Low-power multi-parameter intelligent sensing method, device and computer equipment

Abstract

The present application relates to a low-power multi-parameter intelligent sensing method, device, computer equipment, computer-readable storage medium, and computer program product. The method includes: installing a measuring energy acquisition gripper module on each conductor of a transmission line, and electrically connecting the measuring energy acquisition gripper module to a multi-parameter intelligent monitoring host; using the measuring energy acquisition gripper module to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line, and transmitting them to the multi-parameter intelligent monitoring host; using the multi-parameter intelligent monitoring host to process the power consumption of the transmission line; wherein, using the first processor of the multi-parameter intelligent monitoring host to perform AI recognition and multimedia interaction on the transmission line, and using the second processor of the multi-parameter intelligent monitoring host to control the low-power operation and power management of the multi-parameter intelligent monitoring host. The use of this method can improve the performance and efficiency of the monitoring device, while enhancing the stability and reliability of the device.

Description

Technical Field

[0001] The present application relates to the technical field of power transmission line power consumption monitoring, and in particular to a low-power multi-parameter intelligent sensing method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art

[0002] In recent years, my country has placed significant emphasis on digital development, raising the bar for the application of digital technologies, including intelligent sensing, in the power industry. Related technologies point to a transparent grid as the future of the power grid. This approach effectively integrates sensor technology, information technology, data communications technology, electronic control technology, and artificial intelligence into power systems, enabling transparency in equipment status, operational status, and transaction status.

[0003] Currently, major online monitoring systems use numerous discrete, single sensors to monitor power system operating conditions. This lacks effective integration and information sharing at the sensor level, hindering the development of technologies such as multi-parameter information fusion and sharing, as well as comprehensive diagnostics, making them inadequate for the development of smart grids. Multi-integrated sensors, on the other hand, utilize miniaturized integration, simultaneous detection of multiple physical quantities, full-scale measurement, and on-demand analog / digital formats. These sensors integrate sensitive components, signal conditioning circuits, microprocessors, and communication interface modules, demonstrating the intelligent sensing of multiple environmental physical quantities and sensor information fusion. The intelligentization and informatization of smart grids require the deployment of a large number of sensors and data acquisition modules. The integration of sensors and corresponding data acquisition and transmission systems to form multi-physical quantity integrated sensor arrays and the use of multi-dimensional information analysis techniques for efficient device status analysis and fault diagnosis is a hot research topic in the development of digital power grids.

[0004] The contradiction between the rapid growth of power grid operation and maintenance line mileage and the relatively insufficient number of grid operation and maintenance personnel is gradually emerging. With the advancement of smart grid construction and the development of artificial intelligence technology, transmission line inspections have transitioned from traditional "human patrols" to a "human patrol + drone patrol" phase. However, drone flight capabilities are limited by weather and battery life. There are also problems such as limited monitoring capacity to images, high operator skill requirements, short patrol distances, and the impact of no-fly zones. As a result, they fail to fully and real-timely cover the monitoring needs of transmission lines. Furthermore, there is the challenge of how to achieve data fusion from multiple integrated sensors and transmit data over long distances back to the server. Therefore, in order to further improve the observability of power grid operation and enhance the information perception capability of transmission lines, it is necessary to study multi-sensor integration technology to realize all-round and multi-angle monitoring of transmission lines. By studying multi-physical quantity integrated sensor technology, massive deployment of integrated sensor elements can be realized; multi-physical quantity integrated sensor distributed self-organizing network data communication technology can be studied to complete the networking communication between multiple multi-physical quantity integrated sensor devices; integrated sensor multi-physical quantity data analysis, feature extraction technology and auxiliary decision-making technology can be studied, multi-physical quantity data fusion application system can be developed, and dynamic capacity expansion monitoring software module for transmission line can be developed to promote the application of artificial intelligence technology in massive monitoring data of transmission lines, solve the actual operation and maintenance needs of transmission lines, realize high-efficiency and low-latency real-time transmission of measurement data to the server for processing and real-time monitoring of the working status of transmission lines, so as to achieve the goal of automation, informatization and digitization of intelligent monitoring of transmission lines, and ultimately achieve the goal of transparent perception of power grids.

[0005] In order to solve the above problems, the present invention proposes a low-power multi-parameter intelligent sensing method, device, computer equipment, computer-readable storage medium and computer program product, aiming to improve the performance and efficiency of the monitoring device while enhancing the stability and reliability of the device. Summary of the Invention

[0006] Based on this, it is necessary to provide a low-power multi-parameter intelligent sensing method, device, computer equipment, computer-readable storage medium and computer program product to address the above technical problems, which can improve the performance and efficiency of the monitoring device while enhancing the stability and reliability of the device.

[0007] In a first aspect, the present application provides a low-power multi-parameter intelligent sensing method, comprising:

[0008] A measuring and energy-taking gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality of the measuring and energy-taking gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring and energy-taking gripper module is electrically connected to a multi-parameter intelligent monitoring host, and the equipotentiality of the measuring and energy-taking gripper module and the multi-parameter intelligent monitoring host is achieved through a power ground wire;

[0009] The measuring and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; wherein, the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal;

[0010] The multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host, and the first processor has an embedded neural network processing unit.

[0011] In one embodiment, the first processor is communicatively connected to the second processor and shares a same wireless communication module; wherein the first processor and the second processor do not use the wireless communication module at the same time; and the specific process of the first processor and the second processor not using the wireless communication module at the same time includes:

[0012] Before the first processor or the second processor applies to use the wireless communication module, determining whether an application mark exists in an application register of the wireless communication module;

[0013] In the absence of the application mark, it indicates that the working state of the wireless communication module is an idle state, and the use of the wireless communication module is allowed.

[0014] In one embodiment, the processing of the power transmission line power consumption by the multi-parameter intelligent monitoring host includes:

[0015] Monitoring the motion data of the conductor using an accelerometer and a posture sensing unit, wherein the motion data includes vibration data, galloping data, windage data, and torsion data;

[0016] analyzing, based on the motion data, whether the lateral acceleration of the wire exceeds a preset acceleration threshold;

[0017] When the lateral acceleration exceeds a preset acceleration threshold, a galloping recording function is triggered and the conductor galloping amplitude is calculated.

[0018] In one embodiment, the process of calculating the wire galloping amplitude includes:

[0019] Filtering the collected acceleration signals and angular velocity signals;

[0020] Through numerical integration, the filtered acceleration signal and angular velocity signal are converted into velocity signal, and then into displacement signal;

[0021] Identify the periodic characteristics of the conductor's galloping motion and determine the zero velocity point;

[0022] In each dancing cycle, piecewise integration is performed from the velocity zero point to the next velocity zero point to calculate the displacement change in each cycle;

[0023] According to the displacement change in each cycle, the average displacement in all dancing cycles is calculated to obtain the wire dancing amplitude.

