Cloud-edge diagnosis system and device diagnosis method

Abstract

The application discloses a cloud-edge diagnosis system and a device diagnosis method. The system comprises an intelligent terminal and a graphical configuration tool arranged separately. The intelligent terminal comprises a system mainboard, an extension module, a man-machine interface unit and a platform software system which communicate through an internal bus. The graphical configuration tool generates a configuration file for the intelligent terminal to download and run. The method comprises the following steps: defining diagnosis logic through visual operation and generating a configuration file; downloading to the intelligent terminal; performing local diagnosis analysis based on collected data; uploading diagnosis data to a remote system or receiving an instruction for updating. Through hardware platformization and software configurable architecture, the application has high-performance power data collection and flexible configuration capability, and can be flexibly adapted to various industrial scenes.

Description

Technical Field

[0001] This invention relates to the field of industrial automation and intelligent equipment technology, and in particular to a cloud-edge diagnostic system and equipment diagnostic method. Background Technology

[0002] Currently, in the fields of industrial internet and power system automation, there are two main types of terminal equipment: microprocessor-based protection devices and programmable logic controllers (PLCs). Microprocessor-based protection devices excel in high-frequency acquisition and processing of analog power quantities (such as current and voltage), but they are designed for specific protection functions (such as line overcurrent), with fixed hardware interfaces (such as fixed analog inputs and digital input / output channels), closed and unchangeable software logic, and poor functional scalability. When facing new application scenarios (such as transformer condition monitoring), hardware selection and software development must be carried out again, which is time-consuming, costly, and creates information silos between different devices. Therefore, they are difficult to adapt to diverse application scenarios. PLCs, on the other hand, have powerful logic programming capabilities and flexible modular I / O expansion, but they are insufficient in processing high-frequency, high-precision analog signals in power systems, and their communication protocol libraries are usually not deeply customized for power systems, making it difficult to develop complex power diagnostic logic.

[0003] Meanwhile, under the cloud-edge collaborative architecture, existing edge devices mostly adopt a customized development model. Different hardware and dedicated software need to be developed for different applications (such as relay protection and condition monitoring), resulting in long development cycles, high costs, poor maintainability, and difficulty in sharing and reusing data and algorithms between different devices. Summary of the Invention

[0004] To address the aforementioned issues, this invention provides a cloud-edge diagnostic system and device diagnostic method. Through a hardware platform and software configurable architecture, coupled with a graphical configuration tool with separate settings, a general-purpose intelligent edge system is constructed that combines high-performance power data acquisition with open programmability. It features both high-performance power data acquisition and flexible configuration capabilities. By implementing a cloud-edge collaborative mechanism, the diagnostic capabilities continuously evolve, solving the problems of fixed functions, long development cycles, and unusable knowledge in traditional devices.

[0005] This invention provides a cloud-edge diagnostic system, the specific technical solution of which is as follows: Includes: a smart terminal, and a graphical configuration tool that is set separately from the smart terminal; The smart terminal includes: The system motherboard and at least one expansion module that communicates with the system motherboard via an internal bus, the expansion module having a built-in independent microcontroller; the system motherboard includes: a core processor, an analog sampling module, and a memory group; the internal bus is a CAN bus. The human-machine interface unit is connected to the system motherboard; A platform-based software system is integrated and runs on the system motherboard, wherein the platform-based software system includes an expert diagnostic function module; The graphical configuration tool runs on an external computing device and is used to generate configuration files; the smart terminal is configured to download and run the configuration files to perform corresponding operations according to the logic defined in the configuration files.

[0006] Furthermore, the expansion module includes at least one of the following: an intelligent input / output module, an AC / DC analog quantity acquisition module, a DC signal acquisition module, and a circuit breaker operating circuit module.

[0007] Furthermore, the system motherboard also includes a communication interface for data communication with the graphical configuration tool and the remote system; the communication interface is an Ethernet interface and / or a serial communication interface.

[0008] Furthermore, the graphical configuration tool includes a graphical configurable logic programming platform, which provides graphical functional elements corresponding to the algorithms and criteria in the expert diagnosis function module. Users can build and compile the configuration file through the graphical configurable logic programming platform.

