Atmosphere patrol monitoring method and system

Abstract

The invention discloses an atmosphere patrol monitoring method and system, belongs to the technical field of environment monitoring, and solves the problems that pollutants can be accumulated and diffused slowly in regional static and stable weather, and single-point monitoring data may be abnormally increased in the weather during detection but is difficult to distinguish whether the weather is affected by weather or a sudden emission source. Comprising the following steps: acquiring an original signal of a four-dimensional sensor array through a signal acquisition module; separating a meteorological background value and an emergent pollution signal in a baseline separation module to carry out dynamic baseline separation; the space gradient, the time mutation rate and the pollutant fingerprint ratio are calculated in the feature extraction module, and spatial-temporal feature extraction is achieved; and calculating a meteorological static stability index based on the output of the feature extraction module for static stability judgment. When the method works, through layer processing such as signal acquisition, baseline separation, feature extraction, environment compensation, static stability judgment, judgment logic, direction traceability and output interface, closed loop is completed, the static stability weather misjudgment rate is reduced, and the problem of confusion of data anomaly causes is solved.

Description

Technical Field

[0001] This invention relates to the field of environmental monitoring technology, and in particular to an atmospheric patrol and monitoring method and system. Background Technology

[0002] Atmospheric monitoring is a crucial means of dynamically supervising the atmospheric environment. By combining ground-based manual inspections, real-time sampling by mobile monitoring vehicles, aerial remote sensing by drones, and data linkage with fixed monitoring stations, it enables comprehensive investigation of key areas, pollution sources, and their surrounding environment. Its core function is to rapidly identify abnormal concentrations of air pollutants and trace pollution sources, particularly targeting issues such as industrial waste gas emissions, dust pollution, and straw burning, promptly detecting illegal and irregular activities such as exceeding emission standards and unauthorized discharges. Simultaneously, this work can analyze pollution diffusion trends in conjunction with meteorological conditions, providing data support for emergency response and precise pollution control, helping to improve the efficiency and targeting of atmospheric environmental quality management, and is a key link in ensuring continuous improvement in air quality.

[0003] In regional air quality monitoring, stable weather conditions, such as prolonged periods of no wind and temperature inversion, can cause pollutants to accumulate due to impeded dispersion, resulting in abnormally high levels of pollutants in monitoring data. However, such meteorological conditions can also mask the true impact of sudden emission sources, such as industrial accident leaks or illegal discharges, making it difficult for monitoring systems to distinguish whether data fluctuations are primarily caused by meteorological factors or human-caused emissions. This confusion can directly lead to misjudgments of short-term pollution causes, such as incorrectly attributing pollution peaks caused by illegal factory discharges to "natural meteorological processes," leading to insufficiently targeted control measures and ultimately weakening the effectiveness of pollution control.

[0004] Therefore, an atmospheric patrol and monitoring method and system are proposed to solve or alleviate the above problems. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing an atmospheric patrol and monitoring method and system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: An atmospheric patrol and monitoring method includes the following steps: The raw signals from the four-dimensional sensor array are acquired through the signal acquisition module; Dynamic baseline separation is performed by separating meteorological background values ​​from sudden pollution signals in the baseline separation module. In the feature extraction module, spatial gradient, temporal abrupt change rate, and pollutant fingerprint ratio are calculated to achieve spatiotemporal feature extraction; The static stability is determined by calculating the meteorological static stability index based on the output of the feature extraction module. The hardware condition decision is executed in the decision logic module to complete the fifth-level decision. When the response judgment logic module is triggered, the azimuth angle of the pollution source is calculated in the direction tracing module to locate the pollution source; Environmental compensation is achieved by real-time correction of environmental interference through an environmental compensation module. The signal is output by converting industry standard signals through the output interface module.

[0007] Preferably, the dynamic baseline separation of meteorological background values ​​and sudden pollution signals in the baseline separation module specifically includes the following steps: The original sensor signal was processed using a low-pass filter with a time constant of thirty minutes to extract the background signal; The sudden pollution signal is obtained by subtracting 20% ​​of the background signal value from the original signal; The physical response is achieved through programmable filters and analog switching circuits.

