Atmospheric particle scattering detection method for photoelectric scattering detection instrument

Abstract

The invention discloses an atmospheric particle scattering detection method for a photoelectric scattering detection instrument, and relates to the field of atmospheric particle scattering detection. Then, a variable coefficient is extracted from an obtained scattered light sampling sequence from a statistical angle, so that whether foreign matters exist in a sampling space or not can be detected, and different foreign matter types including winged insects and rainfall particles can be identified by combining wave crest extraction operation in two dimensions of a frequency domain and a time domain; the method is characterized in that a scattered light sampling sequence is obtained in a current detection period, and then inversion results of the scattered light sampling sequence in the current detection period can be processed differently when foreign matters exist in a sampling space, so that accurate atmospheric particle scattering detection results can be obtained, and the method is realized based on an original light path of a photoelectric scattering detection instrument. And the accuracy and the reliability of atmospheric particle scattering detection can be improved.

Description

Technical Field

[0001] The present application relates to the field of atmospheric particle scattering detection, and in particular to an atmospheric particle scattering detection method for a photoelectric scattering detection instrument. Background Art

[0002] Photoelectric scattering detection instruments are a type of measurement device widely used in meteorological observation. Photoelectric scattering detection instruments mainly include a light emitting unit, a light receiving unit and a signal processing unit. The light emitting unit generates a modulated emission light beam, which forms an overlap area with the receiving field of view of the light receiving unit, namely the sampling space. After the emission light beam generated by the light emitting unit is scattered by particles in the sampling space, part of it enters the light receiving unit to generate a receiving signal and provides it to the signal processing unit. The signal processing unit can invert the measurement result by analyzing the receiving signal.

[0003] Photoelectric scattering detection instruments used for atmospheric and meteorological research are usually installed outdoors. Therefore, in addition to microscopic particles, foreign objects such as flying insects and precipitation particles are prone to appear in the sampling space of the photoelectric scattering detection instrument. These foreign objects will also scatter the transmitted light beam, and the intensity of the scattered light generated 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 the photoelectric scattering detection instrument and reduce the accuracy of the inversion results. Summary of the invention

[0004] In view of the above problems and technical requirements, this application proposes an atmospheric particle scattering detection method of a photoelectric scattering detection instrument. The technical solution of this application is as follows:

[0005] An atmospheric particle scattering method for a photoelectric scattering detection instrument, the atmospheric particle scattering detection method comprising:

[0006] The pulse signal is used to drive the light emitting unit in the photoelectric scattering detection instrument to generate pulse light, and the light receiving unit in the photoelectric scattering detection instrument obtains the received signal in the form of pulse, wherein the frequency of the driving pulse of the light emitting unit is much greater than the wing flapping frequency of the flying insect;

[0007] Discretely sampling the received signal and obtaining a scattered light sampling sequence in each detection cycle, wherein the scattered light sampling sequence includes scattered light signals received by the light receiving unit at different sampling times;

[0008] Obtain scattered light sampling sequences of the current detection cycle and the most recent detection cycles before it and splice them in time sequence to form a detection sequence;

[0009] When it is detected that the data stability of the detection sequence meets the data stability requirement, it is determined that there is no foreign matter in the sampling space of the photoelectric scattering detection instrument, and the inversion result of the scattered light sampling sequence in the current detection cycle is used as the atmospheric particle scattering detection result of the current detection cycle;

[0010] When it is detected that the data stability of the detection sequence does not meet the data stability requirements, it is determined that there is a foreign object in the sampling space of the photoelectric scattering detection instrument, and 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 the 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.

[0011] A further technical solution is to determine the types of foreign matter contained in the sampling space according to the peak detection results of the detection sequence in the frequency domain and the time domain, including:

[0012] Extracting frequency domain features of the detection sequence and performing peak detection on the frequency domain features of the detection sequence;

[0013] When it is determined according to the peak detection result 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 cycle contains a flying insect wing flapping signal and the type of foreign matter in the sampling space is determined to be a flying insect foreign matter;

[0014] When it is determined according to the peak detection result in the frequency domain that the frequency domain characteristics of the detection sequence do not contain a single peak, it is determined that the sampling space does not contain flying insect foreign matter and the type of foreign matter in the sampling space is determined according to the peak detection result in the time domain of the detection sequence.