[0024] In one embodiment, the processing of the power transmission line power consumption by the multi-parameter intelligent monitoring host includes:

[0025] When the CT energy voltage data is less than a first preset voltage threshold, the system enters an ultra-low power consumption mode, controls the first starter module to suspend operation, controls the wireless communication module and the temperature and humidity sensing unit to operate, and uploads temperature and humidity data at preset intervals;

[0026] When the CT energy acquisition voltage data is greater than or equal to a first preset voltage threshold and less than a second preset voltage threshold, the system enters a low power consumption mode, controls the wireless communication module, the Beidou unit, and the attitude sensing unit to operate, controls the first starter module to suspend operation, uses a dancing amplitude estimation model constructed based on historical dancing amplitude data to estimate the conductor dancing amplitude, and uploads conductor dancing and sag data; and, when sufficient power is supplied, iteratively updates the dancing amplitude estimation model in real time using the acceleration signal and angular velocity signal measured by the attitude sensing unit.

[0027] When the CT energy-taking voltage data is greater than or equal to the second preset voltage threshold, the full-function mode is entered, the first starter module is controlled to start working, local debugging is performed, and alarm data in the image data of the power line is monitored and transmitted.

[0028] In a second aspect, the present application also provides a low-power multi-parameter intelligent sensing device, comprising:

[0029] The measuring energy acquisition gripper module is electrically connected to the multi-parameter intelligent monitoring host and is installed on each conductor of the transmission line; the power output is formed by electromagnetic induction, and the equipotentiality of the measuring energy acquisition gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring energy acquisition gripper module is electrically connected to the multi-parameter intelligent monitoring host, and the equipotentiality of the measuring energy acquisition gripper module and the multi-parameter intelligent monitoring host is achieved through the power ground wire;

[0030] The measuring and energy acquisition gripper module is used to collect current data, conductor temperature data and CT energy acquisition voltage data of the transmission line, wherein the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal;

[0031] The multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line, wherein the multi-parameter intelligent monitoring host includes a first processor and a second processor, and the first processor has an embedded neural network processing unit;

[0032] The first processor is used to perform AI recognition and multimedia interaction on the transmission line;

[0033] The second processor is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host.

[0034] In one embodiment, a shielded cable containing multiple conductor cores is used to transmit information between the measuring and energy-acquisition gripper module and the multi-parameter intelligent monitoring host;

[0035] At least one conductor core of the shielded cable is used to transmit conductor temperature data, at least one conductor core is used to transmit current data of the transmission line, and at least one conductor core is used to transmit CT energy supply voltage data.

[0036] In one embodiment, the first processor includes a first main control chip, and a posture sensing unit, a battery detection unit, a capacitance detection unit, a CT energy acquisition voltage data detection unit, a temperature and humidity sensing unit, an air pressure sensing unit, an accelerometer and a Beidou unit connected to the first main control chip;

[0037] The second processor includes a second main control chip, and a WIFI module, an embedded multimedia card EMMC, a power chip and a camera unit connected to the second main control chip.

[0038] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0039] A measuring and energy-taking gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality of the measuring and energy-taking gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring and energy-taking gripper module is electrically connected to a multi-parameter intelligent monitoring host, and the equipotentiality of the measuring and energy-taking gripper module and the multi-parameter intelligent monitoring host is achieved through a power ground wire;

[0040] The measuring and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; wherein, the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal;

[0041] The multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host, and the first processor has an embedded neural network processing unit.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0043] A measuring and energy-taking gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality of the measuring and energy-taking gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring and energy-taking gripper module is electrically connected to a multi-parameter intelligent monitoring host, and the equipotentiality of the measuring and energy-taking gripper module and the multi-parameter intelligent monitoring host is achieved through a power ground wire;

[0044] The measuring and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; wherein, the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal;

[0045] The multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host, and the first processor has an embedded neural network processing unit.

[0046] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0047] A measuring and energy-taking gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality of the measuring and energy-taking gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring and energy-taking gripper module is electrically connected to a multi-parameter intelligent monitoring host, and the equipotentiality of the measuring and energy-taking gripper module and the multi-parameter intelligent monitoring host is achieved through a power ground wire;

[0048] The measuring and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; wherein, the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal;

[0049] The multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host, and the first processor has an embedded neural network processing unit.

[0050] The low-power, multi-parameter intelligent sensing method, device, computer equipment, computer-readable storage medium, and computer program product described above, by installing a measurement and energy acquisition gripper module on each conductor, can collect real-time data on transmission line current, conductor temperature, and CT energy draw voltage, ensuring the timeliness and accuracy of the monitoring data. The multi-parameter intelligent monitoring host can effectively monitor the power consumption of transmission lines, provide real-time energy consumption analysis, and help optimize grid operation. The first processor implements AI recognition and multimedia interaction for transmission lines, automatically identifying potential fault risks and providing feedback through multimedia data (such as images and videos), enhancing the intelligent level of monitoring. The second processor controls the low-power operation and power management of the multi-parameter intelligent monitoring host, adjusting the system's operating state based on actual CT energy draw voltage conditions, extending the device's service life and reducing energy consumption. The separation of the measurement and energy acquisition gripper module and the multi-parameter intelligent monitoring host improves system maintainability and reliability, facilitating troubleshooting and repair. In summary, this method, through its dual-controller architecture and modular design, enhances the intelligent, real-time, and energy-efficient management capabilities of transmission line monitoring, offering significant technical advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 A diagram illustrating an application environment of a low-power multi-parameter intelligent sensing method according to an embodiment;

[0053] Figure 2 A power transmission line multi-physical quantity integrated sensor for a low-power multi-parameter intelligent sensing device in one embodiment;

[0054] Figure 3 A standard spacer rod for a low-power multi-parameter intelligent sensing device in one embodiment;

[0055] Figure 4 1 is a flow chart of a low-power multi-parameter intelligent sensing method according to an embodiment;

[0056] Figure 5 1 is a flow chart of a low-power multi-parameter intelligent sensing method according to another embodiment;

[0057] Figure 6 A structural block diagram of a low-power multi-parameter intelligent sensing device according to an embodiment;

[0058] Figure 7 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0060] The low-power multi-parameter intelligent sensing method provided by the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 via a network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104 or placed on the cloud or other network servers.

[0061] The server 104 uses the measurement and energy acquisition claw module to collect the current data, conductor temperature data and CT energy acquisition voltage data of the transmission line, and transmits it to the multi-parameter intelligent monitoring host; the multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host.

[0062] Terminal 102 may include, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, smart car devices, and projectors. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Head-mounted devices may include virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, and the like. Server 104 may be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server providing cloud computing services.

[0063] like Figure 2 As shown, the multi-physical integrated sensor of the transmission line is demonstrated ( Figure 3 The multi-physical quantity integrated sensor (multi-split) for transmission lines is a smart housekeeper for panoramic real-time monitoring and intelligent early warning of overhead transmission lines. It adopts wide-range induction self-powering technology to ensure continuous and reliable operation of the device, and provides continuous and reliable power supply to the sensor through distributed wide-range induction power supply modules, realizing real-time online intelligent monitoring of low-load lines, and has the advantages of easy scalability and high reliability.