[0008] Preferably, the step of calculating the spatial gradient, temporal abrupt change rate, and contaminant fingerprint ratio in the feature extraction module to achieve spatiotemporal feature extraction specifically includes the following steps: The spatial gradient is obtained by directly measuring the absolute difference between the output voltages of two adjacent sensors. Calculate the difference between the current signal and the signal from thirty seconds ago, and divide it by the thirty-second time interval to obtain the time abrupt change rate; The pollutant fingerprint ratio is obtained by dividing the nitrogen oxide sensor voltage value by the carbon monoxide sensor voltage value plus zero.

[0009] Preferably, the step of calculating the meteorological static stability index based on the output of the feature extraction module to determine static stability specifically includes the following steps: The static stability index is calculated by adding the square of the wind speed measurement to one hundred and multiplying by the absolute value of the temperature gradient. When the static stability index is less than 1.0, it is determined to be a static and stable weather condition. The calculation is implemented using an envelope detection circuit and a differential amplifier hardware.

[0010] Preferably, the step of performing hardware condition judgment to complete the five-level judgment in the judgment logic module specifically includes the following steps: An alarm is triggered when the judgment logic module simultaneously meets the following conditions: the time mutation rate is greater than 20 micrograms per cubic meter per minute, the spatial gradient is greater than 0.1 volts, the static stability index is less than 1.0, and the pollutant fingerprint ratio is greater than 2.0. Joint judgment is achieved through comparator array and logic gate chip.

[0011] Preferably, when the response decision logic module is triggered, the pollution source azimuth angle is calculated in the direction tracing module to locate the pollution source, specifically including the following steps: Directly measure the time difference of pollutants arriving at different sensors; Multiply the vertical time difference by the speed of sound and then divide by the product of the horizontal time difference and the 50-centimeter sensor spacing. The azimuth angle can be obtained by calculating the arctangent of this ratio. This is achieved using a high-precision time conversion chip and an analog computer.

[0012] Preferably, the step of real-time correction of environmental interference by the environmental compensation module for environmental compensation specifically includes the following steps: The compensation coefficient can be obtained by querying the pre-stored coefficient table based on the temperature and humidity parameters; Real-time correction is achieved by multiplying the original signal by a compensation coefficient obtained from a lookup table. This is achieved through hardware components including memory chips and analog multipliers.

[0013] Preferably, the step of converting industrial standard signals through the output interface module for signal output specifically includes the following steps: Convert the azimuth angle signal into a current signal of four to twenty milliamps; Drive the relay to output a switch alarm signal; Data packets containing the coordinates of the pollution source are sent via a serial communication interface.

[0014] The present invention also provides an atmospheric patrol and monitoring system for implementing the atmospheric patrol and monitoring method described above, including a signal acquisition module, a baseline separation module, a feature extraction module, a decision logic module, a direction tracing module, an output interface module, and an environmental compensation module; The output of the signal acquisition module is connected to the input of the baseline separation module, the output of the baseline separation module is connected to the input of the feature extraction module, the output of the feature extraction module is connected to the input of the decision logic module, the output of the decision logic module is connected to the trigger of the direction tracing module, the output of the direction tracing module is connected to the input of the output interface module, and the compensation output of the environmental compensation module is connected to the compensation input of the signal acquisition module, the compensation input of the baseline separation module, and the compensation input of the feature extraction module, respectively. The signal acquisition module is used to receive the raw signals from the four-dimensional sensor array and output them in a standardized manner. The baseline separation module is used to separate meteorological background values ​​from sudden pollution signals; The feature extraction module is used to calculate the spatial gradient, temporal derivative, and pollutant fingerprint ratio. The decision logic module is used to execute five-level hardware condition decisions; The direction tracing module is used to calculate the azimuth angle of the pollution source; The output interface module is used to convert industry standard signals; The environmental compensation module is used to generate temperature and humidity compensation coefficients.

