A lightning prevention and attraction device and method based on convolutional neural network control of laser and high-voltage pulse electric field

Abstract

The application provides a laser and high-voltage pulse electric field collaborative lightning prevention and attraction device and method based on convolutional neural network control, and belongs to the technical field of lightning protection. The device comprises a perception module, a convolutional neural network control module, a laser emission module, a high-voltage pulse electric field generation module, an energy supply module and a grounding module. The perception module collects environmental parameters and lightning precursor signals in real time and transmits them to the convolutional neural network control module. The convolutional neural network control module performs risk assessment based on the built-in convolutional neural network model, generates a control strategy, and collaboratively controls the laser emission module to generate a plasma channel, and the high-voltage pulse electric field generation module forms a high-voltage pulse electric field in the channel area to strengthen ionization, prolong the channel life and intervene the lightning cloud charge distribution. Through multi-physical field collaboration and intelligent control, the application realizes accurate and active prevention and control of lightning, and significantly improves the effectiveness, reliability and environmental adaptability of lightning protection.

Description

Technical Field

[0001] This invention relates to the field of lightning protection technology, and more particularly to a lightning protection and lightning attraction device and method based on laser and high-voltage pulsed electric field coordinated control by convolutional neural network. Background Technology

[0002] Lightning is a violent discharge phenomenon caused by strong convective activity in the atmosphere. Its discharge process is accompanied by instantaneous currents of tens of thousands of amperes and temperatures of tens of thousands of degrees Celsius, making it extremely destructive. Lightning strikes not only directly damage buildings, power facilities, and other ground targets, but the resulting electromagnetic pulses can also cause secondary damage to electronic equipment. Modern lightning protection technologies are mainly divided into two categories: passive protection and active intervention. Passive protection uses facilities such as lightning rods and grounding grids to divert lightning current, while active intervention technologies aim to guide or suppress the lightning discharge process through artificial means. With the increasing intelligence of power systems and the widespread application of sophisticated electronic equipment, traditional passive lightning protection technologies are no longer sufficient to meet the needs for selective and precise protection against lightning strikes, necessitating the development of comprehensive lightning protection solutions with active control capabilities.

[0003] Current active lightning protection technologies mainly include laser-guided lightning, high-voltage pulse-guided lightning, and composite lightning interception devices, but all have significant limitations. Laser-guided lightning relies on high-energy lasers to generate plasma channels. Although it can guide lightning directionally, its channel stability and lightning-guided efficiency drop sharply under complex weather conditions due to atmospheric attenuation. High-voltage pulse-guided lightning induces leaders through artificial electric field distortion, but single pulse parameters are difficult to adapt to the variable charge distribution of thunderclouds, easily leading to false triggering or response delays. In addition, existing technologies mostly adopt independent control modes. For example, laser and high-voltage pulse systems often operate in a time-sharing manner, resulting in insufficient spatiotemporal coordination between electric field control and channel establishment, and failing to achieve coupled optimization of multiple physical fields (such as electric field, optical field, and thermal field). On the other hand, traditional devices lack the ability to sense dynamic parameters of thunderclouds in real time. Their trigger thresholds are mostly fixed values, making it difficult to dynamically adjust intervention strategies based on key parameters such as leader development speed and space charge density. This results in poor adaptability when dealing with significantly different lightning types such as cloud-to-ground lightning and cloud-to-cloud lightning. Summary of the Invention

[0004] To address the aforementioned technical problems of existing lightning protection devices, such as their simplistic operation, inability to achieve multi-physics field synergistic optimization, lack of intelligent sensing and real-time decision-making capabilities, and weak environmental adaptability, this invention provides a laser and high-voltage pulsed electric field synergistic lightning protection and attraction device and method based on convolutional neural network control. This invention primarily utilizes a sensing module to collect environmental parameters and lightning precursor signals of the lightning protection area in real time. A convolutional neural network control module performs data analysis, lightning risk assessment, and generates a lightning protection control strategy. This strategy then collaboratively controls a laser emission module to emit a laser towards the target area to generate a plasma channel, and a high-voltage pulsed electric field generation module to form a high-voltage pulsed electric field in and around the plasma channel area. This achieves the synergistic effect of the laser and the high-voltage pulsed electric field across multiple physics fields, thereby improving the effectiveness, reliability, and adaptability of active lightning protection. It enables precise intervention in the conditions and development paths of lightning generation, meeting the diverse and high-standard lightning protection needs under complex and variable thunderstorm environments.

[0005] The technical means employed in this invention are as follows: A laser and high-voltage pulsed electric field coordinated lightning protection and attraction device based on convolutional neural network control includes: a sensing module, a convolutional neural network control module, a laser emission module, a high-voltage pulsed electric field generation module, an energy supply module, and a grounding module, wherein: The sensing module establishes a signal connection with the convolutional neural network control module to collect environmental parameters and lightning precursor signals of the lightning protection area in real time, and transmits the collected environmental parameters and lightning precursor signals of the lightning protection area to the convolutional neural network control module. The convolutional neural network control module establishes signal connections with the laser emitting module and the high-voltage pulse electric field generating module, respectively. It is used to receive the environmental parameters of the lightning protection area and the lightning precursor signals collected by the sensing module, perform lightning risk assessment based on the built-in convolutional neural network model, generate lightning protection control strategy, and output laser control command to the laser emitting module and electric field control command to the high-voltage pulse electric field generating module according to the lightning protection control strategy. The laser emitting module is used to receive laser control commands and emit lasers toward the target area according to the laser control commands to generate a stable long-distance plasma channel in the air, providing a guiding path for the development of lightning. The high-voltage pulse electric field generating module is used to receive electric field control commands and form a high-voltage pulse electric field in and around the long-distance plasma channel region according to the electric field control commands to enhance the air ionization effect, extend the plasma channel life and interfere with the lightning cloud charge distribution, destroy the natural formation conditions of lightning or guide lightning to develop along a preset path. The energy supply module establishes electrical connections with the sensing module, the convolutional neural network control module, the laser emission module, and the high-voltage pulse electric field generation module, respectively, and is used to provide electrical energy to the sensing module, the convolutional neural network control module, the laser emission module, and the high-voltage pulse electric field generation module. The grounding module is electrically connected to the high-voltage pulse electric field generating module to safely guide the induced charge, leakage current and guided lightning current generated during equipment operation to the ground.

