Method and device for meteorological monitoring around power facilities based on quantum radar

Abstract

The present application relates to the field of meteorological monitoring technology, and specifically discloses a method and device for meteorological monitoring around power facilities based on quantum radar. A meteorological parameter set is obtained, and the quantum radar detection system is controlled to emit quantum laser pulses; based on a preset analog channel and / or single photon counting channel, the photon detection signal corresponding to the quantum laser pulse is received and processed to obtain the current meteorological data corresponding to the meteorological parameter set. The present application collects meteorological data by using quantum radar. The quantum radar uses single-photon detection technology, which can achieve a higher signal-to-noise ratio when the emitted laser energy is low, and can effectively and accurately identify and measure the echo signal, thereby avoiding the reduction in data accuracy caused by bad weather.

Description

Technical Field

[0001] The present application relates to the field of meteorological monitoring technology, and in particular to a meteorological monitoring technology around power facilities based on quantum radar. Background Art

[0002] When the laser of traditional atmospheric lidar propagates in the atmosphere, it is easily affected by rain, clouds and fog, resulting in limited detection distance. In addition, in severe weather such as heavy fog, rain and snow, the detection accuracy and range will be reduced, resulting in reduced accuracy of the collected meteorological data.

[0003] In particular, my country's power grid is massive, covers a wide range of areas, and operates in a complex environment. Some of this equipment is located in areas prone to frequent meteorological disasters, which can easily cause power facilities to shut down. Weather is unpredictable, making it virtually impossible to analyze its changes manually. Therefore, new technologies are essential for real-time monitoring of weather conditions so that appropriate measures can be taken to prevent or resolve accidents.

[0004] Chinese patent application publication number CN110221360A discloses a power line thunderstorm warning method and system. This method uses channel cloud maps as training samples to train a neural network, outputting a predicted radar combination reflectivity map to produce a trained radar combination reflectivity prediction model. The channel cloud map to be measured is then input into the radar combination reflectivity prediction model to produce a predicted radar combination reflectivity map. The radar echo correlation tracking method (TREC) is used to track the motion of echoes in the predicted radar combination reflectivity map to predict the radar combination reflectivity map for the next moment. Based on the predicted radar combination reflectivity map for the next moment, thunderstorm warning information is transmitted to towers in different convective intensity zones in the map. This method addresses the existing problem of a limited number of radar observation stations, which prevents comprehensive thunderstorm detection in all regions, and provides early thunderstorm warnings for power lines. However, in severe weather, the accuracy of radar data collected can be reduced, resulting in inaccurate thunderstorm warnings. Summary of the Invention

[0005] The technical problem to be solved by this application is how to improve the accuracy of meteorological data collection for weekly measurements of power facilities.

[0006] In a first aspect, the present application provides a method for meteorological monitoring around power facilities based on quantum radar, the method comprising:

[0007] Get meteorological parameter set;

[0008] Based on the meteorological parameter set, controlling the quantum radar detection system to emit quantum laser pulses;

[0009] Based on a preset analog channel and / or single photon counting channel, receiving a photon detection signal corresponding to the quantum laser pulse;

[0010] Processing the photon detection signal to obtain current meteorological data corresponding to the meteorological parameter set includes:

[0011] Based on a counter or an adder, data accumulation is performed on the photon detection signal to obtain data to be corrected;

[0012] Based on a preset data table, the data to be corrected is corrected to obtain data to be analyzed;

[0013] Based on a preset algorithm, performing spectrum analysis on the data to be analyzed to obtain the frequency characteristics and spectrum diagram of the photon detection signal;

[0014] The frequency characteristics and the spectrum diagram are analyzed to obtain the current meteorological data.

[0015] As a further optimized technical solution, the receiving of the photon detection signal corresponding to the quantum laser pulse based on the preset analog channel and / or single photon counting channel includes:

[0016] Based on the analog channel, a first photon detection signal is received, wherein the first photon detection signal is a signal obtained by analog or linear means from a laser echo signal corresponding to the quantum laser pulse, and / or

[0017] A second photon detection signal is received based on a single-photon counting channel, wherein the second photon detection signal is a signal obtained by a laser echo signal corresponding to the quantum laser pulse in a single-photon mode.

[0018] As a further optimized technical solution, the receiving of the first photon detection signal based on the analog channel includes:

[0019] Based on the signal conditioning module, adjusting the signal output by the quantum detector to obtain the first photon detection signal;

[0020] Based on the differential driver, the analog-to-digital converter is driven to collect the first photon detection signal.

[0021] As a further optimized technical solution, the receiving of the second photon detection signal based on the single photon counting channel includes:

[0022] The target pulse signal is obtained by filtering the photon signal based on the single-channel analyzer;

[0023] The target pulse signal is counted based on a counter to obtain photon flow information, which is used as the second photon detection signal.

[0024] As a further optimized technical solution, the method of correcting the data to be corrected based on a preset data table before obtaining the data to be analyzed further includes:

[0025] Collecting at least one standard signal of known signal strength, and obtaining an output value of an analog-to-digital converter and a measurement value of a quantum detector corresponding to the standard signal;

[0026] Pairing the output value of the analog-to-digital converter with the measurement value of the quantum detector to generate a corresponding relationship between the output value and the measurement value;

[0027] The data table is generated based on the output value of the analog-to-digital converter, the measurement value of the quantum detector, and the corresponding relationship.

[0028] As a further optimized technical solution, the step of obtaining a meteorological parameter set includes:

[0029] Receive user operations;

[0030] Based on the user operation, determining a target warning in a preset weather warning;

[0031] In a preset meteorological parameter database, parameters corresponding to the target warning are obtained to generate the meteorological parameter set.

[0032] As a further optimized technical solution, after processing the photon detection signal to obtain the current meteorological data corresponding to the meteorological parameter set, the method further includes:

[0033] Preprocessing the current meteorological data to obtain meteorological forecast data;

[0034] Processing the weather forecast data based on a target forecast model to obtain a weather forecast result, and obtaining a weather defense strategy based on the weather forecast result;

[0035] A meteorological warning is generated based on the meteorological forecast results and the meteorological defense strategy.