[0015] The present invention has the following beneficial effects: In operation, the signal acquisition layer acquires the raw data from the four-dimensional sensor array and performs temperature compensation. The baseline separation layer extracts the meteorological cumulative background value through a low-pass filter with a 30-minute time constant and removes 20% of the background component from the raw signal in real time to separate the sudden emission signal. This process accurately removes the slow accumulation of pollutants caused by atmospheric diffusion stagnation under stable weather conditions. The feature extraction layer simultaneously calculates the spatial gradient, temporal abrupt change rate, and pollutant fingerprint ratio. Meanwhile, the environmental compensation layer corrects the data by querying a pre-stored coefficient table based on real-time temperature and humidity to eliminate the false high interference of high humidity environment on particulate matter monitoring. The stable weather determination layer adds the square value of wind speed to the absolute value of 100 times the temperature gradient to generate a stable weather index. When the index is less than 1.0, it is confirmed that the current state is windless and temperature inversion. The decision logic layer executes a five-level decision to trigger an alarm when uniform diffusion is excluded, illegal emission characteristics are captured, specific source components are identified, and the stable weather conditions are met. At this moment, the direction tracing layer is immediately activated. Based on the time difference data of the pollution cloud arriving at the four-dimensional sensor array and the fixed spacing of 50 cm, the azimuth tangent value is calculated through the sound speed and temperature compensation model. Finally, the output interface layer converts the azimuth angle into a 4-20mA signal to drive the directional fog cannon, activate the alarm, and upload the pollution source coordinates through the serial interface within a 120-millisecond full process time limit. This enables a closed-loop process of background stripping, feature extraction, meteorological verification, and source analysis, reducing the misjudgment rate under stable weather conditions and solving the problem of confusion between meteorological accumulation and sudden emissions when single-point data shows abnormal increases. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of the present invention; Figure 2 This is a structural block diagram of the atmospheric patrol and monitoring system in this invention.

[0018] In the diagram: 1. Signal acquisition module; 2. Baseline separation module; 3. Feature extraction module; 4. Decision logic module; 5. Direction tracing module; 6. Output interface module; 7. Environmental compensation module. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0021] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0022] In the description of this invention, it should be understood that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product of this invention is in use, or the orientation or positional relationship commonly understood by those skilled in the art. They are only used to facilitate the description of this invention and to simplify the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0023] Furthermore, the terms "first," "second," and "third" are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0024] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0025] An atmospheric patrol and monitoring method, such as Figure 1 As shown, it includes the following steps: The raw signals from the four-dimensional sensor array are acquired through signal acquisition module 1; In baseline separation module 2, meteorological background values ​​and sudden pollution signals are separated for dynamic baseline separation. A low-pass programmable filter with a time constant of 30 minutes is used to process the original sensor signal to extract the background signal. The sudden pollution signal is obtained by subtracting 20% ​​of the background signal value from the original signal. The physical response is realized through a programmable filter and an analog switching circuit. In feature extraction module 3, spatial gradient, temporal abrupt change rate and pollutant fingerprint ratio are calculated to realize spatiotemporal feature extraction. The absolute difference between the output voltages of two adjacent sensors is directly measured as the spatial gradient. The difference between the current signal and the signal 30 seconds ago is calculated and divided by the 30-second time interval to obtain the temporal abrupt change rate. The pollutant fingerprint ratio is obtained by dividing the nitrogen oxide sensor voltage value by the carbon monoxide sensor voltage value and adding 0.1. Based on the output of feature extraction module 3, the meteorological static stability index is calculated to determine static stability. The static stability index is calculated by taking the square of the wind speed measurement value, adding 100, and multiplying by the absolute value of the temperature gradient. When the static stability index is less than 1.0, it is determined to be a static and stable meteorological state. The calculation is realized through envelope detection circuit and differential amplifier hardware. The hardware condition judgment is executed in the judgment logic module 4 to complete the five-level judgment. An alarm is triggered when the judgment logic module 4 meets the following conditions at the same time: the time mutation rate is greater than 20 micrograms per cubic meter per minute, the spatial gradient is greater than 0.1 volts, the static stability index is less than 1.0, and the pollutant fingerprint ratio is greater than 2.0. Joint judgment is achieved through comparator array and logic gate chip. When the response decision logic module 4 is triggered, the azimuth angle of the pollution source is calculated in the direction tracing module 5 to locate the pollution source. The time difference of the pollutants arriving at different sensors is directly measured. The vertical time difference is multiplied by the sound speed value and then divided by the product of the horizontal time difference and the 50-centimeter sensor distance. The arctangent of this ratio is calculated to obtain the azimuth angle, which is achieved through a high-precision time conversion chip and an analog computer. Environmental compensation is achieved by real-time correction of environmental interference through environmental compensation module 7. The compensation coefficient is obtained by querying the pre-stored coefficient table based on temperature and humidity parameters. The original signal is multiplied by the compensation coefficient obtained from the table to achieve real-time correction. This is implemented through storage chip and analog multiplier hardware. The output interface module 6 converts industrial standard signals for signal output, converting the azimuth signal into a 4 to 20 mA current signal to drive the relay to output a switching alarm signal, and sends a data packet containing the coordinates of the pollution source through the serial communication interface.

