Test instrument digital access system and method for distribution network operation situation awareness

Abstract

The invention discloses a test instrument digital access system and method for distribution network operation situation awareness. The method comprises the steps that a multi-mode access terminal is connected with a distribution network on-site multi-source heterogeneous electrical test instrument in a wired / wireless mode; a built-in protocol adaptation module calls a corresponding protocol from a preset protocol library according to the equipment model, and constructs a request packet to obtain original data; the data standardization module converts the original data into a standard data object according to a preset mapping relation; the artificial intelligence module performs multi-dimensional analysis on the standard data to generate classification and grading labels; the mobile application end receives the data and the label and generates a detection report; and the rear-end platform stores the report and the tag to detect object association historical data, implement differential storage strategies and alarm priorities according to the hierarchical tag, and perform identification and structured analysis on the unstructured report, thereby realizing standardized and automatic data access to various electrical test instruments to support accurate real-time situation awareness of the power distribution network.

Description

Technical Field

[0001] This invention relates to the field of situational awareness, and in particular to a digital access system and method for testing instruments for situational awareness of power distribution network operation. Background Technology

[0002] In the current distribution network technology system with a high proportion of renewable energy integration, although power electronic control equipment such as grid-type converters, flexible power flow regulation devices, and power quality adaptive converters have emerged, as well as a series of key supporting technologies and advanced application platforms such as distributed photovoltaic access, active distribution network collaborative control and operation optimization, there are still significant system closures and data acquisition bottlenecks. Specifically, safety control systems that rely on dedicated hardware are difficult to be compatible with existing testing instruments from a wide variety of brands in the field; advanced data analysis applications, such as load capacity assessment, risk warning, and source-grid-load collaborative scheduling, often assume that the underlying data can be easily obtained and is standardized, but in reality, the difficulty in data acquisition caused by the heterogeneity of communication protocols of front-end testing equipment has become the "last mile" problem hindering their effective implementation; at the same time, existing collaborative control systems and their demonstration projects also generally suffer from idealized data sources and system closures, making it difficult to adapt to the complex environment of multiple brands and protocols of equipment coexisting in reality, thus limiting their large-scale promotion and actual control effects.

[0003] The electrical testing instruments used in power distribution networks are numerous and varied in brand and model, including DC high-voltage generators, loop resistance testers, dielectric loss testers, and handheld infrared imagers. These instruments are typically manufactured by different companies, employing different physical interfaces, communication protocols, and data formats. This heterogeneity in protocols prevents direct communication between devices, hindering automatic data integration and creating numerous data silos. The communication protocols used by existing testing instruments differ widely, lacking a unified standard, making the unified and automated access and management of data from these heterogeneous devices a systemic industry challenge. Data generated by different instruments varies in structure, format, and units; even manual collection requires extensive cleaning and conversion before comprehensive analysis, resulting in a massive workload and a high risk of errors. Due to difficulties in data acquisition and inconsistent formats, large amounts of historical test data are difficult to store, query, and correlate for analysis. This hinders the formation of time-series analyses of equipment health status, provides a lack of effective prediction of fault trends, and results in extremely low data utilization rates.

[0004] The distribution network after the integration of new energy sources experiences rapid and highly uncertain changes in its operating status, placing higher demands on real-time data. However, traditional manual operation and maintenance methods cannot meet this requirement. For example, in handling abnormal line losses in distribution areas, staff need to monitor current and voltage waveforms on-site and perform comparative analysis to locate the fault point, such as a loose current transformer terminal. This process is time-consuming and labor-intensive, and the integration of new energy sources will make such problems more frequent and complex. For issues such as three-phase imbalance and low voltage, the current approach mainly relies on staff measuring the load on-site during peak electricity consumption periods and then making adjustments based on experience. This method is slow and cannot adapt to the fluctuations in distribution area status caused by rapid changes in new energy output. Due to the lack of real-time data support, traditional operation and maintenance methods struggle to predict and warn of the distribution network's operating status, only responding after problems occur, resulting in a passive approach. Summary of the Invention

[0005] In view of the aforementioned existing problems, this invention is proposed. Therefore, this invention provides a digital access system and method for testing instruments used in distribution network operation situation awareness, solving the problems in the prior art caused by the complexity of testing instrument brands and protocols, resulting in difficulties in collecting distribution network operation data, low efficiency, inconsistent standards, and the inability to fully utilize data value.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a digital access system for testing instruments used in distribution network operation status awareness, comprising: Multimodal access terminal, communication module, protocol adaptation module, data standardization and conversion module, AI-driven data intelligent classification and grading module, mobile application terminal and backend service platform; The multimodal access terminal is connected to multi-source heterogeneous electrical testing instruments in the power distribution network via wired or wireless means. The protocol adaptation module is built into the multimodal access terminal and is used to call the corresponding communication protocol from the pre-set multi-protocol library according to the equipment model of the connected electrical test instrument, and construct a data request packet that conforms to the communication protocol specification to obtain the original test data. The data standardization and conversion module is used to parse and convert the original test data into standardized data objects according to a preset mapping relationship; The AI-driven data intelligent classification and grading module is used to perform multi-dimensional analysis on the standardized data objects and generate corresponding classification and grading labels. The mobile application communicates with the multimodal access terminal wirelessly or via wired means to receive the standardized data objects and their tags, and to generate a detection report. The backend service platform is connected to the mobile application via a communication network to receive and store the test reports and tags, associate historical test reports by the test object, trigger differentiated data storage strategies and alarm push priorities based on the graded tags, and perform optical character recognition and structured parsing on unstructured test report files to achieve digital management of test data.