[0006] Furthermore, the sensing module includes a lightning precursor signal sensor, an environmental parameter sensor, and a positioning module, wherein: The lightning precursor signal sensor uses an electric field sensor, a magnetic field sensor, a radio frequency signal sensor, and an optical sensor to collect the electric field strength and rate of change, the magnetic field strength and rate of change, the intensity and spectral characteristics of lightning-related radio frequency signals, and sky optical signals in the lightning protection area, respectively, to comprehensively capture the characteristic signals before lightning formation. The environmental parameter sensor collects environmental data, including wind speed, wind direction, temperature, humidity and air pressure, to analyze the impact of environmental factors on lightning protection effectiveness. The positioning module uses GPS / BeiDou dual-mode positioning to accurately obtain the geographical coordinates of the device's own location and the lightning protection area.

[0007] Furthermore, the convolutional neural network control module includes a data preprocessing unit, a model training and inference unit, and a control decision unit, wherein: The data preprocessing unit receives the lightning protection area environmental parameters and lightning precursor signals collected by the sensing module, and performs preprocessing on the collected lightning protection area environmental parameters and lightning precursor signals, including normalization, noise reduction, and feature extraction, to convert the multi-dimensional raw data into standardized data that meets the input requirements of the convolutional neural network. The model training and inference unit receives standardized data output by the data preprocessing unit in real time, and infers and outputs the probability of lightning occurrence, the expected occurrence time, the lightning intensity level, and the optimal laser parameters and high-voltage pulse electric field parameters through the built-in trained convolutional neural network model. The convolutional neural network model uses historical environmental parameters, lightning precursor signal data, and corresponding lightning protection effect data as training samples. Through a network structure including convolutional layers, pooling layers, and fully connected layers, it learns the laws of lightning formation and development, as well as the mapping relationship between laser parameters, high-voltage pulse electric field parameters, and lightning protection effect. The control decision unit receives the inference results output by the convolutional neural network model and generates control commands based on the inference results to control the start-up and shutdown of the laser emitting module and the high-voltage pulse electric field generating module and adjust the operating parameters, while coordinating the working timing of the laser emitting module and the high-voltage pulse electric field generating module.

[0008] Furthermore, the laser parameters include emission power, pulse width, repetition frequency, and focusing angle; the high-voltage pulse electric field parameters include voltage amplitude and polarity, pulse frequency, and electric field distribution range.

[0009] Furthermore, the laser emitting module includes a laser generator, a beam shaper, a steering device, and a cooling system, wherein: The laser generator establishes an electrical connection with the energy supply module to obtain electrical energy, and uses an ultrashort pulse laser source to generate a laser beam with a pulse duration on the order of picoseconds or femtoseconds, a peak power on the order of terawatts, and adjustable power and controllable pulse parameters to meet the requirements of long-distance ionization. The beam shaper receives the laser beam output from the laser generator and focuses and collimates the laser beam to optimize the energy distribution of the laser beam, improve the ionization efficiency of the laser on the air, and ensure the formation of a uniform and stable plasma channel. The steering device establishes a signal connection with the convolutional neural network control module to receive the laser control command, and uses a high-precision electric gimbal to adjust the laser emission direction and angle according to the laser control command to accurately point to the target area; The cooling system is thermally connected to the laser generator and uses water cooling or air cooling to cool the laser generator in real time.

[0010] Furthermore, the high-voltage pulse electric field generating module includes a high-voltage pulse generator, an electrode array, and an insulation protection unit, wherein: The high-voltage pulse generator establishes an electrical connection with the energy supply module to obtain electrical energy, and establishes a signal connection with the convolutional neural network control module to receive the electric field control command. According to the electric field control command, the output parameters are adjusted in real time, and a high-voltage pulse signal with adjustable voltage amplitude and controllable pulse frequency is output to the electrode array. The electrode array consists of multiple metal electrodes arranged according to a specific pattern. It is installed at key positions in the laser emission path and establishes an electrical connection with the high-voltage pulse generator to receive the high-voltage pulse electrical signal. It converts the high-voltage pulse electrical signal into a preset distributed high-voltage pulse electric field to work in conjunction with the plasma channel generated by the laser emission module. The insulation protection unit uses high-strength insulation material to wrap and protect the electrode array and the connection lines between the high-voltage pulse generator and the electrode array, so as to prevent high-voltage discharge from causing accidental damage to the equipment itself and surrounding objects.

[0011] Furthermore, the high-voltage pulse generator includes a pre-amplifier module, a high-voltage transformer, a positive and negative polarity voltage multiplier rectifier circuit, a positive and negative polarity switching circuit, a high-voltage acquisition circuit, a voltage control circuit, and a protection circuit, wherein: The front-end inverter module establishes an electrical connection with the energy supply module to receive DC power, and uses a push-pull circuit or a full-bridge inverter circuit to invert the DC power into high-frequency AC power for output to the high-voltage transformer. The high-voltage transformer establishes an electrical connection with the front-end inverter module to receive high-frequency AC power, and outputs 5kV high-voltage AC power on the secondary side through primary and secondary electromagnetic coupling. The positive and negative polarity voltage multiplier rectifier circuit establishes an electrical connection with the secondary output terminal of the high voltage transformer to receive high voltage AC power, and adopts a 14-stage voltage multiplier rectifier structure to rectify and multiply the high voltage AC power into DC high voltage output to the positive and negative polarity switching circuit. The positive and negative polarity switching circuit establishes an electrical connection with the positive and negative polarity voltage multiplier rectifier circuit to receive DC high voltage, and switches the voltage polarity output to the electrode array under the drive of the motor. The motor and the high voltage electrode are connected by an insulating structure, and the insulation voltage of the insulating structure is greater than 150kV. The high-voltage acquisition circuit establishes a signal connection with the positive and negative polarity voltage multiplier rectifier circuit or the positive and negative polarity switching circuit to acquire the output voltage signal and transmit the output voltage signal to the voltage control circuit. The voltage control circuit establishes a signal connection with the high voltage acquisition circuit to receive the voltage signal, and uses a voltage and current dual-loop series structure to generate a control signal based on the output voltage signal and output it to the front-end inverter module to adjust the output of the front-end inverter module. The protection circuit is connected across the secondary output terminal of the high-voltage transformer or the output terminal of the positive and negative polarity voltage multiplier rectifier circuit to provide overvoltage protection.

