Atmospheric particle scattering detection method for photoelectric scattering detection instrument

Abstract

An atmospheric particle scattering detection method for a photoelectric scattering detection instrument. A modulation frequency far greater than a wing flapping frequency of a winged insect is used to modulate a light source; then, a variable coefficient is extracted from an acquired scattered light sampling sequence from a statistical perspective, so as to detect whether there is foreign matter in a sampling space, and wave crest extraction operations in two dimensions of a frequency domain and a time domain are combined to identify different foreign matter types including a winged insect and a precipitation particle, such that when there is foreign matter in the sampling space, different processing can be performed on an inversion result of a scattered light sampling sequence within the current detection period, so as to obtain a relatively accurate atmospheric particle scattering detection result, thereby facilitating an improvement in the accuracy and reliability of atmospheric particle scattering detection.

Description

A method for detecting atmospheric particle scattering in photoelectric scattering detectors Technical Field

[0001] This application relates to the field of atmospheric particle scattering detection, and in particular to an atmospheric particle scattering detection method for use in photoelectric scattering detection instruments. Background Technology

[0002] Photoelectric scattering detection instruments are a type of measuring device widely used in meteorological observations. These instruments mainly consist of a light emitting unit, a light receiving unit, and a signal processing unit. The light emitting unit generates a modulated emitted beam, which overlaps with the receiving field of view of the light receiving unit, forming a sampling space. After being scattered by particles within the sampling space, a portion of the emitted beam enters the light receiving unit, generating a received signal which is then provided to the signal processing unit. By analyzing the received signal, the signal processing unit can retrieve the measurement result.

[0003] Photoelectric scattering detection instruments used in atmospheric and meteorological research are usually installed outdoors. Therefore, in addition to microscopic particles, foreign objects such as flying insects and precipitation particles are likely to appear in the sampling space of photoelectric scattering detection instruments. These foreign objects will also scatter the emitted light beam, and the intensity of the scattered light produced by these foreign objects can be several orders of magnitude higher than that of microscopic particles. Therefore, these foreign objects will affect the measurement results of photoelectric scattering detection instruments and reduce the accuracy of the inversion results. Technical issues

[0004] Foreign objects such as flying insects and precipitation particles can affect the measurement results of photoelectric scattering detection instruments, reducing the accuracy of the inversion results. Technical solutions

[0005] This application addresses the aforementioned problems and technical needs by proposing a method for detecting atmospheric particle scattering using a photoelectric scattering detection instrument. The technical solution of this application is as follows:

[0006] An atmospheric particle scattering method for use in a photoelectric scattering detection instrument, the atmospheric particle scattering detection method comprising:

[0007] The light emitting unit in the photoelectric scattering detection instrument is driven by a pulse signal to generate pulsed light, and the light receiving unit in the photoelectric scattering detection instrument obtains the pulsed received signal. The frequency of the driving pulse of the light emitting unit is much greater than the wing flapping frequency of the flying insect.

[0008] The received signal is discretely sampled to obtain the scattered light sampling sequence in each detection period. The scattered light sampling sequence includes the scattered light signal received by the optical receiving unit at different sampling times.

[0009] The scattered light sampling sequences of the current detection cycle and the most recent several detection cycles are obtained and spliced ​​in time to form a detection sequence;

[0010] When the data stability of the detection sequence meets the data stability requirements, it is determined that there are no foreign objects in the sampling space of the photoelectric scattering detection instrument, and the inversion result of the scattered light sampling sequence in the current detection period is used as the atmospheric particle scattering detection result of the current detection period.

[0011] When the data stability of the detection sequence is found to be below the data stability requirement, it is determined that there are foreign objects in the sampling space of the photoelectric scattering detection instrument. Based on the peak detection results of the detection sequence in the frequency domain and time domain, the type of foreign object in the sampling space is determined. After performing data post-processing on the inversion results of the scattered light sampling sequence in the current detection period according to the post-processing strategy corresponding to the foreign object type, the atmospheric particle scattering detection results of the current detection period are obtained. Different foreign object types correspond to different post-processing strategies.

