A lightning location network integrating lightning energy parameters

Abstract

The present invention belongs to the field of lightning location technology and provides a lightning location network that integrates lightning energy parameters. The network comprises: a plurality of detection substations and a central detection station; the detection substations comprise: a low-frequency detection magnetic antenna, a filter amplifier circuit, a control panel, a Beidou antenna connected to the control panel, and an industrial control integrated computer; the central detection station comprises: a product module, an averaging module, an integration module, a lightning position calculation module, a host computer display module, and a risk assessment module. By providing the product module, averaging module, and integration module in the server of the central detection station, the present invention performs product calculations, averaging calculations, and integration calculations on lightning current data and vertical channel length. This overcomes the limitation of existing lightning location networks that use current maximum value to assess lightning energy, and enables accurate assessment of the risk of forest fires caused by lightning and the discharge phenomena caused by mid- and high-level discharges.

Description

Technical Field

[0001] The present invention relates to the technical field of lightning location, and in particular to a lightning location network integrating lightning energy parameters. Background Art

[0002] Lightning disasters are among the ten most serious natural disasters. Among meteorological disasters, lightning strikes are second only to rainstorms, floods, and meteorological and geological disasters in terms of casualties. Preventing lightning-related damage requires effective detection and location of lightning. Therefore, specialized equipment is urgently needed to monitor and locate lightning. This ensures that warnings can be issued to potentially affected areas and regions before a thunderstorm strikes, minimizing damage caused by lightning. Monitoring the direction, frequency, and intensity of lightning activity can also forecast severe weather events such as heavy rain, hurricanes, and hail, and provide effective early warning for rocket and satellite launches. A popular lightning location method currently involves deploying lightning detection equipment at multiple sites to form a two-dimensional or three-dimensional lightning location network, effectively detecting and locating lightning strikes. Single-site lightning detection equipment primarily consists of a low-frequency magnetic antenna for detecting lightning signals, an atmospheric electric field meter, a lightning signal processor, GPS, a wireless transmission module, and a lightning data processing terminal. This lightning location network captures lightning parameters such as lightning location and peak current intensity.

[0003] The lightning information provided by currently deployed lightning location networks primarily consists of conventional parameters such as lightning location and peak current intensity. These parameters are insufficient to accurately assess specific effects caused by lightning, including the ability to cause forest fires and mid- and high-level discharges. Assessing the ability to cause forest fires is crucial for reducing human harm, while assessing the ability to cause mid- and high-level discharges is crucial for the development and utilization of near-space resources. Therefore, accurately assessing these specific effects is an important research direction. In existing lightning location systems, lightning intensity is primarily determined by the peak current (maximum current) of the electromagnetic pulse (EMP) signal radiated during a lightning strike. However, this peak current does not account for time-dependent effects and cannot represent the energy carried by the lightning. Because some specific effects caused by lightning depend on the energy carried by the lightning, the peak current of the EMP signal cannot accurately assess these specific effects. Existing lightning location network systems have significant limitations in assessing these specific effects. Summary of the Invention

[0004] In order to overcome the shortcomings of the existing technology, the purpose of the present invention is to provide a lightning location network that integrates lightning energy parameters. By setting a product module, an averaging module and an integration module in the server of the central detection station, the product of the lightning current data and the vertical channel length is calculated to obtain the lightning time-resolved current moment. The lightning time-resolved current moment is averaged to obtain the mean of the lightning time-resolved current moment. The mean of the lightning time-resolved current moment is then integrated to obtain the lightning pulse charge moment, a parameter representing the lightning energy. This overcomes the limitation of the existing location network in using the maximum current value to evaluate lightning energy, and realizes an accurate assessment of the forest fire risk caused by lightning and the discharge phenomenon caused by mid- and high-level lightning.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A lightning location network integrating lightning energy parameters, characterized by comprising: a plurality of detection substations and a central detection station; the detection substations comprising: a low-frequency detection magnetic antenna, a filter amplifier circuit, a control board with an embedded FPGA board and an STM32 single-chip microcomputer, and a Beidou antenna and an industrial control all-in-one computer connected to the control board; the central detection station comprising: a product module, an average module, an integration module, a lightning position calculation module, a host computer display module, and a risk assessment module;