[0036] As a further optimized technical solution, the preprocessing of the current meteorological data to obtain meteorological forecast data includes:

[0037] The current meteorological data is subjected to data screening and feature construction to obtain meteorological data to be cleaned;

[0038] The meteorological data to be cleaned is cleaned to obtain the meteorological forecast data.

[0039] The present invention also provides a device for monitoring meteorological conditions around power facilities based on quantum radar, comprising:

[0040] A meteorological parameter set acquisition module is used to obtain a meteorological parameter set;

[0041] A quantum laser pulse emission module, configured to control the quantum radar detection system to emit quantum laser pulses based on the meteorological parameter set;

[0042] A photon detection signal receiving module, configured to receive a photon detection signal corresponding to the quantum laser pulse based on a preset analog channel and / or a single photon counting channel;

[0043] The current meteorological data acquisition module is used to process the photon detection signal to obtain the current meteorological data corresponding to the meteorological parameter set, including:

[0044] a data-to-be-corrected obtaining unit, configured to accumulate data on the photon detection signal based on a counter or an adder to obtain data to be corrected;

[0045] a data to be analyzed obtaining unit, configured to correct the data to be corrected based on a preset data table to obtain the data to be analyzed;

[0046] a photon detection signal information obtaining unit, configured to perform spectrum analysis on the data to be analyzed based on a preset algorithm to obtain the frequency characteristics and spectrum diagram of the photon detection signal;

[0047] The current meteorological data obtaining unit is configured to analyze the frequency characteristics and the spectrum diagram to obtain the current meteorological data.

[0048] As a further optimized technical solution, the current meteorological data acquisition module further includes:

[0049] A standard signal acquisition unit, configured to acquire at least one standard signal of known signal strength, and obtain an output value of the analog-to-digital converter and a measurement value of the quantum detector corresponding to the standard signal;

[0050] a relationship obtaining unit, configured to pair the output value of the analog-to-digital converter with the measurement value of the quantum detector to generate a corresponding relationship between the output value and the measurement value;

[0051] A data table generating unit is configured to generate the data table based on the output value of the analog-to-digital converter, the measurement value of the quantum detector, and the corresponding relationship.

[0052] The technical solution of the present invention enables accurate monitoring of the weather around power facilities, such as substations, so that professionals can promptly protect the power facilities accordingly, reducing the probability of power facilities being shut down due to disasters and ensuring electricity for production and daily life. The advantages of the present invention are as follows:

[0053] 1. By using quantum radar to collect meteorological data, quantum radar uses single-photon detection technology, which can achieve a higher signal-to-noise ratio when the emitted laser energy is low. It can effectively identify and measure the echo signal, thus avoiding the reduction of data accuracy caused by bad weather;

[0054] 2. The present invention builds a pre-qualified data table, which is used to calibrate the ADC output value of the actual measurement signal, thereby obtaining more accurate quantum detector measurement values ​​and further improving data accuracy;

[0055] 3. The analog channels and single-photon counting channels can be multiplexed and superimposed according to actual needs to achieve multi-channel and targeted acquisition, thereby improving data acquisition efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0057] Figure 1 This is a schematic flow chart of a first embodiment of a method for monitoring meteorological conditions around power facilities based on quantum radar, according to an embodiment of the present application;

[0058] Figure 2 This is a schematic flow chart of a second embodiment of a method for monitoring meteorological conditions around power facilities based on quantum radar, according to an embodiment of the present application;

[0059] Figure 3 This is a schematic flow chart of a third embodiment of a method for monitoring meteorological conditions around power facilities based on quantum radar, provided in an embodiment of the present application;

[0060] Figure 4 A schematic block diagram of a quantum radar-based meteorological monitoring device for power facilities provided in an embodiment of the present application. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0062] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0063] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0064] It should be further understood that the term “and / or” used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0065] See also Figure 1 , Figure 1 This is a schematic flow chart of a method for meteorological monitoring around power facilities based on quantum radar provided in an embodiment of the present application. This method for meteorological monitoring around power facilities based on quantum radar can be applied to a server to collect meteorological data by adopting quantum radar. Quantum radar uses single-photon detection technology, which can achieve a higher signal-to-noise ratio when the emitted laser energy is low, and can effectively identify and measure echo signals, thereby avoiding the reduction in data accuracy caused by bad weather; analog channels and single-photon counting channels can be multiplexed and superimposed according to actual needs to achieve multi-channel, targeted collection, thereby improving data collection efficiency and accuracy. Among them, the server can be an independent server or a server cluster.

[0066] like Figure 1 As shown, the method for meteorological monitoring around power facilities based on quantum radar specifically includes steps S101 to S104.

[0067] S101, obtaining a meteorological parameter set;

[0068] Furthermore, the obtaining of the meteorological parameter set includes: receiving a user operation; determining a target warning in a preset meteorological warning based on the user operation; obtaining parameters corresponding to the target warning in a preset meteorological parameter database to generate the meteorological parameter set.

[0069] In one embodiment, users can select the required warnings based on actual needs, such as cloud-layer thunderstorm warnings, air pollution warnings, and sandstorm warnings for weekly power facility monitoring. It is understood that the warning types and the meteorological parameters corresponding to each warning type can be pre-packaged in a meteorological parameter database and set in the quantum radar detection system or a device connected to the quantum radar detection system. For example, thunderstorm warnings can include thunderstorm clouds, their movement speed, and their shape.

[0070] In one embodiment, after the target warning is determined, parameters corresponding to the target warning are obtained to generate a meteorological parameter set.

[0071] S102. Based on the meteorological parameter set, control the quantum radar detection system to emit quantum laser pulses;

[0072] In one embodiment, the control center of the quantum radar detection system generates an acquisition command based on the obtained meteorological parameter set to be collected, and controls the transmitter of the quantum radar detection system to emit quantum laser pulses according to the acquisition command.

