Control method of high altitude trapping lamp based on pest trapping

Abstract

The present invention relates to the field of pest control technology, and in particular to a high-altitude trapping lamp control method based on pest trapping, comprising the following steps: S1: real-time acquisition of multi-dimensional environmental parameters and generation of height distribution data; S2: adjustment of the height of the trapping lamp; S3: dynamic adjustment of the spectral output of the trapping lamp; S4: using a feedback adjustment mechanism to adjust the height, spectrum and brightness of the trapping lamp according to actual capture data; S5: activating a light source or vibration signal of a predetermined wavelength to expel non-target insects; S6: adjusting the working time and spectral output of the trapping lamp. The present invention, by adjusting the height, spectrum and brightness in real time, specifically attracts target pests and reduces the misattraction of non-target insects, and at the same time applies an energy consumption optimization algorithm to reduce energy consumption, thereby significantly improving trapping efficiency and environmental sustainability.

Description

Technical Field

[0001] The invention relates to the technical field of pest control, and in particular to a method for controlling a high-altitude trapping lamp based on pest trapping. Background Art

[0002] In the field of pest management and control, high-altitude trapping lights are widely used in agriculture and forestry as an effective physical control method to reduce damage to crops and vegetation by pests. Traditional high-altitude trapping light systems mainly rely on fixed light sources and height settings to attract specific types of pests. However, due to the variability of environmental conditions and the complexity of pest behavior, these systems often cannot adapt to environmental changes, resulting in low trapping efficiency. In addition, traditional systems often lack flexibility in operation and cannot be adjusted according to real-time monitoring data, which is particularly insufficient in dynamically changing natural environments.

[0003] At present, the main problems faced by pest trapping lamp systems include the fixed height of the trapping lamps and the uniformity of the spectral output, which limits their adaptability to different environments and to a variety of pest species. In addition, the problem of misattraction of non-target insects often leads to interference with the ecological balance and waste of energy.

[0004] Therefore, there is an urgent need to develop a control method for smart trapping lights that can adjust the spectrum and height in real time while optimizing energy consumption to improve trapping efficiency and reduce the impact on non-target species. Summary of the invention

[0005] Based on the above objectives, the present invention provides a high-altitude trapping lamp control method based on pest trapping.

[0006] The high-altitude trapping lamp control method based on pest trapping includes the following steps:

[0007] S1: Sensors are deployed at different heights to obtain multi-dimensional environmental parameters including temperature, humidity and light intensity in real time, and environmental analysis algorithms are used to analyze the activity levels of pests to generate height distribution data;

[0008] S2: Based on the height distribution data generated in S1, adjust the height of the trapping light so that the light is focused on the height area where pest activities are most intensive;

[0009] S3: Based on the light intensity data obtained in S1 and the sensitivity of pests to different spectra, a preset spectrum control algorithm is applied to dynamically adjust the spectral output of the trapping light to match the spectral preference of the target pests and reduce the false attraction of non-target insects;

[0010] S4: Optical monitoring equipment is installed at multiple heights to monitor the capture of pests in real time during the trapping process, and a feedback adjustment mechanism is used to adjust the height, spectrum and brightness of the trapping light according to the actual capture data;

[0011] S5: During the monitoring process of S4, when non-target insects are detected approaching the trapping light, a light source or vibration signal of a predetermined wavelength will be activated to expel the non-target insects;

[0012] S6: Combined with the real-time monitoring data obtained in S4, the energy consumption optimization algorithm is applied to automatically adjust the working time and spectral output of the trapping lamp while ensuring the trapping effect, and switch to low power consumption mode to save energy during the off-peak period of pest activity.

[0013] Optionally, the S1 specifically includes:

[0014] S11: Install temperature sensors, humidity sensors and light intensity sensors at different heights to obtain temperature, humidity and light intensity parameters in real time. The heights are determined by analyzing the flight altitude range of target pests and the height of crop vegetation. The specific altitudes include 1 meter, 3 meters, 5 meters, 7 meters and 10 meters to cover all levels of pest activities. All sensors transmit the collected data to the central control unit in real time via a wireless network. The collection frequency of each sensor is once per minute.

[0015] S12: After receiving the data transmitted by each height sensor, the central control unit performs preliminary processing of data filtering and outlier exclusion on the temperature, humidity and light intensity data, and stores the processed data in the form of time series in the database of the central control unit;

[0016] S13: The central control unit analyzes the pest activity level by combining historical environmental data and current environmental data through a built-in environmental analysis algorithm. The environmental analysis algorithm calculates the pest activity intensity value at each height level based on the known reaction rules of pests to temperature, humidity and light intensity;

[0017] S14: Generate a height distribution data graph based on the pest activity intensity value obtained by the analysis in S13, which is used to mark the pest activity intensive areas at each height level. The height distribution data graph is represented by a two-dimensional coordinate, with the height as the vertical coordinate and the pest activity intensity value as the horizontal coordinate.