[0009] Furthermore, the graphical configuration tool also includes: The human-machine interface design module is used to design the interface template for display by the human-machine interface unit; The debugging module is communicatively connected to the smart terminal to debug the smart terminal.

[0010] Furthermore, the graphical configuration tool also includes a logic simulation module, which verifies diagnostic and control logic based on simulated or measured data.

[0011] Furthermore, the expert diagnostic function module is encapsulated in the form of a dynamic link library, including an algorithm library and a criterion library; The algorithm library includes at least one of the following: Fourier transform algorithm, order component calculation algorithm, power calculation algorithm, RMS value calculation algorithm, and integration / differentiation algorithm; The criterion library includes at least one of the following: overcurrent criterion, differential current criterion, overvoltage / undervoltage criterion, circuit breaker mechanical characteristic analysis criterion, coil current waveform analysis criterion, and inverse time overheating model.

[0012] The present invention also provides a device diagnostic method, based on the cloud-edge diagnostic system described above, the method comprising: Define diagnostic logic through visual operations and generate corresponding configuration files; Download the configuration file to the smart terminal; The smart terminal runs the configuration file and performs local diagnostic analysis based on the collected data. The smart terminal uploads diagnostic process data, feature data, or diagnostic results to the remote system and / or receives instructions or updates from the remote system.

[0013] Furthermore, the definition of diagnostic logic through visual operations includes: Configure hardware resources in a graphical configurable logic programming platform; Associate the virtual channel with the actual physical signal and rename it; Call the algorithm definition execution data in the expert diagnosis function module; Construct a diagnostic logic chain by dragging and dropping criteria and logic gate components; Compile to generate a structured configuration file.

[0014] Furthermore, the smart terminal runs the configuration file to perform local diagnostic analysis, including: The system motherboard acquires current and voltage signals at a fixed frequency; The expansion module's independent microcontroller collects switch signals and DC signals in real time and sends them to the system motherboard via an internal bus; The expert diagnostic module extracts signals from the real-time data queue according to the configuration file, calls the specified algorithm for calculation, and inputs the specified criteria for logical judgment. When the logical conditions are met, a local action is triggered, an event log is generated, and feature data is extracted.

[0015] Furthermore, the interaction between the smart terminal and the remote system includes: Diagnostic event reports and characteristic data waveform files are uploaded to the cloud-based expert system via the IEC 61850 MMS protocol; Receive updates to optimization algorithm models or criterion thresholds from the cloud-based expert system; New configuration files are loaded online to iteratively optimize diagnostic capabilities.

[0016] The beneficial effects of this invention are as follows: 1. This invention combines a hardware platform architecture of system motherboard + intelligent expansion module with a software architecture of platform software system + expert diagnostic function module, and with a separately configured graphical configuration tool, to build a general-purpose intelligent edge system that combines high-performance power data acquisition with open programmable capabilities. It retains the performance advantages of dedicated microcomputer protection devices in high-frequency and high-precision analog quantity acquisition, and also has the flexible configuration capability of programmable logic controllers, thus solving the inherent defects of the two types of traditional devices.

[0017] 2. This invention utilizes a two-way data interaction mechanism between intelligent terminals and remote systems. The edge focuses on executing real-time diagnostic tasks, while the cloud optimizes diagnostic algorithms through big data analysis and issues updates, forming a closed loop of edge execution and cloud evolution. This breaks through the limitations of traditional dedicated equipment software logic being closed and unchangeable, enabling diagnostic capabilities to be continuously iterated and optimized with technological development, and solving the problem of knowledge not being able to be accumulated and reused under customized development models.

[0018] 3. This invention, by combining different hardware expansion modules (intelligent input / output modules, AC / DC analog signal acquisition modules, DC small signal acquisition modules, and circuit breaker operating circuit modules) and graphical configuration, allows for the rapid customization of specialized equipment suitable for different scenarios, much like assembling building blocks. Through the visual configuration of hardware resources and the graphical programming of diagnostic logic, the development cycle of new applications is shortened, significantly reducing R&D costs.

