60 μL / L.

[0208] Note: Total hydrocarbon content ranges from 60 μL / L to 100 μL / L.

[0209] Generally: Total hydrocarbon content is between 100 μL / L and 150 μL / L.

[0210] Serious: Total hydrocarbon content is greater than or equal to 150 μL / L.

[0211] (4) Relative gas production rate

[0212] Note: The relative gas production rate is between 0% and 10%.

[0213] Serious: Relative gas production rate is greater than or equal to 10%.

[0214] (5) Withstand voltage (breakdown voltage)

[0215] Normal: Breakdown voltage is greater than or equal to 35 kV.

[0216] Generally, the breakdown voltage is between 30 kV and 35 kV.

[0217] Severe: Breakdown voltage is below 30 kV.

[0218] (6) Moisture content

[0219] For 110kV equipment:

[0220] Normal: The trace moisture content is between 0 mg / kg and 30 mg / kg.

[0221] Note: The trace moisture content is between 30 mg / kg and 35 mg / kg.

[0222] Serious: Trace moisture content greater than or equal to 35 mg / kg.

[0223] For 220kV equipment:

[0224] Normal: The trace moisture content is between 0 mg / kg and 20 mg / kg.

[0225] Note: The trace moisture content is between 20 mg / kg and 25 mg / kg.

[0226] Serious: Trace moisture content greater than or equal to 25 mg / kg.

[0227] In addition to single-parameter threshold judgment, the system also defines a state escalation logic based on multi-parameter interlocking analysis. This logic stipulates that when multiple parameters simultaneously become abnormal, the overall state level of the equipment will be increased based on the highest state level (Xmax) of each individual parameter.

[0228] Characteristic gas + characteristic gas: When two different characteristic gas parameters are abnormal at the same time, the overall status level is increased by one level (Xmax+1).

[0229] Characteristic gas + relative gas production rate: When a certain characteristic gas is abnormal and its relative gas production rate is also abnormal, the overall status level is increased by one level (Xmax+1).

[0230] Characteristic gas + withstand pressure: When both the characteristic gas and withstand pressure values ​​are abnormal, the overall status level is raised by one level (Xmax+1). In particular, when the equipment status has already reached the severe level due to a single parameter, the addition of any other abnormal parameter can further escalate the status to a critical state.

[0231] Characteristic gas + trace moisture: When the characteristic gas is abnormal and the trace moisture content is also abnormal, the overall status level is increased by one level (Xmax+1).

[0232] Characteristic gas + pressure resistance + trace moisture: When the three parameters of characteristic gas, pressure resistance and trace moisture are abnormal at the same time, the overall status level is increased by two levels (Xmax+2).

[0233] Pressure resistance + slight moisture content: When both the pressure resistance value and the slight moisture content are abnormal, the overall status level is increased by one level (Xmax+1).

[0234] Interlocking analysis logic:

[0235] Preliminary diagnosis (based on a single parameter): First, compare the measured value of each parameter with the set attention threshold and warning threshold to preliminarily determine the equipment status (normal, warning, general, serious, critical). Compare and analyze the equipment with main transformers, bushings, or CT scanners of the same manufacturer and model within the region.

[0236] Cross-validation and weight adjustment:

[0237] 1. Correction of gas production rate and gas analysis of different components. When the dissolved gas analysis results show that a certain component exceeds the warning value and the relative gas production rate exceeds the warning value; or when the dissolved gas analysis results show that a certain component exceeds the warning value and another component exceeds the warning value, a higher-level "critical" state is triggered in conjunction with the previous "normal" state.

[0238] 2. Correction of withstand voltage by trace moisture. When the breakdown voltage is slightly higher than the attention threshold but not the critical threshold, if the moisture content is also significantly exceeded, the algorithm will determine that the moisture has posed a substantial threat to the insulation strength, thereby increasing the weight of the breakdown voltage and triggering a higher level of "critical" state, rather than a single "attention" state.