[0073] In one embodiment, a quantum radar detection system includes a data acquisition system and a transmission subsystem. The core device of the transmission subsystem is a laser, which emits quantum laser pulses through the laser. The data acquisition system is a subsystem of the quantum radar detection system and consists of hardware and software. The hardware component is responsible for quickly and accurately digitizing the signal output by the quantum detector and transmitting the acquired data to the data processing system in real time. The data acquisition software is the control center of the quantum radar system. It is responsible for sending the set acquisition parameters and acquisition commands to the hardware devices and receiving large amounts of data transmitted from the hardware devices. In addition, it is also necessary to transmit the data to the inversion calculation module, human-computer interface, or database. To achieve hardware reconfiguration and improve the reusability of the hardware design, most of the digital circuits in the system hardware framework are implemented using FPGAs (Field Programmable Logic Arrays). When the digital circuit design needs to be modified, it can be achieved by reprogramming the FPGA. When the FPGA chip itself is upgraded, most of the digital circuit designs can also be directly transplanted without the need for additional development.

[0074] In one embodiment, a data acquisition system includes a timing control section, primarily divided into two parts: timing signal input and timing signal output. The timing signal input section primarily consists of a comparator and a delay device within the FPGA. The comparator is used to identify the input gate signal, eliminate the effects of noise, and prevent false triggering. A high-speed comparator with a delay of less than 5ns should be used. The delay device primarily delays the input gate signal. In some applications, after the gate signal arrives, a delay is required before operation begins. Delay accuracy is not critical here; a delay accuracy of the order of 4-10ns is sufficient, and this can be achieved using the FPGA's internal counter. The gate output section primarily consists of a programmable timing control circuit within the FPGA. This circuit primarily consists of a command buffer and a delay device. The command buffer can be implemented using internal memory, and the delay device can be implemented using a counter. Timing parameters are programmed on a computer and written into the timing control circuit's buffer. The timing parameters are then read sequentially and the output level adjusted. A counter is used to control the interval between parameter readouts.

[0075] In one embodiment, the data acquisition system also includes a centralized control section, which primarily implements all control functions except timing control. It consists of digital I / O, analog input, and output, and controls peripheral devices digitally or analogically. The digital I / O is primarily used to control mechanical components and communicate with other electronic devices, such as digital sensors. Analog input is primarily used to monitor detector operating voltage and analog sensor signals, primarily through a high-precision ADC (Analog to Digital Converter). Analog output is primarily used to control detector operating voltage and output laser modulation signals, primarily through a high-precision DAC (Digital to Analog Converter). The data interface, consisting of data interface circuitry within the FPGA and an independent interface chip, primarily enables communication with a computer. To achieve high-speed data transmission while achieving optimal universal applicability, the system primarily utilizes the Universal Serial Bus (USB) and Ethernet, currently the most widely used in the computer field.

[0076] In one embodiment, the data acquisition system needs to provide a current-to-voltage gain of 10⁶-10⁸ times, based on the detector's output range, to facilitate analog-to-digital conversion. Signal gain is primarily composed of detector gain and amplifier gain. Although detector gain is relatively high, such as a photomultiplier tube gain of 10⁶, the output current signal is still very weak, typically in the nA (nanoampere, a unit of current), due to the weak echo signal. This weak current is not conducive to signal acquisition.

[0077] In one embodiment, the signal conditioning circuitry of the data acquisition system should provide an analog bandwidth of approximately 100 MHz (megahertz, a unit of frequency) to allow the echo pulse to pass through without distortion. Currently, narrow laser pulses are commonly used for detection. Their leading edge is typically faster than their trailing edge, and the leading edge typically has a quasi-Gaussian waveform. This Gaussian waveform bandwidth implies that the laser pulse's signal bandwidth, fS (frequency), is approximately between 10 and 100 MHz. Given the detector's frequency response, this signal can pass smoothly.

[0078] In one embodiment, in a photon counting detection mode, the data acquisition system needs to configure information such as the count rate, timing width, dead time, and number of count bits based on the characteristics of photon counting detection. Specifically, regarding the count rate: In the photon counting mode, the arrival time of photon pulses is random, and two photon pulses may be very close together. If the distance is too close, the quantum detector cannot distinguish them and will be output as a single photon. Therefore, the quantum detector in single-photon counting mode has a maximum count rate, which represents the minimum pulse time interval that the quantum detector can resolve. In the data acquisition system, the maximum count rate of the counter should be greater than or equal to the maximum count rate output by the quantum detector to meet the counting requirements. The dead time of PMT (photomultiplier tube) and APD (avalanche photodiode) ranges from a few nanoseconds to tens of nanoseconds, and the maximum count rate should be between 10 MHz and 100 MHz. Timing width: During photon counting detection, the accumulated values ​​need to be saved at regular intervals. The minimum counting time width represents the time interval between two adjacent values ​​and corresponds to the distance resolution of the quantum radar. Theoretically, the shorter the minimum counting time width, the better. However, due to limitations on the number of counters and the storage and accumulation time, the minimum counting time width is generally required to be several nanoseconds to tens of nanoseconds. Dead time: The dead time of a data acquisition system originally refers to the time during which a counter cannot receive photon pulses due to data storage. However, due to the common ping-pong mode, which allows normal counting while data is stored, the dead time of the data acquisition system has been redefined: when counters switch, all counters may be inactive for a short period due to fluctuations in the control signal. This period is called the dead time of the data acquisition system. To achieve a counting accuracy of 99.50%, the dead time is generally required to be no more than 50% of the timing width. Number of counting bits: When operating in photon counting mode, detection results must be accumulated multiple times to achieve a usable signal-to-noise ratio. The resulting data may be large, so a certain number of counting bits is required to avoid data overflow. However, setting the number of bits too high will affect the accumulation speed and, therefore, the minimum counting time width. Therefore, the number of counting bits is typically set between 16 and 20.