[0012] Furthermore, the energy supply module includes a main power supply, a backup power supply, and a power management unit, wherein: The main power supply adopts 220V or 380V AC mains power, and converts the AC mains power into DC voltage required by the sensing module, convolutional neural network control module, laser emission module and high voltage pulse electric field generation module through transformer, rectifier and filter. The backup power supply uses a large-capacity lithium battery pack, which is used to automatically switch to backup power supply mode when the main power is interrupted, so as to ensure that the equipment can still work normally in the event of a sudden power outage. The power management unit establishes electrical connections with the main power supply and the backup power supply to receive electrical energy, and performs voltage regulation and current limiting control on the power output. It monitors the energy consumption of the sensing module, convolutional neural network control module, laser emission module and high-voltage pulse electric field generation module to allocate electrical energy reasonably. It also has overvoltage, overcurrent and short-circuit protection functions.

[0013] Furthermore, the grounding module includes a grounding electrode, a grounding busbar, and connecting wires, wherein: The grounding electrode is made of copper or galvanized steel, buried at a depth of not less than 2m underground, and the grounding resistance is not greater than 4Ω. The grounding busbar is used to collect lightning current; The connecting line is used to electrically connect the high-voltage pulse electric field generating module to the grounding busbar and to the grounding electrode, so as to safely conduct the induced charge, leakage current and guided lightning current generated during the operation of the equipment into the ground via the grounding busbar and the grounding electrode.

[0014] This invention also provides a method for coordinated lightning protection and attraction of laser and high-voltage pulsed electric fields based on convolutional neural network control, implemented using the aforementioned laser and high-voltage pulsed electric field coordinated lightning protection and attraction device, comprising: S1. The sensing module continuously collects lightning precursor signals and environmental parameters of the lightning protection area. At the same time, it obtains geographic coordinate information through the positioning module and transmits the collected multi-dimensional raw data to the data preprocessing unit of the convolutional neural network control module for normalization, noise reduction and feature extraction, and converts it into standardized data. S2. The model training and inference unit of the convolutional neural network control module receives the standardized data, performs inference analysis through the built-in convolutional neural network model, calculates the probability of lightning occurrence, the expected occurrence time and the lightning intensity level in the current area, and outputs the optimal laser parameters and high-voltage pulse electric field parameters according to the preset lightning protection target. The control decision unit generates corresponding control commands based on the model output results, and clarifies the start-up timing, operating parameters and working sequence of the laser emission module and the high-voltage pulse electric field generation module. S3. The laser emitting module activates the laser generator according to the control command. The laser beam, optimized by the beam shaper, is precisely pointed to the target area through the steering device, generating a long-distance plasma channel in the air. At the same time, the high-voltage pulse electric field generating module activates the high-voltage pulse generator according to the control command, forming a high-voltage pulse electric field with preset parameters in the plasma channel area and its surroundings through the electrode array. The plasma channel provides a low-impedance path for charge migration, and the high-voltage pulse electric field enhances air ionization to prolong the life and conductivity of the plasma channel. It also changes the charge distribution at the bottom of the thundercloud, disrupts the electric field conditions naturally formed by lightning, or guides the charge in the thundercloud to migrate directionally along the plasma channel. S4. When lightning forms, it preferentially develops along the plasma channel. If the lightning protection target is to guide the lightning, the plasma channel will guide the lightning to the area above the preset grounding module, and the lightning current will be safely introduced into the ground through the grounding module. If the lightning protection target is to prevent lightning from forming in the protected area, the synergistic effect of the high-voltage pulse electric field and the plasma channel will continuously interfere with the accumulation and migration of thundercloud charge in order to destroy the necessary conditions for lightning formation. If the destruction fails, it will turn to guiding.

[0015] Compared with the prior art, the present invention has the following advantages: 1. The laser and high-voltage pulse electric field coordinated lightning protection and attraction device based on convolutional neural network control provided by the present invention achieves dual intervention on the conditions for lightning generation and development path by coordinating with the plasma channel generated by the laser emission module and the high-voltage pulse electric field generated by the high-voltage pulse electric field generation module. This greatly improves the effectiveness of lightning control and can more accurately prevent lightning from forming in the protected area or guide lightning to a safe area.

[0016] 2. The device provided by the present invention achieves dynamic adaptive adjustment of laser parameters and high-voltage pulse electric field parameters by intelligently analyzing and making decisions on environmental parameters and lightning precursor signals collected in real time by the sensing module in conjunction with the convolutional neural network control module. This adapts to the lightning protection requirements under different meteorological conditions and different lightning intensities, thereby improving the environmental adaptability and lightning protection reliability of the equipment.

[0017] 3. The device provided by this invention, in conjunction with an automated control mode, a cooling system and a backup power supply, achieves long-term continuous and stable operation without frequent manual intervention, and has stronger continuous working capability and ease of operation compared with rocket-guided lightning technology.

[0018] 4. The device provided by this invention, through coordinated protection with the insulation protection unit and the grounding module, effectively avoids accidental damage from high-voltage discharge and safely discharges lightning current, reducing the risk of ground potential backflash. Moreover, the device has a compact structure and can be flexibly installed in various places that require lightning protection, making it widely applicable.

[0019] 5. The device provided by this invention achieves a breakthrough in active lightning protection technology by combining the intelligent control of convolutional neural networks with the synergistic effect of laser and high-voltage pulse electric field. It overcomes the shortcomings of existing new lightning arresters, such as limited lightning protection effect, complex operation of rocket lightning attraction, and insufficient lifespan of laser lightning attraction channels. It has significant technical innovation and practical value.

[0020] In summary, the technical solution of this invention solves the problems of limited lightning protection effect, insufficient reliability, weak environmental adaptability, complex operation, and difficulty in continuous operation in the prior art.

[0021] Based on the above reasons, this invention can be widely promoted in the fields of lightning protection for building rooftops, lightning protection for power transmission line towers, lightning protection for substations, lightning protection for oil fields, and lightning protection for storage facilities. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a structural block diagram of the device of the present invention.

