Electric power communication monitoring and analyzing device based on clustering technology

Abstract

The utility model discloses an electric power communication monitoring and analyzing device based on a clustering technology. The electric power communication monitoring and analyzing device comprises a data processing device, an external storage device and a wireless communication device, the data processing device and the system-on-chip are respectively connected with the Ethernet interface, the serial peripheral interface, the SD card interface and the PCB antenna through a bus, and the system-on-chip comprises an LPDDR4 memory, a four-core CPU and a GPU and is used for deploying a clustering algorithm for electric power communication detection to analyze and process communication data of an electric power system; the external storage device adopts an SD (Secure Digital) card; and the wireless communication device and the WiFi control chip are used for converting analysis and processing results of the communication data of the power system into wireless signals. The device is simple to operate, provides better guarantee for improving the clustering classification accuracy and sensitivity, and has universality and applicability.

Description

Technical Field

[0001] This utility model relates to a power communication monitoring and analysis device based on clustering technology, belonging to the field of power system computer technology. Background Technology

[0002] Power communication monitoring and analysis technology has gained increasing attention with the intelligentization and informatization of power systems. As a crucial information transmission link in the power system, power communication undertakes key tasks such as data exchange between equipment, status monitoring, and fault diagnosis. Traditional power communication monitoring methods mainly rely on manual inspections and simple data recording. This approach is not only inefficient but also susceptible to human factors, leading to inaccurate or missing data. Therefore, power communication monitoring and analysis devices based on modern information technology have emerged to improve the safety and reliability of power systems.

[0003] In recent years, with the rapid development of the Internet, big data, and artificial intelligence technologies, power communication monitoring and analysis has gradually transformed towards automation and intelligence. Existing power communication monitoring devices and methods, including network protocol-based monitoring tools, data acquisition terminals, and remote monitoring systems, while improving monitoring efficiency to some extent, still suffer from insufficient data processing capabilities, long response times, and poor adaptability. These devices often struggle to analyze large amounts of data in real time and fail to promptly identify potential anomalies, thus impacting the overall operation of the power system.

[0004] Against this backdrop, clustering technology, as an effective data mining and analysis method, has gradually been introduced into power communication monitoring and analysis. Clustering technology can automatically identify patterns and trends in large amounts of data through classification and summarization, thereby helping maintenance personnel quickly locate problems and improve fault prediction capabilities. However, existing power communication monitoring and analysis devices are no longer able to efficiently integrate clustering technology for power communication monitoring and analysis. Therefore, those skilled in the art urgently need to improve power communication monitoring and analysis devices that utilize clustering technology. Utility Model Content

[0005] Objective: To overcome the shortcomings of existing technologies, this utility model provides a power communication monitoring and analysis device based on clustering technology. It provides an efficient, low-power, and flexible edge computing device for real-time collection of power communication network data and for clustering and analysis of power communication data. It also provides a platform for optimizing power communication network configuration and expanding the application of machine learning in the field of power communication security device technology.

[0006] Technical solution: To solve the above technical problems, the technical solution adopted by this utility model is as follows:

[0007] A power communication monitoring and analysis device based on clustering technology includes: a data processing device, an external storage device, and a wireless communication device.

[0008] The data processing device includes a motherboard, on which a system-on-a-chip (SoC), an Ethernet interface, a serial peripheral interface, an SD card interface, and a PCB antenna are mounted. The SoC is connected to the Ethernet interface, the serial peripheral interface, the SD card interface, and the PCB antenna via a bus. The SoC includes LPDDR4 memory, a quad-core CPU, and a GPU, and is used to deploy a clustering algorithm for power communication detection to analyze and process power system communication data.

[0009] The external storage device uses an SD card, which is connected to an SD card interface to store power system communication data.

[0010] The wireless communication device includes: a serial interface and a WiFi control chip. The serial interface is connected to a serial peripheral interface. The WiFi control chip is used to convert the analysis and processing results of power system communication data into wireless signals. The wireless signals are sent to the serial peripheral interface of the data processing device through the serial interface, and then sent to the host computer through the PCB antenna connected to the bus.