[0019] 4. The motherboard of this invention uses a high-performance processor in conjunction with a hardware floating-point arithmetic unit. The analog sampling module performs synchronous sampling at a high sampling rate per cycle, ensuring the real-time performance and phase accuracy of the data. The expansion module has a built-in independent microcontroller that achieves distributed acquisition and control through an internal bus, reducing the burden on the main processor. Meanwhile, graphical programming frees domain experts from low-level code, enabling them to directly participate in application development, lowering the technical threshold and solving the problem of difficult development of complex power diagnostic logic.

[0020] 5. The expert diagnostic function module of this invention is encapsulated in the form of a dynamic link library, containing an algorithm library and a criterion library. As a knowledge base that can be independently maintained and expanded, it achieves effective accumulation of core technologies. The graphical configuration tool provides graphical functional elements corresponding to the knowledge base, transforming tacit knowledge into reusable standardized components, thus solving the problem of data and algorithm sharing and reuse between different devices. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the cloud-edge diagnostic system of the present invention.

[0022] Figure 2 This is a schematic diagram of the intelligent terminal structure of the present invention.

[0023] Figure 3 This is a schematic diagram of the platform-based software system structure of the present invention.

[0024] Figure 4 This is a schematic diagram of the system motherboard structure of the present invention.

[0025] Figure 5 This is a schematic diagram of the intelligent expansion module structure of the present invention.

[0026] Figure 6This is a schematic diagram of the human-machine interface module structure of the present invention.

[0027] Figure 7 This is a schematic diagram of the device diagnostic method of the present invention. Detailed Implementation

[0028] The technical solutions in the embodiments of the present invention are clearly and completely described in the following description. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0029] In the description of the embodiments of the present invention, it should be noted that the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the product of the invention is conventionally placed during use, or the orientation or positional relationship in which those skilled in the art conventionally understand it during use. This is only for the convenience of describing the present invention and simplifying the description, and is not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of the present invention. Furthermore, the terms "first" and "second" are only used to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0030] In the description of the embodiments of the present invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0031] Example 1 Embodiment 1 of the present invention discloses a cloud-edge diagnostic system, such as Figure 1 As shown, the details are as follows: Includes a smart terminal, and a graphical configuration tool that is set separately from the smart terminal; Among them, such as Figure 2 As shown, the intelligent terminal 101 is deployed at the substation site and includes a system motherboard 120, an expansion module 140, a human-machine interface unit 130, and a platform-based software system 110.

[0032] The system motherboard uses a high-performance microcontroller based on the ARM Cortex-M7 core, with a built-in hardware floating-point unit (FPU) and a main frequency of over 300MHz. It is responsible for running the entire platform software system and executing complex power algorithms, multi-task scheduling, and system management.

[0033] The graphical configuration tool 102 runs on the Windows system of the remote engineering station. It connects to the ETH1 interface (10 / 100M adaptive industrial Ethernet interface) of the smart terminal via a network cable to download configuration files and upgrade programs.

[0034] like Figure 4 As shown, the system motherboard 120 includes a core processor 1, a memory bank 3, an analog sampling module 4, and a communication interface 5. The core processor is a high-performance microcontroller with an ARM Cortex-M7 core and a built-in hardware floating-point unit (FPU). Its clock speed exceeds 300MHz, and it is responsible for running the entire platform software system 110, executing complex power algorithms, multi-task scheduling, and system management. The memory bank includes a 16MB NOR Flash chip for storing the bootloader and application software; a 256MB NAND Flash chip for storing historical events, waveform recordings, and other large data; and an FRAM chip connected via an SPI interface for storing frequently modified key parameters (such as setpoints) to ensure they are not lost during power loss.

[0035] Expansion module 140 is inserted into the terminal chassis backplane via a unified board interface, and the backplane integrates a CAN bus. Each module is intelligently designed, with a built-in independent MCU (such as an ARM Cortex-M0 core), communicating with the system motherboard via the CAN bus. Figure 5 As shown, the expansion module 140 includes intelligent input / output modules, AC / DC analog quantity acquisition modules, DC small signal acquisition modules, circuit breaker operation circuit modules, and the like.