[0079] S103, receiving a photon detection signal corresponding to the quantum laser pulse based on a preset analog channel and / or single photon counting channel;

[0080] Furthermore, the receiving of the photon detection signal corresponding to the quantum laser pulse based on the preset analog channel and / or single-photon counting channel includes: receiving a first photon detection signal based on the analog channel, wherein the first photon detection signal is a signal obtained by the laser echo signal corresponding to the quantum laser pulse in an analog or linear manner, and / or receiving a second photon detection signal based on the single-photon counting channel, wherein the second photon detection signal is a signal obtained by the laser echo signal corresponding to the quantum laser pulse in a single-photon mode.

[0081] In one embodiment, the laser echo signal must be converted into an electrical signal by a quantum detector before it can be collected.

[0082] In one embodiment, the analog channel is composed of an analog signal conditioning module and an analog-to-digital converter, and is used to receive quantum detector signals operating in an analog mode or a linear mode.

[0083] In one embodiment, a single-photon counting channel is composed of a signal conditioning module, a single-channel analyzer, and a counter in an FPGA, and is used to receive signals from a quantum detector operating in a single-photon mode.

[0084] Furthermore, receiving the first photon detection signal based on the analog channel includes: adjusting the signal output by the quantum detector based on a signal conditioning module to obtain the first photon detection signal; and driving the analog-to-digital converter based on a differential driver to collect the first photon detection signal.

[0085] In one embodiment, the ADC is the core chip of the analog channel. Considering the signal characteristics of quantum radar, the sampling rate and sampling accuracy requirements are relatively high. Therefore, a pipelined ADC is the best choice for analog signal acquisition. The dynamic range of quantum radar signals is between 104 and 105 decibels, while the smallest signals of 1 to 2 orders of magnitude are typically acquired using photon counting. Therefore, the dynamic range of the analog channel should reach between 103 and 104 decibels, which requires an ADC sampling accuracy of 12-14 bps. Since the signal bandwidth of quantum radar is approximately 100 MHz, the minimum ADC sampling rate should be 20-200 MSPS. A pipelined ADC with a sampling rate of 14 bps and a sampling rate of 250 MSPS is typically selected.

[0086] The sampling rate refers to the speed at which the ADC samples the signal. The sampling rate determines the quantum radar's range resolution; the higher the sampling rate, the better the range resolution. According to the sampling theorem, the sampling rate should be at least twice the signal bandwidth to acquire the signal without distortion. This is the theoretical minimum requirement. In practice, oversampling should be at least 3-10 times, depending on the bandwidth of the quantum radar's echo signal. Oversampling can improve the sampling signal-to-noise ratio. Therefore, depending on the signal bandwidth, the sampling rate should be between 100MSPS and 1000MSPS. However, high-sampling-rate analog-to-digital converter chips are expensive and difficult to source. Therefore, a compromise between 250MSPS and 500MSPS is acceptable.

[0087] Sampling accuracy refers to the number of bits of data obtained after an ADC samples and quantizes a signal. Theoretically, higher sampling accuracy results in higher signal resolution, meaning smaller recognizable signal amplitudes. However, since sampling noise often exceeds the minimum signal amplitude specified by the sampling accuracy, acquisition accuracy is of limited practical significance. Effective bits, calculated after accounting for the effects of sampling noise, measure the true accuracy of the system and indicate the minimum value that can be truly resolved. Generally, effective bits increase with ADC accuracy. Quantum radars have a large dynamic range, so an ADC with the highest possible accuracy is generally preferred. However, the overall system signal-to-noise ratio (SNR) can render even high accuracy ineffective. Furthermore, ADC accuracy and sampling rate are in conflict. High-precision ADCs often cannot achieve high-speed sampling, so a compromise is typically chosen, with an accuracy of 12-14 bits.

[0088] In one embodiment, the signal conditioning module is used to condition the quantum detector output signal to a signal suitable for ADC sampling. This involves amplifying the signal amplitude and filtering out high-frequency components. Its amplification factor should be between 10⁶ and 10⁸. It specifically includes a preamplifier, a main amplifier, a low-pass filter, and a differential driver. The preamplifier converts the detector's output current signal into a voltage signal, while the main amplifier further amplifies the preamplifier signal. The preamplifier's output signal is typically tens to hundreds of millivolts, and the main amplifier's amplification factor should be between 2 and 20. The low-pass filter filters out high-frequency components in the signal to prevent aliasing after ADC sampling. The cutoff frequency can be selected based on the ADC sampling rate and should not exceed half the sampling frequency. For example, if the ADC sampling rate is 250 MSPS (a unit of conversion rate), the cutoff frequency should not exceed half the sampling frequency. The differential driver converts the single-ended signal into a differential signal to drive the ADC for sampling. Common high-speed differential amplifiers typically require a certain amplification factor for stable operation; generally, a factor of 2-3 is considered acceptable.

[0089] Furthermore, the receiving of the second photon detection signal based on the single-photon counting channel includes: filtering the photon signal based on a single-channel analyzer to obtain a target pulse signal; counting the target pulse signal based on a counter to obtain photon flow information as the second photon detection signal.

[0090] In one embodiment, some single-photon detectors have their own preamplifier and shaping circuit, and their output is directly a digital pulse signal. The photon counting channel connected to such a detector can eliminate the signal conditioning module and the single-channel analyzer, and can directly use the counter for counting. Quantum detectors working in single-photon mode usually have a relatively high operating voltage and a relatively large detector gain, so their signal output amplitude is not lower than that of quantum detectors working in an analog state. The signal conditioning part of the photon counting channel is relatively simple compared to the analog channel, and generally only has a preamplifier and a main amplifier. Similar to the analog channel, the main amplifier has an amplification factor of 20 times. The bandwidth of the entire signal conditioning part is generally required to be 50-100MHz.