[0024] Figure 2 This is a circuit diagram of the device of the present invention.

[0025] Figure 3 This is a flowchart of the adaptive control process of the convolutional neural network control module of the present invention.

[0026] Figure 4 This is a flowchart of the method of the present invention. Detailed Implementation

[0027] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0030] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0031] In the description of this invention, it should be understood that the orientation or positional relationship indicated by directional terms such as "front, back, up, down, left, right", "horizontal, vertical, horizontal" and "top, bottom" is generally based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing this invention and simplifying the description. Unless otherwise stated, these directional terms do not indicate or imply that the device or element referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the scope of protection of this invention. The directional terms "inner" and "outer" refer to the inner and outer contours relative to the outline of each component itself.

[0032] For ease of description, spatial relative terms such as "above," "over," "on the upper surface of," "above," etc., are used herein to describe the spatial positional relationship of a device or feature as shown in the figures to other devices or features. It should be understood that spatial relative terms are intended to encompass different orientations in use or operation besides the orientation of the device as described in the figures. For example, if the device in the figures is inverted, a device described as "above" or "above" other devices or structures would subsequently be positioned as "below" or "under" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below." The device may also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatial relative descriptions used herein will be interpreted accordingly.

[0033] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore should not be construed as limiting the scope of protection of this invention.

[0034] like Figure 1 ,2 As shown, this invention provides a laser and high-voltage pulsed electric field coordinated lightning protection and attraction device based on convolutional neural network control, comprising: a sensing module, a convolutional neural network control module, a laser emission module, a high-voltage pulsed electric field generation module, an energy supply module, and a grounding module, wherein: The sensing module establishes a signal connection with the convolutional neural network control module to collect environmental parameters and lightning precursor signals of the lightning protection area in real time, and transmits the collected environmental parameters and lightning precursor signals of the lightning protection area to the convolutional neural network control module. The convolutional neural network control module establishes signal connections with the laser emitting module and the high-voltage pulse electric field generating module, respectively. It is used to receive the environmental parameters of the lightning protection area and the lightning precursor signals collected by the sensing module, perform lightning risk assessment based on the built-in convolutional neural network model, generate lightning protection control strategy, and output laser control command to the laser emitting module and electric field control command to the high-voltage pulse electric field generating module according to the lightning protection control strategy. The laser emitting module is used to receive laser control commands and emit lasers toward the target area according to the laser control commands to generate a stable long-distance plasma channel in the air, providing a guiding path for the development of lightning. The high-voltage pulse electric field generating module is used to receive electric field control commands and form a high-voltage pulse electric field in and around the long-distance plasma channel region according to the electric field control commands to enhance the air ionization effect, extend the plasma channel life and interfere with the lightning cloud charge distribution, destroy the natural formation conditions of lightning or guide lightning to develop along a preset path. The energy supply module establishes electrical connections with the sensing module, the convolutional neural network control module, the laser emission module, and the high-voltage pulse electric field generation module, respectively, and is used to provide electrical energy to the sensing module, the convolutional neural network control module, the laser emission module, and the high-voltage pulse electric field generation module. The grounding module is electrically connected to the high-voltage pulse electric field generating module to safely guide the induced charge, leakage current and guided lightning current generated during equipment operation to the ground.

[0035] In a specific implementation, as a preferred embodiment of the present invention, the sensing module includes a lightning precursor signal sensor, an environmental parameter sensor, and a positioning module, wherein: The lightning precursor signal sensor employs an electric field sensor, a magnetic field sensor, a radio frequency signal sensor, and an optical sensor to collect the electric field strength and rate of change, magnetic field strength and rate of change, lightning-related radio frequency signal strength and spectral characteristics, and sky optical signals (such as lightning precursor light radiation) in the lightning protection area, thereby comprehensively capturing the characteristic signals before lightning formation. The environmental parameter sensor collects environmental data, including wind speed, wind direction, temperature, humidity and air pressure, to analyze the impact of environmental factors on lightning protection effectiveness. The positioning module uses GPS / BeiDou dual-mode positioning to accurately obtain the geographical coordinates of the device's own location and the lightning protection area.

[0036] In a specific implementation, as a preferred embodiment of the present invention, the convolutional neural network control module includes a data preprocessing unit, a model training and inference unit, and a control decision unit, wherein: The data preprocessing unit receives the lightning protection area environmental parameters and lightning precursor signals collected by the sensing module, and performs preprocessing on the collected lightning protection area environmental parameters and lightning precursor signals, including normalization, noise reduction, and feature extraction, to convert the multi-dimensional raw data into standardized data that meets the input requirements of the convolutional neural network. The model training and inference unit receives standardized data output by the data preprocessing unit in real time, and infers and outputs the probability of lightning occurrence, the expected occurrence time, the lightning intensity level, and the optimal laser parameters and high-voltage pulse electric field parameters through the built-in trained convolutional neural network model. The convolutional neural network model uses historical environmental parameters, lightning precursor signal data, and corresponding lightning protection effect data as training samples. Through a network structure including convolutional layers, pooling layers, and fully connected layers, it learns the laws of lightning formation and development, as well as the mapping relationship between laser parameters, high-voltage pulse electric field parameters, and lightning protection effect. The control decision unit receives the inference results output by the convolutional neural network model and generates control commands based on the inference results to control the start-up and shutdown of the laser emitting module and the high-voltage pulse electric field generating module and adjust the operating parameters. At the same time, it coordinates the working timing of the laser emitting module and the high-voltage pulse electric field generating module to ensure the synergistic effect.