[0036] The intelligent input / output module features an integrated ARM Cortex-M0 core MCU, providing 12 opto-isolated digital inputs for acquiring auxiliary contacts of the GCB (such as open, closed, and energy storage complete) and local / remote pressure plate status; it also provides 6 relay outputs for driving alarm indicator lights or as backup. The module's MCU scans the input status in real time, and when a change occurs, it actively reports it to the system motherboard 120 via the CAN bus with a high-priority frame; simultaneously, it receives control commands from the motherboard via the CAN bus to drive the corresponding relays.

[0037] AC / DC Analog Signal Acquisition Module: Specifically designed for acquiring analog signals with extremely high real-time, synchronous, and accuracy requirements. It connects directly to the system motherboard ADC controller via a high-speed parallel bus or a dedicated sampling bus, integrating precision conditioning circuitry (current transformer isolation, signal amplification, anti-aliasing filtering) and multiple analog switches for receiving AC current, voltage, and DC signals.

[0038] DC small signal acquisition module: Built-in MCU, providing 8 differential input channels (4-20mA or 0-5V), connecting SF6 gas density sensor, energy storage motor current transformer, coil current sensor, etc., and reporting the engineering value through CAN bus after periodic AD conversion.

[0039] Circuit Breaker Operating Circuit Module: An intelligent, configurable circuit breaker operating circuit execution unit that replaces traditional discrete relay hard-wired circuits. It integrates a high-reliability MCU and a powerful optocoupler / relay output circuit, communicating with the system motherboard 120 via an internal bus (CAN bus). It also features a high-voltage interface for direct connection to the circuit breaker's trip / close coils, energy storage motor, auxiliary contacts, and interlocking contacts. The module receives "open" and "close" remote control commands from the system motherboard 120 via the CAN bus, or protection trip commands generated by local logic. The module incorporates anti-pumping logic. Upon receiving and executing a closing command, if another closing command is detected within a preset time (possibly due to contact adhesion), the module automatically interlocks subsequent closing outputs to prevent the circuit breaker from "tripping." The module provides a reliable current holding circuit, ensuring that even if the command contacts return prematurely after a trip / close pulse is issued, the module's internal logic maintains the output until the circuit breaker's auxiliary contacts change position, guaranteeing operation completion. Simultaneously, the module monitors the current and voltage of the output circuit in real time and feeds back status information (such as "closing circuit integrity") to the system mainboard 120. Interlocking conditions (such as SF6 low pressure interlocking and spring unenergized interlocking) can be flexibly configured via the graphical configuration tool 102. The module automatically connects the corresponding interlocking contact signals, achieving software-based configuration of hard-wired connections. This module integrates traditionally distributed and inconsistently reliable relay circuits into standardized, monitorable, and diagnosable intelligent components, significantly improving the reliability and maintainability of the circuit breaker control circuit.

[0040] The analog sampling module 4 can employ an independent 16-bit high-precision ADC chip, supporting simultaneous acquisition of 8 analog signals. Through analog switches, it can manage up to 32 AC voltage / current inputs. This module is directly controlled by the processor, synchronously sampling the current and voltage transformer (CT / PT) signals of the GCB at a rate of 96 points per cycle (corresponding to 4800Hz for a 50Hz power frequency), ensuring real-time data quality and phase accuracy.

[0041] The communication interface 5 is used for data communication with the graphical configuration tool 102 and the remote system, including two 10 / 100M adaptive industrial Ethernet interfaces (ETH1, ETH2); ETH1 is used to communicate with the graphical configuration tool (downloading configuration files, upgrading programs), and ETH2 is used to communicate with the cloud expert system (uploading feature data, receiving instructions); four RS-485 serial interfaces (COM1-COM4) are used to connect other intelligent devices in the station (temperature and humidity monitoring instruments, smart meters, etc.); and one RS-232 interface (COM_HMI) is used to connect to the human-machine interface unit.