[0064] like Figure 3The figure shows a standard spacer. The multi-split version of the transmission line multi-physical quantity integrated sensor is integrated with the standard spacer and can be directly installed on 500kV transmission lines. The dual-split and single-conductor versions feature a scalable, lightweight, integrated design and can be directly installed on 110 / 220kV transmission lines. The power measurement gripper module is compatible with various split conductor types. It utilizes an independent measurement gripper structure and connects to a multi-parameter intelligent monitoring host via a flexible cable. It integrates sub-current data, conductor temperature data, and CT energy voltage data, ensuring reliable equipotential between the device and the conductor. The multi-parameter intelligent monitoring host modularly integrates visible light, ultraviolet light, and infrared cameras, ambient temperature and humidity sensors, air pressure sensors, accelerometers, attitude sensors, and a high-precision Beidou positioning unit. The device supports access to IoT platforms, file servers, and video servers, and features online fusion sensing and intelligent abnormality identification and alarming for physical quantities such as conductor temperature, current, sag, and galloping; ambient temperature, humidity, air pressure, and altitude; and channel visible light images and videos, as well as ultraviolet and infrared (optional).

[0065] In an exemplary embodiment, Figure 4 As shown in the figure, a low-power multi-parameter intelligent sensing method is provided, which is applied to Figure 1 The server in the example is used to illustrate the process, including the following steps S402 to S406.

[0066] In step S402, a measuring energy acquisition gripper module is installed on each conductor of the transmission line, power output is generated through electromagnetic induction, and the equipotentiality of the measuring energy acquisition gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring energy acquisition gripper module is electrically connected to the multi-parameter intelligent monitoring host, and the equipotentiality of the measuring energy acquisition gripper module and the multi-parameter intelligent monitoring host is achieved through the power ground wire.

[0067] Specifically, installing a measurement and energy acquisition gripper module on each conductor enables distributed monitoring of transmission lines. This means that each conductor can independently monitor parameters such as current and temperature, providing more comprehensive line status information. The measurement and energy acquisition gripper module is electrically connected to the multi-parameter intelligent monitoring host via an aviation plug. This design provides a highly reliable connection, ensuring stable and reliable data transmission while also being resistant to the effects of harsh outdoor environments.

[0068] The measurement and energy acquisition gripper module generates electrical energy using the principle of electromagnetic induction. When current flows through a conductor, it generates a magnetic field. The module senses this magnetic field and converts it into electrical energy, generating a power output. To ensure that the measurement and energy acquisition gripper module and the conductor are at the same electrical potential, conductive rubber and electrical connections are used. Conductive rubber, a conductive material, connects the module and the conductor, ensuring a zero potential difference between them, ensuring safe measurement and energy transfer. The measurement and energy acquisition gripper module requires an electrical connection to a central monitoring device—the multi-parameter intelligent monitoring host. The multi-parameter intelligent monitoring host collects, analyzes, and processes data from each module. To ensure a zero potential difference between the measurement and energy acquisition gripper module and the multi-parameter intelligent monitoring host, a power ground wire is used. The power ground wire is a wire that connects the device to the ground. It ensures consistent electrical potential between devices and prevents interference or safety issues caused by potential differences.

[0069] By adding a measurement power gripper module to each conductor, the load on the power supply structure can be effectively distributed, avoiding the bulky and heavy issues associated with single-point power supply structures, thereby reducing overall system power consumption. The measurement power gripper module supports plug-and-play (hot-swappable) connectivity with the multi-parameter intelligent monitoring host, enabling quick and easy module replacement during installation and maintenance, improving maintenance efficiency. The measurement power gripper module also features a reverse power supply function. If the CT power supply voltage is insufficient, the multi-parameter intelligent monitoring host's supercapacitor can supply power to the measurement power gripper module, ensuring its continued operation even in this situation.

[0070] Step S404, using the measurement and energy acquisition gripper module to collect the current data, conductor temperature data and CT energy acquisition voltage data of the transmission line; wherein, the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal.

[0071] Specifically, the measurement and acquisition claw module integrates multiple sensors and a CT voltage sensor to simultaneously collect key operating parameters of the transmission line, including current data, conductor temperature data, and CT voltage data. Using current acquisition capabilities such as Rogowski coils, the measurement claw module monitors conductor current. Using NTC and infrared temperature measurement technologies, the measurement claw module monitors conductor temperature in real time, preventing line failures caused by overheating.

[0072] The measurement and energy acquisition gripper module uses Permalloy as the CT energy voltage core, enabling CT voltage acquisition functionality. This allows for power supply via wire induction while simultaneously collecting CT voltage data to monitor the CT voltage status. The MCU (microcontroller unit) within the measurement and energy acquisition gripper module processes the collected data and communicates with the multi-parameter intelligent monitoring host, transmitting the data to the host. This transmission method multiplexes measurement and CT voltage acquisition, improving data transmission efficiency and reliability.

[0073] Current data is transmitted to the multi-parameter intelligent monitoring host using analog differential signals, which reduces noise interference during transmission and improves signal accuracy and stability. Conductor temperature data and CT energy-sampling voltage data are transmitted using digital signals, which means they are converted to digital format before transmission. This allows for efficient data processing and analysis within the multi-parameter intelligent monitoring host and facilitates integration with other digital systems, such as computers.

[0074] The connection between the measurement and energy acquisition gripper module and the multi-parameter intelligent monitoring host is plug-and-play, which means that modules can be quickly and easily replaced during installation and maintenance, improving maintenance efficiency. During data transmission, the system adopts a low-power design to ensure that energy consumption of the entire monitoring device is minimized, extending the equipment's lifespan and reducing operating costs.

[0075] Step S406, using the multi-parameter intelligent monitoring host to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host, and the first processor has an embedded neural network processing unit.

[0076] Specifically, the multi-parameter intelligent monitoring host is the core of the entire monitoring device. It is responsible for collecting and measuring current data, conductor temperature data, and CT power supply voltage data transmitted by the energy acquisition gripper module. Based on this data, it monitors and manages the power consumption of the transmission line. This helps optimize transmission efficiency and reduce energy loss.

[0077] The first processor (Master 1) of the multi-parameter intelligent monitoring host is a low-power embedded intelligent processor with a built-in neural network processing unit. It is responsible for performing more complex tasks, such as on-device AI recognition. This means it can intelligently analyze the operating status of transmission lines, identify potential external damage risks such as wildfires, smoke, cranes, and excavators, and provide real-time feedback and alarms through multimedia data interaction (such as photos and videos).

[0078] The multi-parameter intelligent monitoring host's second processor (Master 2) is a low-power microprocessor responsible for controlling the low-power operation and power management of the entire monitoring device. This includes adjusting the device's operating mode under different power conditions to ensure optimal energy performance under varying energy supply conditions. For example, when energy is insufficient, it reduces power consumption by shutting down non-essential modules, while when energy is sufficient, it activates more functions for more comprehensive monitoring.

[0079] The dual-controller architecture enables more efficient resource allocation and function management. Master 1 and Master 2 can work together to handle different tasks, while simultaneously communicating via RS485 to ensure accurate data transmission and timely execution of commands.