[0007] As a preferred embodiment of the digital access system for testing instruments for power distribution network operation status awareness described in this invention, the multimodal access terminal includes: a main core board, an AI computing power board, and an integrated multimodal communication interface. The artificial intelligence-driven data intelligent classification and grading module is deployed on the AI ​​computing power board. The multimodal communication interface includes a wireless communication module, a wired communication module, an RJ45 Ethernet port, a USB interface, and an RS-232 / RS-485 serial interface. When the multimodal access terminal connects wirelessly to the multi-source heterogeneous electrical testing instruments in the power distribution network, the main core board is configured to interact with the electrical testing instruments that support Bluetooth communication via the Bluetooth module; it can also act as a Wi-Fi client to connect to the Wi-Fi hotspot emitted by external devices to read device data, or act as a Wi-Fi hotspot for mobile application terminals to access and communicate data. When the multimodal access terminal is connected to the multi-source heterogeneous electrical testing instruments in the power distribution network via a wired connection, the main core board is configured to establish a wired connection with devices supporting the TCP / IP protocol through the RJ45 Ethernet interface; and to connect to external testing instruments through the USB interface to read and store data.

[0008] As a preferred embodiment of the digital access system for testing instruments for power distribution network operation status awareness described in this invention, the protocol adaptation module includes: calling the corresponding communication protocol from a pre-set multi-protocol library according to the equipment model of the electrical testing instrument; constructing a data request packet based on the called communication protocol and sending it to the electrical testing instrument; When the data request packet meets the compliance conditions, the system receives the raw test data returned by the electrical testing instrument and caches the received raw test data in local storage.

[0009] As a preferred embodiment of the digital access system for testing instruments for power distribution network operation status awareness described in this invention, the protocol adaptation module further includes: the data request packet includes a protocol envelope layer and a service instruction layer; The protocol envelope layer carries the communication control information required by the communication protocol, which is used to enable the electrical test instrument to identify and parse the data request packet; the service instruction layer indicates the data reading operation and contains the unique identifier of the parameter to be read in the communication protocol; The compliance conditions include that the data request packet conforms to the coding specifications of the communication protocol; passes the identity authentication and authorization verification mechanism specified by the communication protocol; and the target logical object corresponding to the unique identifier exists in the electrical testing instrument and has access permissions.

[0010] As a preferred embodiment of the digital access system for testing instruments for distribution network operation status awareness described in this invention, the data standardization and conversion module includes: receiving raw protocol messages from electrical testing instruments; parsing the messages and extracting protocol-related raw data objects according to the communication protocol type of the raw protocol messages; Based on a pre-set device model-parameter-protocol address mapping table, determine the corresponding address, data type, and numerical conversion rules of the current device model and the target test parameters in the communication protocol; According to the numerical conversion rules, the original numerical values ​​are converted into actual physical values, and combined with standard parameter names, units, timestamps and data quality status, they are encapsulated into standardized data objects with fixed field structures.

[0011] As a preferred embodiment of the digital access system for testing instruments used in distribution network operation status awareness according to the present invention, the artificial intelligence-driven data intelligent classification and grading module includes: When the received test data contains an explicit type identifier, the corresponding analysis process is matched according to the preset mapping relationship between device type and processing logic; When there is no explicit type identifier, a dynamic identification mechanism is enabled to infer the device type, and a three-level automatic classification process is performed based on the identification result; Based on the classification and grading results, structured tags are attached to the test data, and corresponding advanced analysis models, data storage strategies, or alarm push mechanisms are automatically triggered based on the structured tags.

[0012] As a preferred embodiment of the digital access system for testing instruments used in distribution network operation status awareness according to the present invention, the dynamic identification mechanism includes: Parse the initial frame structure of the data packet to determine whether it conforms to a preset specific format standard; extract keywords from the file path and device information from the auxiliary configuration file to identify the data category; If any method fails to identify the data, the preliminary features of the data are extracted and submitted to the artificial intelligence model for type inference. After manual confirmation, the correct results are stored in the mapping library for self-learning and updating of the classification rules. As a preferred embodiment of the digital access system for testing instruments for power distribution network operation status awareness as described in this invention, the mobile application terminal includes: receiving standardized data from the multimodal access terminal, parsing and displaying the original data according to preset data specifications, and providing secondary editing functions; Based on the standardized data and its accompanying smart tags, a structured test report is automatically generated, and the final confirmed test report is uploaded to the backend service platform.

[0013] As a preferred embodiment of the digital access system for testing instruments used in distribution network operation status awareness according to the present invention, the backend service platform includes: Receive and store the detection report and its smart tags from the mobile application, perform standard difference conversion on the report data, and automatically associate historical detection reports with the detection object as the dimension; Based on the data quality level in the smart tags, automatically trigger differentiated data storage strategies and alarm push priorities; For non-digitalized test reports, optical character recognition technology is used to identify text, tables, and layout structure to generate structured data.