[0026] The present invention also provides an atmospheric patrol and monitoring system for implementing the above-mentioned atmospheric patrol and monitoring method, including a signal acquisition module 1, a baseline separation module 2, a feature extraction module 3, a decision logic module 4, a direction tracing module 5, an output interface module 6, and an environmental compensation module 7. like Figure 2As shown, the output of signal acquisition module 1 is connected to the input of baseline separation module 2, the output of baseline separation module 2 is connected to the input of feature extraction module 3, the output of feature extraction module 3 is connected to the input of decision logic module 4, the output of decision logic module 4 is connected to the trigger of direction tracing module 5, the output of direction tracing module 5 is connected to the input of output interface module 6, and the compensation output of environmental compensation module 7 is connected to the compensation input of signal acquisition module 1, the compensation input of baseline separation module 2, and the compensation input of feature extraction module 3, respectively. Among them, the signal acquisition module 1 is used to receive the raw signals of the four-dimensional sensor array and output them in a standardized manner; the baseline separation module 2 is used to separate the meteorological background value and the sudden pollution signal; the feature extraction module 3 is used to calculate the spatial gradient, time derivative and pollutant fingerprint ratio; the decision logic module 4 is used to execute the five-level hardware condition decision; the direction tracing module 5 is used to calculate the azimuth angle of the pollution source; the output interface module 6 is used to convert the industrial standard signal; and the environmental compensation module 7 is used to generate the temperature and humidity compensation coefficient.

[0027] The signal acquisition module 1 includes a four-dimensional sensor array, a first LMP7721 operational amplifier, a second LMP7721 operational amplifier, a third LMP7721 operational amplifier, a fourth LMP7721 operational amplifier, a CD4052 analog switch, an LM335 temperature sensor, a first AD633 analog multiplier, a first OPA2188 operational amplifier, and a second OPA2188 operational amplifier. The four-dimensional sensor array includes a PM2.5 sensor, a VOC sensor, a NO2 sensor, and a CO sensor. The output terminals of the PM2.5 sensor, VOC sensor, NO2 sensor, and CO sensor are respectively connected to the non-inverting input terminals of the first, second, third, and fourth LMP7721 operational amplifiers. The inverting input terminals of the first, second, third, and fourth LMP7721 operational amplifiers are also connected to the inverting input terminals of the fourth LMP7721 operational amplifier. All input terminals are grounded via a first resistor. The output terminals of the first, second, third, and fourth LMP7721 operational amplifiers are respectively connected to the input terminals of the CD4052 analog switch. The output terminal of the CD4052 analog switch is connected to the first input terminal of the first AD633 analog multiplier. The LM335 temperature sensor collects the ambient temperature, and its output terminal is connected to the second input terminal of the first AD633 analog multiplier. The output terminal of the first AD633 analog multiplier is connected to the non-inverting input terminal of the first OPA2188 operational amplifier via a second resistor. A programmable filter consisting of a third resistor and a first capacitor is connected across the inverting input terminal and the output terminal of the first OPA2188 operational amplifier. The output terminal of the first OPA2188 operational amplifier is connected to the non-inverting input terminal of the second OPA2188 operational amplifier. The output terminal of the second OPA2188 operational amplifier serves as the output terminal of signal acquisition module 1.