[0091] Signal gain is primarily composed of detector gain and amplifier gain. Although detector gain is relatively high—for example, a photomultiplier tube can achieve 10⁶ times gain—the echo signal is too weak, resulting in a very weak output current signal, typically in the nanoamp range. This weak current is not conducive to signal acquisition. The data acquisition system needs to provide a current-to-voltage gain of 10⁶-10⁸ times, depending on the detector's output range, to facilitate analog-to-digital conversion.

[0092] In one embodiment, a single-channel analyzer primarily screens photon signals, filtering out pulses with excessively high or low amplitudes. These pulses are not caused by incident photons, but rather by thermal noise and cosmic rays. The single-channel analyzer primarily consists of two comparators. Considering that the maximum output pulse frequency of a single-photon detector is typically 10-100 MHz, high-speed comparators with a delay time of less than 5 ns should be selected. A counter, used to count pulses output by a single channel, typically needs to save the data at regular intervals. Since saving data takes time, and the counter is unable to count during the data saving process, to avoid missing photon pulses, two counters are typically used in a ping-pong configuration. While one counter is operating, the data from the other is saved. In this case, the minimum counting time duration is equal to the time required to save the data. Furthermore, the photon counting measurement method typically requires the accumulation of multiple detection results to improve the signal-to-noise ratio and obtain a usable signal. Therefore, the data counted during the ping-pong counting process must be accumulated. Therefore, the minimum time duration must be added to the accumulation time. Using more than two counters for ping-pong operation can reduce the minimum time duration.

[0093] S104: Process the photon detection signal to obtain current meteorological data corresponding to the meteorological parameter set.

[0094] In one embodiment, the collected photon detection signals are cached. The analog signal acquisition channel places the greatest demands on data caching. Its high-speed, high-precision sampling results in a continuous influx of data. In most cases, internal memory resources are insufficient to store this large amount of data. Therefore, the data cache consists of internal memory, memory control, and external memory. Internal memory primarily utilizes the FPGA's internal memory resources, offering high speed and ease of operation. However, due to its limited internal memory resources, the FPGA cannot store large amounts of data. External memory utilizes a separate memory chip, such as SDRAM (synchronous dynamic random-access memory). The memory control facilitates data exchange between internal and external memory, as well as between the data processing module. Internal memory is typically used as a high-speed buffer, with a maximum access speed determined by the FPGA chip, typically between 300MHz and 600MHz. Therefore, if the ADC sampling rate exceeds the internal memory's maximum access speed, a serial-to-parallel converter should be added before the high-speed buffer to reduce its data rate. The internal memory capacity should generally be sufficient to store at least all the data required after a single laser pulse emission. The external memory capacity and write speed are generally selected based on the specific requirements of quantum radar data acquisition.

[0095] In one embodiment, processing the acquired photon detection signal primarily involves data accumulation, data correction, and spectrum analysis. Data accumulation can be implemented within the FPGA, specifically involving analog channels and photon counting channels. Data correction can be implemented using a lookup table within the FPGA. Spectral analysis involves Fourier transform, primarily performed using an external DSP (Digital Signal Processor).

[0096] In one embodiment, current meteorological data includes time-domain and frequency-domain information. Time-domain information represents the intensity variation of the laser echo signal over time. Light signals must be converted into electrical signals by a quantum detector before they can be collected. The quantum detector output is linearly related to light intensity, so time-domain information represents the temporal variation of the quantum detector output signal. Frequency-domain information represents the amplitude and phase distribution of each frequency component in the laser echo signal.

[0097] In the above embodiment, meteorological data is collected by using quantum radar. The quantum radar uses single-photon detection technology, which can achieve a higher signal-to-noise ratio when the emitted laser energy is low, and can effectively and accurately identify and measure the echo signal, thereby avoiding the reduction in data accuracy caused by bad weather. The analog channel and the single-photon counting channel can be multiplexed and superimposed according to actual needs to achieve multi-channel, targeted collection, thereby improving data collection efficiency and accuracy.

[0098] See also Figure 2 , Figure 2 This is a schematic flow chart of a quantum radar-based meteorological monitoring method for power facilities, provided in an embodiment of the present application. This quantum radar-based meteorological monitoring method can be applied to a server to accumulate, correct, and perform spectrum analysis on photon detection signals collected by the quantum radar, thereby obtaining meteorological data and improving data collection efficiency and accuracy.

[0099] like Figure 2 As shown, step S104 of the method for monitoring meteorological conditions around power facilities based on quantum radar specifically includes steps S201 to S204.

[0100] S201, accumulating data of the photon detection signal based on a counter or an adder to obtain data to be corrected;

[0101] S202: Based on a preset data table, correct the data to be corrected to obtain data to be analyzed;

[0102] S203, performing spectrum analysis on the data to be analyzed based on a preset algorithm to obtain frequency characteristics and a spectrum diagram of the photon detection signal;

[0103] S204: Analyze the frequency characteristics and the spectrum diagram to obtain the current meteorological data.

[0104] In one embodiment, data accumulation can be implemented inside the FPGA, specifically involving analog channels and photon counting channels.

[0105] In one embodiment, data accumulation in the single-photon counting channel can be achieved directly through asynchronous data loading of the counter. After each data is saved, the data at the next address is loaded into the counter. In this way, in the next counting cycle, the counter value is incremented based on the previous count, thus achieving count accumulation. Data accumulation in the analog channel requires an adder. At high sampling rates, the interval between two samples is often insufficient to complete data reading, accumulation, and writing. In this case, multiple adders can be used to work in rotation, allowing a single accumulation operation to be completed within multiple sampling cycles.

[0106] Furthermore, the correction of the data to be corrected based on a preset data table, before obtaining the data to be analyzed, also includes: collecting at least one standard signal with known signal strength, and obtaining the output value of the analog-to-digital converter and the measurement value of the quantum detector corresponding to the standard signal; pairing the output value of the analog-to-digital converter and the measurement value of the quantum detector to generate a corresponding relationship between the output value and the measurement value; generating the data table based on the output value of the analog-to-digital converter, the measurement value of the quantum detector and the corresponding relationship.