[0014] Secondly, the present invention provides a digital access method for testing instruments for power distribution network operation status awareness, comprising: collecting raw test data through multi-source heterogeneous electrical testing instruments, and preprocessing the raw test data, wherein the preprocessing includes protocol identification, compliance verification, and data request and reception; The received raw test data is parsed and standardized according to a preset mapping relationship to generate standardized data objects; Based on an artificial intelligence model, the standardized data objects are classified and graded into three levels, generating structured tags. On the mobile application, a structured detection report is automatically generated based on the standardized data objects and their tags. The detection report is uploaded to the backend service platform via a communication network. The backend service platform associates historical detection reports with the detection object as the dimension, automatically triggers differentiated data storage strategies and alarm push priorities based on the structured tags, and simultaneously displays the detection results and historical trends on the mobile application and platform.

[0015] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention completely changes the outdated traditional manual data recording mode, avoids human error, and shortens data collection time from tens of minutes to seconds, effectively improving efficiency and reducing the burden on grassroots operation and maintenance personnel. Simultaneously, through a unified data protocol, it solves the problem of data silos, achieving data automation and standardization, and significantly improving efficiency and accuracy. Furthermore, through a built-in, extensible protocol library, it is compatible with most mainstream brands' existing and new testing instruments on the market, eliminating the need to modify or replace existing instruments, effectively protecting the asset investment of power companies and avoiding the risk of being tied to a single equipment vendor. This invention opens up the "field-back-end" data channel, improving data real-time performance and availability, enabling real-time synchronous uploading of test data, allowing managers to grasp the distribution network operation status and equipment health status in near real-time, providing the possibility for rapid decision-making and emergency response. Historical data can also be traced at any time, providing strong support for trend analysis of equipment status and fault early warning. This invention, acting as the "nerve endings" of distribution network situation awareness, provides high-quality, standardized data sources, which are an indispensable prerequisite for realizing advanced applications such as autonomous distribution network governance, intelligent diagnosis, and predictive maintenance. It transforms originally discrete and static test data into continuous and dynamic situation information, thereby improving the digital and intelligent management level of the distribution network. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein: Figure 1 This is a system architecture diagram of a digital access system for testing instruments for power distribution network operation status awareness, according to an embodiment of the present invention. Figure 2 This is a first illustration of a hierarchical example of a digital access system for testing instruments used for distribution network operation status awareness, as described in an embodiment of the present invention. Figure 3 This is a second illustration of a hierarchical example of a digital access system for testing instruments used for distribution network operation status awareness, as described in an embodiment of the present invention. Figure 4 This is a schematic diagram of a method for digital access of testing instruments for power distribution network operation status awareness, according to an embodiment of the present invention. Figure 5 This is a schematic diagram illustrating the workflow of a digital access method for testing instruments used in power distribution network operation status awareness, as described in one embodiment of the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0018] Example 1, referring to Figures 1-3 This is one embodiment of the present invention, which provides a digital access system for testing instruments for power distribution network operation status awareness, including: a multimodal access terminal, a communication module, a protocol adaptation module, a data standardization conversion module, an AI-driven data intelligent classification and grading module, a mobile application terminal, and a back-end service platform; The multimodal access terminal connects to multi-source heterogeneous electrical testing instruments in the power distribution network via wired or wireless means. The protocol adaptation module is built into the multi-mode access terminal. It is used to call the corresponding communication protocol from the pre-set multi-protocol library according to the equipment model of the connected electrical test instrument, and construct a data request packet that conforms to the communication protocol specification in order to obtain the raw test data. The data standardization and transformation module is used to parse and transform the raw test data into standardized data objects according to the preset mapping relationship; The AI-driven data intelligent classification and grading module is used to perform multi-dimensional analysis on standardized data objects and generate corresponding classification and grading labels. The mobile application communicates with the multimodal access terminal wirelessly or via wired means to receive standardized data objects and their tags, and to generate test reports; The backend service platform connects to the mobile application via a communication network to receive and store test reports and tags. It associates historical test reports by the test object, triggers differentiated data storage strategies and alarm push priorities based on graded tags, and performs optical character recognition and structured parsing on unstructured test report files to achieve digital management of test data.

[0019] It should be noted that the terminal adopts an integrated hardware and software design. Its core system architecture consists of a hardware layer, a protocol adaptation layer, and a data intelligence processing layer. The hardware layer forms the foundation for multimodal communication and computing. The terminal hardware system is centered on the main core board, integrating rich communication interfaces to form a robust physical foundation. The main core board, as the system control hub of the terminal, is responsible for overall power management, driver scheduling, task coordination, and basic communication. The main core board is equipped with a high-performance embedded processor and an embedded operating system, ensuring system stability and real-time performance. It also integrates a dedicated AI computing chip, providing the core board with powerful heterogeneous computing capabilities specifically for performing computationally intensive tasks such as image recognition and metadata parsing.

[0020] Furthermore, the multimodal access terminal includes: a main core board, an AI computing power board, and an integrated multimodal communication interface. The AI-driven data intelligent classification and grading module is deployed on the AI ​​computing power board. The multimodal communication interface includes a wireless communication module, a wired communication module, an RJ45 Ethernet port, a USB interface, and an RS-232 / RS-485 serial interface.

