A method for counting insects based on capacitance

Abstract

This invention discloses a capacitance-based insect counting and detection method, relating to the field of agricultural informatization and intelligent monitoring. The method includes: channel arrangement, where capacitance sensing channels and photoelectric sensing channels are sequentially set along the insect's axial direction; signal acquisition and preprocessing, where information from the capacitance and photoelectric sensing channels is acquired independently and synchronously; event detection, where thresholds for the capacitance and photoelectric sensing channels are determined; valid event determination and direction discrimination, used to determine events in which insects pass through the capacitance and photoelectric sensing channels; segmentation of adhered insects and extraction of multi-dimensional information; and data output. This counting and detection method employs a capacitance-photoelectric dual-modal collaborative verification mechanism, counting only occurs when both channels are triggered sequentially and meet time window requirements. This effectively filters out single-channel interference such as dust, vibration, temperature and humidity drift, and ambient light changes, significantly improving counting accuracy.

Description

Technical Field

[0001] This invention relates to the field of agricultural informatization and intelligent monitoring technology, specifically to a capacitance-based insect counting and detection method. Background Technology

[0002] Precise pest monitoring is a core component of integrated pest management in modern agriculture and pest control in storage and logistics. Automatic counting technology, as a key support for precise monitoring, is currently mainly divided into two types: capacitive and photoelectric, but both have significant limitations.

[0003] Capacitive counting schemes utilize the fact that insects have a higher dielectric constant than air to achieve detection. Their advantages include being unaffected by ambient light and color, and having strong resistance to dust. However, single-channel capacitive detection is susceptible to false triggers caused by sudden changes in ambient humidity or the partial passage of insects. It also lacks sufficient sensitivity to rapidly moving, tiny insects, and the accuracy in identifying adhered insects needs improvement. Furthermore, single-capacitive sensing schemes are easily interfered with in complex electromagnetic environments, affecting counting reliability.

[0004] Photoelectric counting schemes trigger counting by blocking infrared beams, offering fast response and simple structure. However, they are susceptible to interference from dust, moisture, and vibration, resulting in false positives. They are also less effective at blocking transparent or light-colored small insects, and their stability decreases in dark or bright light environments, limiting their applicability. Furthermore, traditional dual-photoelectric channel schemes do not adequately consider synergy with other sensing technologies, making them ineffective in handling situations with multiple complex interferences. Additionally, their algorithms for segmenting adhered insects are simplistic, leading to insufficient counting accuracy.

[0005] For example, patent CN118730229A discloses a capacitive counting device and method. The capacitive counting device, constructed using capacitors, resistors, and other components, collects the corresponding voltage value based on the capacitance change caused by the gas flow. It then combines the state transition result of the voltage value to perform the corresponding counting process on the gas meter. This method is not only simple in structure and can be integrated into the main board of the gas meter, greatly reducing investment costs, but also effectively avoids interference problems caused by static magnetic fields and strong light through simple signal processing, thereby ensuring the overall counting accuracy and efficiency.

[0006] For example, patent CN103150593B discloses a photoelectric counting method and device for items. The method includes the following steps: S1, emitting a first light beam; S2, receiving a second light beam, and stopping emitting the first light beam after receiving the second light beam; S3, determining whether light can be received during a first time period after stopping the emission of the first light beam. If so, the second light beam is considered an interference light beam and is not counted; if not, the second light beam is considered a reflected light beam of the first light beam, and the count is incremented by one. This invention utilizes a square wave form of emitting light source to intermittently emit light beams for the technology, and ensures the accuracy of the count by identifying whether the currently received light beam is an effective light beam or an interference light source.

[0007] However, in existing technologies, a single sensing method is difficult to balance anti-interference, response speed and detection accuracy. Simple multi-channel overlay schemes fail to achieve complementary advantages of different sensing technologies and still suffer from problems such as high false alarm rate, limited functionality, and inability to fully meet the monitoring needs of complex scenarios. They are also unable to provide users with the multi-dimensional data required for pest infestation tracing and migration pattern research.