[0012] A further technical solution involves determining the types of foreign objects contained within the sampling space based on the peak detection results of the detection sequence in the frequency and time domains, including:

[0013] Extract the frequency domain features of the detection sequence and perform peak detection on the frequency domain features of the detection sequence;

[0014] When it is determined from the peak detection results in the frequency domain that the frequency domain characteristics of the detection sequence contain a single peak, it is determined that the scattered light sampling sequence of the current detection period contains the wing flapping signal of flying insects and that the type of foreign object in the sampling space is a flying insect.

[0015] When it is determined from the peak detection results in the frequency domain that the frequency domain features of the detection sequence do not contain a single peak, it is determined that there are no flying insects or foreign objects in the sampling space, and the type of foreign object in the sampling space is determined from the peak detection results in the time domain of the detection sequence.

[0016] A further technical solution involves determining the type of foreign object in the sampling space based on the peak detection results of the detection sequence in the time domain, including:

[0017] Peak detection is performed on the temporal characteristics of the detection sequence. If the temporal characteristics of the detection sequence contain at least one peak based on the peak detection results, the foreign object type in the sampling space is determined to be precipitation particle foreign object; otherwise, other foreign object types are determined to be present in the sampling space.

[0018] A further technical solution involves discretely sampling the received signal to obtain a scattered light sampling sequence for each detection period, including:

[0019] Discrete sampling of the received signal yields a received signal sampling sequence, which includes the received signal acquired by the optical receiving unit at each sampling time.

[0020] Data preprocessing is performed on the received signal sampling sequence to remove ambient light signals from the received signal in order to obtain the scattered light sampling sequence for each detection period.

[0021] A further technical solution involves discrete sampling of the received signal, including:

[0022] according to The received signal is discretely sampled at a specified sampling interval, and the phase of the discrete sampling is adjusted so that one of the discrete sampling operations occurs before the end of the positive pulse of the received signal. It is the pulse period of the driving pulse.

[0023] A further technical solution involves preprocessing the received signal sampling sequence to remove ambient light signals from the received signal, including:

[0024] Subtract the received signal at the 2i-1th sampling time from the received signal at the 2i-1th sampling time in the received signal sampling sequence to obtain the scattered light signal received by the optical receiving unit at the 2i-1th sampling time. Extract the scattered light at the 2i-1th sampling time in each detection period in a time sequence to obtain the scattered light sampling sequence in the current detection period.

[0025] The initial value of the integer parameter i is 1. For any value of i, the 2i-1 sampling time and the 2i sampling time correspond to two discrete samplings performed within the same pulse period of the driving pulse, and the 2i-1 sampling time corresponds to the discrete sampling performed before the end of the positive pulse of the received signal of the optical receiving unit.

[0026] A further technical solution is to determine the pulse period of the driving pulse used to drive the optical emitting unit to emit pulsed light. And the frequency of the driving pulse It must reach at least K times the highest wingbeat frequency of a flying insect, with parameter K≥20.

[0027] A further technical solution involves using a pulse signal to drive the light-emitting unit in a photoelectric scattering detection instrument to generate pulsed light, including:

[0028] A controlled constant current source in the light emitting unit is controlled by a pulse signal to drive the light-emitting element connected to the controlled constant current source to emit pulsed light, and the rise time and fall time of the output current of the controlled constant current source do not exceed [a certain value]. ,in, It is the positive pulse width of the driving pulse.

[0029] A further technical solution involves acquiring a pulsed received signal through a light receiving unit in a photoelectric scattering detection instrument, including:

[0030] The photodiode in the optical receiving unit detects the pulsed light and outputs an electrical signal to the signal conditioning circuit. The signal conditioning circuit then outputs a pulsed received signal, and the rise time and fall time of the current in the received signal output by the signal conditioning circuit are both less than [a certain value]. ,in, It is the positive pulse width of the driving pulse.