[0021] Specifically, the wireless communication module integrates Wi-Fi and Bluetooth modules. The Wi-Fi module supports both client (STA) and hotspot (AP) modes. In STA mode, it can actively connect to hotspots from devices such as mobile Wi-Fi devices; in AP mode, it can create its own hotspot for mobile apps to connect to. The Bluetooth module is used for near-field data interaction with instruments that support the Bluetooth protocol. The wired communication module integrates multiple industrial standard physical interfaces. The RJ45 Ethernet port is used for network communication based on the TCP / IP protocol. The USB interfaces include Type-A, Mini-USB, and Type-C, supporting connection to storage devices such as USB flash drives and external hard drives, or direct connection to instruments with USB communication capabilities via a data cable. The RS-232 / RS-485 serial interfaces are used to connect to traditional industrial instruments.

[0022] Furthermore, based on the functional division of the main core board and the AI ​​computing power board, their connection relationships with various interfaces are as follows: When the multimodal access terminal connects to the multi-source heterogeneous electrical testing instruments in the power distribution network via wireless means, the main core board is configured to interact with the electrical testing instruments that support Bluetooth communication via the Bluetooth module; it can also act as a Wi-Fi client to connect to the Wi-Fi hotspot emitted by external devices to read device data, or act as a Wi-Fi hotspot for mobile application terminals to access and communicate data. When the multimodal access terminal is connected via wired connection to multi-source heterogeneous electrical testing instruments in the power distribution network, the main core board is configured to establish a wired connection with devices supporting the TCP / IP protocol via an RJ45 Ethernet interface; and to connect to external testing instruments via a USB interface to read and store data. The USB cable supports interfaces such as mini-USB and Type-C.

[0023] It should be noted that the data interaction in the wireless and wired connection methods is mainly based on API interface calls, including HTTP interface calls and TCP message exchanges. After the data interaction is completed on the main core board, some data will be handed over to the AI ​​computing power part for intelligent processing such as optical character recognition and image recognition.

[0024] In one possible implementation, the wired connection method also includes a USB flash drive connection, where the USB flash drive can be directly inserted into the USB interface of the main core board, and the stored data can be read after successful mounting.

[0025] Furthermore, the protocol adaptation module includes: calling the corresponding communication protocol from a pre-set multi-protocol library according to the equipment model of the electrical test instrument; constructing a data request packet based on the called communication protocol and sending it to the electrical test instrument; When the data request packet meets the compliance conditions, the system receives the raw test data returned by the electrical test instrument and caches the received raw test data in the local storage.

[0026] Furthermore, the protocol adaptation module also includes: the data request packet includes a protocol envelope layer and a business instruction layer; The protocol envelope layer carries the communication control information required by the communication protocol, which enables electrical test instruments to identify and parse data request packets; the service instruction layer indicates the data reading operation and contains the unique identifier of the parameter to be read in the communication protocol. Compliance requirements include that the data request packet conforms to the coding specifications of the communication protocol; that the identity authentication and authorization verification mechanism specified in the communication protocol is passed; and that the target logical object corresponding to the unique identifier exists in the electrical testing instrument and has access permissions.

[0027] Specifically, the terminal establishes communication with various instruments and meters and collects data through a multimodal interface, based on a standardized interaction process. The unified interaction request process includes: Connection establishment: The terminal establishes a connection with the target instrument via physical cable or wireless means.

[0028] Protocol identification and invocation: The terminal invokes the corresponding communication protocol from the built-in multi-protocol library based on the preset or manually selected instrument model.

[0029] Request Initiation and Data Acquisition: Based on the protocol specification, the terminal sends a structured data request packet that conforms to the specific protocol specification. This request packet can be understood as consisting of two layers: the protocol envelope layer contains all the communication control information necessary for the target instrument to recognize and process the message; the service instruction layer carries the specific operational intent and data content.

[0030] Data return: After the data request is compliant, the instrument returns the internally stored test data or real-time data stream to the terminal according to the field format defined in the protocol.

[0031] Data caching: The raw data obtained is temporarily stored in the terminal's local memory for later processing.

[0032] It should be noted that data requests must comply with the coding specifications of the protocol used by the requesting instrument, the security and authorization verification required by the protocol, such as providing identity identifiers, passwords, etc., and the application layer business rules verification of the protocol used. For example, the logical device name, logical node name, and data object name requested by the terminal must exist and be accessible.

[0033] For example, if a user wants to complete the function of "reading parameter B from device A", the terminal will automatically perform the following steps: Select the correct protocol driver based on the model of device A.

[0034] Based on the mapping relationship of parameter B, find the corresponding protocol address / object name.

[0035] Construct a complete request frame containing all necessary verification information (address, function code, checksum, etc.) according to the specifications of the protocol.

[0036] The request is sent via the established physical link.

[0037] Furthermore, the identity authentication and authorization verification mechanisms include: When a user logs into a mobile app using their account, the app sends a request to the terminal or platform, carrying the user's credentials (username / password token). The terminal / platform verifies the credentials against the app's authentication service; a connection is established only after successful verification.

[0038] After successful authentication, the system maps the user's permission information returned by the backend platform to the app's function menus and data access levels. Through an interface gateway and middleware, each access request is authenticated to prevent unauthorized access attempts such as directly entering a URL.