[0037] In this embodiment, as Figure 3The diagram shows the adaptive flowchart of the convolutional neural network control module. Electric field / magnetic field / RF / optical sensors continuously collect lightning precursor signals such as electric field strength and rate of change, magnetic field strength and rate of change, RF signals, and optical signals from the lightning protection area. All these signals are transmitted to the data fusion and preprocessing unit within the convolutional neural network control module. This unit performs spatiotemporal alignment, signal preprocessing, feature fusion, and standardization. The fused feature tensor is first input to the top-level convolutional neural network. This network is specifically trained for classification of macro- and micro-states of thunderclouds and threat assessment. The top-level strategic command and the latest real-time feature tensor are fed into the convolutional neural network algorithm—high-voltage pulse electric field (actually a collaborative control CNN). Based on the actively guided target, combined with the specific threat location, distance, and environmental temperature and humidity, this network calculates the optimal combination of physical intervention parameters and outputs an adaptive control law, including laser parameters and high-voltage pulse electric field parameters. The adaptive control law is sent to the control law module, which, along with the co-controller, sends laser commands to the laser and the steering platform. Almost simultaneously, the high-voltage electric field command drives the high-voltage pulse electric field subsystem polarity switching module to receive positive polarity commands, and the control circuit connects the positive high-voltage path. The positive high-voltage power supply actuator is activated, outputting high-voltage DC according to the commanded voltage amplitude. The high-voltage pulse electric field actuator applies a high-voltage pulse to the electrode array deployed at the starting point of the laser path, forming a positive high-voltage pulse electric field with an intensity of approximately 90 kV / m in the root region of the plasma channel. Throughout the process, the sensing module continuously monitors the process. Upon successful lightning induction, the sensors record the instantaneous collapse of the electric field intensity, the massive optical radiation pulse, and the strong radio frequency signal. This feedback data is transmitted back to the data fusion unit in real time.

[0038] In a specific implementation, as a preferred embodiment of the present invention, the laser parameters include emission power, pulse width, repetition frequency, and focusing angle; the high-voltage pulse electric field parameters include voltage amplitude and polarity, pulse frequency, and electric field distribution range.

[0039] In a specific implementation, as a preferred embodiment of the present invention, the laser emitting module includes a laser generator, a beam shaper, a steering device, and a cooling system, wherein: The laser generator establishes an electrical connection with the energy supply module to obtain electrical energy, and uses an ultrashort pulse laser source to generate a laser beam with a pulse duration on the order of picoseconds or femtoseconds, a peak power on the order of terawatts, and adjustable power and controllable pulse parameters to meet the requirements of long-distance ionization. The beam shaper receives the laser beam output from the laser generator and focuses and collimates the laser beam to optimize the energy distribution of the laser beam, improve the ionization efficiency of the laser on the air, and ensure the formation of a uniform and stable plasma channel. The steering device establishes a signal connection with the convolutional neural network control module to receive the laser control command, and uses a high-precision electric gimbal to adjust the laser emission direction and angle according to the laser control command to accurately point to the target area (such as the possible development path of thunderclouds, the preset lightning interception area). The cooling system is thermally connected to the laser generator and uses water cooling or air cooling to cool the laser generator in real time to avoid overheating damage caused by prolonged operation and to ensure the stability and continuity of laser emission.

[0040] In a specific implementation, as a preferred embodiment of the present invention, the high-voltage pulse electric field generating module includes a high-voltage pulse generator, an electrode array, and an insulation protection unit, wherein: The high-voltage pulse generator establishes an electrical connection with the energy supply module to obtain electrical energy, and establishes a signal connection with the convolutional neural network control module to receive the electric field control command. According to the electric field control command, the output parameters are adjusted in real time to output a high-voltage pulse electrical signal with an adjustable voltage amplitude in the range of 0 to 100kV and a controllable pulse frequency to the electrode array, and it has a fast response capability. The electrode array consists of multiple metal electrodes arranged according to a specific pattern. It is installed at key positions in the laser emission path and establishes an electrical connection with the high-voltage pulse generator to receive the high-voltage pulse electrical signal. It converts the high-voltage pulse electrical signal into a preset distributed high-voltage pulse electric field to work in conjunction with the plasma channel generated by the laser emission module. The insulation protection unit uses high-strength insulation material to wrap and protect the electrode array and the connection lines between the high-voltage pulse generator and the electrode array, so as to prevent high-voltage discharge from causing accidental damage to the equipment itself and surrounding objects.

[0041] In a specific implementation, as a preferred embodiment of the present invention, the high-voltage pulse generator includes a pre-stage inverter module, a high-voltage transformer, a positive and negative polarity voltage multiplier rectifier circuit, a positive and negative polarity switching circuit, a high-voltage acquisition circuit, a voltage control circuit, and a protection circuit, wherein: The front-end inverter module establishes an electrical connection with the energy supply module to receive DC power, and uses a push-pull circuit or a full-bridge inverter circuit to invert the DC power into high-frequency AC power for output to the high-voltage transformer. The high-voltage transformer establishes an electrical connection with the front-end inverter module to receive high-frequency AC power, and outputs 5kV high-voltage AC power on the secondary side through primary and secondary electromagnetic coupling. The positive and negative polarity voltage multiplier rectifier circuit establishes an electrical connection with the secondary output terminal of the high voltage transformer to receive high voltage AC power, and adopts a 14-stage voltage multiplier rectifier structure to rectify and multiply the high voltage AC power into DC high voltage output to the positive and negative polarity switching circuit. The positive and negative polarity switching circuit establishes an electrical connection with the positive and negative polarity voltage multiplier rectifier circuit to receive DC high voltage, and switches the voltage polarity output to the electrode array under the drive of the motor. The motor and the high voltage electrode are connected by an insulating structure, and the insulation voltage of the insulating structure is greater than 150kV. The high-voltage acquisition circuit establishes a signal connection with the positive and negative polarity voltage multiplier rectifier circuit or the positive and negative polarity switching circuit to acquire the output voltage signal and transmit the output voltage signal to the voltage control circuit. The voltage control circuit establishes a signal connection with the high voltage acquisition circuit to receive the voltage signal, and uses a voltage and current dual-loop series structure to generate a control signal based on the output voltage signal and output it to the front-end inverter module to adjust the output of the front-end inverter module. The protection circuit is connected across the secondary output terminal of the high-voltage transformer or the output terminal of the positive and negative polarity voltage multiplier rectifier circuit to provide overvoltage protection.