[0008] To address the aforementioned issues, there is an urgent need for innovative designs based on existing counting methods. Summary of the Invention

[0009] The purpose of this invention is to provide a capacitance-based insect counting and detection method to solve the problems in the prior art mentioned above, where a single sensing method is difficult to balance anti-interference, response speed and detection accuracy, and the simple multi-channel superposition scheme fails to achieve the complementary advantages of different sensing technologies, and still suffers from high false alarm rate, single function, inability to fully meet the monitoring needs of complex scenarios, and difficulty in providing users with the multi-dimensional data required for insect infestation tracing and migration pattern research.

[0010] To achieve the above objectives, the present invention provides the following technical solution: a capacitance-based insect counting and detection method, comprising the following steps:

[0011] Step S1, Channel arrangement: Along the axial direction of the insect's passage, a capacitive sensing channel and a photoelectric sensing channel are set up in sequence.

[0012] Step S2, signal acquisition and preprocessing, independently and synchronously acquire information from the capacitive sensing channel and the photoelectric sensing channel;

[0013] Step S3, event detection, determining the threshold values ​​for the capacitive sensing channel and the photoelectric sensing channel;

[0014] Step S4, valid event determination and direction discrimination, is used to determine the events of the insect passing through the capacitive sensing channel and the photoelectric sensing channel;

[0015] Step S5: Segmentation of the adherent worm body and extraction of multi-dimensional information, used to assess the body shape of the worm body;

[0016] Step S6, Data Output: After each effective detection is completed, output the insect count, movement direction, passage speed, body size grade, and adhesion marker information.

[0017] Preferably, in step S1, the center distance L between the capacitive sensing channel and the photoelectric sensing channel is set to 5-30mm to ensure that the sensing signals of the two channels can be triggered sequentially when the insect passes through, while avoiding signal crosstalk. The electrodes of the capacitive sensing channel adopt a parallel grid or mesh structure and are coated with a hydrophobic insulating coating to reduce the influence of dust adhesion and condensation.

[0018] Preferably, the photoelectric sensing channel adopts an infrared through-beam structure, and the operating wavelength of the emitting tube is 850–950 nm, with a modulation frequency of 1–10 kHz, to suppress ambient light interference. At the same time, a physical isolation zone is provided between the capacitive sensing channel and the photoelectric sensing channel to reduce signal crosstalk.

[0019] Preferably, the specific method in step S2 is as follows: First, a high-frequency excitation signal of the capacitance-based insect counting detection method (100kHz–10MHz) is applied to the capacitance sensing channel, and the capacitance change signal is then processed by the signal conditioning module. The signal is converted into a stable electrical signal and dynamic baseline compensation is performed to offset baseline drift caused by changes in ambient temperature and humidity. Then, the output signal of the receiving tube of the photoelectric sensing channel is monitored in real time and converted into a binary occlusion state signal S, where a high level indicates that the beam is "on" and a low level indicates that the beam is "off". Afterwards, digital filtering is used to filter out glitch noise with a width of less than 10ms to avoid instantaneous interference.

[0020] Preferably, step S3 is specifically performed as follows: first, the preprocessed capacitance change signal is processed... Set a trigger threshold, when When the threshold is exceeded, it is determined to be a capacitance event, and its start time is recorded. Peak time and end time The duration of the event is calculated using the following formula: A capacitance-based insect counting detection method is then used to detect transitions in the occlusion state signal S. When a falling edge from high to low is detected, it is determined as the start of a photoelectric event, and the time is recorded. When a rising edge from low to high is detected, the end time is recorded. Calculate the duration of the event using the following formula: .