[0107] In a specific embodiment, a standard signal source of known intensity is selected, and the frequency, amplitude, and waveform of the signal should match the characteristics of the signal to be measured. The standard signal is input into the system and passed through the ADC and the quantum detector. The analog-to-digital converter converts the received signal into a digital signal and generates a series of digital output values. The quantum detector converts the received signal into an electrical signal, measures it, and records the measured value. The output value of the ADC is paired with the measurement value of the quantum detector to establish a corresponding relationship between them. A data table is created based on the paired output value and measurement value. The data table can contain multiple columns, such as timestamp, ADC output value, quantum detector measurement value, etc. In subsequent data processing, this data table is used to calibrate the ADC output value of the actual measurement signal to obtain more accurate quantum detector measurement values.

[0108] In one embodiment, the data table is updated periodically using a standard signal to account for possible system drift or changes.

[0109] In one embodiment, data correction can be implemented using a lookup table within the FPGA. Specifically, the data acquisition system is calibrated using a standard signal source and quantum detector. The calibrated, accurate data is stored in a lookup table. During data acquisition, the ADC output is used as an address to read the correct data from the lookup table, which is then stored in a cache. The lookup table is primarily implemented using internal FPGA memory, whose bit width matches the ADC resolution and whose depth is 2R (where R is the ADC resolution).

[0110] In one embodiment, spectrum analysis is performed based on a preset algorithm, involving Fourier transform, which is mainly completed using an external DSP to obtain the frequency characteristics and spectrum diagram of the photon detection signal. Specifically, a suitable spectrum analysis algorithm is selected according to the characteristics of the signal and the purpose of analysis. Common algorithms include: fast Fourier transform: converting the time domain signal into the frequency domain signal; short-time Fourier transform: analyzing the local time-frequency characteristics of the signal; wavelet transform: suitable for analyzing non-stationary signals. The selected algorithm is applied to the data to be analyzed to obtain the spectrum characteristics of the signal. Based on the spectrum characteristics, a spectrum diagram is drawn to show the frequency distribution and intensity of the signal.

[0111] In one embodiment, spectrum analysis can convert a signal in the time domain into a spectrum in the frequency domain, thereby revealing information such as the amplitude, phase, and frequency of different frequency components in the signal. In spectrum analysis of photon detection signals, the Fourier transform or its variants (such as the fast Fourier transform, FFT) are typically used to convert the time domain signal into a frequency domain signal. The Fourier transform is a mathematical tool that can represent a function as the sum of a series of sine and cosine functions, where the frequencies of these sine and cosine functions are components of the original function's spectrum.

[0112] The peaks on the spectrum plot correspond to the primary frequency components in the signal. By analyzing the location and amplitude of these peaks, we can understand the primary frequency characteristics of the signal. By analyzing the spectrum plot, we can determine the signal's bandwidth and thus understand its distribution in the frequency domain. The amplitude values ​​on the spectrum plot reflect the energy distribution of the signal at different frequencies. By analyzing these amplitude values, we can understand the energy contribution of the signal at different frequencies.

[0113] In one embodiment, the frequency characteristics and spectrum graph obtained by spectrum analysis can be analyzed to extract information such as the distance, speed, and spectrum characteristics of the target object, such as the distance and moving speed of thunderstorm clouds.

[0114] In the above embodiment, data accumulation and data correction are first performed on the photon detection signals collected by the quantum radar, thereby improving the accuracy of the data to be analyzed, improving the accuracy of the results of the spectrum analysis, and further improving the accuracy of the meteorological data.

[0115] See also Figure 3 , Figure 3 This is a schematic flow chart of a quantum radar-based meteorological monitoring method for power facilities, provided in an embodiment of the present application. This quantum radar-based meteorological monitoring method for power facilities can be applied to a server to predict future weather conditions based on acquired meteorological data and generate different defense strategies based on different prediction results, thereby improving the timeliness and diversity of meteorological defenses.

[0116] like Figure 3As shown, after step S104, the method for monitoring meteorological conditions around power facilities based on quantum radar further includes steps S301 to S303.

[0117] S301, pre-processing the current meteorological data to obtain meteorological forecast data;

[0118] S302: Processing the weather forecast data based on a target forecast model to obtain a weather forecast result, and obtaining a weather defense strategy based on the weather forecast result;

[0119] S303: Generate a weather warning based on the weather forecast result and the weather defense strategy.

[0120] Furthermore, the preprocessing of the current meteorological data to obtain meteorological forecast data includes: performing data screening and feature construction on the current meteorological data to obtain meteorological data to be cleaned; and performing data cleaning on the meteorological data to be cleaned to obtain the meteorological forecast data.

[0121] In one embodiment, a correlation test, such as the Pearson correlation coefficient, Spearman rank correlation, or mutual information, is performed on the current meteorological data. Based on the correlation test results, the current meteorological data is screened to obtain the meteorological data to be cleaned. Specifically, based on the correlation test results, variables that are highly correlated with the prediction target are selected as features. Variables whose correlation with the prediction target is less than a preset threshold or are unrelated are excluded. Finally, one of the two variables whose correlation exceeds the preset threshold is deleted.

[0122] In one embodiment, further feature construction is performed on the filtered data, such as creating lag features, time window features, and deriving new features. Specifically, new features can be derived based on business knowledge or data understanding, such as calculating relative humidity from temperature and absolute humidity. Aggregate statistical features based on fixed time windows (such as the past 3 hours or the past 24 hours) can also be generated, such as total precipitation or average temperature. Various statistics within a rolling time window can also be calculated, such as average, maximum, minimum, and sum.

[0123] In one embodiment, the filtered and constructed meteorological data to be cleaned is cleaned to process missing values, outliers, or erroneous data. Data interpolation techniques are applied to fill missing values, or clustering and outlier detection algorithms are used to identify and process outliers.