[0007] The product module is connected to the averaging module; the averaging module is connected to the integration module; the host computer display module is respectively connected to the integration module, the lightning position calculation module and the risk assessment module; each of the detection substations and the central detection station is connected via a wireless network;

[0008] The low-frequency detection magnetic antenna is used to collect the electromagnetic pulse signal generated when lightning occurs; the filter amplifier circuit is used to amplify and filter the electromagnetic pulse signal to obtain a pre-processed signal; the STM32 single-chip microcomputer is used to parse the received data of the Beidou antenna when receiving the trigger command sent by the FPGA board, obtain the time parameter of the pre-processed signal arriving at the detection substation and the longitude and latitude information of the detection substation, and send the time parameter and the longitude and latitude information to the FPGA board; the FPGA board is used to collect the waveform of the pre-processed signal and extract the peak value of the waveform. When the peak value exceeds a preset threshold, a trigger command is sent to the STM32 single-chip microcomputer, and the data of the pre-processed signal, the time parameter and the longitude and latitude information are integrated to obtain lightning parameters, and the lightning parameters are sent to the industrial control all-in-one computer for display and to the central detection station; the data of the pre-processed signal includes: the waveform of the preprocessed signal, the lightning current value and the length of the lightning current vertical channel; the product module is used to calculate the product of the lightning current value and the lightning current vertical channel length to obtain the lightning time-resolved current moment; the averaging module is used to average the lightning time-resolved current moment to obtain the lightning time-resolved current average moment; the integration module is used to integrate the lightning time-resolved current average moment to obtain the lightning pulse charge moment; the lightning position calculation module is used to perform position calculation using the arrival time difference algorithm based on the time parameters and the longitude and latitude information of all the detection substations to obtain lightning position information; the risk assessment module is used to analyze the lightning pulse charge moment to obtain a risk assessment result, and when the risk assessment result is high risk, send risk alarm information to the target area according to the lightning position information; the host computer display module is used to display the lightning pulse charge moment, the lightning position information and the risk assessment result.

[0009] Preferably, the integration time for calculating the lightning pulse charge moment is 2 ms.

[0010] Preferably, the assessment objects of the risk assessment threshold include: forest fires and mid- and high-level electrical discharge phenomena.

[0011] Preferably, the calculation formula for the lightning pulse charge moment is: Wherein, iCMC is the lightning pulse charge moment; M I (t) is the average moment of the lightning stroke time-resolved current; t is the time integral variable.

[0012] Preferably, the mid- and high-level discharge phenomena include: red sprites, blue jets and giant jets.

[0013] The present invention discloses the following technical effects:

[0014] The present invention provides a lightning location network that integrates lightning energy parameters. By setting a product module, an averaging module and an integration module in the server of the central detection station, the lightning current data and the vertical channel length are multiplied, averaged and integrated. This overcomes the limitation of the existing lightning location network that uses the maximum current value to evaluate lightning energy, and realizes an accurate assessment of the forest fire risk caused by lightning and the discharge phenomenon caused by mid- and high-level lightning. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 A diagram of a lightning location network module that integrates lightning energy parameters, provided by an embodiment of the present invention;

[0017] Description of reference numerals:

[0018] 1-Detection substation, 11-Low-frequency detection magnetic antenna, 12-Filter amplifier circuit, 13-Control board, 14-Beidou antenna, 15-Industrial control computer, 2-Central detection station, 21-Product module, 22-Average module, 23-Integration module, 24-Lightning position calculation module, 25-Upper computer display module, 26-Risk assessment module. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] The purpose of the present invention is to provide a lightning location network that integrates lightning energy parameters. By setting a product module, an averaging module and an integration module in the server of the central detection station, the product of the lightning current data and the vertical channel length is calculated to obtain the lightning time-resolved current moment. The lightning time-resolved current moment is averaged to obtain the mean of the lightning time-resolved current moment. The mean of the lightning time-resolved current moment is then integrated to obtain the lightning pulse charge moment, a parameter representing the lightning energy. This overcomes the limitation of the existing location network in using the maximum current value to evaluate lightning energy, and realizes an accurate assessment of the forest fire risk caused by lightning and the discharge phenomenon caused by mid- and high-level lightning.