[0042] In a specific implementation, as a preferred embodiment of the present invention, the energy supply module includes a main power supply, a backup power supply, and a power management unit, wherein: The main power supply adopts 220V or 380V AC mains power, and converts the AC mains power into DC voltage (such as 12V, 24V, 48V) required by the sensing module, convolutional neural network control module, laser emission module and high voltage pulse electric field generation module through transformer, rectifier and filter. The backup power supply uses a large-capacity lithium battery pack, which is used to automatically switch to backup power supply mode when the main power is interrupted, so as to ensure that the equipment can still work normally in the event of a sudden power outage. The power management unit establishes electrical connections with the main power supply and the backup power supply to receive electrical energy, and performs voltage regulation and current limiting control on the power output. It monitors the energy consumption of the sensing module, convolutional neural network control module, laser emission module and high-voltage pulse electric field generation module to rationally allocate electrical energy and improve energy utilization efficiency. It also has overvoltage, overcurrent and short-circuit protection functions.

[0043] In a specific implementation, as a preferred embodiment of the present invention, the grounding module includes a grounding electrode, a grounding busbar, and connecting wires, wherein: The grounding electrode is made of copper or galvanized steel, buried at a depth of not less than 2m underground, and the grounding resistance is not greater than 4Ω. The grounding busbar is used to collect lightning current; The connecting line is used to electrically connect the high-voltage pulse electric field generating module to the grounding busbar and to the grounding electrode, so as to safely conduct the induced charge, leakage current and guided lightning current generated during the operation of the equipment into the ground via the grounding busbar and the grounding electrode.

[0044] This invention also provides a method for coordinated lightning protection and attraction of laser and high-voltage pulsed electric fields based on convolutional neural network control, implemented using the aforementioned laser and high-voltage pulsed electric field coordinated lightning protection and attraction device, comprising: S1. The sensing module continuously collects lightning precursor signals and environmental parameters of the lightning protection area. At the same time, it obtains geographic coordinate information through the positioning module and transmits the collected multi-dimensional raw data to the data preprocessing unit of the convolutional neural network control module for normalization, noise reduction and feature extraction, and converts it into standardized data. S2. The model training and inference unit of the convolutional neural network control module receives the standardized data, performs inference analysis through the built-in convolutional neural network model, calculates the probability of lightning occurrence, the expected occurrence time and the lightning intensity level in the current area, and outputs the optimal laser parameters and high-voltage pulse electric field parameters according to the preset lightning protection target. The control decision unit generates corresponding control commands based on the model output results, and clarifies the start-up timing, operating parameters and working sequence of the laser emission module and the high-voltage pulse electric field generation module. S3. The laser emitting module activates the laser generator according to the control command. The laser beam, optimized by the beam shaper, is precisely pointed to the target area through the steering device, generating a long-distance plasma channel in the air. At the same time, the high-voltage pulse electric field generating module activates the high-voltage pulse generator according to the control command, forming a high-voltage pulse electric field with preset parameters in the plasma channel area and its surroundings through the electrode array. The plasma channel provides a low-impedance path for charge migration, and the high-voltage pulse electric field enhances air ionization to prolong the life and conductivity of the plasma channel. It also changes the charge distribution at the bottom of the thundercloud, disrupts the electric field conditions naturally formed by lightning, or guides the charge in the thundercloud to migrate directionally along the plasma channel. S4. When lightning forms, it preferentially develops along the plasma channel. If the lightning protection target is to guide the lightning, the plasma channel will guide the lightning to the area above the preset grounding module, and the lightning current will be safely introduced into the ground through the grounding module. If the lightning protection target is to prevent lightning from forming in the protected area, the synergistic effect of the high-voltage pulse electric field and the plasma channel will continuously interfere with the accumulation and migration of thundercloud charge in order to destroy the necessary conditions for lightning formation. If the destruction fails, it will turn to guiding.

[0045] In this embodiment, as Figure 4The diagram shows the flowchart of the method of this invention. The system is initially powered on and initialized, with each module completing self-tests. The energy supply module operates in mains power mode, the sensing module and convolutional neural network control module are in continuous operation, and the laser emission module and high-voltage pulse electric field generation module are in standby low-power mode. The system awaits sensing data input or a manual start command. Data acquisition and preprocessing: Multiple sensors in the sensing module begin synchronous data acquisition, and all raw data is sent to the data preprocessing unit within the convolutional neural network control module. Standardized data input: The preprocessed standardized feature dataset is input into the trained convolutional neural network model according to a preset data structure. Convolutional neural network model inference: The built-in convolutional neural network model performs real-time inference analysis on the input data. The model extracts spatial features through convolutional layers and captures changing trends through temporal analysis layers. The model outputs a structured inference result. Lightning protection target decision: The control decision unit makes specific lightning protection action decisions based on the model's inference result and a preset protection strategy. If the decision is to guide lightning, it will preferentially propagate along the plasma channel and guide it to the preset grounding module. If the decision is to prevent formation, it will collaboratively interfere with the accumulation of charge in the thundercloud, disrupting the conditions for lightning formation. Control commands are generated; the control decision unit generates collaborative control commands containing specific parameters and precise timing based on the above strategy. After the commands are synchronously issued, the laser emission module starts, the laser emits light according to the command parameters, and the beam shaping and steering device operates, forming a stable plasma channel in the air pointing towards the target area. At a specified delay (microseconds) after laser emission, the high-voltage pulse generator outputs a high-voltage pulse to the electrode array according to the command parameters, forming a strong high-voltage pulse electric field at the root of the plasma channel and in the surrounding space. Through synergistic action, the plasma channel (low-impedance path) generated by the laser and the high-voltage pulse electric field (enhanced ionization and active traction) are precisely superimposed and synergistically act in space and time. The combined effect is a significant reduction in the breakdown threshold of the target air gap, causing the lightning's pilot discharge to be "attracted" to this artificial path and to develop along this path towards the preset grounding module. Real-time data feedback: During and after the intervention, the sensing module continuously collects data on changes in electric field, magnetic field, and optical signals. This data is fed back to the data preprocessing unit in real time, forming a closed loop. The control cycle ends when the feedback data indicates that the lightning has been successfully guided to the grounding module for discharge, or when the electric field signal indicates that the threat has been eliminated.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A lightning protection and lightning attraction device based on laser and high-voltage pulsed electric field coordinated control using convolutional neural network control, characterized in that, include: The system comprises a sensing module, a convolutional neural network control module, a laser emission module, a high-voltage pulse electric field generation module, an energy supply module, and a grounding module, wherein: The sensing module establishes a signal connection with the convolutional neural network control module to collect environmental parameters and lightning precursor signals of the lightning protection area in real time, and transmits the collected environmental parameters and lightning precursor signals of the lightning protection area to the convolutional neural network control module. The convolutional neural network control module establishes signal connections with the laser emitting module and the high-voltage pulse electric field generating module, respectively. It is used to receive the environmental parameters of the lightning protection area and the lightning precursor signals collected by the sensing module, perform lightning risk assessment based on the built-in convolutional neural network model, generate lightning protection control strategy, and output laser control command to the laser emitting module and electric field control command to the high-voltage pulse electric field generating module according to the lightning protection control strategy. The laser emitting module is used to receive laser control commands and emit lasers toward the target area according to the laser control commands to generate a stable long-distance plasma channel in the air, providing a guiding path for the development of lightning. The high-voltage pulse electric field generating module is used to receive electric field control commands and form a high-voltage pulse electric field in and around the long-distance plasma channel region according to the electric field control commands to enhance the air ionization effect, extend the plasma channel life and interfere with the lightning cloud charge distribution, destroy the natural formation conditions of lightning or guide lightning to develop along a preset path. The energy supply module establishes electrical connections with the sensing module, the convolutional neural network control module, the laser emission module, and the high-voltage pulse electric field generation module, respectively, and is used to provide electrical energy to the sensing module, the convolutional neural network control module, the laser emission module, and the high-voltage pulse electric field generation module. The grounding module is electrically connected to the high-voltage pulse electric field generating module to safely guide the induced charge, leakage current and guided lightning current generated during equipment operation to the ground.