[0239] 3. Correction of gas analysis by trace moisture content. If the three-ratio method or David's triangle method indicates the presence of low-temperature overheating or partial discharge characteristics, and the trace moisture content increases simultaneously, the algorithm will strengthen the credibility of the diagnosis of "solid insulation deterioration due to moisture". Conversely, if the gas is abnormal but the trace moisture content is extremely low, it may tend to diagnose "bare metal overheating".

[0240] 4. Supporting the analysis of gas by withstand voltage. When the dissolved gas ratio method or the David's triangle method diagnoses serious faults such as arc discharge in the equipment, if the breakdown voltage drops significantly at the same time, the algorithm will confirm that the internal insulation has been severely damaged, upgrade the diagnosis from "serious" to "critical", and automatically adjust the sampling period to the "critical state" period (e.g., 1 week).

[0241] Output and feedback:

[0242] Generate a comprehensive diagnostic report: The algorithm outputs a comprehensive equipment health status level (e.g., Normal, Caution, General, Severe, Critical) and attaches detailed diagnostic evidence, such as "Diagnosis: Medium-temperature overheating with insulation moisture risk".

[0243] Triggering dynamic early warning: Based on the interlocking diagnosis results, the system automatically executes the periodic early warning strategy described in section 2.5 and dynamically adjusts the time of the next sampling test.

[0244] Feedback to the terminal: Diagnostic conclusions and early warning information are synchronized in real time to the smart barcode scanning terminal and PMS system through the cloud platform to guide on-site operation and maintenance decisions.

[0245] 2.5-Period Early Warning Algorithm

[0246] Equipment sampling cycle

[0247] Routine insulation oil tests on different types of power equipment (including main transformers, instrument transformers, GIS, and bushings) at different voltage levels (110kV and 220kV) can have different reference cycles. For example, the cycle for 110kV main transformers is 1 year, for 220kV main transformers it is 6 months, for instrument transformers and GIS it is 3 years, while for bushings it is sampled every time the equipment is shut down. This reference cycle table serves as the basis for the system to determine the sampling timing and provides an initial benchmark for the cloud data platform to execute intelligent diagnosis and dynamically adjust the sampling strategy.

[0248] The above is the normal sampling cycle. When the sampling cycle is one month in advance, a cycle warning will be automatically issued.

[0249] The diagnostic results of the dissolved gas-micro water-pressure-resistant interlocking feedback algorithm are the core basis for periodic early warning.

[0250] When the device status is determined to be "normal" by the algorithm, a warning is issued according to the normal cycle.

[0251] When a case is deemed "serious," the sampling period is shortened to one month.

[0252] When a situation is deemed "critical," the sampling period is shortened to one week.

[0253] Early warning mechanism: The system will automatically issue a periodic warning one month (for normal periods) or one week (for shortened periods) before the dynamically adjusted sampling period.

[0254] This implementation method first improves efficiency and accuracy: by automatically collecting information through barcode scanning, the handover time is reduced from 10-15 minutes in the traditional method to 1-2 minutes, with an information accuracy rate approaching 100%, avoiding disputes and rework caused by manual errors. Secondly, it achieves real-time status monitoring and error prevention: the oil status is updated in real time in the cloud and can be queried at the terminal. By setting status verification logic, the risk of misusing substandard oil or repeated handovers is fundamentally eliminated, ensuring equipment safety. Finally, it establishes a full-process traceability system: all handover operations are automatically recorded and permanently stored in the cloud, forming a complete digital archive. In the event of a quality problem, the flow of all oil products in the same batch and the relevant responsible persons can be quickly and accurately traced, improving the level of quality management. Furthermore, by introducing a dissolved gas-micro water-pressure resistance interlock feedback algorithm, this implementation method achieves a leap from "single-parameter threshold alarm" to "multi-parameter intelligent correlation diagnosis". This algorithm effectively overcomes the limitations of single-index diagnosis, significantly improves the diagnostic accuracy and early warning capability for latent faults and complex defects in oil-filled equipment, provides more scientific and reliable decision support for condition-based maintenance, and greatly reduces the risk of serious equipment accidents.