[0031] A further technical solution involves checking whether the data stability of the detection sequence meets the data stability requirements, including:

[0032] Calculate the mean of the detection sequence. with standard deviation When the standard deviation Exceeding the average If the predetermined threshold is reached, it is determined that the data stability of the detection sequence has not met the data stability requirements; otherwise, it is determined that the data stability of the detection sequence has met the data stability requirements. Beneficial effects

[0033] This application discloses an atmospheric particle scattering detection method for a photoelectric scattering detection instrument. The method is based on the general optical path structure of the photoelectric scattering detection instrument. By extracting the coefficient of variation from the statistical perspective of the scattered light sampling sequence, the presence of foreign objects in the sampling space can be detected. By using a high light source modulation frequency and signal sampling rate, and combining peak extraction operations in both the frequency domain and time domain, different types of foreign objects, including flying insects and precipitation particles, can be identified. Then, the inversion results of the scattered light sampling sequence in the current detection period are processed differently to obtain a more accurate atmospheric particle scattering detection result.

[0034] This method directly identifies flying insects by detecting their wingbeat signals. Compared to first identifying precipitation particles and then combining other conditions to determine if it is an insect, this method has higher accuracy and is more suitable as a basis for data quality control. Furthermore, the presence or absence of wingbeat signals is independent of the insect's size, species, or movement trajectory. Increasing the light source modulation frequency to more than 20 times the highest wingbeat frequency of the insect facilitates the detection of waveform details in the received signal, thus resulting in high accuracy. Moreover, this method does not require a precision optical path, reducing debugging time and facilitating mass production applications. Attached Figure Description

[0035] Figure 1 is a system framework diagram of a photoelectric scattering detection instrument according to an embodiment of this application.

[0036] Figure 2 is a schematic flowchart of an atmospheric particle scattering detection method according to an embodiment of this application.

[0037] Figure 3 is a schematic diagram of removing ambient light signals from the received signal sampling sequence to obtain a scattered light sampling sequence in one example of this application. Embodiments of the present invention

[0038] The specific embodiments of this application will be further described below with reference to the accompanying drawings.

[0039] This application discloses an atmospheric particle scattering detection method for a photoelectric scattering detection instrument. The method is applied in the photoelectric scattering detection instrument, the structural schematic of which is shown in Figure 1. It also includes a light emitting unit, a light receiving unit, and a signal processing unit, and the overlapping area of ​​the illumination region of the light emitting unit and the receiving field of view of the light receiving unit forms a three-dimensional sampling space. However, this application modifies and optimizes the atmospheric particle scattering detection method executed by the signal processing unit, including:

[0040] Step 1: Use a pulse signal to drive the light emitting unit in the photoelectric scattering detection instrument to generate pulsed light. The frequency of the driving pulse of the light emitting unit (i.e., the modulation frequency of the light source) is much greater than the wing flapping frequency of the flying insect.

[0041] The signal processing unit generates a drive pulse, the period of which is denoted as . The positive pulse width of the driving pulse is denoted as Because the wingbeat frequency of flying insects is relatively high, and this application will subsequently detect foreign objects in flying insects by detecting the wingbeat frequency, the driving pulse must have a high pulse frequency to facilitate subsequent frequency detection; at least, the pulse frequency must be much higher than the wingbeat frequency of the flying insects. In one embodiment, the pulse period of the driving pulse is... And the modulation frequency of the driving pulse The pulse period must be at least K times the highest wingbeat frequency of the flying insect, where K ≥ 20. Generally, the highest wingbeat frequency of the flying insect is taken as 1 kHz, then the pulse period... In order to minimize average power consumption while maintaining a relatively high pulse frequency, the positive pulse width... In one embodiment, the value should be as small as possible. .

[0042] The light emitting unit includes a controlled constant current source and a connected light-emitting element, which can be a common LED or LD. By using the generated driving pulses to control the controlled constant current source, the light-emitting element can be driven to emit pulsed light. To ensure effective driving, the rise time of the output current of the controlled constant current source must be guaranteed. and the output current fall time of the controlled constant current source Among them, the rise time of the output current. This refers to the time required for the controlled constant current source to rise from 10% to 90% of its current stability value, and the output current fall time. It refers to the time required for a controlled constant current source to decrease from 90% to 10% of its current stability value.