[0021] Preferably, step S4 is specifically implemented by first setting an effective time window. A capacitance-based insect counting and detection method, in which The capacitance-based insect counting detection method uses the minimum effective insect velocity, which is taken as 10–50 mm / s, to calculate the time difference between the onset of the capacitance event and the photoelectric event. The calculation formula is as follows: Then, valid events are determined, and the logic for determining valid events is: only if a valid event is found that the event is valid (based on the capacitance-based insect counting detection method). < When the two events are triggered sequentially according to the capacitance channel and photoelectric channel in the capacitance-based insect counting detection method, they are determined to be valid insect passage events. If only one channel detects the event and the other channel does not respond, it is determined to be an interference event and is not counted. Simultaneously, if the capacitance signal exhibits multi-peak characteristics or if an abnormal level transition occurs during photoelectric signal obstruction, it is marked as a suspected abnormal event, triggering a secondary verification, combined with a consistency check of the two channel signals. Finally, direction determination is performed: if... < and < This indicates that the insect first passes through the capacitive sensing channel and then through the photoelectric sensing channel, which is determined to be forward movement; if < and < If the passage is determined to be in the opposite direction, the forward counter and the reverse counter are used to accumulate the count.

[0022] Preferably, step S5 is specifically implemented as follows: first, based on the typical length of the target pest... With average speed Calculate the normal passage time threshold for a single insect. If the duration of the capacitor event is valid, or duration of photoelectric events Exceed The passage was determined to be due to multiple insects adhering together; a segmentation algorithm that integrates the durations of the two channels was used to calculate the number of adhering insects. This method achieves accurate counting of adherent insects; subsequently, it uses a capacitance-based insect counting detection method based on the distance between two channels and the time difference between two event feature points. Calculate the passage speed of the insect. Based on the peak amplitude of the capacitance signal and the preset size level threshold, the insects are divided into three levels: small, medium and large, to achieve size assessment.

[0023] Preferably, in step S6, after each effective detection is completed, the counting result, movement direction, passage speed, body size level and adhesion mark information are output. For interference events, the interference type is recorded and entered into the log to provide a reference for equipment maintenance.

[0024] Preferably, the interference types include capacitive single-channel interference, photoelectric single-channel interference, and abnormal signal interference.

[0025] Compared with the prior art, the beneficial effects of the present invention are:

[0026] 1. A capacitive-photoelectric dual-mode collaborative mutual verification mechanism is adopted. Counting only occurs when the two channels are triggered sequentially and the time window requirements are met. This can effectively filter out single-channel interference such as dust, vibration, temperature and humidity drift, and ambient light changes, thereby effectively improving the counting accuracy.

[0027] 2. Strong environmental adaptability: Inheriting the advantage of capacitive sensing being unaffected by light and color, and combined with the anti-interference design of photoelectric sensing, it can work stably in complex environments such as day and night alternation, high dust, high humidity, strong light or darkness, and is applicable to a wide range of scenarios.

[0028] 3. It can output multi-dimensional data, not only achieving accurate counting, but also simultaneously outputting movement direction, passage speed, body size level and adhesion marks, providing comprehensive data support for pest source tracing, migration pattern research and pest spread early warning, significantly enhancing data value;

[0029] 4. Wide adaptability: By adjusting the channel spacing, trigger threshold and time parameters, it can be adapted to the detection of pests of different sizes and movement speeds, such as rice weevils, aphids and whiteflies. There is no need to redesign the scheme for specific pests, and it has strong versatility.

[0030] 5. Through multiple mechanisms such as signal preprocessing, dual-modal mutual verification, and secondary verification of abnormal events, it can effectively resist various types of interference such as electromagnetic interference, transient foreign object interference, and signal drift, ensuring stable and reliable detection results and improving anti-interference capability.

[0031] 6. Based on the traditional single-channel solution, only one complementary sensing component is added, which simplifies circuit design and logic processing, keeps costs under control, and facilitates mass production and engineering deployment. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the counting method of the present invention. Detailed Implementation

[0033] 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] This application provides a capacitance-based insect counting and detection method. To better understand the above technical solution, it will be described in detail below with reference to the accompanying drawings and specific implementation methods. Figure 1 As shown in this embodiment of the present application, a capacitance-based insect counting and detection method includes the following steps:

[0035] Step S1, Channel arrangement: Along the axial direction of the insect's passage, a capacitive sensing channel and a photoelectric sensing channel are set up in sequence.