[0255] This implementation provides an integrated process of "scanning code - status verification - data upload". It not only uses scanning code as a means of reading information, but also as a core event to trigger status verification, update data in real time, and synchronize to the management system, thus constructing a complete business closed loop.

[0256] This implementation provides an intelligent diagnostic algorithm based on multi-parameter interlocking feedback. It performs linked analysis of three key indicators: dissolved gas analysis, trace moisture content, and breakdown voltage of insulating oil. Through cross-validation and weight correction, it generates more accurate equipment health status diagnostic results and dynamically adjusts monitoring strategies accordingly. This algorithm is the core of enhancing device intelligence and can be widely applied in the field of power equipment condition monitoring and fault prediction.

[0257] Specific implementation case: Insulating oil testing and handover

[0258] An insulating oil handover test was conducted on the main transformer of a 220kV substation. After the intelligent scanning terminal scanned the container's QR code, the cloud platform received the test data: trace moisture content 45ppm (severe threshold is 35ppm), breakdown voltage 32kV (general threshold is 35kV, severe threshold is 30kV), dissolved gas analysis showed C2H2 content 8μL / L (severe threshold is 5μL / L), and the three-ratio code was "102" (medium-temperature overheating).

[0259] Single parameter analysis: Severe moisture content, moderate pressure resistance, and gas quality (overheating at medium temperature).

[0260] Analysis of interlocking feedback algorithm:

[0261] The algorithm initiates the micro-moisture-gas correction logic: high micro-moisture content strengthens the diagnostic tendency that "medium-temperature overheating" may be related to the moisture aging of insulating paperboard.

[0262] The algorithm initiates withstand voltage-gas analysis to corroborate the logic: the breakdown voltage is close to the critical threshold, and combined with the overheating fault and insulation dampness, it indicates that the internal insulation of the transformer has undergone substantial deterioration.

[0263] Output result: The algorithm determines the equipment status as "critical" and the diagnosis conclusion is "there is a medium-temperature overheating fault inside the transformer, and the solid insulation is damp, the insulation strength is reduced, and the risk level is high".

[0264] According to embodiments of the present invention, an electronic device is provided. The electronic device in this embodiment may include one or more of the following components: a processor, a network interface, memory, non-volatile memory, and one or more application programs. The one or more application programs may be stored in the non-volatile memory and configured to be executed by one or more processors. The one or more programs are configured to perform the methods described in the foregoing method embodiments. The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent management system for routine testing and handover of insulating oil, characterized in that, include: A unique identification code is configured to be attached to the insulating oil container and stores the static identification information of the insulating oil container; The intelligent QR code scanning terminal includes a scanning module, a communication module, and a processing module; wherein, the scanning module is configured to read the unique identification code; the communication module is configured to interact with a cloud data platform; and the processing module is configured to execute a preset handover logic operation based on information obtained from the cloud data platform. The cloud data platform is configured to maintain the dynamic status information of the insulating oil container associated with the static identification information, and in response to a query request from the smart barcode scanning terminal, return the corresponding dynamic status information to the smart barcode scanning terminal.

2. The intelligent management system according to claim 1, characterized in that, The processing module is configured to perform preset handover logic operations based on information obtained from the cloud data platform, including: Verification is performed based on the dynamic status information obtained from the cloud data platform; If the verification is successful, a handover confirmation command is generated and sent to the cloud data platform through the communication module to trigger the cloud data platform to update the dynamic status information of the insulating oil container; If the verification fails, an alarm message will be generated and output.

3. The intelligent management system according to claim 1 or 2, characterized in that, The dynamic status information maintained by the cloud data platform includes the test status information and / or equipment association information of the insulating oil container; wherein, the test status information is used to indicate whether the insulating oil container is in a state that allows handover, and the equipment association information is used to indicate the matching relationship between the insulating oil container and the target power equipment.

4. The intelligent management system according to claim 3, characterized in that, The verification operation based on the dynamic status information obtained from the cloud data platform includes: Verify whether the test status information indicates that handover is permitted and / or verify whether the equipment association information matches the target power equipment; When the test status information indicates that handover is allowed and the equipment association information matches, the verification is deemed to have passed; otherwise, the verification is deemed to have failed.