[0042] In a preferred embodiment, the system motherboard 120 further includes an internal bus and a dedicated communication interface 5; the internal bus is a CAN bus, used to connect various intelligent expansion modules 140. The dedicated communication interface 5 may be an RS-232 interface (COM_HMI) used to connect to the human-machine interface unit 130; like Figure 6 As shown, the human-machine interface unit 130, as an independent unit with an MCU and a liquid crystal display (LCD), is connected to the system motherboard 120 via a dedicated RS-232 interface (COM_HMI). Its MCU is responsible for driving the LCD to display screen data (real-time data, alarm list, setpoint menu) and scanning buttons to upload button events.

[0043] like Figure 3 As shown, the platform-based software system 110 includes a real-time operating system kernel (μC / OS-III), a file system (RL-FlashFS), an expert diagnostic function module 111, and a communication protocol stack. The expert diagnostic function module encapsulates the power knowledge base in the form of a dynamic link library; Specifically, the real-time operating system kernel uses µC / OS-III, which is responsible for scheduling system tasks (such as data acquisition tasks, protection computing tasks, communication tasks, etc.) to ensure timely response to high-priority tasks (such as fault diagnosis).

[0044] The file system is based on RL-FlashFS and is responsible for managing storage devices such as NAND Flash to enable the creation, storage, and retrieval of waveform recording files (recording analog and digital waveforms before and after a fault), event log files, and log files.

[0045] The power knowledge base includes an algorithm library and a criterion library; The algorithm library includes at least one of the following: Fourier transform algorithm, order component calculation algorithm, power calculation algorithm, RMS value calculation algorithm, and integration / differentiation algorithm; The criterion library includes at least one of the following: overcurrent criterion, differential current criterion, overvoltage / undervoltage criterion, circuit breaker mechanical characteristic analysis criterion, coil current waveform analysis criterion, and inverse time overheating model.

[0046] The communication protocol stack integrates a complete TCP / IP protocol stack and implements the IEC 61850 MMS client / server protocol, the IEC 60870-5-104 telecontrol protocol, and the Modbus TCP / RTU protocol. This enables the intelligent terminal 101 to act as an IEC 61850 server to upload data to the station control layer, as a 104 substation to communicate with the dispatch master station, and to access third-party systems via the Modbus protocol.

[0047] The graphical configuration tool 102 includes a graphical configurable logic programming platform that runs on a Windows system. It is used to provide graphical functional components corresponding to the algorithms and criteria in the expert diagnostic function module. Engineers can build diagnostic logic by dragging and connecting lines and compile it to generate a structured XML format configuration file. The graphical configuration tool 102 also includes a human-machine interface design module and a debugging module. The human-machine interface design module is used to design interface templates for display by the human-machine interface unit 130; the debugging module communicates with the smart terminal 101 and is used to debug the smart terminal 101. The graphical configuration tool 102 also includes a logic simulation module, used to verify diagnostic and control logic based on simulated data or measured data.

[0048] The intelligent terminal 101 is deployed at the substation site and connects to the cloud-based expert system (remote system) via the substation's local area network or wireless network. The intelligent terminal 101 receives the configuration file through the ETH1 interface and stores it in the system motherboard memory. After power-on, the platform software system loads and parses the configuration file and executes data acquisition, algorithm calculation, logical judgment, and control actions according to the defined logic.

[0049] Example 2 Embodiment 2 of the present invention discloses a device diagnostic method, based on the cloud-edge diagnostic system described in Embodiment 1 above, such as... Figure 7 As shown, the specific process is as follows: S1: Define diagnostic logic through visual operations and generate corresponding configuration files, as follows: S101: Configure hardware resources in the graphical configurable logic programming platform: Create a new project in the platform and drag and drop the corresponding hardware icons from the virtual hardware library to "configure". For example: add a "System Motherboard (Model XX)", two "Intelligent Input / Output Modules", and one "DC Small Signal Acquisition Module". The platform will automatically generate default names for each module's channels (such as DI1, AI1).

[0050] S102: Associate the virtual channel with the actual physical signal and rename it; for example, name the input module DI1 as "GCB_Close" and DI2 as "GCB_Open"; name the DC module AI1 as "SF6 Pressure" and AI2 as "Close Coil Current".