[0036] In practice, the center-to-center distance L between the capacitive sensing channel and the photoelectric sensing channel is first set to 5-30mm to ensure that the sensing signals of the two channels are triggered sequentially when an insect passes through, while avoiding signal crosstalk. The electrodes of the capacitive sensing channel adopt a parallel grid or mesh structure and are coated with a hydrophobic insulating coating to reduce the influence of dust adhesion and condensation. The photoelectric sensing channel adopts an infrared through-beam structure, and the operating wavelength of the emitting tube is 850-950nm, with a modulation frequency of 1-10kHz, to suppress ambient light interference. At the same time, a physical isolation zone is set between the capacitive sensing channel and the photoelectric sensing channel to reduce signal crosstalk.

[0037] In this embodiment, the channel arrangement enables dual-sensor synergy and complementarity. The capacitive sensor is unaffected by the insect's color and transparency, accurately identifying transparent and light-colored insects. The photoelectric sensor has a fast response speed and is sensitive to capturing the insect's outline. The axial arrangement of the two sensors forms "dual verification," compensating for the detection blind spots of a single sensor and improving detection reliability from a hardware perspective. It provides a foundation for direction determination and speed calculation. The dual channels are arranged in an orderly manner along the insect's path. The time difference between the insect passing through the two channels can be directly used for speed calculation. The direction of movement can be determined by the triggering sequence of the two channel signals, eliminating the need for additional detection modules, simplifying the structure while enriching the detection dimensions. It optimizes insect passage guidance. The axial arrangement conforms to the insect's natural passage trajectory, avoiding interference from the channel structure on the insect's movement, reducing detection errors caused by insect stagnation and reversals, and adapting to scenarios with large numbers of insects passing continuously.

[0038] Step S2, signal acquisition and preprocessing, independently and synchronously acquire information from the capacitive sensing channel and the photoelectric sensing channel;

[0039] In specific implementation, a high-frequency excitation signal based on the capacitance-based insect counting detection method (100kHz–10MHz) is first applied to the capacitance sensing channel. The capacitance change signal is then processed by the signal conditioning module. The signal is converted into a stable electrical signal and dynamic baseline compensation is performed to offset baseline drift caused by changes in ambient temperature and humidity. Then, the output signal of the receiving tube of the photoelectric sensing channel is monitored in real time and converted into a binary occlusion state signal S, where a high level indicates that the beam is "on" and a low level indicates that the beam is "off". Afterwards, digital filtering is used to filter out glitch noise with a width of less than 10ms to avoid instantaneous interference.

[0040] In this embodiment, signal acquisition and preprocessing ensure signal independence and synchronization. Independent acquisition avoids mutual interference between dual-channel signals, ensuring the integrity of the original data for capacitance signals (reflecting the insect's dielectric properties and size) and photoelectric signals (reflecting the insect's outline and passage sequence). Synchronous acquisition accurately corresponds to the signal characteristics of the same insect in both channels, providing data support for subsequent event correlation analysis. It also improves signal quality by filtering out environmental interference (such as electromagnetic interference and light fluctuations), amplifying weak capacitance signals, and reducing noise in photoelectric signals, thus solving signal distortion problems in complex environments and laying a solid data foundation for subsequent threshold judgment and event detection. Furthermore, it reduces the pressure on subsequent processing by regularizing signals and removing redundant data, reducing the burden of invalid data on subsequent algorithms, improving overall detection efficiency, ensuring real-time performance, and adapting to high-speed insect passage scenarios.

[0041] Step S3, event detection, determining the threshold values ​​for the capacitive sensing channel and the photoelectric sensing channel;

[0042] In practice, the preprocessed capacitance change signal is first processed. Set a trigger threshold, when When the threshold is exceeded, it is determined to be a capacitance event, and its start time is recorded. Peak time and end time The duration of the event is calculated using the following formula: A capacitance-based insect counting detection method is then used to detect transitions in the occlusion state signal S. When a falling edge from high to low is detected, it is determined as the start of a photoelectric event, and the time is recorded. When a rising edge from low to high is detected, the end time is recorded. Calculate the duration of the event using the following formula: .