[0124] In one embodiment, the target prediction model can be determined by the location information corresponding to the current meteorological data. Different prediction models are used for different locations to improve the accuracy of the prediction results. The target prediction model can also be determined by the type of warning (such as atmospheric pollutant warning, thunderstorm warning, wind warning, etc.). Using different prediction models for different location information or different warning types can improve the adaptability of the prediction model to the meteorological forecast data, maximize the performance of the prediction model, and improve the accuracy of the prediction results.

[0125] In a specific embodiment, there can be many types of target prediction models, including but not limited to statistical models, machine learning models, deep learning models, etc. Exemplarily, the target prediction model can be a long short-term memory network, including an input layer: receiving weather forecast data. Embedding layer: If the input weather forecast data is classified data, the embedding layer can be used to convert the category features into dense vectors. LSTM (long short-term memory) layer: one or more LSTM layers are used to process the input data to capture long-term dependencies in the time series. Fully connected layer: one or more fully connected layers, used to learn complex nonlinear relationships. Output layer: the last fully connected layer, whose activation function and output dimension are determined according to the nature of the prediction task (for example, linear activation function is used for regression tasks, softmax activation function is used for multi-class classification tasks), and outputs the prediction results.

[0126] In one embodiment, a target prediction model is used to obtain a weather forecast result based on weather forecast data, and then a weather defense strategy is searched based on the weather forecast result. Specifically, the weather defense strategy corresponding to the weather forecast result can be searched in a pre-generated weather forecast result and weather defense strategy mapping table.

[0127] In one embodiment, a weather warning is generated by combining weather forecast results and weather defense strategies, and is displayed to the user to remind the user of weather changes and provide the user with defense reference strategies.

[0128] See also Figure 4 , Figure 4 This is a schematic block diagram of a quantum radar-based meteorological monitoring device for power facilities, provided in an embodiment of the present application. This quantum radar-based meteorological monitoring device is configured to perform the aforementioned quantum radar-based meteorological monitoring method for power facilities. The quantum radar-based meteorological monitoring device for power facilities can be deployed on a server.

[0129] like Figure 4 As shown, the power facility perimeter weather monitoring device 400 based on quantum radar includes:

[0130] Meteorological parameter set acquisition module 401, used to acquire a meteorological parameter set;

[0131] A quantum laser pulse emission module 402 is configured to control the quantum radar detection system to emit quantum laser pulses based on the meteorological parameter set;

[0132] A photon detection signal receiving module 403 is configured to receive a photon detection signal corresponding to the quantum laser pulse based on a preset analog channel and / or single photon counting channel;

[0133] The current meteorological data acquisition module 404 is used to process the photon detection signal to obtain the current meteorological data corresponding to the meteorological parameter set.

[0134] Furthermore, the photon detection signal receiving module 403 includes:

[0135] A first photon detection signal receiving unit is configured to receive a first photon detection signal based on the analog channel, wherein the first photon detection signal is a signal obtained by analog or linear means from a laser echo signal corresponding to the quantum laser pulse, and / or

[0136] The second photon detection signal receiving unit is used to receive a second photon detection signal based on a single photon counting channel, wherein the second photon detection signal is a signal obtained by the laser echo signal corresponding to the quantum laser pulse in a single photon mode.

[0137] Furthermore, the first photon detection signal receiving unit includes:

[0138] A first photon detection signal obtaining subunit is configured to adjust the signal output by the quantum detector based on the signal conditioning module to obtain the first photon detection signal;

[0139] The first photon detection signal acquisition subunit is configured to drive the analog-to-digital converter based on a differential driver to acquire the first photon detection signal.

[0140] Furthermore, the second photon detection signal receiving unit includes:

[0141] A target pulse signal acquisition subunit is used to filter the photon signal based on a single-channel analyzer to obtain a target pulse signal;

[0142] The photon flow information obtaining subunit is configured to count the target pulse signal based on a counter to obtain photon flow information as the second photon detection signal.

[0143] Furthermore, the current meteorological data acquisition module 404 includes:

[0144] a data-to-be-corrected obtaining unit, configured to accumulate data on the photon detection signal based on a counter or an adder to obtain data to be corrected;

[0145] a data to be analyzed obtaining unit, configured to correct the data to be corrected based on a preset data table to obtain the data to be analyzed;

[0146] a photon detection signal information obtaining unit, configured to perform spectrum analysis on the data to be analyzed based on a preset algorithm to obtain the frequency characteristics and spectrum diagram of the photon detection signal;

[0147] The current meteorological data obtaining unit is configured to analyze the frequency characteristics and the spectrum diagram to obtain the current meteorological data.

[0148] Furthermore, the current meteorological data obtaining module 404 further includes:

[0149] A standard signal acquisition unit, configured to acquire at least one standard signal of known signal strength, and obtain an output value of the analog-to-digital converter and a measurement value of the quantum detector corresponding to the standard signal;

[0150] a relationship obtaining unit, configured to pair the output value of the analog-to-digital converter with the measurement value of the quantum detector to generate a corresponding relationship between the output value and the measurement value;

[0151] A data table generating unit is configured to generate the data table based on the output value of the analog-to-digital converter, the measurement value of the quantum detector, and the corresponding relationship.

[0152] Furthermore, the meteorological parameter set acquisition module 401 includes:

[0153] A user operation receiving unit, configured to receive user operations;

[0154] a target warning obtaining unit, configured to determine a target warning from preset weather warnings based on the user operation;

[0155] The meteorological parameter set generating unit is used to obtain the parameters corresponding to the target warning in a preset meteorological parameter database and generate the meteorological parameter set.

[0156] Furthermore, the quantum radar-based power facility perimeter meteorological monitoring device 400 further includes a meteorological warning generation module, and the meteorological data generation module includes:

[0157] A weather forecast data obtaining unit, configured to pre-process the current weather data to obtain weather forecast data;

[0158] a weather defense strategy obtaining unit, configured to process the weather forecast data based on a target forecast model to obtain a weather forecast result, and obtain a weather defense strategy based on the weather forecast result;

[0159] A meteorological warning generating unit is used to generate a meteorological warning based on the meteorological forecast result and the meteorological defense strategy.