[0051] S103: Call the algorithm definition in the expert diagnostic function module to calculate and monitor the running data in real time; for example, by dragging a "RMS calculation" algorithm block, the original signal of "closing coil current" is connected, and the output is defined as "closing coil current_RMS"; drag a "waveform integration" algorithm block, connect the same current signal, and the output is defined as "closing coil current_integral value" (reflecting coil energy).

[0052] S104: Engineers drag and drop the required criteria and logic gates from the component library to make connections. Taking monitoring a "closing coil fault" as an example: Drag and drop a "Timer" block and a "Compare" block; Use the "GCB_closed" switch value as the trigger signal for the timer; Connect the timer output (closing command duration) to one input of the "compare" block, and set a threshold (e.g., 200ms) to the other input of the "compare" block. Connect the "closing coil current_RMS" signal to an "overcurrent criterion" block; Connect the "Compare" block (output True indicates that the closing command has not returned within 200ms) and the "Overcurrent Criterion" block (output True indicates that the coil current abnormality has not disappeared) using an "AND" logic block. Connect the output of the "AND" logic block to the "Action Output" block, which is associated with a relay in the output module to illuminate the local "Coil Fault" indicator light and is associated with the actions of "Generate Alarm Event" and "Send to Cloud".

[0053] S105: After the logic is written, click the compile button. The platform will convert the graphical logic into a structured XML configuration file. Before downloading, you can use the platform's built-in function to import a recording of an actual GCB closing process (including current waveforms and switching quantity changes), run the simulation, and intuitively observe the state changes of each component in the logic chain to verify the correctness of the logic.

[0054] S106: Connect the ETH1 interface of the smart terminal 101 via the network cable of the engineering station, and use the platform's download function to download the compiled configuration file and the display screen file created using the accompanying human-machine interface template design software to the memory of the system motherboard 120 of the smart terminal 101.

[0055] S2: The smart terminal 101 runs the configuration file and performs local diagnostic analysis based on the collected data, as follows: S201: The system motherboard 120 collects current and voltage signals at a fixed frequency; S202: The MCU of the input / output module and the DC acquisition module collects switch signals and DC signals in real time, and actively or periodically sends data packets to the system motherboard 120 through the internal bus. S203: The expert diagnostic function module 111 in the platform software system 110 extracts the required signals from the real-time data queue according to the definition in the configuration file; calls the algorithm specified in the configuration file (such as calculating the effective value of the coil current) to perform calculation; and inputs the calculation results into the criteria specified in the configuration file (such as overcurrent criterion, timer) for logical judgment. When the logical conditions are met, a local action is triggered, an event log is generated, and feature data is extracted. For example, when the logical condition of "closing coil fault" is met, a preset action is triggered immediately: a) Send a command to the input / output module via the CAN bus to drive the specified relay to act (the local indicator light illuminates); b) Generate a high-priority event "GCB001 closing coil fault" and store it in the file system; c) Extract fault feature data (such as the coil current waveform for 5 cycles before and after the fault).

[0056] S3: The intelligent terminal uploads diagnostic process data, feature data, or diagnostic results to the remote system, and / or receives instructions or updates from the remote system, as follows: S301: Upload diagnostic event reports and characteristic data waveform files to the cloud expert system via the IEC 61850 MMS protocol; for example, the communication task of smart terminal 101 uses the ETH2 interface and the IEC 61850 MMS protocol to automatically upload the generated "closing coil fault" event report and the compressed characteristic data waveform file to the cloud expert system.

[0057] The cloud-based expert system aggregates monitoring data from multiple similar GCBs across the network. Through big data analysis, it may discover new fault modes (for example, a specific waveform of coil current may indicate a certain type of valve core jamming). The cloud-based experts can then optimize their diagnostic algorithms based on this information.

[0058] The cloud-based expert system can send the optimized algorithm model or new criterion thresholds to the smart terminal 101 via a secure channel in the form of configuration file updates.

[0059] S302: The smart terminal 101 receives the optimization algorithm model or criterion threshold update issued by the cloud expert system; S303: After engineer confirmation, the new configuration file is loaded online to enable iteration and optimization of diagnostic capabilities.