[0028] Baseline separation module 2 includes an LTC1064 programmable filter, an LF398 sample-and-hold circuit, a CD4053 analog switch, an NE555 timer, and a third OPA2188 operational amplifier. The input of the LTC1064 programmable filter is connected to the output of the second OPA2188 operational amplifier in signal acquisition module 1. The output of the LTC1064 programmable filter is connected to the analog signal input of the LF398 sample-and-hold circuit. The output of the LF398 sample-and-hold circuit is connected to the first channel of the CD4053 analog switch, and the second channel of the CD4053 analog switch... The output of the second OPA2188 operational amplifier in the signal acquisition module 1 is connected to the output of the CD4053 analog switch. The common output of the CD4053 analog switch is connected to the non-inverting input of the third OPA2188 operational amplifier. The output of the NE555 timer is connected to the selection terminal of the CD4053 analog switch. The inverting input of the third OPA2188 operational amplifier is connected to the output of the LF398 sample-and-hold circuit through the fourth resistor. The inverting input of the third OPA2188 operational amplifier is grounded through the fifth resistor. The output of the third OPA2188 operational amplifier serves as the output of the baseline separation module 2.

[0029] Feature extraction module 3 includes an INA826 instrumentation amplifier, an OP37 operational amplifier, an AD8337 variable gain amplifier, and an AD734 divider. The input of the INA826 instrumentation amplifier is connected to the output of the third OPA2188 operational amplifier in baseline separation module 2 to receive differential signals. The output of the INA826 instrumentation amplifier is connected to the input of the AD8337 variable gain amplifier, and the output of the AD8337 variable gain amplifier outputs spatial gradients. The input of the OP37 operational amplifier is connected to the output of the third OPA2188 operational amplifier in baseline separation module 2 through a sixth resistor. The input of the OP37 operational amplifier is connected to the output of the OP37 operational amplifier through a second capacitor. The input of the OP37 operational amplifier is connected to the output of the OP37 operational amplifier through a seventh resistor. The second capacitor and the seventh resistor form an RC network. The output of the OP37 operational amplifier is connected to the input of the AD734 divider. The input of the AD734 divider is connected to the outputs of the NO2 sensor and the CO sensor. The output of the AD734 divider outputs fingerprint ratios.

[0030] The decision logic module 4 includes a first LM393 comparator, a second LM393 comparator, a third LM393 comparator, a fourth LM393 comparator, a fifth LM393 comparator, a sixth LM393 comparator, a seventh LM393 comparator, an eighth LM393 comparator, a first CD4081 AND gate, a second CD4081 AND gate, a CD4075 OR gate, and a CD4532 priority encoder. The non-inverting inputs of the first, second, third, fourth, fifth, sixth, seventh, and eighth LM393 comparators are connected to the outputs of the feature extraction module 3. The first, second, third, and fourth LM393 comparators are connected to the outputs of the feature extraction module 3. The inverting inputs of the 93 comparator, the fifth LM393 comparator, the sixth LM393 comparator, the seventh LM393 comparator, and the eighth LM393 comparator are connected to the threshold reference voltage. The outputs of the first LM393 comparator, the second LM393 comparator, the third LM393 comparator, and the fourth LM393 comparator are connected to the input of the first CD4081 AND gate. The outputs of the fifth LM393 comparator, the sixth LM393 comparator, the seventh LM393 comparator, and the eighth LM393 comparator are connected to the input of the second CD4081 AND gate. The outputs of the first CD4081 AND gate and the second CD4081 AND gate are connected to the input of the CD4075 OR gate. The output of the CD4075 OR gate is connected to the enable terminal of the CD4532 priority encoder. The output of the CD4532 priority encoder outputs an alarm code.