[0160] Furthermore, the weather forecast data obtaining unit includes:

[0161] A data screening subunit, configured to screen the current meteorological data and construct features to obtain meteorological data to be cleaned;

[0162] The data cleaning subunit is used to clean the meteorological data to be cleaned to obtain the meteorological forecast data.

[0163] It should be noted that those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0164] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for monitoring the weather around power facilities based on quantum radar, characterized in that: include: Get meteorological parameter set; Based on the meteorological parameter set, the quantum radar detection system is controlled to emit quantum laser pulses; Based on a preset analog channel and / or single photon counting channel, receiving a photon detection signal corresponding to a quantum laser pulse; Process the photon detection signal to obtain the current meteorological data corresponding to the meteorological parameter set, including: Based on a counter or adder, the photon detection signal is accumulated to obtain the data to be corrected; Based on the preset data table, the data to be corrected is corrected to obtain the data to be analyzed; Based on the preset algorithm, the spectrum analysis of the data to be analyzed is performed to obtain the frequency characteristics and spectrum diagram of the photon detection signal; Analyze frequency characteristics and spectrum diagrams to obtain current meteorological data; Based on the preset data table, the data to be corrected is corrected. Before obtaining the data to be analyzed, the following is also included: Collecting at least one standard signal of known signal strength, and obtaining the output value of the analog-to-digital converter and the measurement value of the quantum detector corresponding to the standard signal; Pairing the output value of the analog-to-digital converter with the measurement value of the quantum detector to generate a corresponding relationship between the output value and the measurement value; A data table is generated based on the output value of the analog-to-digital converter, the measurement value of the quantum detector and the corresponding relationship.

2. The method for monitoring meteorological conditions around power facilities based on quantum radar according to claim 1, characterized in that: The receiving of the photon detection signal corresponding to the quantum laser pulse based on the preset analog channel and / or single photon counting channel includes: Based on the analog channel, a first photon detection signal is received, wherein the first photon detection signal is a signal obtained by analog or linear means from a laser echo signal corresponding to the quantum laser pulse, and / or A second photon detection signal is received based on a single-photon counting channel, wherein the second photon detection signal is a signal obtained by a laser echo signal corresponding to the quantum laser pulse in a single-photon mode.

3. The method for monitoring meteorological conditions around power facilities based on quantum radar according to claim 2, characterized in that: The receiving a first photon detection signal based on the analog channel includes: Based on the signal conditioning module, adjusting the signal output by the quantum detector to obtain the first photon detection signal; Based on the differential driver, the analog-to-digital converter is driven to collect the first photon detection signal.

4. The method for monitoring meteorological conditions around power facilities based on quantum radar according to claim 2, characterized in that: The receiving of the second photon detection signal based on the single photon counting channel includes: The target pulse signal is obtained by filtering the photon signal based on the single-channel analyzer; The target pulse signal is counted based on a counter to obtain photon flow information, which is used as the second photon detection signal.

5. The method for monitoring meteorological conditions around power facilities based on quantum radar according to any one of claims 1 to 4, characterized in that: The obtaining of the meteorological parameter set includes: Receive user operations; Based on the user operation, determining a target warning in a preset weather warning; In a preset meteorological parameter database, parameters corresponding to the target warning are obtained to generate the meteorological parameter set.

6. The method for monitoring meteorological conditions around power facilities based on quantum radar according to claim 1, characterized in that: After processing the photon detection signal to obtain current meteorological data corresponding to the meteorological parameter set, the method further includes: Preprocessing the current meteorological data to obtain meteorological forecast data; Processing the weather forecast data based on a target forecast model to obtain a weather forecast result, and obtaining a weather defense strategy based on the weather forecast result; A meteorological warning is generated based on the meteorological forecast results and the meteorological defense strategy.

7. The method for monitoring meteorological conditions around power facilities based on quantum radar according to claim 6, characterized in that: The preprocessing of the current meteorological data to obtain meteorological forecast data includes: The current meteorological data is subjected to data screening and feature construction to obtain meteorological data to be cleaned; The meteorological data to be cleaned is cleaned to obtain the meteorological forecast data.

8. A quantum radar-based meteorological monitoring device for power facilities, characterized in that: include: A meteorological parameter set acquisition module is used to obtain a meteorological parameter set; A quantum laser pulse emission module, configured to control the quantum radar detection system to emit quantum laser pulses based on the meteorological parameter set; A photon detection signal receiving module, configured to receive a photon detection signal corresponding to the quantum laser pulse based on a preset analog channel and / or a single photon counting channel; The current meteorological data acquisition module is used to process the photon detection signal to obtain the current meteorological data corresponding to the meteorological parameter set, including: a data-to-be-corrected obtaining unit, configured to accumulate data on the photon detection signal based on a counter or an adder to obtain data to be corrected; a data to be analyzed obtaining unit, configured to correct the data to be corrected based on a preset data table to obtain the data to be analyzed; a photon detection signal information obtaining unit, configured to perform spectrum analysis on the data to be analyzed based on a preset algorithm to obtain the frequency characteristics and spectrum diagram of the photon detection signal; a current meteorological data obtaining unit, configured to analyze the frequency characteristics and the spectrum graph to obtain the current meteorological data; The current meteorological data acquisition module also includes: A standard signal acquisition unit, configured to acquire at least one standard signal of known signal strength, and obtain an output value of an analog-to-digital converter and a measurement value of a quantum detector corresponding to the standard signal; a relationship obtaining unit, configured to pair the output value of the analog-to-digital converter with the measurement value of the quantum detector to generate a corresponding relationship between the output value and the measurement value; A data table generating unit is configured to generate the data table based on the output value of the analog-to-digital converter, the measurement value of the quantum detector, and the corresponding relationship.

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