[0080] In this low-power, multi-parameter intelligent sensing method, by installing a measurement and energy acquisition gripper module on each conductor, real-time data on transmission line current, conductor temperature, and CT power supply voltage can be collected, ensuring the timeliness and accuracy of the monitoring data. The multi-parameter intelligent monitoring host effectively monitors power consumption on the transmission line, provides real-time energy consumption analysis, and helps optimize grid operation. The first processor implements AI-powered recognition and multimedia interaction for the transmission line, automatically identifying potential fault risks and providing feedback through multimedia data (such as images and videos), enhancing the intelligent level of monitoring. The second processor controls the low-power operation and power management of the multi-parameter intelligent monitoring host, adjusting the system's operating state based on actual CT power supply voltage conditions, extending the equipment's service life and reducing energy consumption. The separation of the measurement and energy acquisition gripper module and the multi-parameter intelligent monitoring host enhances system maintainability and reliability, facilitating troubleshooting and repair. In summary, this method, through its dual-controller architecture and modular design, enhances the intelligent, real-time, and energy-efficient management capabilities of transmission line monitoring, offering significant technical advantages.

[0081] In an exemplary embodiment, the first processor is communicatively connected to the second processor and shares the same wireless communication module; wherein the first processor and the second processor do not use the wireless communication module at the same time.

[0082] Specifically, the first processor communicates with the wireless communication module via USB, while the second processor communicates with the wireless communication module via serial ports such as RS232 or RS485. This serial communication protocol allows the two processors to exchange data and instructions, ensuring that the different functions of the monitoring device can work together. Due to space and energy constraints in the monitoring device, the first and second processors share the same wireless communication module to achieve remote data transmission. This avoids the need for a separate wireless communication module for each processor, saving space and energy.

[0083] In this embodiment, through the communication protocol and the mutual exclusion lock mechanism, the first processor and the second processor can effectively share the wireless communication module to achieve stable data transmission, while avoiding resource conflicts and improving the operating efficiency and reliability of the entire monitoring device.

[0084] In an exemplary embodiment, Figure 5 As shown, the specific process of the first processor and the second processor not using the wireless communication module at the same time includes:

[0085] Step S502: Before applying to use the wireless communication module, the first processor or the second processor determines whether an application mark exists in an application register of the wireless communication module;

[0086] Step S504: when there is no application mark, it indicates that the working state of the wireless communication module is idle, and the use of the wireless communication module is allowed.

[0087] Specifically, before the first processor or the second processor needs to use the wireless communication module, it will first check a shared application register, which is used to identify whether the wireless communication module has been applied for.

[0088] The first or second processor checks the wireless communication module's request register for a request flag. This flag indicates whether another processor has requested access to the wireless communication module. If a request flag is present in the request register, the wireless communication module is currently in use by another processor. The requesting processor will be unable to obtain access and may need to wait or perform other tasks. If a request flag is absent, the wireless communication module is currently idle and not being used by any processor.

[0089] After confirming that the wireless communication module is idle (i.e., the application flag is not present in the application register), the current processor sets the application flag in the application register to formally apply for use of the wireless communication module. This step indicates that the current processor has obtained the right to use the wireless communication module.

[0090] Once the request register is marked, the current processor can start the wireless communication module to perform data transmission or other wireless communication tasks. During this process, other processors will not be able to access the wireless communication module until the processor with the current right of use completes the communication task and releases the wireless communication module.

[0091] When the current processor completes the wireless communication task, it will clear the application flag in the application register, release the wireless communication module, and make it idle again, so that it can be applied for by other processors.

[0092] For example, to prevent conflicts caused by two processors accessing the wireless communication module simultaneously, a 4G / 5G mutual exclusion lock mechanism based on the inter-board RS485 protocol was designed. This mechanism ensures that only one processor can use the wireless communication module at any given time. When the first processor (Master 1) needs to use the 4G / 5G module, it sets a bit in a predefined 4G / 5G request register. The second processor (Master 2) polls this request register. If it finds that the 4G / 5G request register is set and the 4G / 5G module is not currently in use, it sets a bit in another 4G / 5G available register to indicate that the 4G / 5G module is occupied by the first processor. After completing communication, the first processor resets the 4G / 5G request register, releasing the 4G / 5G module for use by the second processor.

[0093] In this embodiment, the first processor and the second processor can orderly share the wireless communication module, thereby avoiding conflicts caused by simultaneous access and ensuring the stability of data transmission and the efficient operation of the monitoring device.

[0094] In an exemplary embodiment, a multi-parameter intelligent monitoring host is used to process power consumption of a transmission line, including:

[0095] The motion data of the conductor is monitored by an accelerometer and an attitude sensing unit, and the motion data includes vibration data, galloping data, windage data and torsion data;

[0096] Analyzing the lateral acceleration of the conductor based on the motion data to determine whether it exceeds a preset acceleration threshold;

[0097] When the lateral acceleration exceeds the preset acceleration threshold, the galloping recording function is triggered and the wire galloping amplitude is calculated.

[0098] Specifically, accelerometers and attitude sensing units are used to monitor conductor motion. These sensors capture various conductor motion data, including vibration, galloping, windage (conductor deviation due to wind pressure), and torsion (conductor rotation or twisting). The monitored motion data is used to analyze the conductor's lateral acceleration. Lateral acceleration refers to the acceleration component perpendicular to the conductor's axis and is directly related to conductor galloping.

[0099] A lateral acceleration threshold is set to distinguish between normal and galloping states. When the lateral acceleration exceeds this threshold, the system deems the conductor to be in a galloping state. Once the detected lateral acceleration exceeds the preset threshold, the system automatically triggers the galloping recording function. This function records detailed information about the galloping event, including the start time, duration, and intensity of the galloping. When the galloping recording function is triggered, the system also calculates the conductor's galloping amplitude. The galloping amplitude refers to the maximum distance the conductor deviates from its stationary position during the galloping process and is a key parameter for assessing the severity of the galloping.

[0100] In this embodiment, by analyzing the galloping amplitude, it is possible to evaluate the impact of the galloping on the transmission line and whether corresponding measures need to be taken to reduce the galloping or its impact.

[0101] In an exemplary embodiment, the process of calculating the wire galloping amplitude includes:

[0102] Filtering the collected acceleration signals and angular velocity signals;

[0103] Through numerical integration, the filtered acceleration signal and angular velocity signal are converted into velocity signal, and then into displacement signal;

[0104] Identify the periodic characteristics of the conductor's galloping motion and determine the zero velocity point;

[0105] In each dancing cycle, piecewise integration is performed from the velocity zero point to the next velocity zero point to calculate the displacement change in each cycle;

[0106] According to the displacement change in each cycle, the average displacement in all dancing cycles is calculated to obtain the wire dancing amplitude.

[0107] Specifically, the collected acceleration and angular velocity signals often contain noise and interference. The goal of filtering is to remove this unwanted high-frequency noise while retaining the effective low-frequency signals, making the signals clearer and more accurate. Common filtering methods include low-pass filters, band-pass filters, and Kalman filters.

[0108] The filtered acceleration and angular velocity signals need to be converted into velocity and displacement signals. This step is usually achieved through numerical integration. The acceleration signal is integrated to obtain the velocity signal, which is then integrated again to obtain the displacement signal. Numerical integration methods include trapezoidal integration and Simpson integration. The galloping of transmission lines is often periodic, meaning that the movement of the conductor repeats at certain time intervals. By analyzing the velocity signal, the periodic characteristics of the gallop can be identified, namely points where the conductor velocity is zero, which mark the beginning and end of a galloping cycle.