[0043] Step 2: Acquire a pulsed received signal through the light receiving unit in the photoelectric scattering detection instrument. The signal period of this received signal is the same as the pulse period of the driving pulse. Consistent.

[0044] In one embodiment, the optical receiving unit includes a photodiode and a connected signal conditioning circuit. The photodiode detects pulsed light and outputs an electrical signal to the signal conditioning circuit. The signal conditioning circuit then conditions the pulsed light and outputs a received signal. To ensure effective reception, the rise time of the current in the received signal output by the signal conditioning circuit is... The current fall time of the received signal .

[0045] Step 3 involves discretely sampling the received signal to obtain a scattered light sampling sequence for each detection period. This scattered light sampling sequence includes the scattered light signals received by the optical receiving unit at different sampling times. The detection frequency of the detection period can be customized, typically set to multiple pulse periods.

[0046] In reality, the received signal from the optical receiving unit often contains ambient light signals in addition to the scattered light signals within the sampling space. Therefore, this step first performs discrete sampling of the received signal to obtain a received signal sampling sequence. This received signal sampling sequence includes the received signals acquired by the optical receiving unit at each sampling time. Then, the received signal sampling sequence is further preprocessed to remove ambient light signals from the received signal to obtain the scattered light sampling sequence for each detection period.

[0047] The discrete sampling operation in this step can be implemented using the built-in analog-to-digital conversion function of the signal processing unit, or through a dedicated analog-to-digital conversion module. As shown in Figure 1, in the latter case, the optical receiving unit is connected to the signal processing unit after passing through the analog-to-digital conversion module. The analog-to-digital conversion module performs discrete sampling on the received signal output from the optical receiving unit to obtain a received signal sampling sequence and outputs it to the signal processing unit. In one embodiment, the analog-to-digital conversion module includes an analog-to-digital converter, a FIFO memory, and necessary peripheral circuitry. The analog-to-digital converter temporarily stores the received signals acquired at each sampling time into the FIFO memory sequentially, and reads out N received signals acquired in each detection cycle at once and transmits them to the signal processing unit, continuously outputting in this manner, where N is an integer parameter.

[0048] The signal processing unit then performs data preprocessing on the received signal sampling sequence to obtain the scattered light sampling sequence. To facilitate the removal of ambient light signals from the received signal sampling sequence, this step is designed for discrete sampling as follows: [Following the...] The received signal is discretely sampled at specific sampling intervals, and the phase of each discrete sample is adjusted so that one of the discrete sampling operations occurs before the end of the positive pulse of the received signal. Generally, the quantization accuracy of an analog-to-digital converter (ADC) is required to be no less than 14 bits.

[0049] Referring to the flowchart shown in Figure 2, after receiving the received signal sampling sequence, the signal processing unit subtracts the received signal at the 2i-th sampling moment from the received signal at the 2i-1-th sampling moment to obtain the scattered light signal received by the optical receiving unit at the 2i-1-th sampling moment. Here, the integer parameter i starts at 1. For any value of i, the 2i-1-th sampling moment and the 2i-th sampling moment correspond to two discrete samplings performed within the same pulse period of the driving pulse, and the 2i-1-th sampling moment corresponds to the discrete sampling performed before the end of the positive pulse of the received signal from the optical receiving unit. Therefore, the received signal at the 2i-1-th sampling moment includes the scattered light signal of the ambient light signal, while the received signal at the 2i-th sampling moment only contains the ambient light signal. Since the 2i-1-th sampling moment and the 2i-th sampling moment are within the same pulse period, their ambient light signals can be considered identical. Subtracting them yields the scattered light signal at the 2i-1-th sampling moment. Please refer to Figure 3, which shows the scattered light signals at sampling times 1 to 6. The scattered light signals at sampling times 1, 3, and 5 can be obtained by interleaving and subtracting them.