[0039] Furthermore, the data standardization and conversion module includes: receiving raw protocol messages from electrical testing instruments; parsing the messages and extracting protocol-related raw data objects based on the communication protocol type of the raw protocol messages; Based on a pre-set device model-parameter-protocol address mapping table, determine the corresponding address, data type, and value conversion rules of the current device model and target test parameters in the communication protocol; According to the numerical conversion rules, the original numerical values ​​are converted into actual physical values, and combined with standard parameter names, units, timestamps and data quality status, they are encapsulated into standardized data objects with fixed field structures.

[0040] Specifically, the collected raw data is processed collaboratively by the core board and its AI computing power to achieve intelligent hierarchical, classification, and standardization. The terminal has a built-in data standardization and protocol conversion module. Internally, the terminal contains a data standardization conversion library. This library, referencing standards such as the "Q / GDW Technical Specification for Data and Communication of Digital Test Instruments for Electrical Equipment," encapsulates and decouples the communication rules, data frame structures, and function codes of various communication protocols (such as Modbus, IEC 61850, IEC 104, and other proprietary or standard protocols). Regardless of the protocol used by external devices, the terminal performs data conversion through the library, thus shielding the differences in underlying protocols. Its core function is to map raw data obtained from different protocols into a unified data object model defined internally by the system.

[0041] In one feasible approach, the terminal parses the received raw binary stream or message according to the protocol specification. Taking Modbus as an example, it identifies the outgoing address and function code, and extracts the register address and corresponding value from the message based on the format of the function code. For IEC 61850, it parses complex ASN.1 encoded messages, unpacking them to extract logical devices, logical nodes, data attribute names, and corresponding data values, quality stamps, timestamps, etc. At the end of this stage, the raw message is transformed into a "raw data object," but its structure remains protocol-dependent.

[0042] The terminal uses a pre-defined "device model-parameter-protocol address" mapping table to convert the previously parsed protocol-related raw data objects into a unified data model defined internally by the system. This process first uses the mapping table to find the specific protocol address, data type, and conversion rules corresponding to the current device model and parameters; then, it performs corresponding numerical calculations or format parsing to convert the raw values ​​into actual values ​​with clear physical meaning; finally, it fills this actual value, along with its complete semantic information (such as standard parameter names and units), data quality status, and timestamps, into a unified data model object with a fixed structure. At this point, heterogeneous data from different protocols is completely transformed into homogeneous data objects with the same fields, semantics, and format.

[0043] For example, whether device A returns the "voltage value" via Modbus and stores it in register 40001, or device B reports it via IEC 61850 using the MMXU1.PhV.phsA.cVal.mag.f model, both are ultimately converted into standard, unified data messages such as {"parameter":"phaseA_voltage","value":220.5,"unit":"kV"} within the system, defining a unified data structure, unit, and identifier.

[0044] Furthermore, the AI-driven data intelligence classification and grading module includes: When the received test data contains an explicit type identifier, the corresponding analysis process is matched according to the preset mapping relationship between device type and processing logic; When there is no explicit type identifier, a dynamic identification mechanism is enabled to infer the device type, and a three-level automatic classification process is performed based on the identification result; Based on the classification and grading results, structured tags are attached to the test data, and corresponding advanced analysis models, data storage strategies, or alarm push mechanisms are automatically triggered based on the structured tags.

[0045] It should be noted that the data processing program in this embodiment of the invention has a built-in mapping relationship between device type and processing logic; the mapping relationship in the system is mainly divided into basic mapping relationship and dynamic identification and matching. When the data source has a label that indicates the data type (manually identified, known data type, or using common file extensions), the system will use the corresponding report template and analysis process in subsequent processing and analysis. When the data source is unknown, the system will use multi-level feature recognition to dynamically determine the processing logic.

[0046] Specifically, when the source of data is unknown, it is determined by parsing the inherent characteristics of the data, such as the file header / data packet features; the structure of the starting frame of the data stream at the beginning of the file is analyzed to determine whether it conforms to specific format standards such as FLIR infrared images and ultrasonic partial discharge signals.

[0047] The system reads keywords from the file path, embedded EXIF ​​information, or associated configuration files for identification; for example, it extracts “HIKVISION” and “thermal” from the file path / … / HIKVISION_thermal_20231027.jpg as key evidence for device type inference.

[0048] For new devices or data of unknown format that cannot be matched using conventional mapping relationships, the system submits preliminary characteristics of the data (such as binary structure features and partially readable text) to the AI ​​module for rapid comparison and type inference, which is then confirmed by a human. Correct inference results are retained, enabling self-learning of mapping relationships.

[0049] Furthermore, the dynamic identification mechanism includes: parsing the initial frame structure of the data packet to determine whether it conforms to a preset specific format standard; extracting keywords from the file path and device information from the auxiliary configuration file to identify the data category; If any method fails to identify the data, the preliminary features of the data are extracted and submitted to the artificial intelligence model for type inference. After manual confirmation, the correct results are stored in the mapping library for self-learning and updating of the classification rules. It should be noted that the grading mechanism is executed by the AI ​​computing power component, automatically grading data across multiple dimensions based on data characteristics. The core of the grading mechanism is to classify device data into business-meaning levels based on data characteristics using a pre-defined rule model. The specific rules are as follows: Level 1: Manufacturer Identification: Identifying the manufacturer of the equipment, serving as the most basic classification label.