[0015] A further technical solution is to determine the type of foreign matter in the sampling space according to the peak detection result of the detection sequence in the time domain, including:

[0016] Peak detection is performed on the time domain characteristics of the detection sequence. When it is determined according to the peak detection result of the time domain that the time domain characteristics of the detection sequence contain at least one peak, the type of foreign matter in the sampling space is determined to be precipitation particle foreign matter, otherwise it is determined that the sampling space contains other types of foreign matter.

[0017] A further technical solution is to discretely sample the received signal and obtain a scattered light sampling sequence in each detection cycle, including:

[0018] Discretely sampling the received signal to obtain a received signal sampling sequence, where the received signal sampling sequence includes the received signal obtained by the optical receiving unit at each sampling moment;

[0019] The received signal sampling sequence is subjected to data preprocessing to eliminate the ambient light signal in the received signal so as to obtain the scattered light sampling sequence in each detection cycle.

[0020] A further technical solution is that discrete sampling of the received signal includes:

[0021] According to 0.5T MOD The received signal is discretely sampled at a sampling interval of , and the phase of the discrete sampling is adjusted so that one discrete sampling operation occurs before the end of the positive pulse of the received signal, T MOD is the pulse period of the driving pulse.

[0022] A further technical solution is that data preprocessing is performed on the received signal sampling sequence to remove the ambient light signal in the received signal, including:

[0023] The received signal at the 2i-th sampling moment in the received signal sampling sequence is subtracted from the received signal at the 2i-th sampling moment in the received signal sampling sequence to obtain the scattered light signal received by the light receiving unit at the 2i-1th sampling moment, and the scattered light at the 2i-1th sampling moment arranged in time sequence in each detection cycle is extracted to obtain the scattered light sampling sequence in the current detection cycle;

[0024] Among them, the starting value of the integer parameter i is 1. For any value of i, the 2i-1th 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-1th sampling moment corresponds to the discrete sampling performed before the end of the positive pulse of the receiving signal of the light receiving unit.

[0025] A further technical solution is that the pulse period T of the driving pulse used to drive the light emitting unit to emit pulse light is MOD =1 / f MOD , and the frequency of the driving pulse f MOD It should be at least K times the highest wingbeat frequency of the flying insect, and the parameter K should be ≥ 20.

[0026] A further technical solution is to use a pulse signal to drive a light emitting unit in a photoelectric scattering detection instrument to generate pulse light, including:

[0027] 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 rise time and fall time of the controlled constant current source are both less than 0.1t ON , where t ON is the positive pulse width of the drive pulse.

[0028] A further technical solution is that obtaining a received signal in the form of a pulse by a light receiving unit in a photoelectric scattering detection instrument comprises:

[0029] The photodiode in the light receiving unit detects the pulse light and outputs an electrical signal to the signal conditioning circuit, which outputs a pulsed receiving signal. The current rise time and current fall time of the receiving signal output by the signal conditioning circuit are both less than 0.2t. ON , where t ON is the positive pulse width of the drive pulse.

[0030] A further technical solution is to detect whether the data stability of the detection sequence meets the data stability requirements, including:

[0031] The mean μ and standard deviation σ of the detection sequence are calculated. When the standard deviation σ exceeds the mean μ and reaches a predetermined threshold, it is determined that the data stability of the detection sequence does not meet the data stability requirement. Otherwise, it is determined that the data stability of the detection sequence meets the data stability requirement.

[0032] The beneficial technical effects of this application are:

[0033] The present application discloses an atmospheric particle scattering detection method for a photoelectric scattering detection instrument. The method is implemented based on the general optical path structure of the photoelectric scattering detection instrument. The coefficient of variation of the scattered light sampling sequence is extracted from a statistical perspective to detect whether there are foreign objects in the sampling space. A higher light source modulation frequency and signal sampling rate are used, and peak extraction operations in both frequency domain and time domain dimensions are combined to identify different types of foreign objects including flying insects and precipitation particles. Subsequently, different processing is performed on the inversion results of the scattered light sampling sequence in the current detection period to obtain a more accurate atmospheric particle scattering detection result.