[0050] Then, the scattered light at the 2i-1th sampling moment arranged in time sequence within each detection period is extracted to obtain the scattered light sampling sequence within the current detection period. When the first received signal in the received signal sampling sequence output by the analog-to-digital converter to the signal processing unit in each detection period is located before the end of the positive pulse, and N is an integer power of 2, the scattered light sampling sequence within the current detection period obtained through the above operation contains N / 2 discrete points of scattered light signals.

[0051] Step 4: Obtain the scattered light sampling sequences of the current detection period and the most recent several detection periods in time and splice them together to form a detection sequence. This is because the application will subsequently perform peak detection on the sampling sequence, and a randomly divided single detection period may not contain a complete peak. Therefore, in order to ensure the accuracy of subsequent peak detection, several detection periods will be considered to ensure the integrity of the signal features. Generally, the scattered light sampling sequences of the current detection period and the previous detection period are spliced ​​together to form a detection sequence. The first detection period can be directly taken from the current detection period.

[0052] Step 5: Check whether the data stability of the above detection sequence meets the data stability requirements. This includes: calculating the mean of the detection sequence. with standard deviation When the standard deviation Exceeding the average When a predetermined threshold is reached, it is determined that the data stability of the detection sequence has not met the data stability requirements; otherwise, it is determined that the data stability of the detection sequence has met the data stability requirements. In one example, when... This indicates that the data stability has not met the data stability requirements, as shown in the flowchart in Figure 2.

[0053] Step 6: When the data stability of the detection sequence meets the data stability requirements, it is determined that there are no foreign objects in the sampling space of the photoelectric scattering detection instrument, and the inversion result of the scattered light sampling sequence in the current detection period is directly used as the atmospheric particle scattering detection result of the current detection period. The specific data inversion method adopts the existing inversion method, which will not be elaborated in this application.

[0054] Step 7: When the data stability of the detection sequence does not meet the data stability requirements, it is determined that there are foreign objects in the sampling space of the photoelectric scattering detection instrument. Then, the type of foreign object in the sampling space is further determined based on the peak detection results of the detection sequence in the frequency domain and time domain.

[0055] Common foreign object types in the sampling space can be mainly divided into three categories based on their varying degrees of influence on atmospheric particle scattering inversion results: flying insects, precipitation particles, and other types of foreign objects. Among these, flying insects are not typical atmospheric particles; therefore, when flying insects are present in the sampling space, the inversion results obtained from the scattered light sampling sequence within the current detection period will have significant deviations and cannot represent the true atmospheric particle scattering situation, rendering the data unusable. Rain and snow particles, on the other hand, are common and representative atmospheric particles. When precipitation particles are present in the sampling space, the inversion results obtained within the current detection period are reasonable, and only data correction is needed in specific applications. Other types of foreign objects have a lower probability of occurrence compared to flying insects and precipitation particles, but they still have a certain chance of appearing. Therefore, to ensure the integrity of the scheme, other types of foreign objects are also included.

[0056] As can be seen above, the impact of flying insect foreign objects on the atmospheric particle scattering detection process is actually far greater than that of precipitation particle foreign objects and other types of foreign objects. Therefore, the identification mechanism adopted in this application first distinguishes flying insect foreign objects from two other types of foreign objects based on the wingbeat signals of flying insects, including:

[0057] (1) First, extract the frequency domain features of the detection sequence and perform peak detection on the frequency domain features of the detection sequence. In one embodiment, extracting the frequency domain features of the detection sequence includes first windowing the detection sequence, and then performing a fast Fourier transform to extract the frequency domain features. The actual methods used for extracting frequency domain features and peak detection can be various existing methods, and this application is not limited to them.

[0058] (2) When it is determined from the peak detection results in the frequency domain that the frequency domain characteristics of the detection sequence contain a single peak, it is determined that the scattered light sampling sequence of the current detection period contains a flying insect wing flapping signal and that the type of foreign object in the sampling space is a flying insect. As mentioned above, since flying insects have the greatest impact on atmospheric particle scattering detection, there is no need to make further judgments when it is determined that the sampling space contains flying insects, and the subsequent step 8 can be executed directly.