[0050] Level 2: Equipment Subtype / Model Classification: Within the same manufacturer, further subdivisions are made based on equipment performance, precision, or model.

[0051] Level 3: Data Quality and Importance Classification: Based on the data's completeness, clarity, outlier rate, etc., the data's credibility and priority are classified.

[0052] Reference Figure 2 and Figure 3 In one feasible approach, for image data generated by infrared imagers, OCR technology is used to identify specific locations in the image, such as the manufacturer's logo text in the upper right and lower left corners, such as "FLIR" and "HIKVISION", as well as resolution information, such as 640x512, thereby classifying the equipment manufacturer and subtype (high-precision type, ordinary type).

[0053] For example: classifying images according to the text information within them. Figure 2 Top right corner Figure 3 The bottom left corner contains the manufacturer's logo. After OCR recognition, the manufacturer and equipment subtype can be classified based on information such as text, location, and image resolution.

[0054] In another feasible approach, for device data containing metadata such as EXIF ​​information, the AI ​​computing power directly parses key fields such as "manufacturer" and "device model" to achieve accurate manufacturer and subtype classification. For example, by reading the "metadata" in the device data, basic information about the device (manufacturer, device model, etc.) can be obtained, allowing for classification by manufacturer and device subtype.

[0055] It should be noted that AI-based intelligent data classification and grading is a crucial step in the entire data acquisition and processing solution, bridging the gap between preceding and subsequent steps. This module is responsible for extracting relevant features from standard data and labeling the data accordingly. The subsequent system can automatically select the most suitable advanced analysis model based on these labels, triggering different storage strategies and influencing alarm and push priorities. Furthermore, this data filtering also empowers application platforms. When the data is finally presented in the APP or power service command center, the accompanying labels allow for intuitive classification, filtering, aggregation, and statistical analysis. Simultaneously, it provides a structured data foundation for asset inventory and equipment reliability analysis.

[0056] It should be noted that the standardized data is uploaded to the backend service platform in real time via 4G / 5G modules. The transmission protocol follows the standard MQTT protocol, establishing a lightweight, efficient, and reliable data channel. The terminal supports a breakpoint resume mechanism, caching data locally in the event of network anomalies and automatically resuming transmission upon recovery, ensuring data integrity. The terminal supports data push to the APP and backend platform. Cross-system collaboration is achieved by developing specific programs or SDKs for different operating systems. The system supports private cloud deployment, enabling cross-regional and multi-departmental technical management and efficient collaboration via the Internet (supplemented with strict network security protection).

[0057] Furthermore, the mobile application includes: receiving standardized data from multimodal access terminals, parsing and displaying the raw data according to preset data specifications, and providing secondary editing functions; Structured test reports are automatically generated based on standardized data and its accompanying smart tags, and the final confirmed test reports are uploaded to the backend service platform.

[0058] Specifically, on the APP side, the mobile application receives standardized data from instruments and equipment via wired or wireless means such as WiFi, Bluetooth, NFC, or USB. It then processes and parses the data according to the "Technical Specification for Data and Communication of Digital Testing Instruments for Electrical Equipment" to ensure data standardization and usability. The parsed data is displayed in list format, allowing team members to view the raw data from the testing instruments and providing secondary editing functions to correct errors. The APP can also automatically generate test reports from the raw data and its generated smart tags. Reports include test type, report number, affiliated unit, tested object, test time, test results, and report generation time, and are displayed in list format, supporting user management operations such as viewing and exporting. For equipment that cannot obtain data through the communication interface, the APP provides a manual data entry function, using standardized data entry field templates to ensure data consistency. Before the report is uploaded to the backend service platform, users can edit and correct it, and the APP automatically fills in location and weather information. Simultaneously, the APP provides a report search function, enabling precise searches by parameters such as report generation time, data type, and report number, as well as a defect tracking function, allowing testing personnel to describe equipment defects and record subsequent processing.

[0059] Furthermore, the backend service platform includes: Receive and store the test reports and their smart tags from the mobile application, perform standard difference conversion on the report data, and automatically associate historical test reports with the test object as the dimension; Based on the data quality level in the smart tags, automatically trigger differentiated data storage strategies and alarm push priorities; For non-digitalized test reports, optical character recognition technology is used to identify text, tables, and layout structure to generate structured data.

[0060] Specifically, the backend service platform is responsible for receiving and processing the test task reports and their accompanying intelligent classification and grading tags submitted by the APP. First, it performs standard difference conversion on the data that conforms to the specifications, using standard protocols and data specifications to ensure the data is presented correctly. The platform displays the report details in an interface format, including test type, report number, affiliated unit, test object, test time, report generation time, report upload time, original test data, and intelligent tags, and categorizes them according to test nature and classification results.

[0061] Furthermore, the platform automatically associates historical test report information with the same test object, facilitating user traceability and analysis. It can automatically trigger different storage strategies and alarm push priorities based on AI-graded tags (such as data quality levels) in the report. The report retrieval function allows for precise searches by parameters such as report generation time, equipment type, report number, and category tags. Users can view and edit reports themselves and upload them to the data platform as needed to achieve task closure. For reports submitted through non-digital processes, the platform uses optical character recognition (OCR) technology to analyze and recognize text, tables, and images in real time, obtaining text and layout information. It then achieves digital conversion by segmenting image and text data, labeling attribute features, and determining logical structure, ultimately pushing the recognition results to the platform's front end. In addition, the platform supports report export, archiving output data or reports from different types of testing instruments according to existing test templates, and provides defect tracking functionality for testing personnel to describe equipment defects and provide subsequent processing instructions, thereby ensuring the efficiency and data integrity of the entire testing process.