2. The lightning protection and lightning attraction device based on laser and high-voltage pulsed electric field coordinated control according to claim 1, characterized in that, The sensing module includes a lightning precursor signal sensor, an environmental parameter sensor, and a positioning module, wherein: The lightning precursor signal sensor uses an electric field sensor, a magnetic field sensor, a radio frequency signal sensor, and an optical sensor to collect the electric field strength and rate of change, the magnetic field strength and rate of change, the intensity and spectral characteristics of lightning-related radio frequency signals, and sky optical signals in the lightning protection area, respectively, to comprehensively capture the characteristic signals before lightning formation. The environmental parameter sensor collects environmental data, including wind speed, wind direction, temperature, humidity and air pressure, to analyze the impact of environmental factors on lightning protection effectiveness. The positioning module uses GPS / BeiDou dual-mode positioning to accurately obtain the geographical coordinates of the device's own location and the lightning protection area.

3. The lightning protection and lightning attraction device based on laser and high-voltage pulsed electric field coordinated control according to claim 1, characterized in that, The convolutional neural network control module includes a data preprocessing unit, a model training and inference unit, and a control decision unit, wherein: The data preprocessing unit receives the lightning protection area environmental parameters and lightning precursor signals collected by the sensing module, and performs preprocessing on the collected lightning protection area environmental parameters and lightning precursor signals, including normalization, noise reduction, and feature extraction, to convert the multi-dimensional raw data into standardized data that meets the input requirements of the convolutional neural network. The model training and inference unit receives standardized data output by the data preprocessing unit in real time, and infers and outputs the probability of lightning occurrence, the expected occurrence time, the lightning intensity level, and the optimal laser parameters and high-voltage pulse electric field parameters through the built-in trained convolutional neural network model. The convolutional neural network model uses historical environmental parameters, lightning precursor signal data, and corresponding lightning protection effect data as training samples. Through a network structure including convolutional layers, pooling layers, and fully connected layers, it learns the laws of lightning formation and development, as well as the mapping relationship between laser parameters, high-voltage pulse electric field parameters, and lightning protection effect. The control decision unit receives the inference results output by the convolutional neural network model and generates control commands based on the inference results to control the start-up and shutdown of the laser emitting module and the high-voltage pulse electric field generating module and adjust the operating parameters, while coordinating the working timing of the laser emitting module and the high-voltage pulse electric field generating module.

4. The lightning protection and lightning attraction device based on laser and high-voltage pulsed electric field coordinated by convolutional neural network control according to claim 3, characterized in that, The laser parameters include emission power, pulse width, repetition frequency, and focusing angle; the high-voltage pulse electric field parameters include voltage amplitude and polarity, pulse frequency, and electric field distribution range.

5. The lightning protection and lightning attraction device based on laser and high-voltage pulsed electric field coordinated control according to claim 1, characterized in that, The laser emitting module includes a laser generator, a beam shaper, a steering device, and a cooling system, wherein: The laser generator establishes an electrical connection with the energy supply module to obtain electrical energy, and uses an ultrashort pulse laser source to generate a laser beam with a pulse duration on the order of picoseconds or femtoseconds, a peak power on the order of terawatts, and adjustable power and controllable pulse parameters to meet the requirements of long-distance ionization. The beam shaper receives the laser beam output from the laser generator and focuses and collimates the laser beam to optimize the energy distribution of the laser beam, improve the ionization efficiency of the laser on the air, and ensure the formation of a uniform and stable plasma channel. The steering device establishes a signal connection with the convolutional neural network control module to receive the laser control command, and uses a high-precision electric gimbal to adjust the laser emission direction and angle according to the laser control command to accurately point to the target area; The cooling system is thermally connected to the laser generator and uses water cooling or air cooling to cool the laser generator in real time.

6. The lightning protection and lightning induction device based on laser and high-voltage pulsed electric field controlled by convolutional neural network according to claim 1, characterized in that, The high-voltage pulse electric field generating module includes a high-voltage pulse generator, an electrode array, and an insulation protection unit, wherein: The high-voltage pulse generator establishes an electrical connection with the energy supply module to obtain electrical energy, and establishes a signal connection with the convolutional neural network control module to receive the electric field control command. According to the electric field control command, the output parameters are adjusted in real time, and a high-voltage pulse signal with adjustable voltage amplitude and controllable pulse frequency is output to the electrode array. The electrode array consists of multiple metal electrodes arranged according to a specific pattern. It is installed at key positions in the laser emission path and establishes an electrical connection with the high-voltage pulse generator to receive the high-voltage pulse electrical signal. It converts the high-voltage pulse electrical signal into a preset distributed high-voltage pulse electric field to work in conjunction with the plasma channel generated by the laser emission module. The insulation protection unit uses high-strength insulation material to wrap and protect the electrode array and the connection lines between the high-voltage pulse generator and the electrode array, so as to prevent high-voltage discharge from causing accidental damage to the equipment itself and surrounding objects.