[0059] (3) When the frequency domain peak detection results determine that the frequency domain features of the detection sequence do not contain a single peak, it is determined that the sampling space does not contain flying insects or foreign objects, and the type of foreign object in the sampling space is determined based on the peak detection results of the detection sequence in the time domain. That is, peak detection is performed on the time domain features of the detection sequence. When the peak detection results in the time domain determine that the time domain features of the detection sequence contain at least one peak, the type of foreign object in the sampling space is determined to be precipitation particles; otherwise, the type of foreign object in the sampling space is determined to be other types of foreign objects. Various existing peak detection methods can also be used in the same time domain scenario.

[0060] Step 8: After performing data post-processing on the inversion results of the scattered light sampling sequence in the current detection period according to the post-processing strategy corresponding to the foreign object type, the atmospheric particle scattering detection results for the current detection period are obtained.

[0061] Different foreign object types correspond to different post-processing strategies, and each post-processing strategy can be pre-defined. For example, as mentioned above, flying insects have a significant impact on atmospheric particle scattering. Post-processing the inversion results according to the post-processing strategy for flying insects, including discarding the inversion results from the current detection period, allows the atmospheric particle scattering detection results from the most recent detection period to be used as the atmospheric particle scattering detection results for the current detection period. Atmospheric particle scattering detection results under the influence of precipitation particles are correlated with the inversion results. Therefore, post-processing the inversion results according to the post-processing strategy for precipitation particles, including correcting the inversion results according to a predetermined data correction method, allows the results to be used as the atmospheric particle scattering detection results for the current detection period. This predetermined data correction method can be determined in advance through fitting or experimental methods. Post-processing strategies for other foreign object types can also be customized. Since flying insects and precipitation particles are the most common foreign objects detected, feedback information can be provided when other types of foreign objects are detected, prompting maintenance personnel to promptly check whether the sampling space is affected and requires manual intervention, etc.

[0062] The above descriptions are merely preferred embodiments of this application, and this application is not limited to the above embodiments. It is understood that other improvements and variations that can be directly derived or conceived by those skilled in the art without departing from the spirit and concept of this application should be considered to be included within the protection scope of this application.

Claims

1. A method for detecting atmospheric particle scattering in a photoelectric scattering detection instrument, characterized in that, The atmospheric particle scattering detection method includes: The light emitting unit in the photoelectric scattering detection instrument is driven by a pulse signal to generate pulsed light, and the light receiving unit in the photoelectric scattering detection instrument obtains the pulsed received signal. The frequency of the driving pulse of the light emitting unit is much greater than the wing flapping frequency of the flying insect. The received signal is discretely sampled to obtain a scattered light sampling sequence for each detection period. The scattered light sampling sequence includes the scattered light signal received by the optical receiving unit at different sampling times. The scattered light sampling sequences of the current detection cycle and the most recent several detection cycles are obtained and spliced ​​in time to form a detection sequence; When the data stability of the detection sequence is detected to meet the data stability requirements, it is determined that there are no foreign objects in the sampling space of the photoelectric scattering detection instrument, and the inversion result of the scattered light sampling sequence in the current detection period is taken as the atmospheric particle scattering detection result of the current detection period. When the data stability of the detection sequence is found to be below the data stability requirement, it is determined that there are foreign objects in the sampling space of the photoelectric scattering detection instrument. The type of foreign object in the sampling space is determined according to the peak detection results of the detection sequence in the frequency domain and time domain. The inversion results of the scattered light sampling sequence in the current detection period are post-processed according to the post-processing strategy corresponding to the foreign object type to obtain the atmospheric particle scattering detection results of the current detection period. Different foreign object types correspond to different post-processing strategies.