[0062] It should be noted that for new instrument types, quick integration can be achieved simply by adding the corresponding protocol parsing plugin to the terminal's protocol library or through OTA online updates, requiring minimal changes to the hardware and core system architecture. The product adopts a microservice architecture, allowing for functional expansion to meet new business needs by defining new software functional modules or services (such as new AI analysis algorithms). The product provides standard data encryption interfaces (such as AES), physical interfaces (WiFi, RJ45, etc.), and application software interfaces (RESTful API, HTTP, etc.), facilitating information exchange with other company systems and demonstrating excellent compatibility, flexibility, and scalability.

[0063] Example 2, refer to Figures 4-5 This is one embodiment of the present invention, which differs from the first embodiment in that it provides a digital access method for testing instruments for distribution network operation status awareness, including: S100: Collects raw test data through multi-source heterogeneous electrical test instruments and preprocesses the raw test data, including protocol identification, compliance verification, and data request and reception. S200: The received raw test data is parsed and standardized according to the preset mapping relationship to generate standardized data objects; S300: Based on an artificial intelligence model, standardized data objects are classified and graded into three levels, generating structured tags. On the mobile application terminal, a structured detection report is automatically generated based on the standardized data objects and their tags. S400: The test report is uploaded to the backend service platform through the communication network. The backend service platform associates historical test reports with the test object as the dimension, automatically triggers differentiated data storage strategies and alarm push priorities based on structured tags, and displays the test results and historical trends simultaneously on the mobile application and platform.

[0064] Reference Figure 5 The digitalization process for instruments and meters includes: Scenario 1: Device without ports or protocols If a PDF report exists, team members will generate it using dedicated equipment analysis software after completing on-site testing. The file will then be transferred to the intranet via USB flash drive or external hard drive and uploaded to the backend service platform. The platform will use recognition technology to perform image analysis and data extraction on the report, ultimately generating and presenting the report on the backend service platform and in the app.

[0065] If a PDF report is not available, team members will manually enter the test data into the "Manual Report Entry" module of the APP after completing the test on-site, thereby generating and submitting the report.

[0066] Scenario 2: Devices with ports and protocols Team members bring access terminals to the work site, complete testing and inspection, collect and analyze data from instruments using the access terminals, and upload the results to the APP. Users can edit and process the data in the APP, generate reports, and submit them, enabling the reports to be displayed on both the APP and the backend power service platform.

[0067] Scenario 3: When there is a new device, the process is the same as for devices with ports and protocols: Team members bring access terminals to the work site. After testing, they collect and analyze data through the access terminals and upload it to the APP. Users edit and process the data to generate reports and submit them. Finally, the APP and the backend service platform display the data.

[0068] This invention achieves data automation and standardization through a unified data protocol, significantly improving efficiency and accuracy. Furthermore, its built-in, extensible protocol library ensures compatibility with most mainstream brands' existing and new testing instruments, eliminating the need for modification or obsolescence of existing equipment. This effectively protects power companies' asset investments and avoids the risk of being tied to a single equipment vendor. The invention establishes a seamless "field-back-end" data channel, enhancing data real-time performance and availability. Real-time synchronous uploading of test data allows managers to monitor the distribution network's operational status and equipment health in near real-time, facilitating rapid decision-making and emergency response. Historical data can also be readily traced, providing strong support for trend analysis and fault early warning of equipment status. Finally, this invention provides a high-quality, standardized data source, transforming previously discrete and static test data into continuous and dynamic situational information, thus enhancing the digital and intelligent management level of the distribution network.

[0069] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A digital access system for testing instruments used in power distribution network operation status awareness, characterized in that, include: Multimodal access terminal, communication module, protocol adaptation module, data standardization and conversion module, AI-driven data intelligent classification and grading module, mobile application terminal and backend service platform; The multimodal access terminal is connected to multi-source heterogeneous electrical testing instruments in the power distribution network via wired or wireless means. The protocol adaptation module is built into the multimodal access terminal and is used to call the corresponding communication protocol from the pre-set multi-protocol library according to the equipment model of the connected electrical test instrument, and construct a data request packet that conforms to the communication protocol specification to obtain the original test data. The data standardization and conversion module is used to parse and convert the original test data into standardized data objects according to a preset mapping relationship; The AI-driven data intelligent classification and grading module is used to perform multi-dimensional analysis on the standardized data objects and generate corresponding classification and grading labels. The mobile application communicates with the multimodal access terminal wirelessly or via wired means to receive the standardized data objects and their tags, and to generate a detection report. The backend service platform is connected to the mobile application via a communication network to receive and store the test reports and tags, associate historical test reports by the test object, trigger differentiated data storage strategies and alarm push priorities based on the graded tags, and perform optical character recognition and structured parsing on unstructured test report files to achieve digital management of test data.