[0031] The direction tracing module 5 includes a TDC7201 time digital rotary transformer, an AD538 analog computer, and an AD2S1200 rotary transformer. The STOP channel of the TDC7201 time digital rotary transformer is connected to the output of the four-dimensional sensor array. The START channel of the TDC7201 time digital rotary transformer is used to receive synchronization signals. The output of the TDC7201 time digital rotary transformer is connected to the input of the AD538 analog computer to transmit time difference data. The AD538 analog computer is configured in arctan mode. The output of the AD538 analog computer is connected to the input of the AD2S1200 rotary transformer. The output of the AD2S1200 rotary transformer outputs azimuth voltage.

[0032] The environmental compensation module 7 includes an SHT31 temperature and humidity sensor, an AT24C02 electrically erasable programmable read-only memory (EROM), a second AD633 analog multiplier, and an AD8605 operational amplifier. The SHT31 temperature and humidity sensor collects ambient temperature and humidity data and transmits signals. The output of the SHT31 temperature and humidity sensor is connected to the AT24C02 EROM. The AT24C02 EROM is connected to the input of the second AD633 analog multiplier. The non-inverting input of the AD8605 operational amplifier is connected to the output of the SHT31 temperature and humidity sensor. The output of the AD8605 operational amplifier is connected to the input of the second AD633 analog multiplier. The output of the second AD633 analog multiplier outputs the compensated signal.

[0033] Output interface module 6 includes an XTR111 voltage-to-current converter, a ULN2003 Darlington array, an ISO7221 digital isolator, and an RS485 transceiver ADM3485. The input of the XTR111 voltage-to-current converter receives direction signals, the input of the ULN2003 Darlington array receives judgment signals, the input of the ISO7221 digital isolator receives status signals, and the input of the RS485 transceiver ADM3485 receives data signals. The outputs of the XTR111 voltage-to-current converter, the ULN2003 Darlington array, the ISO7221 digital isolator, and the RS485 transceiver ADM3485 are all used to transmit signals to the host computer.

[0034] In actual operation, the first, second, third, and fourth LMP7721 operational amplifiers of the signal acquisition module 1 receive the current signals from the PM2.5 sensor, VOC sensor, NO2 sensor, and CO sensor in real time and convert them into voltage signals.

[0035] After the CD4052 analog switch selects the effective channel, the signal is input to the first AD633 analog multiplier. Here, the environmental parameters provided by the LM335 temperature sensor compensate for the temperature drift error in real time. After compensation, the signal enters the baseline separation module 2, where the LTC1064 programmable filter performs a low-pass filter with a 30-minute time constant to extract the meteorological background accumulation value. This background value is locked to the peak value by the LF398 sample-and-hold circuit. At the same time, the NE555 timer controls the CD4053 analog switch to perform dynamic switching. When a sudden pollution event is detected, the original signal will be reduced by 20% of the background value to separate the sudden component. In this way, the pollutant accumulation effect caused by slow atmospheric diffusion under calm and stable weather conditions can be removed.

[0036] After passing through the background separation signal input feature extraction module 3, the INA826 instrumentation amplifier calculates the voltage difference between the two sensors 50 cm apart as the spatial gradient feature. At the same time, the OP37 operational amplifier calculates the concentration change rate within a 30-second time window through the RC network differentiating circuit composed of the second capacitor and the seventh resistor.

[0037] The AD734 divider generates the NO2 to CO concentration ratio as a pollutant fingerprint feature. Meanwhile, the SHT31 temperature and humidity sensor in the environmental compensation module 7 continuously collects environmental parameters, queries the optimal compensation value through the compensation coefficient table pre-stored in the AT24C02 electrically erasable programmable read-only memory, and the second AD633 multiplier performs real-time correction on the signals of the first three modules, effectively eliminating the false high interference of high humidity environment on PM2.5 monitoring.