2. The atmospheric particle scattering detection method according to claim 1, characterized in that, Based on the peak detection results of the detection sequence in the frequency and time domains, the types of foreign objects contained in the sampling space are determined to include: Extract the frequency domain features of the detection sequence and perform peak detection on the frequency domain features of the detection sequence; When it is determined from the peak detection results in the frequency domain that the frequency domain characteristics of the detection sequence contain a single peak, it is determined that the scattered light sampling sequence of the current detection period contains a flying insect wing flapping signal and that the type of foreign object in the sampling space is a flying insect foreign object. When it is determined from the peak detection results in the frequency domain that the frequency domain features of the detection sequence do not contain a single peak, it is determined that the sampling space does not contain flying insects or foreign objects, and the type of foreign object in the sampling space is determined from the peak detection results in the time domain of the detection sequence.

3. The atmospheric particle scattering detection method according to claim 2, characterized in that, Determining the type of foreign object in the sampling space based on the peak detection results of the detection sequence in the time domain includes: Peak detection is performed on the temporal features of the detection sequence. If the temporal features of the detection sequence contain at least one peak based on the peak detection results, the foreign object type in the sampling space is determined to be precipitation particle foreign object; otherwise, other foreign object types are determined to be present in the sampling space.

4. The atmospheric particle scattering detection method according to claim 1, characterized in that, Discrete sampling of the received signal to obtain the scattered light sampling sequence for each detection period includes: Discrete sampling is performed on the received signal to obtain a received signal sampling sequence, which includes the received signal acquired by the optical receiving unit at each sampling time. The received signal sampling sequence is preprocessed to remove ambient light signals from the received signal to obtain the scattered light sampling sequence for each detection period.

5. The atmospheric particle scattering detection method according to claim 4, characterized in that, Discrete sampling of the received signal includes: According to discretely sampling the received signal at a sampling interval, and adjusting the phase of the discretely sampled signal such that one of the discrete sampling operations occurs before the end of the positive pulse of the received signal, It is the pulse period of the driving pulse.

6. The atmospheric particle scattering detection method according to claim 5, wherein, Preprocessing the received signal sampling sequence to remove ambient light signals from the received signal includes: Subtract the received signal at the 2i-1th sampling time from the received signal at the 2i-1th sampling time in the received signal sampling sequence to obtain the scattered light signal received by the optical receiving unit at the 2i-1th sampling time. Extract the scattered light at the 2i-1th sampling time in each detection period in chronological order to obtain the scattered light sampling sequence in the current detection period. The initial value of the integer parameter i is 1. For any value of i, the 2i-1 sampling time and the 2i sampling time correspond to two discrete samplings performed within the same pulse period of the driving pulse, and the 2i-1 sampling time corresponds to the discrete sampling performed before the end of the positive pulse of the received signal of the optical receiving unit.

7. The atmospheric particle scattering detection method according to claim 1, wherein, Period of a drive pulse for driving a light emitting unit to emit pulsed light , and the frequency of the drive pulse at least reaches K times the highest wing beat frequency of the flying insects, and parameter K ≥ 20.

8. The atmospheric particle scattering detection method according to claim 1, wherein, Using pulse signals to drive the light emitting unit in a photoelectric scattering detection instrument to generate pulsed light includes: The controlled constant current source in the light emitting unit is controlled by a pulse signal to drive the light emitting element connected to the controlled constant current source to emit pulse light, and the output current rising time and falling time of the controlled constant current source are both not more than 1 / 10 of the pulse period. wherein, It is the positive pulse width of the driving pulse.

9. The atmospheric particle scattering detection method according to claim 1, wherein, Acquiring pulsed received signals through the light receiving unit in an atmospheric particle scattering instrument includes: The pulse light is detected by a photodiode in the light receiving unit and an electric signal is output to a signal conditioning circuit. The signal conditioning circuit outputs a received signal in the form of a pulse, and the current rise time and current fall time of the received signal output by the signal conditioning circuit are both less than 1 ns. wherein, It is the positive pulse width of the driving pulse.

10. The method of claim 1, wherein, Detecting whether the data stability of the detection sequence meets the data stability requirements includes: calculating a mean value of the detection sequences with standard deviation when the standard deviation above average If a predetermined threshold is reached, it is determined that the data stability of the detection sequence has not met the data stability requirements; otherwise, it is determined that the data stability of the detection sequence has met the data stability requirements.

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