[0021] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Figure 1 A module diagram of a lightning location network integrating lightning energy parameters provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the present invention provides a lightning location network integrating lightning energy parameters, characterized in that it includes: a plurality of detection substations 1 and a central detection station 2; the detection substation 1 includes: a low-frequency detection magnetic antenna 11, a filter amplifier circuit 12, a control board 13 with an embedded FPGA board and an STM32 single-chip microcomputer, and a Beidou antenna and an industrial control all-in-one computer 1514 connected to the control board; the central detection station 2 includes: a product module 21, an average value calculation module 22, an integration module 23, a lightning position calculation module 24, a host computer display module 25, and a risk assessment module 26;

[0023] The product module 21 is connected to the averaging module 22; the averaging module 22 is connected to the integration module 23; the host computer display module 25 is connected to the integration module 23, the lightning position calculation module 24 and the risk assessment module 26 respectively; each detection substation 1 and the central detection station 2 are connected via a wireless network;

[0024] The low-frequency detection magnetic antenna 11 is used to collect the electromagnetic pulse signal generated when lightning occurs; the filter amplifier circuit 12 is used to amplify the electromagnetic pulse signal and filter out noise to obtain a pre-processed signal; the STM32 single-chip microcomputer is used to parse the received data of the Beidou antenna 14 when receiving the trigger command sent by the FPGA board, and obtain the time parameter of the pre-processed signal arriving at the detection substation 1 and the longitude and latitude information of the detection substation 1, and send the time parameter and longitude and latitude information to the FPGA board; the FPGA board is used to collect the waveform of the pre-processed signal and extract the peak value of the waveform. When the peak value exceeds the preset threshold, a trigger command is sent to the STM32 single-chip microcomputer, and the data, time parameter and longitude and latitude information of the pre-processed signal are integrated to obtain the lightning parameters, and the lightning parameters are sent to the industrial control all-in-one computer 15 for display and to the central detection station 2; the data of the pre-processed signal includes: waveform, lightning current value and lightning current vertical channel length; the product module 21 is used to calculate the product of the lightning current value and the lightning current vertical channel length to obtain the lightning time-resolved current moment; the averaging module 22 is used to average the lightning time-resolved current moment to obtain the lightning time-resolved current average moment; the integration module 23 is used to integrate the lightning time-resolved current average moment to obtain the lightning pulse charge moment; the lightning position calculation module 24 is used to perform position calculation using the arrival time difference algorithm based on the time parameters and longitude and latitude information of all detection substations 1 to obtain lightning position information; the risk assessment module 26 is used to analyze the lightning pulse charge moment to obtain a risk assessment result, and when the risk assessment result is high risk, send risk alarm information to the target area according to the lightning position information; the host computer display module 25 is used to display the lightning pulse charge moment, lightning position information and risk assessment results.

[0025] Preferably, the integration time for calculating the lightning pulse charge moment is 2 ms.

[0026] Optionally, the assessment objects of the risk assessment threshold include: forest fires and mid- and high-level electrical discharge phenomena.

[0027] Specifically, the calculation formula for the lightning pulse charge moment is: Where iCMC is the lightning pulse charge moment; M I (t) is the average moment of the lightning stroke time-resolved current; t is the time integral variable.

[0028] Optionally, mid- and high-level discharge phenomena include: red sprites, blue jets, and giant jets.

[0029] Specifically, when lightning occurs, various electromagnetic pulse signals with a wide frequency range are generated. The low-frequency detection magnetic antenna 11 is used to collect the electromagnetic pulse signals generated when lightning occurs. The electromagnetic pulse signals are sent to the filter amplifier circuit 12 to amplify the weak electromagnetic pulse signals. The filter circuit is then used to filter out the noise contained in the amplified electromagnetic pulse signals to obtain electromagnetic pulse signals within the low-frequency range. The electromagnetic pulse signals within the low-frequency range are then sent to the control board 13, which combines the FPGA board and the STM32 microcontroller, for processing. When the control board 13 determines that the peak value of the electromagnetic pulse signal waveform within the low-frequency range exceeds the set threshold, it is determined to be an electromagnetic pulse signal triggered by lightning. The FPGA board sends a trigger signal to the STM32 microcontroller, and the STM32 microcontroller begins to parse the data in the Beidou antenna 14 and transmits the parsed data to the FPGA board via the serial port. The FPGA board sends the sorted electromagnetic pulse signal data and the data parsed by the STM32 microcontroller to the industrial control all-in-one computer 15 for display and sends them to the central detection station 2. The work of the control board 13 includes data collection, data analysis, and data uploading.