[0043] In this embodiment, valid detection events can be quickly identified. By setting corresponding thresholds for dual channels (capacitive signal threshold reflecting changes in the insect's dielectric constant, and photoelectric signal threshold reflecting changes in the insect's occlusion and reflection of light), "insect passage" and "environmental noise interference" can be quickly distinguished, avoiding misjudgment based on a single threshold and reducing the probability of missed or false detections. Preliminary event screening can be achieved, triggering subsequent analysis processes only when the signal exceeds the set threshold, reducing the consumption of system resources by meaningless events and improving the targeting and efficiency of the detection process. It can adapt to different insect characteristics, and the dual-channel thresholds can be flexibly adjusted according to parameters such as the size, dielectric constant, and color of the insect to be detected, expanding the applicability range of the method. It can detect both small storage pests and medium-sized agricultural pests.

[0044] Step S4, valid event determination and direction discrimination, is used to determine the events of the insect passing through the capacitive sensing channel and the photoelectric sensing channel;

[0045] In practice, the effective time window is first set. A capacitance-based insect counting and detection method, in which The capacitance-based insect counting detection method uses the minimum effective insect velocity, which is taken as 10–50 mm / s, to calculate the time difference between the onset of the capacitance event and the photoelectric event. The calculation formula is as follows: Then, valid events are determined, and the logic for determining valid events is: only if a valid event is found that the event is valid (based on the capacitance-based insect counting detection method). < When the two events are triggered sequentially according to the capacitance channel and photoelectric channel in the capacitance-based insect counting detection method, they are determined to be valid insect passage events. If only one channel detects the event and the other channel does not respond, it is determined to be an interference event and is not counted. Simultaneously, if the capacitance signal exhibits multi-peak characteristics or if an abnormal level transition occurs during photoelectric signal obstruction, it is marked as a suspected abnormal event, triggering a secondary verification, combined with a consistency check of the two channel signals. Finally, direction determination is performed: if... < and < This indicates that the insect first passes through the capacitive sensing channel and then through the photoelectric sensing channel, which is determined to be forward movement; if < and < If the passage is determined to be in the opposite direction, the forward counter and the reverse counter are used to accumulate the count.

[0046] In this embodiment, invalid interference events can be eliminated. Combined with the triggering logic of the dual-channel signals (e.g., only when both channels detect signals exceeding the threshold and the signal timing conforms to the insect's movement pattern is it determined to be a valid event), false triggering of a single channel (such as dust interference or sudden changes in light) can be eliminated, further improving the counting accuracy. Movement direction discrimination can be achieved. Based on the triggering order of the dual-channel signals (capacitive channel triggered first, photoelectric channel triggered later, or vice versa), it is possible to accurately determine whether the insect is moving forward or turning back, solving the problem that traditional methods cannot distinguish the insect's movement direction, leading to repeated counting. This is especially suitable for open insect passage scenarios. It also provides a basis for subsequent data processing: while clearly determining valid events, direction information is recorded simultaneously, making the detection results more valuable.

[0047] Step S5: Segmentation of the adherent worm body and extraction of multi-dimensional information, used to assess the body shape of the worm body;

[0048] In practice, the first step is to determine the typical length of the target pest. With average speed Calculate the normal passage time threshold for a single insect. If the duration of the capacitor event is valid, or duration of photoelectric events Exceed The passage was determined to be due to multiple insects adhering together; a segmentation algorithm that integrates the durations of the two channels was used to calculate the number of adhering insects. This method achieves accurate counting of adherent insects; subsequently, it uses a capacitance-based insect counting detection method based on the distance between two channels and the time difference between two event feature points. Calculate the passage speed of the insect. Based on the peak amplitude of the capacitance signal and the preset size level threshold, the insects are divided into three levels: small, medium and large, to achieve size assessment.