[0011] As a preferred option, the system-on-a-chip (SoC) is a Broadcom BCM2711 SoC. The Broadcom BCM2711 SoC features 4GB of LPDDR4 memory, a quad-core ARM Cortex-A72 CPU, and a Videocore VI GPU that supports OpenGL ES 3.0, which is used to further support the operation of clustering algorithms.

[0012] As a preferred embodiment, the data processing device is a Raspberry Pi 4.

[0013] As a preferred option, the SD card is an external Samsung EVO Select SDXC storage card with a capacity of 64GB.

[0014] As a preferred option, the WiFi control chip is a Broadcom BCM43455.

[0015] As a preferred option, the Ethernet interface adopts an RJ-45 interface.

[0016] Beneficial Effects: This utility model provides a power communication monitoring and analysis device based on clustering technology. The Raspberry Pi 4, as a highly flexible and powerful terminal hardware device, can support complex algorithms and multitasking. Its compact size and low power consumption allow for flexible deployment in various environments, providing a new solution for power communication monitoring. This utility model is simple to operate, provides better assurance for improving the accuracy and sensitivity of clustering classification, and has versatility and applicability. Attached Figure Description

[0017] Figure 1 This is a structural framework diagram of the analytical device of this utility model.

[0018] Figure 2 This is a schematic diagram of the framework principle of the power communication monitoring cluster analysis system of this utility model.

[0019] Figure 3 This is a physical image of the data processing device of this utility model.

[0020] Figure 4 This is a physical diagram of the interface of the data processing device of this utility model. Detailed Implementation

[0021] The technical solutions of this utility model will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this utility model, and not all embodiments. Based on the embodiments of this utility model, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of this utility model.

[0022] The present invention will be further described below with reference to specific embodiments.

[0023] Example 1:

[0024] This embodiment introduces a power communication monitoring and analysis device based on clustering technology, such as... Figure 1 As shown, it includes: a data processing device 1, an external storage device 2, and a wireless communication device 3.

[0025] The data processing device 1 includes a motherboard, on which a system-on-a-chip (SoC), an Ethernet interface, a serial peripheral interface, an SD card interface, and a PCB antenna are mounted. The SoC is connected to the Ethernet interface, the serial peripheral interface, the SD card interface, and the PCB antenna via a bus. The SoC includes LPDDR4 memory, a quad-core CPU, and a GPU, and is used to deploy a clustering algorithm for power communication detection to analyze and process power system communication data.

[0026] The external storage device 2 uses an SD card, which is connected to an SD card interface and is used to store power system communication data.

[0027] The wireless communication device 3 includes: a serial interface and a WiFi control chip. The serial interface is connected to a serial peripheral interface. The WiFi control chip is used to convert the analysis and processing results of power system communication data into wireless signals. The wireless signals are sent to the serial peripheral interface of the data processing device 1 through the serial interface, and then sent to the host computer through the PCB antenna connected to the bus.

[0028] Furthermore, the system-on-a-chip (SoC) is a Broadcom BCM2711 SoC, which features 4GB of LPDDR4 memory, a quad-core ARM Cortex-A72 CPU, and a Videocore VI GPU supporting OpenGL ES 3.0, making it suitable for running clustering algorithms.

[0029] Furthermore, the data processing device 1 uses a Raspberry Pi 4.

[0030] Furthermore, the SD card is an external Samsung EVO Select SDXC storage card with a capacity of 64GB.

[0031] Furthermore, the WiFi control chip is a Broadcom BCM43455.

[0032] Example 2:

[0033] This embodiment describes the working principle of a power communication monitoring and analysis device based on clustering technology, such as... Figure 2 As shown, the power system network equipment is connected to the Ethernet port of the Raspberry Pi 4 platform of this device via an Ethernet port. The Raspberry Pi 4 platform runs data acquisition scripts through protocols such as RESTful API, Socket, or SNMP, and acquires power system communication data through the Ethernet port. This power system communication data is then transmitted to an external SD card via the SD card interface, providing data for subsequent power communication processing. The power system communication data includes user access and data stream information.