[0038] After the spatial gradient, temporal abrupt change rate, and pollutant fingerprint ratio output by feature extraction module 3 are input into decision logic module 4, the first, second, third, fourth, fifth, sixth, seventh, and eighth LM393 comparators simultaneously perform threshold determination. The temporal abrupt change rate corresponding to the industrial illegal discharge characteristic must exceed 20 μg / m³. 3 / min, the spatial gradient used to exclude the meteorological influence of uniform diffusion must be greater than 0.1V, the pollutant fingerprint ratio for identifying specific pollution sources must be greater than 2.0, and at the same time, the parallel AD8337 envelope detection circuit and AD8276 differential amplifier in the feature extraction module 3 calculate the static stability index of the combination of the square of the wind speed and the absolute value of the temperature gradient. When the index is less than 1.0, it is verified by the LM393 comparator, that is, it is confirmed that the current state is windless and temperature inversion.

[0039] After the above four sets of conditions are logically ANDed through the first CD4081 AND gate and the second CD4081 AND gate, the alarm level is output by the CD4532 priority encoder. This five-level hardware decision mechanism solves the problem of not being able to distinguish between meteorological accumulation and sudden emission when a single point of data abnormally rises.

[0040] When the judgment logic module 4 triggers the alarm enable signal, the TDC7201 time digital rotary transformer of the direction tracing module 5 is immediately started to measure the microsecond-level time difference of the pollution cloud arriving at the four-dimensional sensor array. The AD538 analog computer calculates the azimuth tangent value based on the time difference data and the 50 cm sensor spacing, and then outputs a 0-5V azimuth voltage through the AD2S1200 rotary transformer.

[0041] The XTR111 voltage-to-current converter in the final output interface module 6 converts the azimuth angle into a 4-20mA standard signal, the ULN2003 Darlington array synchronously transmits the signal, and the RS485 transceiver ADM3485 further uploads the pollution source coordinates and characteristic parameters to the host computer.

[0042] In this way, the signal acquisition module 1 completes multi-sensor synchronous sampling, the baseline separation module 2 removes the meteorological background in a short time, the feature extraction module 3 calculates the spatiotemporal features and pollutant fingerprints, the decision logic module 4 completes the five-level condition judgment, the direction tracing module 5 calculates the azimuth angle, and finally the output interface module 6 converts the industrial signal.

[0043] To achieve precise interception of pollution plumes at a faster speed and before they spread, reduce the misjudgment rate under calm and stable weather conditions, and solve or alleviate the dilemma of tracing pollution sources caused by stagnant atmospheric diffusion.

[0044] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An atmospheric patrol and monitoring method, characterized in that, Includes the following steps: The original signals of the four-dimensional sensor array are acquired through the signal acquisition module (1); Dynamic baseline separation is performed by separating meteorological background values ​​and sudden pollution signals in the baseline separation module (2); In the feature extraction module (3), spatial gradient, temporal abrupt change rate and pollutant fingerprint ratio are calculated to realize spatiotemporal feature extraction; Based on the output of the feature extraction module (3), the meteorological static stability index is calculated to determine static stability. The hardware condition decision is executed in the decision logic module (4) to complete the five-level decision; When the response decision logic module (4) is triggered, the azimuth angle of the pollution source is calculated in the direction tracing module (5) to locate the pollution source; Environmental compensation is performed in real time by correcting environmental disturbances through the environmental compensation module (7). The output interface module (6) converts industrial standard signals for signal output.

2. The atmospheric patrol and monitoring method according to claim 1, characterized in that, The dynamic baseline separation process, which separates meteorological background values ​​from sudden pollution signals in the baseline separation module (2), specifically includes the following steps: The original sensor signal was processed using a low-pass filter with a time constant of thirty minutes to extract the background signal; The sudden pollution signal is obtained by subtracting 20% ​​of the background signal value from the original signal; The physical response is achieved through programmable filters and analog switching circuits.

3. The atmospheric patrol and monitoring method according to claim 1, characterized in that, The calculation of spatial gradient, temporal abrupt change rate, and pollutant fingerprint ratio in the feature extraction module (3) to achieve spatiotemporal feature extraction specifically includes the following steps: The spatial gradient is obtained by directly measuring the absolute difference between the output voltages of two adjacent sensors. Calculate the difference between the current signal and the signal from thirty seconds ago, and divide it by the thirty-second time interval to obtain the time abrupt change rate; The pollutant fingerprint ratio is obtained by dividing the nitrogen oxide sensor voltage value by the carbon monoxide sensor voltage value plus zero.