[0030] Specifically, currently used lightning location networks cannot provide information on the energy of detected lightning and are incapable of accurately assessing certain specific effects caused by lightning. The lightning location network system of this embodiment incorporates lightning energy parameters, characterized by the lightning pulse charge moment, which fully accounts for the time-accumulated effect of charge transfer during lightning discharge. The lightning pulse charge moment parameter calculated in this embodiment can be used to determine the lightning energy, providing a scientific basis for accurately assessing certain specific effects caused by lightning.

[0031] Furthermore, to accurately assess the ability of lightning to cause specific effects, it is necessary to consider the time-accumulated effect of charge transfer during lightning discharge. To calculate the energy carried by lightning, this embodiment introduces a parameter indicator reflecting lightning energy—the lightning pulse charge moment. This indicator parameter represents a type of energy measurement. The calculation formula for the lightning pulse charge moment is the product of the amount of charge during the lightning discharge and the spatial height of the charge distribution. The actual method for calculating this indicator is to filter the electromagnetic pulse signal using a low-pass filter circuit to retain the slowly varying portion of the electromagnetic pulse waveform. The area enclosed by the slowly varying curve and the time axis of the pulse waveform is then calculated to obtain the value of the lightning pulse charge moment, and thus the energy carried by the lightning. If the part of the pulse curve with a larger amplitude of change is used for measurement, the waveform will fluctuate violently up and down, and the area size cannot be calculated. Moreover, it is meaningless to use the part of the pulse curve that changes rapidly to calculate the energy. Energy is an accumulation effect, so the time is longer and the pulse width will be wider. What is retained after low-pass filtering is the slow change process in the pulse waveform curve. This slow change process is actually the process of charge transfer. Slow transmission is equivalent to the process of continuous charge output after the channel is established.

[0032] Specifically, the calculation formula for the lightning pulse charge moment (unit: C·Km) is as follows:

[0033]

[0034] Preferably, in the lightning location network that integrates lightning energy parameters in this embodiment, each detection substation 1 primarily provides conventional parameters, such as the waveform of the lightning-triggered pulse signal, the time the lightning-triggered pulse signal arrives at the detection substation, the latitude and longitude of the detection substation, the lightning current value measured by the detection substation 1, and the length of the lightning current vertical channel. In addition to calculating lightning location information based on the time difference between the lightning-triggered electromagnetic pulse signal and the latitude and longitude of each detection substation 1, the central detection station 2 also needs to provide the lightning pulse charge moment obtained by the above calculation formula. This parameter can more accurately represent lightning energy. If this parameter value is large, it means that the lightning carries a large amount of energy, which can cause forest fires or cause environmental disturbances in the middle and upper atmosphere, thus having a significant impact on human production and life. Therefore, integrating the lightning pulse charge moment parameter into the lightning location network can provide a scientific basis for accurately assessing some specific effects caused by lightning, filling the gap in the existing lightning location network in assessing specific effects caused by lightning, and has strong practical value.

[0035] Furthermore, lightning can cause some specific effects, such as the ability to cause forest fires and the ability to cause mid- and high-level discharges. The existing lightning location network cannot accurately evaluate these specific effects caused by lightning. The lightning location network that integrates lightning energy parameters in this embodiment evaluates these specific effects by providing a parameter called lightning pulse charge moment. The lightning pulse charge moment reflects the product of the amount of charge and the spatial height of the charge distribution during the lightning discharge process. The larger the pulse charge moment, the greater the energy of the lightning discharge. Forest fires are often caused by lightning strikes, especially when lightning strikes trees or the ground, and the high temperature and sparks generated will ignite combustibles. Therefore, the energy of lightning (related to the lightning pulse charge moment) is one of the key factors that determine whether it will cause a forest fire.