[0060] This invention is not limited to the specific embodiments described above. The invention extends to any new feature or combination disclosed in this specification, as well as any new method or process step or combination disclosed herein.

Claims

1. A cloud-edge diagnostic system, characterized in that, include: A smart terminal, and a graphical configuration tool that is set separately from the smart terminal; The smart terminal includes: The system motherboard and at least one expansion module that communicates with the system motherboard via an internal bus, the expansion module having an independent microcontroller built in, the system motherboard including: a core processor, an analog sampling module and a memory group; The human-machine interface unit is connected to the system motherboard; A platform-based software system is integrated and runs on the system motherboard, wherein the platform-based software system includes an expert diagnostic function module; The graphical configuration tool runs on an external computing device and is used to generate configuration files; the smart terminal is configured to download and run the configuration files to perform corresponding operations according to the logic defined in the configuration files.

2. The cloud-edge diagnostic system according to claim 1, characterized in that, The expansion module includes at least one of the following: intelligent input / output module, AC / DC analog quantity acquisition module, DC signal acquisition module, and circuit breaker operation circuit module.

3. The cloud-edge diagnostic system according to claim 1, characterized in that, The system motherboard also includes a communication interface for data communication with the graphical configuration tool and the remote system; the communication interface is an Ethernet interface and / or a serial communication interface.

4. The cloud-edge diagnostic system according to claim 1, characterized in that, The graphical configuration tool includes a graphical configurable logic programming platform, which provides graphical functional elements corresponding to the algorithms and criteria in the expert diagnosis function module. Users can build and compile the configuration file through the graphical configurable logic programming platform.

5. The cloud-edge diagnostic system according to claim 4, characterized in that, The graphical configuration tool also includes: The human-machine interface design module is used to design the interface template for display by the human-machine interface unit; The debugging module is communicatively connected to the smart terminal to debug the smart terminal.

6. The cloud-edge diagnostic system according to claim 4, characterized in that, The graphical configuration tool also includes a logic simulation module, which verifies diagnostic and control logic based on simulated or measured data.

7. The cloud-edge diagnostic system according to claim 1, characterized in that, The expert diagnostic function module is encapsulated in the form of a dynamic link library, including an algorithm library and a criterion library; The algorithm library includes at least one of the following: Fourier transform algorithm, order component calculation algorithm, power calculation algorithm, RMS value calculation algorithm, and integration / differentiation algorithm; The criterion library includes at least one of the following: overcurrent criterion, differential current criterion, overvoltage / undervoltage criterion, circuit breaker mechanical characteristic analysis criterion, coil current waveform analysis criterion, and inverse time overheating model.

8. A method for diagnosing equipment, characterized in that, Based on the cloud-edge diagnostic system according to any one of claims 1-7, the method includes: Define diagnostic logic through visual operations and generate corresponding configuration files; Download the configuration file to the smart terminal; The smart terminal runs the configuration file and performs local diagnostic analysis based on the collected data. The intelligent terminal uploads diagnostic process data, feature data, or diagnostic results to the remote system and / or receives instructions or updates from the remote system.

9. The equipment diagnostic method according to claim 8, characterized in that, The definition of diagnostic logic through visual operations includes: Configure hardware resources in a graphical configurable logic programming platform; Associate the virtual channel with the actual physical signal and rename it; Call the algorithm definition execution data in the expert diagnosis function module; Construct a diagnostic logic chain by dragging and dropping criteria and logic gate components; Compile to generate a structured configuration file.

10. The equipment diagnostic method according to claim 8, characterized in that, The smart terminal runs the configuration file to perform local diagnostic analysis, including: The system motherboard acquires current and voltage signals at a fixed frequency; The expansion module's independent microcontroller collects switch signals and DC signals in real time and sends them to the system motherboard via an internal bus; The expert diagnostic module extracts signals from the real-time data queue according to the configuration file, calls the specified algorithm for calculation, and inputs the specified criteria for logical judgment. When the logical conditions are met, a local action is triggered, an event log is generated, and feature data is extracted.

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