[0109] Within each galloping cycle, piecewise integration is performed from zero velocity to the next zero velocity point, and the displacement change within each cycle is calculated. This means that within each cycle, the velocity signal is integrated from the moment the conductor velocity reaches zero to the moment the next velocity reaches zero, resulting in the displacement change within that cycle. Based on the displacement change within each cycle, the maximum displacement for each cycle, i.e., the galloping amplitude, can be calculated. The galloping amplitude refers to the maximum distance a conductor deviates from its stationary position during galloping and is an important parameter for assessing the severity of galloping. To obtain an overall galloping amplitude, the average displacement over all galloping cycles needs to be calculated. This can be achieved by adding the maximum displacement values ​​across all cycles and dividing by the number of cycles. The calculated average displacement value can be used to assess the severity and potential impact of transmission line galloping. If the galloping amplitude exceeds the designed safety threshold, measures may be necessary to reduce the galloping, such as increasing conductor tension or installing anti-galloping devices.

[0110] In this embodiment, the dance cycle and speed zero point are automatically identified, which reduces the workload of manual monitoring and improves the degree of automation of monitoring. Through precise numerical integration and piecewise integration methods, the displacement change within each dance cycle is calculated, thereby obtaining an accurate dance amplitude.

[0111] In an exemplary embodiment, a multi-parameter intelligent monitoring host is used to process power consumption of a transmission line, including:

[0112] When the CT energy voltage data is less than the first preset voltage threshold, the system enters the ultra-low power consumption mode, controls the first starter module to suspend operation, controls the wireless communication module and the temperature and humidity sensing unit to operate, and uploads the temperature and humidity data at a preset interval;

[0113] When the CT energy acquisition voltage data is greater than or equal to a first preset voltage threshold and less than a second preset voltage threshold, the system enters a low power consumption mode, controls the wireless communication module, the Beidou unit, and the attitude sensing unit to operate, controls the first starter module to suspend operation, uses a dancing amplitude estimation model constructed based on historical dancing amplitude data to estimate the conductor dancing amplitude, and uploads conductor dancing and sag data; and, when sufficient power is supplied, iteratively updates the dancing amplitude estimation model in real time using the acceleration signal and angular velocity signal measured by the attitude sensing unit.

[0114] When the CT energy-taking voltage data is greater than or equal to the second preset voltage threshold, the full-function mode is entered, the first starter module is controlled to start working, local debugging is performed, and alarm data in the image data of the power line is monitored and transmitted.

[0115] Specifically, when the CT energy acquisition voltage data collected by the energy acquisition gripper module is less than a first preset voltage threshold (e.g., 32V), the system enters ultra-low power mode. At this point, the multi-parameter intelligent monitoring host will control the first processor (main control 1) to suspend operation to reduce energy consumption. At the same time, the wireless communication module and temperature and humidity sensing unit remain operational, and temperature and humidity data are uploaded at preset intervals to maintain basic communication with the monitoring platform and environmental monitoring.

[0116] When the CT power supply voltage data is greater than or equal to a first preset voltage threshold and less than a second preset voltage threshold (e.g., 32-36V), the system enters low-power mode. At this point, the multi-parameter intelligent monitoring host controls the wireless communication module, Beidou unit (RTK), and attitude sensor unit. The first processor (main control 1) remains suspended while monitoring conductor galloping and sag data using the attitude sensor and RTK, and transmits this data to the monitoring platform via the 4G / 5G module. Using historical galloping amplitude data to build a prediction model can improve the accuracy of future galloping amplitude predictions. This model, typically based on statistical analysis, machine learning, or deep learning techniques, learns from historical data and predicts future trends. The prediction model can be integrated into the real-time monitoring system. Once a potential galloping risk is predicted, the system can automatically issue an alert, providing maintenance personnel with sufficient time to respond and take action, mitigating the risk of potential line failures. Predicting galloping amplitude helps power companies more effectively allocate maintenance resources and schedule maintenance work. For example, during periods of high risk, line inspections can be increased or emergency response measures can be deployed in advance.

[0117] When the CT energy-acquisition voltage data is greater than or equal to a second preset voltage threshold (for example, 36V), the system enters full-function mode. The multi-parameter intelligent monitoring host controls the first processor (Master Controller 1) to start operation and perform local debugging. Simultaneously, the specified visible light camera module is activated according to the operating mode set by Master Controller 2 to monitor the transmission line image data and identify warning data, such as wildfires and smoke. Once a risk is identified, the warning information and images are uploaded to the monitoring platform via the 4G / 5G module.

[0118] In this embodiment, the multi-parameter intelligent monitoring host dynamically adjusts its operating mode based on the CT power supply voltage, minimizing power consumption while ensuring monitoring efficiency. This intelligent adjustment mechanism enables the monitoring device to adapt to varying energy supply conditions, improving its ability to operate in the field for long periods of time and ensuring the provision of detailed monitoring data and alarm information at critical moments.

[0119] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0120] Based on the same inventive concept, the embodiments of the present application also provide a low-power multi-parameter intelligent sensing device for implementing the low-power multi-parameter intelligent sensing method mentioned above. The implementation solution provided by this device is similar to the implementation solution described in the above method. Therefore, the specific limitations of one or more low-power multi-parameter intelligent sensing device embodiments provided below can be found in the above-mentioned limitations of the low-power multi-parameter intelligent sensing method and will not be repeated here.

[0121] In an exemplary embodiment, Figure 6 As shown, a low-power multi-parameter intelligent sensing device is provided, including: the device includes a measuring energy acquisition gripper module 602 and a multi-parameter intelligent monitoring host 604, the measuring energy acquisition gripper module 602 and the multi-parameter intelligent monitoring host 604 are electrically connected, and both are installed on each conductor of the transmission line; the power output is generated by electromagnetic induction, and the equipotentiality of the measuring energy acquisition gripper module 602 and the conductor is achieved through conductive rubber and electrical connection; the measuring energy acquisition gripper module 602 is electrically connected to the multi-parameter intelligent monitoring host 604, and the equipotentiality of the measuring energy acquisition gripper module 602 and the multi-parameter intelligent monitoring host 604 is achieved through the power ground wire;

[0122] The measurement and energy acquisition gripper module 602 is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line and transmit them to the multi-parameter intelligent monitoring host 604. The current data is transmitted to the multi-parameter intelligent monitoring host 604 using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host 604 using a digital signal.

[0123] A multi-parameter intelligent monitoring host 604 is used to process the power consumption of the transmission line, wherein the multi-parameter intelligent monitoring host 604 includes a first processor 6042 and a second processor 6044, and the first processor 6042 and the second processor 6044 have embedded neural network processing units;

[0124] The first processor 6042 is configured to perform AI recognition and multimedia interaction on the power transmission line;

[0125] The second processor 6044 is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host 604.

[0126] In an exemplary embodiment, a shielded cable containing multiple conductor cores is used to transmit information between the measurement and energy acquisition gripper module 602 and the multi-parameter intelligent monitoring host 604;

[0127] At least one conductor core of the shielded cable is used to transmit conductor temperature data, at least one conductor core is used to transmit current data of the transmission line, and at least one conductor core is used to transmit CT energy supply voltage data.