[0036] Specifically, mid- and high-level discharge phenomena include red sprites, blue jets, and giant jets, all of which are typically associated with lightning discharges in the troposphere. The magnitude and distribution of the lightning pulse charge moment affect the charge distribution and electric field strength in the mid- and high-level atmosphere, thereby triggering or promoting mid- and high-level discharges. Mid- and high-level discharges can have diverse impacts on the atmospheric environment and ionospheric structure, affecting human development and utilization of near-space resources.

[0037] The beneficial effects of the present invention are as follows:

[0038] The present invention sets a product module, an averaging module and an integration module in the server of the central detection station, calculates the product of lightning current data and the vertical channel length to obtain the lightning time-resolved current moment, averages the lightning time-resolved current moment to obtain the mean of the lightning time-resolved current moment, and then integrates the mean of the lightning time-resolved current moment to obtain the lightning pulse charge moment, a parameter representing the lightning energy. This overcomes the limitation of the existing positioning network in using the maximum current value to evaluate lightning energy, and realizes an accurate assessment of the risk of forest fire caused by lightning and the discharge phenomenon caused by mid- and high-level lightning.

[0039] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0040] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A lightning location network integrating lightning energy parameters, characterized by: include: Several detection substations and a central detection station; The detection substation includes: a low-frequency detection magnetic antenna, a filter amplifier circuit, a control board with an embedded FPGA board and an STM32 single-chip microcomputer, and a Beidou antenna and an industrial control integrated computer connected to the control board; the central detection station includes: a product module, an average module, an integration module, a lightning position calculation module, a host computer display module, and a risk assessment module; The product module is connected to the averaging module; the averaging module is connected to the integration module; the host computer display module is respectively connected to the integration module, the lightning position calculation module and the risk assessment module; each of the detection substations and the central detection station is connected via a wireless network; The low-frequency detection magnetic antenna is used to collect the electromagnetic pulse signal generated when lightning occurs; the filter amplifier circuit is used to amplify and filter the electromagnetic pulse signal to obtain a pre-processed signal; the STM32 single-chip microcomputer is used to parse the received data of the Beidou antenna when receiving the trigger command sent by the FPGA board, obtain the time parameter of the pre-processed signal arriving at the detection substation and the longitude and latitude information of the detection substation, and send the time parameter and the longitude and latitude information to the FPGA board; the FPGA board is used to collect the waveform of the pre-processed signal and extract the peak value of the waveform. When the peak value exceeds a preset threshold, a trigger command is sent to the STM32 single-chip microcomputer, and the data of the pre-processed signal, the time parameter and the longitude and latitude information are integrated to obtain lightning parameters, and the lightning parameters are sent to the industrial control all-in-one computer for display and to the central detection station; the data of the pre-processed signal includes: the waveform of the preprocessed signal, the lightning current value and the length of the lightning current vertical channel; the product module is used to calculate the product of the lightning current value and the lightning current vertical channel length to obtain the lightning time-resolved current moment; the averaging module is used to average the lightning time-resolved current moment to obtain the lightning time-resolved current average moment; the integration module is used to integrate the lightning time-resolved current average moment to obtain the lightning pulse charge moment; the lightning position calculation module is used to perform position calculation using the arrival time difference algorithm based on the time parameters and the longitude and latitude information of all the detection substations to obtain lightning position information; the risk assessment module is used to analyze the lightning pulse charge moment to obtain a risk assessment result, and when the risk assessment result is high risk, send risk alarm information to the target area according to the lightning position information; the host computer display module is used to display the lightning pulse charge moment, the lightning position information and the risk assessment result.

2. A lightning location network integrating lightning energy parameters according to claim 1, characterized in that: The integration time for calculating the lightning pulse charge moment is 2 ms.

3. The lightning location network integrating lightning energy parameters according to claim 1, characterized in that: The objects of the risk assessment include: forest fires and mid- and high-level electrical discharges.

4. A lightning location network integrating lightning energy parameters according to claim 2, characterized in that: The calculation formula of the lightning pulse charge moment is: Wherein, iCMC is the lightning pulse charge moment; M I (t) is the average moment of the lightning stroke time-resolved current; t is the time integral variable.

5. The lightning location network integrating lightning energy parameters according to claim 3 is characterized in that: The mid- and high-level discharge phenomena include red sprites, blue jets and giant jets.

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