[0034] This method directly identifies flying insects by detecting their wing-flapping signals. Compared with first identifying precipitation particles and then judging whether they are flying insects based on other conditions, this method has higher recognition accuracy and is more suitable as a basis for data quality control. Moreover, the presence or absence of flying insect wing-flapping signals has nothing to do with the size, type, and movement trajectory of the flying insects. Increasing the light source modulation frequency to more than 20 times the highest wing-flapping frequency of the flying insects makes it easier to detect the peak details in the received signal, so the recognition accuracy is also higher. Moreover, this method does not require the use of a precision optical path, which reduces debugging time and is convenient for mass production applications. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0036] Figure 2 It is a schematic flow chart of an atmospheric particle scattering detection method according to an embodiment of the present application.

[0037] Figure 3It is a schematic diagram of removing the ambient light signal from the received signal sampling sequence to obtain the scattered light sampling sequence in an example of the present application. DETAILED DESCRIPTION

[0038] The specific implementation of the present application is further described below in conjunction with the accompanying drawings.

[0039] The present application discloses an atmospheric particle scattering detection method for a photoelectric scattering detection instrument. The atmospheric particle scattering detection method is applied to a photoelectric scattering detection instrument. The schematic diagram of the structure of the photoelectric scattering detection instrument is shown in FIG. Figure 1 As shown, it also includes a light emitting unit, a light receiving unit and a signal processing unit, and the overlapping area of ​​the light emitting unit's illumination area and the light receiving unit's receiving field of view is a three-dimensional sampling space. However, the present application has modified and optimized the atmospheric particle scattering detection method performed by the signal processing unit, including:

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

[0041] The signal processing unit generates a driving pulse, the pulse period of which is recorded as T MOD , the positive pulse width of the driving pulse is recorded as t ON Since the wing-flapping frequency of flying insects is relatively high, and the present application will subsequently detect flying insect foreign bodies by detecting the wing-flapping frequency of flying insects, in order to facilitate subsequent frequency detection, the driving pulse must have a relatively high pulse frequency, at least ensuring that the pulse frequency is much greater than the wing-flapping frequency of flying insects. In one embodiment, the pulse period T of the driving pulse is MOD =1 / f MOD , and the modulation frequency of the drive pulse f MOD At least K times the maximum wing beat frequency of the flying insect, parameter K ≥ 20. Generally, the maximum wing beat frequency of the flying insect is 1kHz, then the pulse period T MOD ≤20μs. In order to reduce the average power consumption as much as possible under the premise of higher pulse frequency, the positive pulse width t ON Take as small as possible. In one embodiment, t ON ≤0.1T MOD .

[0042] The light emitting unit includes a controlled constant current source and a light emitting element connected thereto. The light emitting element can be a common LED or LD. The controlled constant current source can be controlled by the driving pulse generated above to drive the light emitting element to emit pulse light. In order to ensure effective driving, the output current rise time t of the controlled constant current source needs to be guaranteed. TX_R ≤0.1t ON And the output current fall time t of the controlled constant current sourceTX_F ≤0.1t ON Among them, the output current rise time t TX_R It refers to the time required for the controlled constant current source to rise from 10% to 90% of the current stable value, and the output current fall time t TX_F It refers to the time required for the controlled constant current source to drop from 90% to 10% of the stable current value.

[0043] Step 2, obtaining a received signal in the form of a pulse through a light receiving unit in a photoelectric scattering detection instrument, the signal period of the received signal is the same as the pulse period T of the driving pulse MOD Consistent.

[0044] In one embodiment, the light receiving unit includes a photodiode and a signal conditioning circuit connected thereto. The photodiode detects pulse light and outputs an electrical signal to the signal conditioning circuit, which then outputs a received signal in the form of a pulse after conditioning. In order to ensure effective reception, the current rise time t of the received signal output by the signal conditioning circuit is RX_R <0.2t ON , the current fall time t of the received signal RX_F <0.2t ON .

[0045] Step 3, discretely sample the received signal and obtain a scattered light sampling sequence in each detection cycle, wherein the scattered light sampling sequence includes scattered light signals received by the light receiving unit at different sampling times. The detection frequency of the detection cycle can be customized, and is generally set to multiple pulse cycles.