5. The intelligent management system according to claim 1, characterized in that, The intelligent scanning terminal also includes a human-computer interaction interface module, which is communicatively connected to the processing module. The human-computer interaction interface module is configured as follows: Display the dynamic status information obtained from the cloud data platform; And / or receive confirmation commands from the user; And / or output the alarm information.

6. The intelligent management system according to any one of claims 1-5, characterized in that, The intelligent scanning terminal also includes an identity recognition module and a label management module; The identification module is configured to receive and record the oil sample information of the insulating oil to be sampled, the oil sample information including equipment information and test properties; The label management module is communicatively connected to the identity recognition module and is configured to generate and print the unique identification code based on the oil sample information, wherein the oil sample information represents information that constitutes at least a part of the static identification information.

7. An intelligent management method for routine testing and handover of insulating oil, characterized in that, The method, employing the intelligent management system as described in any one of claims 1-6, comprises the following steps: The unique identification code attached to the insulating oil container is read through the scanning module of the intelligent scanning terminal. In response to reading the identification code, the smart scanning terminal sends a query request to the cloud data platform; In response to the query request, the cloud data platform executes a preset dynamic status information generation and update strategy to generate or update dynamic status information. The cloud data platform returns the dynamic status information to the smart scanning terminal; Based on the received dynamic status information, the intelligent scanning terminal executes a preset handover logic operation to control the handover process of the insulating oil container.

8. The intelligent management method according to claim 7, characterized in that, The step of executing a preset dynamic state information generation and update strategy to generate or update dynamic state information includes: Intelligent diagnostic algorithms based on multi-parameter interlocking feedback are used to generate or update dynamic status information.

9. The intelligent management method according to claim 8, characterized in that, The intelligent diagnostic algorithm based on multi-parameter interlocking feedback, in the steps of generating or updating dynamic state information, includes: Obtain test result data associated with the insulating oil container, including dissolved gas content, trace water content, and breakdown voltage value; Cross-validation analysis was performed on at least two items of the experimental results data; Based on the results of the cross-validation analysis, a comprehensive equipment health status diagnosis conclusion is generated. Based on the comprehensive diagnostic conclusions, the test status information in the dynamic status information is generated or updated.

10. The intelligent management method according to claim 9, characterized in that, The step of performing cross-validation analysis on at least two items of the experimental result data includes at least one of the following analysis logics: The first analysis logic is configured to, when the concentration of any gas component in the dissolved gas content exceeds its preset attention threshold and the relative gas production rate of that gas component exceeds its preset rate threshold, upgrade the single-parameter state judgment result based on the concentration of that gas component from a first preset level to a more severe second preset level; or, when the concentration of the first gas component in the dissolved gas content exceeds its preset attention threshold and the concentration of the second gas component also exceeds its preset attention threshold, upgrade the single-parameter state judgment result based on the concentrations of the two gas components from the first preset level to the second preset level. The second analysis logic is configured to upgrade the single-parameter state judgment result based on the breakdown voltage value from the first preset level to the second preset level when the breakdown voltage value is higher than its preset attention threshold but lower than its preset severity threshold, and the micro-moisture content exceeds its preset attention threshold. The third analysis logic is configured to strengthen the diagnostic tendency of solid insulation moisture degradation when the equipment is determined to have fault characteristics of low temperature overheating or partial discharge based on the dissolved gas content using the three ratio method or the David triangle method, and the trace moisture content exceeds its preset attention threshold; conversely, when the fault characteristics are present and the trace moisture content is lower than its preset low threshold, the diagnostic tendency of bare metal overheating is strengthened. The fourth analysis logic is configured to, when the equipment is determined to have arc discharge fault characteristics based on the dissolved gas content using the three-ratio method or the David's triangle method, and the breakdown voltage value is lower than its preset severity threshold, upgrade the status level corresponding to the fault diagnosis conclusion based on the dissolved gas content from the second preset level to a more severe third preset level.

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