[0049] This embodiment solves the problem of counting adhered insects. Traditional single-sensor methods struggle to distinguish between adhered insects and individual insects. This step integrates capacitance signals (reflecting the dielectric change amplitude caused by differences in insect volume) and photoelectric signals (reflecting the adhesion characteristics of insect outlines) to achieve accurate segmentation of adhered insects, preventing multiple adhered insects from being mistakenly counted as a single insect and significantly improving counting accuracy. It also enables size classification. By extracting multi-dimensional information such as the amplitude of capacitance signal changes (positively correlated with insect volume) and the duration of photoelectric signal occlusion (positively correlated with insect length), insect size can be classified (e.g., small, medium, large), overcoming the limitations of traditional methods that can only count but not assess individual insect characteristics. Furthermore, it provides data support for subsequent applications. Information such as size classification and adhesion markers can provide richer decision-making basis for agricultural pest and disease control (e.g., distinguishing between adults and larvae for targeted pesticide application) and biological population research (e.g., analyzing insect population structure).

[0050] Step S6, Data Output: After each effective detection is completed, output the insect count, movement direction, passage speed, size grade, and adhesion marker information;

[0051] In practice, after each effective detection is completed, the counting result, movement direction, passage speed, body size level and adhesion mark information are output. For interference events, the interference type is recorded and entered into the log to provide a reference for equipment maintenance. The interference types include capacitive single-channel interference, photoelectric single-channel interference and abnormal signal interference.

[0052] This embodiment can meet the needs of multiple application scenarios: it outputs counting results, movement direction, passage speed, body size level, and adhesion markers in one go, which not only meets the basic needs of counting pests in storage, but also meets the advanced needs of agricultural field monitoring and biological experimental research for multi-dimensional characteristics of insects, thus improving the versatility of the method; it achieves the purpose of traceable and analyzable detection data, outputs various types of data in a structured manner, which makes it easy for staff to grasp the detection dynamics in real time, and provides complete data support for subsequent data review, algorithm optimization, and insect behavior analysis, helping to form a closed loop of "detection-analysis-optimization"; it improves work efficiency, without the need for additional secondary data processing, directly outputs standardized results, reduces the difficulty of operation for staff, adapts to automated and intelligent detection scenarios, and can be linked with remote terminals and data management platforms to achieve the effect of unattended monitoring.

[0053] In summary, this method forms a complete "hardware deployment-signal processing-event analysis-data output" chain. Its core advantage lies in the fusion of capacitive and photoelectric sensing, which retains the characteristics of strong anti-interference and adaptability to various insects of capacitive sensing, while improving the ability of temporal recognition and contour capture by photoelectric sensing. At the same time, through adhesion segmentation and multi-dimensional extraction, it breaks through the functional limitations of traditional counting methods, taking into account accuracy, efficiency and versatility, and is suitable for insect detection needs in multiple scenarios such as agriculture, warehousing, and biological research.

[0054] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A capacitance-based insect counting and detection method, characterized in that, The counting detection method includes the following steps: Step S1, Channel arrangement: Along the axial direction of the insect passage, a capacitive sensing channel and a photoelectric sensing channel are set up in sequence. Step S2, signal acquisition and preprocessing, independently and synchronously acquire information from the capacitive sensing channel and the photoelectric sensing channel; Step S3, event detection, determining the threshold values ​​for the capacitive sensing channel and the photoelectric sensing channel; Step S4, valid event determination and direction discrimination, is used to determine the events of the insect passing through the capacitive sensing channel and the photoelectric sensing channel; Step S5: Segmentation of the adherent worm body and extraction of multi-dimensional information, used to assess the body shape of the worm body; Step S6, Data Output: After each valid detection is completed, output the insect count, movement direction, passage speed, size grade, and adhesion marker information.

2. The insect counting and detection method based on capacitance according to claim 1, characterized in that: In step S1, the center distance L between the capacitive sensing channel and the photoelectric sensing channel is set to 5-30mm to ensure that the sensing signals of the two channels are triggered sequentially when the insect passes through, while avoiding signal crosstalk. The electrodes of the capacitive sensing channel adopt a parallel grid and are coated with a hydrophobic insulating coating to reduce the influence of dust adhesion and condensation.