[0046] In fact, in addition to the scattered light signal in the sampling space, the received signal received by the light receiving unit is often mixed with the ambient light signal. Therefore, this step actually first discretely samples the received signal to obtain a received signal sampling sequence. At this time, the received signal sampling sequence obtained includes the received signal obtained by the light receiving unit at each sampling moment. Then, the received signal sampling sequence is further preprocessed to remove the ambient light signal in the received signal to obtain the scattered light sampling sequence in each detection cycle.

[0047] The discrete sampling operation in this step can be implemented by using the analog-to-digital conversion function of the signal processing unit, or by a dedicated analog-to-digital conversion module, such as Figure 1Taking the latter case as an example, the light receiving unit is connected to the signal processing unit after passing through the analog-to-digital conversion module. The analog-to-digital conversion module discretely samples the received signal output by the light 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 circuits. The analog-to-digital converter temporarily stores the received signals obtained at each sampling moment into the FIFO memory in sequence, and reads out the N received signals obtained in each detection cycle at one time and transmits them to the signal processing unit, and outputs continuously in this way, where N is an integer parameter.

[0048] Then the signal processing unit further performs data preprocessing on the received signal sampling sequence to obtain the scattered light sampling sequence. In order to conveniently remove the ambient light signal from the received signal sampling sequence, the discrete sampling is designed as follows: MOD The received signal is discretely sampled at a sampling interval and the phase of the discrete sampling is adjusted so that one discrete sampling operation occurs before the positive pulse of the received signal ends. The quantization accuracy of the general analog-to-digital converter is required to be no less than 14 bits.

[0049] Please refer to Figure 2 As shown in the flowchart, after the signal processing unit receives the received signal sampling sequence, it subtracts the received signal at the 2i-th sampling moment in the received signal sampling sequence from the received signal at the 2i-th sampling moment in the received signal sampling sequence to obtain the scattered light signal received by the light receiving unit at the 2i-1th sampling moment, wherein the starting value of the integer parameter i is 1, and for any value of i, the 2i-1th 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-1th sampling moment corresponds to the discrete sampling performed before the end of the positive pulse of the received signal of the light receiving unit. Therefore, the received signal at the 2i-1th 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-1th sampling moment and the 2i-th sampling moment are within the same pulse period, it can be considered that the ambient light signals of the two are consistent, and the scattered light signal at the 2i-1th sampling moment can be obtained by subtracting them. Please refer to Figure 3 The scattered light signals at the 1st to 6th sampling moments are shown as an example, and the scattered light signals at the 1st, 3rd and 5th sampling moments can be obtained by interleaving subtraction.

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

[0051] Step 4, obtain the scattered light sampling sequences of the current detection cycle and the most recent several detection cycles before it, and splice them in time sequence to form a detection sequence. This is because the sampling sequence will be subjected to peak detection in the subsequent application, and a single randomly divided detection cycle may not necessarily contain a complete peak. Therefore, in order to ensure the accuracy of subsequent peak detection, several detection cycles will be comprehensively considered here to ensure the integrity of the signal characteristics. Generally, the scattered light sampling sequences of the current detection cycle and the previous detection cycle are spliced ​​to form a detection sequence, and the first detection cycle can be directly taken as the current detection cycle.

[0052] Step 5, detecting whether the data stability of the above detection sequence meets the data stability requirement. This includes: calculating the mean μ and standard deviation σ of the detection sequence, and when the standard deviation σ exceeds the mean μ and reaches a predetermined threshold, determining that the data stability of the detection sequence does not meet the data stability requirement, otherwise determining that the data stability of the detection sequence meets the data stability requirement. In one example, when σ>10μ, it means that the data stability does not meet the data stability requirement, such as Figure 2 The flowchart of this is taken as an example.

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

[0054] Step 7, when it is detected that the data stability of the detection sequence does not meet the data stability requirements, it is determined that there is a foreign object in the sampling space of the photoelectric scattering detection instrument, and 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 matter types in the sampling space can be divided into three categories according to the degree of influence on the atmospheric particle scattering inversion results: flying insect foreign matter, precipitation particle foreign matter and other foreign matter types. Among them, flying insect foreign matter is not a typical atmospheric particle. Therefore, when there are flying insect foreign matter in the sampling space, the inversion result obtained according to the scattered light sampling sequence in the current detection period will have a significant deviation, which cannot represent the actual atmospheric particle scattering situation, and the data is unavailable. However, precipitation particle foreign matter such as rain and snow are common and representative atmospheric particles. When there are precipitation particle foreign matter in the sampling space, the inversion result obtained in the current detection period is reasonable, and only data correction is required in specific applications. Compared with flying insect foreign matter and precipitation particle foreign matter, other foreign matter types have a lower probability of occurrence, but there is still a certain probability of occurrence. Therefore, in order to ensure the integrity of the solution, other foreign matter types are also retained.