[0128] In an exemplary embodiment, the first processor 6042 includes a first main control chip, and a posture sensing unit, a battery detection unit, a capacitance detection unit, a CT energy acquisition voltage data detection unit, a temperature and humidity sensing unit, an air pressure sensing unit, an accelerometer, and a BeiDou unit connected to the first main control chip;

[0129] The second processor 6044 includes a second main control chip, and a WIFI module, an embedded multimedia card EMMC, a power chip and a camera unit connected to the second main control chip.

[0130] An embodiment of the present application is:

[0131] The low-power multi-parameter intelligent sensing device is divided into a measurement and energy-taking gripper module and a multi-parameter intelligent monitoring host. The device can exchange data with an online monitoring platform (hereinafter referred to as the platform).

[0132] The measurement and energy acquisition gripper module includes current acquisition, CT energy acquisition voltage, conductor temperature measurement, and distributed fault location functions. Current acquisition is achieved using a Rogowski coil, while Permalloy is used as the CT energy acquisition voltage core. Conductor temperature measurement utilizes a combination of NTC and infrared temperature measurement. The measurement and energy acquisition gripper module includes an MCU, responsible for transmitting conductor temperature data collected by the gripper module to a multi-parameter intelligent monitoring host. Because the device needs to acquire current from each split conductor to monitor the conductor's energized state and support further functions such as fault location, and because it integrates multiple sensing functions and wireless long-distance communication, the system consumes high power. Using a single-conductor inductive power supply scheme presents problems such as bulky and heavy power acquisition structures, resulting in unbalanced forces across the conductors. Therefore, this application employs the addition of a measurement and energy acquisition gripper module to each conductor. The measurement and energy acquisition gripper module connects to the multi-parameter intelligent monitoring host via an 8-core dedicated aviation connector and shielded cable, achieving highly reliable CT energy acquisition voltage and communication multiplexing.

[0133] The measurement and energy acquisition gripper module transmits information to the multi-parameter intelligent monitoring host using an 8-core shielded cable. Two cores are responsible for RS485 communication of conductor temperature, four cores are responsible for current acquisition, and two cores are responsible for the power supply CT voltage acquisition, enabling multiplexing of measurement and CT voltage acquisition. Connecting to the multi-parameter intelligent monitoring host via a dedicated aviation connector makes the measurement and energy acquisition gripper module plug-and-play (hot-swappable), making installation and maintenance more convenient.

[0134] Taking into account the risk that the CT energy acquisition voltage in a certain measurement energy acquisition gripper module may fail or the wire current may be zero, the measurement energy acquisition gripper module also has a reverse power supply function: when the CT energy acquisition voltage is less than 3.6V, the supercapacitor on the power board will reverse power the measurement energy acquisition gripper module, thereby ensuring that the measurement energy acquisition gripper module can still work normally when the CT energy acquisition voltage is insufficient.

[0135] The multi-parameter intelligent monitoring host is powered by a power board equipped with a supercapacitor, which uses a power management chip to manage the entire device's power supply. The multi-parameter intelligent monitoring host utilizes a dual-controller architecture, integrating an ad hoc network (short-range communication) module, RTK, a nine-axis attitude sensor, a temperature and humidity sensor, an accelerometer, a visible light camera, and a Wi-Fi module. The RV1126 chip (controller 1) handles multimedia data exchange (photos and videos), device-side AI recognition, file exchange, local Wi-Fi debugging, and configuration file storage. Another MCU chip (controller 2) handles the accelerometer, temperature and humidity, current measurement data, and power consumption mode management. Controllers 1 and 2 communicate via the RS485 protocol. They share a 4G / 5G module, connected to it via USB and via UART. Controller 1's power is controlled by controller 2.

[0136] During operation, the device will set the operating state to different states according to the current CT energy supply voltage.

[0137] When the device's built-in supercapacitor voltage drops below 3.2V, Master 2 shuts down Master 1, leaving only the 4G / 5G module power and the temperature and humidity sensor operational. It periodically uploads current ambient temperature and humidity data every 10 minutes to maintain a heartbeat signal. This minimizes device power consumption through Master 2's low-power characteristics, retaining only minimal communication functionality with the platform and achieving ultra-low-power operation.

[0138] When the device's built-in supercapacitor voltage is greater than or equal to 3.2V and less than 3.6V, Master Controller 2 activates the 4G / 5G module, RTK, attitude sensor, and temperature and humidity sensor peripherals, and shuts down Master Controller 1. Master Controller 2 can now monitor wire galloping and sag data using the attitude sensor and RTK, and transmits this data to the platform via the 4G / 5G module, achieving a low-power operating state.

[0139] When the voltage of the device's built-in supercapacitor reaches 3.6V or greater, Master Controller 2 activates all peripheral modules and powers on Master Controller 1. Simultaneously, Master Controller 1's operating mode is set via the RS485 protocol between the power boards. Master Controller 1 then activates the Wi-Fi module for local debugging and, based on the operating mode set by Master Controller 2, activates the specified visible light camera module. The camera control utilizes a MIPI gating chip to accommodate more cameras within the limited encoding capabilities of the NPU chip. The cameras can perform patrol photography at specified (configurable) intervals. If a transmission channel breach risk (such as wildfire, smoke, crane, excavator, etc.) is detected, an alert and image are uploaded to the platform via the 4G / 5G module using the HTTP file transfer protocol. Master Controller 1 is also responsible for storing the device configuration file issued by the platform in XML format. This configuration includes serial number information, data upload intervals, and more.

[0140] To resolve conflicts caused by dual-CPU 4G / 5G module reuse, a 4G / 5G mutual exclusion lock based on the inter-board RS485 protocol is implemented. This mechanism ensures that only one processor can use the wireless communication module at any given time. When the first processor (CPU 1) requires the 4G / 5G module, it sets a bit in a predefined 4G / 5G request register. The second processor (CPU 2) polls this request register. If it finds that the 4G / 5G request register is set and the 4G / 5G module is not currently in use, it sets a bit in another 4G / 5G available register, indicating that the 4G / 5G module is occupied by the first processor. After completing communication, the first processor resets the 4G / 5G request register, releasing the 4G / 5G module for use by the second processor.

[0141] Compared to traditional single-controller monitoring devices, the dual-controller architecture leverages the low power consumption of the MCU chip and integrates the powerful computing power of the NPU chip to achieve on-device AI recognition. This dual-controller architecture leverages both strengths and weaknesses, enabling energy-based spatiotemporal scheduling and resource allocation for sensor modules, further improving system performance and efficiency.

[0142] The structure with separate measurement and energy acquisition gripper module and multi-parameter intelligent monitoring host makes it easier to repair device failures. The module realizes energy acquisition and measurement multiplexing through 8-core shielded cable, which improves the connection reliability between modules and further reduces the failure rate of the device.

[0143] Each module in the low-power, multi-parameter intelligent sensing device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0144] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 7 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store current data, wire temperature data and CT energy voltage data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a low-power multi-parameter intelligent sensing method is implemented.

[0145] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0146] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0147] A measuring energy gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality between the measuring energy gripper module and the conductor is achieved through conductive rubber and electrical connections; the measuring energy gripper module is electrically connected to the multi-parameter intelligent monitoring host, and the equipotentiality between the measuring energy gripper module and the multi-parameter intelligent monitoring host is achieved through the power ground wire;

[0148] The measurement and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; the current data is transmitted to the multi-parameter intelligent monitoring host using analog differential signals, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using digital signals;

[0149] A multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host. The first processor has an embedded neural network processing unit.