7. The lightning protection and lightning attraction device based on laser and high-voltage pulsed electric field coordinated control according to claim 6, characterized in that, The high-voltage pulse generator includes a pre-amplifier module, a high-voltage transformer, a positive and negative polarity voltage multiplier rectifier circuit, a positive and negative polarity switching circuit, a high-voltage acquisition circuit, a voltage control circuit, and a protection circuit, wherein: The front-end inverter module establishes an electrical connection with the energy supply module to receive DC power, and uses a push-pull circuit or a full-bridge inverter circuit to invert the DC power into high-frequency AC power for output to the high-voltage transformer. The high-voltage transformer establishes an electrical connection with the front-end inverter module to receive high-frequency AC power, and outputs 5kV high-voltage AC power on the secondary side through primary and secondary electromagnetic coupling. The positive and negative polarity voltage multiplier rectifier circuit establishes an electrical connection with the secondary output terminal of the high voltage transformer to receive high voltage AC power, and adopts a 14-stage voltage multiplier rectifier structure to rectify and multiply the high voltage AC power into DC high voltage output to the positive and negative polarity switching circuit. The positive and negative polarity switching circuit establishes an electrical connection with the positive and negative polarity voltage multiplier rectifier circuit to receive DC high voltage, and switches the voltage polarity output to the electrode array under the drive of the motor. The motor and the high voltage electrode are connected by an insulating structure, and the insulation voltage of the insulating structure is greater than 150kV. The high-voltage acquisition circuit establishes a signal connection with the positive and negative polarity voltage multiplier rectifier circuit or the positive and negative polarity switching circuit to acquire the output voltage signal and transmit the output voltage signal to the voltage control circuit. The voltage control circuit establishes a signal connection with the high voltage acquisition circuit to receive the voltage signal, and uses a voltage and current dual-loop series structure to generate a control signal based on the output voltage signal and output it to the front-end inverter module to adjust the output of the front-end inverter module. The protection circuit is connected across the secondary output terminal of the high-voltage transformer or the output terminal of the positive and negative polarity voltage multiplier rectifier circuit to provide overvoltage protection.

8. The lightning protection and lightning attraction device based on laser and high-voltage pulsed electric field coordinated control according to claim 1, characterized in that, The energy supply module includes a main power supply, a backup power supply, and a power management unit, wherein: The main power supply adopts 220V or 380V AC mains power, and converts the AC mains power into DC voltage required by the sensing module, convolutional neural network control module, laser emission module and high voltage pulse electric field generation module through transformer, rectifier and filter. The backup power supply uses a large-capacity lithium battery pack, which is used to automatically switch to backup power supply mode when the main power is interrupted, so as to ensure that the equipment can still work normally in the event of a sudden power outage. The power management unit establishes electrical connections with the main power supply and the backup power supply to receive electrical energy, and performs voltage regulation and current limiting control on the power output. It monitors the energy consumption of the sensing module, convolutional neural network control module, laser emission module and high-voltage pulse electric field generation module to allocate electrical energy reasonably. It also has overvoltage, overcurrent and short-circuit protection functions.

9. A lightning protection and lightning induction device based on laser and high-voltage pulsed electric field controlled by convolutional neural network according to claim 1, characterized in that, The grounding module includes a grounding electrode, a grounding busbar, and connecting wires, wherein: The grounding electrode is made of copper or galvanized steel, buried at a depth of not less than 2m underground, and the grounding resistance is not greater than 4Ω. The grounding busbar is used to collect lightning current; The connecting line is used to electrically connect the high-voltage pulse electric field generating module to the grounding busbar and to the grounding electrode, so as to safely conduct the induced charge, leakage current and guided lightning current generated during the operation of the equipment into the ground via the grounding busbar and the grounding electrode.

10. A method for coordinated lightning protection and attraction based on laser and high-voltage pulsed electric field controlled by convolutional neural network, implemented based on the laser and high-voltage pulsed electric field coordinated lightning protection and attraction device controlled by convolutional neural network as described in any one of claims 1-9, characterized in that, include: S1. The sensing module continuously collects lightning precursor signals and environmental parameters of the lightning protection area. At the same time, it obtains geographic coordinate information through the positioning module and transmits the collected multi-dimensional raw data to the data preprocessing unit of the convolutional neural network control module for normalization, noise reduction and feature extraction, and converts it into standardized data. S2. The model training and inference unit of the convolutional neural network control module receives the standardized data, performs inference analysis through the built-in convolutional neural network model, calculates the probability of lightning occurrence, the expected occurrence time and the lightning intensity level in the current area, and outputs the optimal laser parameters and high-voltage pulse electric field parameters according to the preset lightning protection target. The control decision unit generates corresponding control commands based on the model output results, and clarifies the start-up timing, operating parameters and working sequence of the laser emission module and the high-voltage pulse electric field generation module. S3. The laser emitting module activates the laser generator according to the control command. The laser beam, optimized by the beam shaper, is precisely pointed to the target area through the steering device, generating a long-distance plasma channel in the air. At the same time, the high-voltage pulse electric field generating module activates the high-voltage pulse generator according to the control command, forming a high-voltage pulse electric field with preset parameters in the plasma channel area and its surroundings through the electrode array. The plasma channel provides a low-impedance path for charge migration, and the high-voltage pulse electric field enhances air ionization to prolong the life and conductivity of the plasma channel. It also changes the charge distribution at the bottom of the thundercloud, disrupts the electric field conditions naturally formed by lightning, or guides the charge in the thundercloud to migrate directionally along the plasma channel. S4. When lightning forms, it preferentially develops along the plasma channel. If the lightning protection target is to guide the lightning, the plasma channel will guide the lightning to the area above the preset grounding module, and the lightning current will be safely introduced into the ground through the grounding module. If the lightning protection target is to prevent lightning from forming in the protected area, the synergistic effect of the high-voltage pulse electric field and the plasma channel will continuously interfere with the accumulation and migration of thundercloud charge in order to destroy the necessary conditions for lightning formation. If the destruction fails, it will turn to guiding.

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