[0056] As can be seen above, the impact of flying insects on the atmospheric particle scattering detection process is actually much greater than that of precipitation particles and other types of foreign matter. Therefore, the recognition mechanism adopted in this application is to first distinguish flying insects from the other two types of foreign matter based on the flying insect wing flapping signal, 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 performing windowing processing on the detection sequence and then performing fast Fourier transform to extract the frequency domain features. The actual method for extracting frequency domain features and the method for peak detection can adopt various existing methods, which are not limited in this application.

[0058] (2) When it is determined that the frequency domain characteristics of the detection sequence contain a single peak according to the peak detection result in the frequency domain, it is determined that the scattered light sampling sequence of the current detection period contains a flying insect wing flapping signal and the type of foreign matter in the sampling space is determined to be a flying insect foreign matter. As described above, since flying insect foreign matter has the greatest impact on atmospheric particle scattering detection, when it is determined that the sampling space contains flying insect foreign matter, no subsequent judgment is required, and the subsequent step 8 can be directly executed.

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

[0060] Step 8: Perform 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 body type to obtain the atmospheric particle scattering detection result of the current detection period.

[0061] Different types of foreign matter correspond to different post-processing strategies, and the post-processing strategy for each type of foreign matter can be pre-calibrated. For example, as described above, flying insect foreign matter has a greater impact on atmospheric particle scattering. According to the post-processing strategy corresponding to the flying insect foreign matter, the inversion result is post-processed, including discarding the inversion result of the current detection cycle, and the atmospheric particle scattering detection result of the most recent detection cycle can continue to be used as the atmospheric particle scattering detection result of the current detection cycle. The atmospheric particle scattering detection under the influence of precipitation particle foreign matter is correlated with the inversion result. Therefore, according to the post-processing strategy corresponding to the precipitation particle foreign matter, the inversion result is post-processed, including correcting the inversion result according to the predetermined data correction method as the atmospheric particle scattering detection result of the current detection cycle. The predetermined data correction method here can be determined in advance by fitting or experimental methods. The post-processing strategies corresponding to other types of foreign matter can also be customized, and because flying insect foreign matter and precipitation particle foreign matter are usually the main foreign matter, prompt information can also be fed back when other types of foreign matter are detected to prompt maintenance personnel to promptly check whether the sampling space is affected and requires manual intervention, etc.

[0062] The above is only a preferred embodiment of the present application, and the present application is not limited to the above embodiments. It is understood that other improvements and changes directly derived or associated by those skilled in the art without departing from the spirit and concept of the present application should be considered to be included in the protection scope of the present 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 comprises: A pulse signal is used to drive a light emitting unit in a photoelectric scattering detection instrument to generate pulse light, and a pulse receiving signal is obtained through a light receiving unit in the photoelectric scattering detection instrument, wherein the frequency of the driving pulse of the light emitting unit is much greater than the wing flapping frequency of the flying insect; Discretely sampling the received signal and obtaining a scattered light sampling sequence in each detection cycle, wherein the scattered light sampling sequence includes scattered light signals received by the light receiving unit at different sampling moments; Obtain scattered light sampling sequences of the current detection cycle and the most recent detection cycles before it and splice them in time sequence to form a detection sequence; When it is detected that the data stability of the detection sequence meets the data stability requirement, it is determined that there is no foreign matter in the sampling space of the photoelectric scattering detection instrument, and the inversion result of the scattered light sampling sequence in the current detection cycle is used as the atmospheric particle scattering detection result of the current detection cycle; When it is detected that the data stability of the detection sequence does not meet the data stability requirements, it is determined that there is a foreign object in the sampling space of the photoelectric scattering detection instrument, and the type of the foreign object in the sampling space is determined according to the peak detection results of the detection sequence in the frequency domain and the time domain. After 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, the atmospheric particle scattering detection result of the current detection period is obtained, and different foreign object types correspond to different post-processing strategies.