3. The insect counting and detection method based on capacitance according to claim 2, characterized in that: The photoelectric sensing channel adopts an infrared through-beam structure, and the operating wavelength of the emitting tube is 850–950nm, with a modulation frequency of 1–10kHz, to suppress ambient light interference. At the same time, a physical isolation zone is provided between the capacitive sensing channel and the photoelectric sensing channel to reduce signal crosstalk.

4. The insect counting and detection method based on capacitance according to claim 1, characterized in that: The specific method in step S2 is as follows: First, a high-frequency excitation signal based on the capacitance-based insect counting detection method (100kHz–10MHz) is applied to the capacitance sensing channel. Then, the capacitance change signal is processed by the signal conditioning module. It is converted into a stable electrical signal and dynamic baseline compensation is performed to counteract baseline drift caused by changes in ambient temperature and humidity. Then, the output signal of the receiving tube of the photoelectric sensing channel is monitored in real time and converted into a binary occlusion state signal S based on capacitance-based insect counting detection method. After that, the glitch noise of the capacitance-based insect counting detection method with a width of less than 10ms is filtered out by digital filtering to avoid instantaneous interference.

5. The insect counting and detection method based on capacitance according to claim 1, characterized in that: The specific method of step S3 is as follows: First, the preprocessed capacitance change signal is processed... Set a trigger threshold, when When the threshold is exceeded, it is determined to be a capacitance event, and its start time is recorded. Peak time and end time The duration of the event is calculated using the following formula: A capacitance-based insect counting detection method is then used to detect transitions in the occlusion state signal S. When a falling edge from high to low is detected, it is determined as the start of a photoelectric event, and the time is recorded. When a rising edge from low to high is detected, the end time is recorded. Calculate the duration of the event using the following formula: .

6. The insect counting and detection method based on capacitance according to claim 1, characterized in that: The specific method of step S4 is as follows: First, set an effective time window. A capacitance-based insect counting and detection method, in which The capacitance-based insect counting detection method uses the minimum effective insect velocity, which is taken as 10–50 mm / s, to calculate the time difference between the onset of the capacitance event and the photoelectric event. The calculation formula is as follows: Then, valid events are determined, and the logic for determining valid events is: only if a valid event is found that the event is valid (based on the capacitance-based insect counting detection method). < When the two events are triggered in the order of capacitance channel - photoelectric channel, the insect counting detection method based on capacitance is determined to be a valid insect passage event. If only one channel detects an event while the other channel does not respond, it is considered an interference event and is not counted. Simultaneously, if the capacitance signal exhibits multi-peak characteristics or if abnormal level transitions occur during photoelectric signal obstruction, it is marked as a suspected abnormal event, triggering a secondary verification, combined with a consistency check of the two channel signals. Finally, direction determination is performed: if... < and < This indicates that the insect first passes through the capacitive sensing channel and then through the photoelectric sensing channel, which is determined to be forward movement; if < and < If the passage is determined to be in the opposite direction, the forward counter and the reverse counter are used to accumulate the count.

7. The insect counting and detection method based on capacitance according to claim 1, characterized in that: The specific method of step S5 is as follows: First, based on the typical length of the target pest... With average speed Calculate the normal passage time threshold for a single insect. If the duration of the capacitor event is valid, Exceed The passage was determined to be due to multiple insects adhering together; a segmentation algorithm that integrates the durations of the two channels was used to calculate the number of adhering insects. This method achieves accurate counting of adherent insects; subsequently, it uses a capacitance-based insect counting detection method based on the distance between two channels and the time difference between two event feature points. Calculate the passage speed of the insect. Based on the peak amplitude of the capacitance signal and the preset size level threshold, the insects are divided into three levels: small, medium and large, to achieve size assessment.

8. The insect counting and detection method based on capacitance according to claim 1, characterized in that: In step S6, after each effective detection is completed, the counting result, movement direction, passage speed, body size level and adhesion mark information are output. For interference events, the interference type is recorded and entered into the log to provide a reference for equipment maintenance.

9. The insect counting and detection method based on capacitance according to claim 8, characterized in that: The interference types include capacitor single-channel interference, photoelectric single-channel interference, and abnormal signal interference.

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