4. The atmospheric patrol and monitoring method according to claim 1, characterized in that, The step of calculating the meteorological stability index based on the output of the feature extraction module (3) to determine the stability includes the following steps: The static stability index is calculated by adding the square of the wind speed measurement to one hundred and multiplying by the absolute value of the temperature gradient. When the static stability index is less than 1.0, it is determined to be a static and stable weather condition. The calculation is implemented using an envelope detection circuit and a differential amplifier hardware.

5. The atmospheric patrol and monitoring method according to claim 1, characterized in that, The step of performing hardware condition judgment in the judgment logic module (4) to complete the five-level judgment includes the following steps: An alarm is triggered when the following conditions are met simultaneously in the judgment logic module (4): the time mutation rate is greater than 20 micrograms per cubic meter per minute, the spatial gradient is greater than 0.1 volts, the static stability index is less than 1.0, and the pollutant fingerprint ratio is greater than 2.

0. Joint judgment is achieved through comparator array and logic gate chip.

6. The atmospheric patrol and monitoring method according to claim 1, characterized in that, The response decision logic module (4) is triggered, and the azimuth angle of the pollution source is calculated in the direction tracing module (5) to locate the pollution source. The specific steps include the following: Directly measure the time difference of pollutants arriving at different sensors; Multiply the vertical time difference by the speed of sound and then divide by the product of the horizontal time difference and the 50-centimeter sensor spacing. The azimuth angle can be obtained by calculating the arctangent of this ratio. This is achieved using a high-precision time conversion chip and an analog computer.

7. The atmospheric patrol and monitoring method according to claim 1, characterized in that, The environmental compensation method, which uses the environmental compensation module (7) to correct environmental interference in real time, includes the following steps: The compensation coefficient can be obtained by querying the pre-stored coefficient table based on the temperature and humidity parameters; Real-time correction is achieved by multiplying the original signal by a compensation coefficient obtained from a lookup table. This is achieved through hardware components including memory chips and analog multipliers.

8. The atmospheric patrol and monitoring method according to claim 1, characterized in that, The process of converting industrial standard signals through the output interface module (6) for signal output specifically includes the following steps: Convert the azimuth angle signal into a current signal of four to twenty milliamps; Drive the relay to output a switch alarm signal; Data packets containing the coordinates of the pollution source are sent via a serial communication interface.

9. An atmospheric patrol and monitoring system, the system being used to implement the atmospheric patrol and monitoring method as described in any one of claims 1-8, characterized in that, It includes a signal acquisition module (1), a baseline separation module (2), a feature extraction module (3), a decision logic module (4), a direction tracing module (5), an output interface module (6), and an environmental compensation module (7). The output of the signal acquisition module (1) is connected to the input of the baseline separation module (2), the output of the baseline separation module (2) is connected to the input of the feature extraction module (3), the output of the feature extraction module (3) is connected to the input of the decision logic module (4), the output of the decision logic module (4) is connected to the trigger of the direction tracing module (5), the output of the direction tracing module (5) is connected to the input of the output interface module (6), and the compensation output of the environmental compensation module (7) is connected to the compensation input of the signal acquisition module (1), the compensation input of the baseline separation module (2), and the compensation input of the feature extraction module (3), respectively. The signal acquisition module (1) is used to receive the raw signals from the four-dimensional sensor array and output them in a standardized manner. The baseline separation module (2) is used to separate meteorological background values ​​from sudden pollution signals; The feature extraction module (3) is used to calculate the spatial gradient, temporal derivative and pollutant fingerprint ratio; The decision logic module (4) is used to execute the five-level hardware condition decision; The direction tracing module (5) is used to calculate the azimuth angle of the pollution source; The output interface module (6) is used to convert industrial standard signals; The environmental compensation module (7) is used to generate temperature and humidity compensation coefficients.

Images