2. The atmospheric particle scattering detection method according to claim 1, characterized in that: Determining the types of foreign matter contained in the sampling space according to the peak detection results of the detection sequence in the frequency domain and the time domain includes: Extracting frequency domain features of the detection sequence and performing peak detection on the frequency domain features of the detection sequence; When it is determined according to the peak detection result 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 in the current detection period contains a flying insect wing flapping signal and the type of the foreign matter in the sampling space is determined to be a flying insect foreign matter; When it is determined according to the peak detection result in the frequency domain that the frequency domain characteristics of the detection sequence do not contain a single peak, it is determined that the sampling space does not contain flying insect foreign matter and the type of foreign matter in the sampling space is determined according to the peak detection result 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 matter in the sampling space according to the peak detection result of the detection sequence in the time domain includes: Peak detection is performed on the time domain characteristics of the detection sequence. When it is determined that the time domain characteristics of the detection sequence contain at least one peak according to the time domain peak detection result, the type of foreign matter in the sampling space is determined to be precipitation particle foreign matter, otherwise it is determined that the sampling space contains other types of foreign matter.

4. The atmospheric particle scattering detection method according to claim 1, characterized in that: Discretely sampling the received signal and obtaining a scattered light sampling sequence in each detection cycle includes: Discretely sampling the received signal to obtain a received signal sampling sequence, wherein the received signal sampling sequence includes the received signal obtained by the optical receiving unit at each sampling moment; The received signal sampling sequence is subjected to data preprocessing to remove the ambient light signal in the received signal to obtain the scattered light sampling sequence in each detection cycle.

5. The atmospheric particle scattering detection method according to claim 4, characterized in that: Discretely sampling the received signal includes: According to 0.5T MOD The received signal is discretely sampled at a sampling interval of , and the phase of the discrete sampling is adjusted so that one discrete sampling operation occurs before the positive pulse of the received signal ends, T MOD is the pulse period of the driving pulse.

6. The atmospheric particle scattering detection method according to claim 5, characterized in that: Performing data preprocessing on the received signal sampling sequence to remove the ambient light signal in the received signal includes: Subtracting the received signal at the 2i-th sampling moment in the received signal sampling sequence from the received signal at the 2i-th sampling moment in the received signal sampling sequence to obtain the scattered light signal received by the light receiving unit at the 2i-1th sampling moment, and extracting the scattered light at the 2i-1th sampling moment arranged in time sequence in each detection cycle to obtain the scattered light sampling sequence in the current detection cycle; Among them, the starting value of the integer parameter i is 1. For any value of i, the 2i-1th 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-1th sampling moment corresponds to the discrete sampling performed before the end of the positive pulse of the receiving signal of the light receiving unit.

7. The atmospheric particle scattering detection method according to claim 1, characterized in that: The period T of the driving pulse for driving the light emitting unit to emit pulse light MOD =1 / f MOD , and the frequency of the driving pulse f MOD It should be at least K times the highest wingbeat frequency of the flying insect, and the parameter K should be ≥ 20.

8. The atmospheric particle scattering detection method according to claim 1, characterized in that: Using a pulse signal to drive the light emitting unit in the photoelectric scattering detection instrument to generate pulse 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 rise time and fall time of the controlled constant current source are both less than 0.1t ON , where t ON is the positive pulse width of the drive pulse.

9. The atmospheric particle scattering detection method according to claim 1, characterized in that: The received signal in pulse form obtained by the light receiving unit in the atmospheric particle scattering instrument includes: The photodiode in the light receiving unit detects the pulse light and outputs an electrical signal to the signal conditioning circuit, and the signal conditioning circuit outputs a pulsed receiving signal, and the current rise time and current fall time of the receiving signal output by the signal conditioning circuit are both less than 0.2t ON , where t ON is the positive pulse width of the drive pulse.

10. The atmospheric particle scattering detection method according to claim 1, characterized in that: Detecting whether the data stability of the detection sequence meets the data stability requirements includes: The mean μ and the standard deviation σ of the detection sequence are calculated. When the standard deviation σ exceeds the mean μ and reaches a predetermined threshold, it is determined that the data stability of the detection sequence does not meet the data stability requirement. Otherwise, it is determined that the data stability of the detection sequence meets the data stability requirement.

Images