[0150] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0151] The first processor is communicatively connected to the second processor and shares the same wireless communication module; wherein the first processor and the second processor do not use the wireless communication module at the same time.

[0152] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0153] Before the first processor or the second processor applies to use the wireless communication module, determining whether an application mark exists in an application register of the wireless communication module;

[0154] In the absence of the application mark, it indicates that the working state of the wireless communication module is idle, and the use of the wireless communication module is allowed.

[0155] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0156] The motion data of the conductor is monitored by an accelerometer and an attitude sensing unit, and the motion data includes vibration data, galloping data, windage data and torsion data;

[0157] Analyzing the lateral acceleration of the conductor based on the motion data to determine whether it exceeds a preset acceleration threshold;

[0158] When the lateral acceleration exceeds the preset acceleration threshold, the galloping recording function is triggered and the wire galloping amplitude is calculated.

[0159] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0160] Filtering the collected acceleration signals and angular velocity signals;

[0161] Through numerical integration, the filtered acceleration signal and angular velocity signal are converted into velocity signal, and then into displacement signal;

[0162] Identify the periodic characteristics of the conductor's galloping motion and determine the zero velocity point;

[0163] In each dancing cycle, piecewise integration is performed from the velocity zero point to the next velocity zero point to calculate the displacement change in each cycle;

[0164] According to the displacement change in each cycle, the average displacement in all dancing cycles is calculated to obtain the wire dancing amplitude.

[0165] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0166] When the CT energy voltage data is less than the first preset voltage threshold, the system enters the ultra-low power consumption mode, controls the first starter module to suspend operation, controls the wireless communication module and the temperature and humidity sensing unit to operate, and uploads the temperature and humidity data at a preset interval;

[0167] When the CT energy acquisition voltage data is greater than or equal to a first preset voltage threshold and less than a second preset voltage threshold, the system enters a low power consumption mode, controls the wireless communication module, the Beidou unit, and the attitude sensing unit to operate, controls the first starter module to suspend operation, uses a galloping amplitude estimation model constructed based on historical galloping amplitude data to estimate the conductor galloping amplitude, and uploads the conductor galloping and sag data;

[0168] When the CT energy-taking voltage data is greater than or equal to the second preset voltage threshold, the full-function mode is entered, the first starter module is controlled to start working, local debugging is performed, and alarm data in the image data of the power line is monitored and transmitted.

[0169] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0170] A measuring energy gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality between the measuring energy gripper module and the conductor is achieved through conductive rubber and electrical connections; the measuring energy gripper module is electrically connected to the multi-parameter intelligent monitoring host, and the equipotentiality between the measuring energy gripper module and the multi-parameter intelligent monitoring host is achieved through the power ground wire;

[0171] The measurement and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; the current data is transmitted to the multi-parameter intelligent monitoring host using analog differential signals, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using digital signals;

[0172] A multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host. The first processor has an embedded neural network processing unit.

[0173] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0174] The first processor is communicatively connected to the second processor and shares the same wireless communication module; wherein the first processor and the second processor do not use the wireless communication module at the same time.

[0175] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0176] Before the first processor or the second processor applies to use the wireless communication module, determining whether an application mark exists in an application register of the wireless communication module;

[0177] In the absence of the application mark, it indicates that the working state of the wireless communication module is idle, and the use of the wireless communication module is allowed.

[0178] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0179] The motion data of the conductor is monitored by an accelerometer and an attitude sensing unit, and the motion data includes vibration data, galloping data, windage data and torsion data;

[0180] Analyzing the lateral acceleration of the conductor based on the motion data to determine whether it exceeds a preset acceleration threshold;

[0181] When the lateral acceleration exceeds the preset acceleration threshold, the galloping recording function is triggered and the wire galloping amplitude is calculated.

[0182] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0183] Filtering the collected acceleration signals and angular velocity signals;

[0184] Through numerical integration, the filtered acceleration signal and angular velocity signal are converted into velocity signal, and then into displacement signal;

[0185] Identify the periodic characteristics of the conductor's galloping motion and determine the zero velocity point;

[0186] In each dancing cycle, piecewise integration is performed from the velocity zero point to the next velocity zero point to calculate the displacement change in each cycle;

[0187] According to the displacement change in each cycle, the average displacement in all dancing cycles is calculated to obtain the wire dancing amplitude.

[0188] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0189] When the CT energy voltage data is less than the first preset voltage threshold, the system enters the ultra-low power consumption mode, controls the first starter module to suspend operation, controls the wireless communication module and the temperature and humidity sensing unit to operate, and uploads the temperature and humidity data at a preset interval;

[0190] When the CT energy acquisition voltage data is greater than or equal to a first preset voltage threshold and less than a second preset voltage threshold, the system enters a low power consumption mode, controls the wireless communication module, the Beidou unit, and the attitude sensing unit to operate, controls the first starter module to suspend operation, uses a galloping amplitude estimation model constructed based on historical galloping amplitude data to estimate the conductor galloping amplitude, and uploads the conductor galloping and sag data;

[0191] When the CT energy-taking voltage data is greater than or equal to the second preset voltage threshold, the full-function mode is entered, the first starter module is controlled to start working, local debugging is performed, and alarm data in the image data of the power line is monitored and transmitted.

[0192] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0193] A measuring energy gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality between the measuring energy gripper module and the conductor is achieved through conductive rubber and electrical connections; the measuring energy gripper module is electrically connected to the multi-parameter intelligent monitoring host, and the equipotentiality between the measuring energy gripper module and the multi-parameter intelligent monitoring host is achieved through the power ground wire;

[0194] The measurement and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; the current data is transmitted to the multi-parameter intelligent monitoring host using analog differential signals, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using digital signals;

[0195] A multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to perform AI recognition and multimedia interaction on the transmission line, and the second processor of the multi-parameter intelligent monitoring host is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host. The first processor has an embedded neural network processing unit.

[0196] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0197] The first processor is communicatively connected to the second processor and shares the same wireless communication module; wherein the first processor and the second processor do not use the wireless communication module at the same time.

[0198] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0199] Before the first processor or the second processor applies to use the wireless communication module, determining whether an application mark exists in an application register of the wireless communication module;

[0200] In the absence of the application mark, it indicates that the working state of the wireless communication module is idle, and the use of the wireless communication module is allowed.

[0201] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0202] The motion data of the conductor is monitored by an accelerometer and an attitude sensing unit. The motion data includes vibration data, galloping data, windage data and torsion data.

[0203] Analyzing the lateral acceleration of the conductor based on the motion data to determine whether it exceeds a preset acceleration threshold;

[0204] When the lateral acceleration exceeds the preset acceleration threshold, the galloping recording function is triggered and the wire galloping amplitude is calculated.

[0205] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0206] Filtering the collected acceleration signals and angular velocity signals;

[0207] Through numerical integration, the filtered acceleration signal and angular velocity signal are converted into velocity signal, and then into displacement signal;

[0208] Identify the periodic characteristics of the conductor's galloping motion and determine the zero velocity point;

[0209] In each dancing cycle, piecewise integration is performed from the velocity zero point to the next velocity zero point to calculate the displacement change in each cycle;

[0210] According to the displacement change in each cycle, the average displacement in all dancing cycles is calculated to obtain the wire dancing amplitude.