[0034] The process of setting up the Raspberry Pi 4 platform environment is as follows: (1) Connect the peripheral storage module to the Ethernet and power communication system; (2) Burn the system image; (3) Start the hardware platform; (4) Install the Python module; (5) Install the corresponding packages for clustering and analysis algorithms; (6) Run the corresponding script files.

[0035] The Raspberry Pi 4 platform preprocesses the collected user access and data flow information to obtain data with the same format and structure as the dataset used in training the model. It then uses the clustering algorithm deployed for power communication detection to process the extracted features, thereby enabling the detection and identification of intrusions. The detection results are then visualized and an analysis report is generated and sent to the terminal control unit of the power communication monitoring system, enabling interactive control between the device and the outside world.

[0036] The power communication monitoring and analysis device based on clustering technology provides an effective platform for real-time processing of large amounts of data from the power system and automatic generation of monitoring reports through cluster analysis, helping maintenance personnel make decisions more quickly. Furthermore, leveraging the multiple interfaces and scalability of the Raspberry Pi 4, the device can be easily integrated with existing monitoring systems to achieve data interconnection. The advantages of this device lie in its efficiency and intelligence, significantly reducing the need for manual intervention and improving the accuracy and timeliness of power communication monitoring.

[0037] like Figure 3-4 As shown, the Raspberry Pi 4 integrates a chip for implementing clustering analysis algorithms, as well as other dedicated interfaces for easy data acquisition and computation. It integrates an HDMI data transfer interface, a gigabit Ethernet port, and Bluetooth for easy transmission of various information, and a USB serial port for expanding power supply to other hardware devices and development platforms.

[0038] The above description is only a preferred embodiment of the present utility model. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present utility model, and these improvements and modifications should also be considered within the protection scope of the present utility model.

Claims

1. A power communication monitoring and analysis device based on clustering technology, characterized in that: include: Data processing device, external storage device, and wireless communication device; The data processing device includes: a motherboard, on which a system-on-a-chip (SoC), an Ethernet interface, a serial peripheral interface, an SD card interface, and a PCB antenna are mounted. The SoC is connected to the Ethernet interface, the serial peripheral interface, the SD card interface, and the PCB antenna via a bus. The SoC includes LPDDR4 memory, a quad-core CPU, and a GPU, and is used to deploy a clustering algorithm for power communication detection to analyze and process power system communication data. The external storage device uses an SD card, which is connected to an SD card interface and is used to store power system communication data. The wireless communication device includes: a serial interface and a WiFi control chip. The serial interface is connected to a serial peripheral interface. The WiFi control chip is used to convert the analysis and processing results of power system communication data into wireless signals. The wireless signals are sent to the serial peripheral interface of the data processing device through the serial interface, and then sent to the host computer through the PCB antenna connected to the bus.

2. The power communication monitoring and analysis device based on clustering technology according to claim 1, characterized in that: The system-on-a-chip (SoC) is a Broadcom BCM2711 SoC. The Broadcom BCM2711 SoC features 4GB of LPDDR4 memory, a quad-core ARM Cortex-A72 CPU, and a Videocore VI GPU that supports OpenGL ES 3.0, which is used to further support the operation of clustering algorithms.

3. The power communication monitoring and analysis device based on clustering technology according to claim 2, characterized in that: The data processing device is a Raspberry Pi 4.

4. The power communication monitoring and analysis device based on clustering technology according to claim 1, characterized in that: The SD card is an external Samsung EVO Select SDXC with a storage capacity of 64GB.

5. The power communication monitoring and analysis device based on clustering technology according to claim 1, characterized in that: The WiFi control chip is a Broadcom BCM43455.

6. The power communication monitoring and analysis device based on clustering technology according to claim 1, characterized in that: The Ethernet interface uses an RJ-45 interface.

Images