2. The digital access system for testing instruments for distribution network operation status awareness as described in claim 1, characterized in that, The multimodal access terminal includes: a main core board, an AI computing power board, and an integrated multimodal communication interface. The AI-driven data intelligent classification and grading module is deployed on the AI ​​computing power board. The multimodal communication interface includes a wireless communication module, a wired communication module, an RJ45 Ethernet port, a USB interface, and an RS-232 / RS-485 serial interface. When the multimodal access terminal connects wirelessly to the multi-source heterogeneous electrical testing instruments in the power distribution network, the main core board is configured to interact with the electrical testing instruments that support Bluetooth communication via the Bluetooth module; it can also act as a Wi-Fi client to connect to the Wi-Fi hotspot emitted by external devices to read device data, or act as a Wi-Fi hotspot for mobile application terminals to access and communicate data. When the multimodal access terminal is connected to the multi-source heterogeneous electrical testing instruments in the power distribution network via a wired connection, the main core board is configured to establish a wired connection with devices supporting the TCP / IP protocol through the RJ45 Ethernet interface; and to connect to external testing instruments through the USB interface to read and store data.

3. The digital access system for testing instruments for distribution network operation status awareness as described in claim 2, characterized in that, The protocol adaptation module includes: calling the corresponding communication protocol from a pre-set multi-protocol library according to the device model of the electrical test instrument; constructing a data request packet based on the called communication protocol and sending it to the electrical test instrument; When the data request packet meets the compliance conditions, the system receives the raw test data returned by the electrical testing instrument and caches the received raw test data in local storage.

4. The digital access system for testing instruments for distribution network operation status awareness as described in claim 3, characterized in that, The protocol adaptation module further includes: the data request packet includes a protocol envelope layer and a business instruction layer; The protocol envelope layer carries the communication control information required by the communication protocol, which is used to enable the electrical test instrument to identify and parse the data request packet; the service instruction layer indicates the data reading operation and contains the unique identifier of the parameter to be read in the communication protocol; The compliance conditions include that the data request packet conforms to the coding specifications of the communication protocol; passes the identity authentication and authorization verification mechanism specified by the communication protocol; and the target logical object corresponding to the unique identifier exists in the electrical testing instrument and has access permissions.

5. The digital access system for testing instruments for distribution network operation status awareness as described in claim 4, characterized in that, The data standardization and conversion module includes: receiving raw protocol messages from electrical testing instruments; parsing the messages and extracting protocol-related raw data objects according to the communication protocol type of the raw protocol messages; Based on a pre-set device model-parameter-protocol address mapping table, determine the corresponding address, data type, and numerical conversion rules of the current device model and the target test parameters in the communication protocol; According to the numerical conversion rules, the original numerical values ​​are converted into actual physical values, and combined with standard parameter names, units, timestamps and data quality status, they are encapsulated into standardized data objects with fixed field structures.

6. The digital access system for testing instruments for distribution network operation status awareness as described in claim 5, characterized in that, The AI-driven data intelligent classification and grading module includes: When the received test data contains an explicit type identifier, the corresponding analysis process is matched according to the preset mapping relationship between device type and processing logic; When there is no explicit type identifier, a dynamic identification mechanism is enabled to infer the device type, and a three-level automatic classification process is performed based on the identification result; Based on the classification and grading results, structured tags are attached to the test data, and corresponding advanced analysis models, data storage strategies, or alarm push mechanisms are automatically triggered based on the structured tags.

7. The digital access system for testing instruments for distribution network operation status awareness as described in claim 6, characterized in that, The dynamic recognition mechanism includes: Parse the initial frame structure of the data packet to determine whether it conforms to a preset specific format standard; extract keywords from the file path and device information from the auxiliary configuration file to identify the data category; If any method fails to identify the data, preliminary features are extracted and submitted to the artificial intelligence model for type inference. After manual confirmation, the correct results are stored in the mapping library for self-learning and updating of classification rules.

8. The digital access system for testing instruments for distribution network operation status awareness as described in claim 7, characterized in that, The mobile application includes: receiving standardized data from the multimodal access terminal, parsing and displaying the original data according to preset data specifications, and providing secondary editing functions; Based on the standardized data and its accompanying smart tags, a structured test report is automatically generated, and the final confirmed test report is uploaded to the backend service platform.

9. The digital access system for testing instruments for distribution network operation status awareness as described in claim 8, characterized in that, The backend service platform includes: Receive and store the detection report and its smart tags from the mobile application, perform standard difference conversion on the report data, and automatically associate historical detection reports with the detection object as the dimension; Based on the data quality level in the smart tags, automatically trigger differentiated data storage strategies and alarm push priorities; For non-digitalized test reports, optical character recognition technology is used to identify text, tables, and layout structure to generate structured data.

10. A method for digital access of testing instruments for power distribution network operation status awareness, characterized in that, include: Raw test data is collected using multi-source heterogeneous electrical test instruments, and the raw test data is preprocessed, including protocol identification, compliance verification, and data request and reception. The received raw test data is parsed and standardized according to a preset mapping relationship to generate standardized data objects; Based on an artificial intelligence model, the standardized data objects are classified and graded into three levels, generating structured tags. On the mobile application, a structured detection report is automatically generated based on the standardized data objects and their tags. The detection report is uploaded to the backend service platform via a communication network. The backend service platform associates historical detection reports with the detection object as the dimension, automatically triggers differentiated data storage strategies and alarm push priorities based on the structured tags, and simultaneously displays the detection results and historical trends on the mobile application and platform.

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