[0211] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0212] When the CT energy voltage data is less than the first preset voltage threshold, the system enters the ultra-low power consumption mode, controls the first starter module to suspend operation, controls the wireless communication module and the temperature and humidity sensing unit to operate, and uploads the temperature and humidity data at a preset interval;

[0213] When the CT energy acquisition voltage data is greater than or equal to a first preset voltage threshold and less than a second preset voltage threshold, the system enters a low power consumption mode, controls the wireless communication module, the Beidou unit, and the attitude sensing unit to operate, controls the first starter module to suspend operation, uses a galloping amplitude estimation model constructed based on historical galloping amplitude data to estimate the conductor galloping amplitude, and uploads the conductor galloping and sag data;

[0214] When the CT energy-taking voltage data is greater than or equal to the second preset voltage threshold, the full-function mode is entered, the first starter module is controlled to start working, local debugging is performed, and alarm data in the image data of the power line is monitored and transmitted.

[0215] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0216] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0217] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0218] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A low-power multi-parameter intelligent sensing method, characterized in that: The method comprises: A measuring and energy-taking gripper module is installed on each conductor of the transmission line; power output is generated through electromagnetic induction, and the equipotentiality of the measuring and energy-taking gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring and energy-taking gripper module is electrically connected to a multi-parameter intelligent monitoring host, and the equipotentiality of the measuring and energy-taking gripper module and the multi-parameter intelligent monitoring host is achieved through a power ground wire; The measuring and energy acquisition gripper module is used to collect current data, conductor temperature data, and CT energy acquisition voltage data of the transmission line; wherein, the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal; The multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line; wherein, the first processor of the multi-parameter intelligent monitoring host is used to intelligently process the transmission line information, including AI recognition and multimedia interaction, and the second processor of the multi-parameter intelligent monitoring host is used as the sensor main control processor to control the low-power operation and power management of the multi-parameter intelligent monitoring host, and adjust the working state of the system according to the actual CT energy supply voltage condition. The first processor has an embedded neural network processing unit.

2. The method according to claim 1, characterized in that The first processor is communicatively connected to the second processor and shares a same wireless communication module; wherein the first processor and the second processor do not use the wireless communication module at the same time; the specific process of the first processor and the second processor not using the wireless communication module at the same time includes: Before the first processor or the second processor applies to use the wireless communication module, determining whether an application mark exists in an application register of the wireless communication module; In the absence of the application mark, it indicates that the working state of the wireless communication module is an idle state, and the use of the wireless communication module is allowed.

3. The method according to claim 2, characterized in that The first processor includes a first main control chip, and a posture sensing unit, a temperature and humidity sensing unit, an accelerometer, and a Beidou unit connected to the first main control chip; the multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line, including: When the CT energy acquisition voltage data is less than a first preset voltage threshold, the system enters an ultra-low power consumption mode, controls the first processor to suspend operation, controls the wireless communication module and the temperature and humidity sensing unit to operate, and uploads temperature and humidity data at preset intervals; When the CT energy acquisition voltage data is greater than or equal to a first preset voltage threshold and less than a second preset voltage threshold, the system enters a low power consumption mode, controls the wireless communication module, the Beidou unit, and the attitude sensing unit to operate, and controls the first processor to suspend operation; uses a dancing amplitude estimation model constructed based on historical dancing amplitude data to estimate the conductor dancing amplitude, and uploads conductor dancing and sag data; and, when sufficient power is supplied, iteratively updates the dancing amplitude estimation model in real time using the acceleration signal and angular velocity signal measured by the attitude sensing unit; When the CT energy voltage data is greater than or equal to the second preset voltage threshold, the system enters the full-function mode, controls the first processor to start working, performs local debugging, and monitors and transmits alarm data in the image data of the power line.

4. The method according to claim 3, characterized in that The processing of the power consumption of the transmission line by using the multi-parameter intelligent monitoring host includes: Monitoring the motion data of the conductor using an accelerometer and a posture sensing unit, wherein the motion data includes vibration data, galloping data, windage data, and torsion data; analyzing, based on the motion data, whether the lateral acceleration of the wire exceeds a preset acceleration threshold; When the lateral acceleration exceeds a preset acceleration threshold, a galloping recording function is triggered and the conductor galloping amplitude is calculated.

5. The method according to claim 4, characterized in that The process of calculating the wire galloping amplitude includes: Filtering the collected acceleration signals and angular velocity signals; Through numerical integration, the filtered acceleration signal and angular velocity signal are converted into velocity signal, and then into displacement signal; Identify the periodic characteristics of the conductor's galloping motion and determine the zero velocity point; In each dancing cycle, piecewise integration is performed from the velocity zero point to the next velocity zero point to calculate the displacement change in each cycle; According to the displacement change in each cycle, the average displacement in all dancing cycles is calculated to obtain the wire dancing amplitude.

6. A low-power multi-parameter intelligent sensing device, characterized in that: The device includes a measuring energy acquisition gripper module and a multi-parameter intelligent monitoring host, the measuring energy acquisition gripper module is electrically connected to the multi-parameter intelligent monitoring host, and both are installed on each conductor of the transmission line; power output is formed by electromagnetic induction, and the equipotentiality of the measuring energy acquisition gripper module and the conductor is achieved through conductive rubber and electrical connection; the measuring energy acquisition gripper module is electrically connected to the multi-parameter intelligent monitoring host, and the equipotentiality of the measuring energy acquisition gripper module and the multi-parameter intelligent monitoring host is achieved through the power ground wire; The measuring and energy acquisition gripper module is used to collect current data, conductor temperature data and CT energy acquisition voltage data of the transmission line, wherein the current data is transmitted to the multi-parameter intelligent monitoring host using an analog differential signal, and the conductor temperature data and CT energy acquisition voltage data are transmitted to the multi-parameter intelligent monitoring host using a digital signal; The multi-parameter intelligent monitoring host is used to process the power consumption of the transmission line, wherein the multi-parameter intelligent monitoring host includes a first processor and a second processor, and the first processor has an embedded neural network processing unit; The first processor is used to perform AI recognition and multimedia interaction on the transmission line; The second processor is used to control the low-power operation and power management of the multi-parameter intelligent monitoring host and adjust the working state of the system according to the actual CT energy supply voltage condition.

7. The device according to claim 6, characterized in that A shielded cable containing multiple conductor cores is used to transmit information between the measuring and energy-acquisition gripper module and the multi-parameter intelligent monitoring host; At least one conductor core of the shielded cable is used to transmit conductor temperature data, at least one conductor core is used to transmit current data of the transmission line, and at least one conductor core is used to transmit CT energy supply voltage data.

8. The device according to claim 6, characterized in that The first processor includes a first main control chip, and a posture sensing unit, a battery detection unit, a capacitance detection unit, a CT energy acquisition voltage data detection unit, a temperature and humidity sensing unit, an air pressure sensing unit, an accelerometer and a Beidou unit connected to the first main control chip; The second processor includes a second main control chip, and a WIFI module, an embedded multimedia card EMMC, a power chip and a camera unit connected to the second main control chip.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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