[0018] Optionally, the S13 specifically includes:

[0019] S131: Processing the acquired historical environmental data and current environmental data through a standardized algorithm;

[0020] S132: Based on the known responses of different pests to temperature, humidity and light intensity, a preset response function is applied to calculate the pest activity intensity value at each height level. Suppose the pest response function to temperature is , the response function to humidity is , the response function to light intensity is , then at height Pest activity intensity value The calculation formula is:

[0021] ,in, is the weighted coefficient of the effect of temperature on the intensity of pest activity, is the weighted coefficient of the effect of humidity on the intensity of pest activity, is the weighted coefficient of the effect of light intensity on the intensity of pest activity;

[0022] The expression of the temperature response function is: ,in, is the standardized temperature data; is the peak coefficient of temperature response intensity; The ideal temperature for pests that are most sensitive to temperature; is the width parameter of the temperature response curve; exp is the exponential function;

[0023] The response function of humidity is expressed as: ,in, is the standardized humidity data; is the peak coefficient of humidity response intensity; The ideal humidity for pests that are most sensitive to humidity; is the width parameter of the humidity response curve;

[0024] The response function of light intensity is expressed as: ,in, is the standardized light intensity data; is the peak factor of the light intensity response intensity; The ideal light intensity for pests to be most sensitive to light intensity; is the width parameter of the light intensity response curve;

[0025] S133: For data collected by multiple sensors at the same height level, a weighted average algorithm is used to calculate the height The activity intensity values ​​at are weighted averaged, and the number of sensors is , No. Sensors at height The pest activity intensity calculated at , the weight coefficient is , then the calculation formula of the weighted average pest activity intensity value is:

[0026] ,in, For height The final weighted average pest activity intensity value at ;

[0027] S134: The pest activity intensity values ​​at each height level calculated in S133 are Summarize and generate pest activity intensity curves at different height levels.

[0028] Optionally, the S2 specifically includes:

[0029] S21: By analyzing the height distribution data generated in S1, identify the target height area with the highest pest activity intensity, specifically select the pest activity intensity value in the height distribution data graph Reaching the preset threshold The height interval above is recorded as to range, where and They represent the lower and upper altitudes of the areas with the most intensive pest activities;

[0030] S22: According to the upper and lower limit heights of the target height area and , use the optimal height calculation formula to determine the adjustment height of the trapping light ;

[0031] S23: The optimal height calculated in S22 As the working height of the trap light, the trap light is adjusted to the height by controlling the drive system. , so that the light is focused on the height area where the target pest activity is most intensive.

[0032] Optionally, the S3 specifically includes:

[0033] S31: Light intensity data obtained from S1 After preprocessing, compared with historical lighting data Compare to evaluate the current ambient lighting conditions and calculate the deviation between the current light intensity and the historical light average ;when The absolute value of exceeds the preset trigger threshold When , then the spectrum control algorithm is started to dynamically adjust the spectrum output of the trapping lamp;

[0034] S32: Spectral preference analysis of target pests is performed, and according to the known sensitivity of target pests to spectra of different wavelengths, a spectral response model of target pests is established to define the response intensity of target pests to light of different wavelengths, and the response intensity data of light of different wavelengths are integrated into a spectral preference curve of target pests;

[0035] S33: In parallel with the spectral preference analysis of target pests, a spectral repulsion model for non-target insects is established to identify and define the repulsion of non-target insects to spectra of different wavelengths and generate a spectral sensitivity curve for non-target insects;

[0036] S34: Based on the spectral preference curve of the target pest in S32 and the spectral sensitivity curve of the non-target insect in S33, combined with the current ambient light intensity, a dynamic spectral control scheme is generated to determine the spectral range and intensity that the trapping lamp should output under the current conditions;

[0037] S35: According to the spectrum control scheme generated in S34, the spectrum output is dynamically adjusted by adjusting the light source combination and spectrum distribution of the trapping lamp.

[0038] Optionally, the S32 specifically includes:

[0039] S321: Based on experimental data and literature, obtain the response data of target pests under different wavelength spectra. Suppose the wavelength of the spectrum is , at each wavelength Next, record the activity intensity data of target pests ;

[0040] S322: Establish a spectral response model of target pests by fitting the standardized spectral response data. Specifically, set the spectral wavelength response of target pests The response function of the response intensity is , the response function is fitted with a Gaussian function, and the model of the response intensity is expressed as: ,in, is the peak factor of the response intensity, The wavelength that the target pests are most sensitive to. is the standard deviation of the response function, is an exponential function;

[0041] S323: Using the spectral response model established in S322, calculate the theoretical response intensity of the target pest at each wavelength , the formula is: ,in, Wavelength for target pests Theoretical response intensity value of

[0042] S324: All wavelengths Theoretical response intensity value under Integrate and plot the spectral preference curve of the target pest, with the vertical axis being the response intensity value , the horizontal axis is the wavelength .

[0043] Optionally, the S34 specifically includes:

[0044] S341: According to the spectral preference curve of the target pest generated in S32, determine the spectral range to which the target pest is most sensitive in the current environment ;

[0045] S342: According to the spectral sensitivity curve of the non-target insects generated in S33, the spectral range preliminarily determined in S341 is corrected;

[0046] S343: Combine the current ambient light intensity data and the corrected spectral range to calculate the trapping light at each wavelength The spectral output intensity at ;

[0047] S344: Each wavelength calculated in S343 The spectral intensity Integrate and generate spectral control solutions.

[0048] Optionally, the S4 specifically includes:

[0049] S41: Install optical monitoring equipment at different heights to collect image data to obtain the number and type of pests entering the range of the trapping light;

[0050] S42: The central control unit uses a built-in image recognition algorithm to analyze the image data collected by the optical monitoring device, extract the number and type of pests actually captured, and compare it with the preset target capture number and type to calculate the capture deviation value;

[0051] S43: Based on the deviation value of the actual captured data, the height, spectrum and brightness of the trapping light are adjusted in real time using a feedback adjustment mechanism;

[0052] S44: Increase the brightness of the trap light when the actual number of catches is lower than expected and the target is still not reached after spectrum adjustment. , enhancing the trapping effect by increasing the brightness.

[0053] Optionally, the S5 specifically includes:

[0054] S51: The optical monitoring device installed in S4 captures the insect activities around the trapping light in real time. When the system detects that the type and number of non-target insects exceed the set threshold, the expulsion mechanism is immediately triggered;

[0055] S52: based on the spectral repulsion curve of non-target insects in S33, selecting a light source or vibration signal of a predetermined wavelength to expel the non-target insects;

[0056] S53: After the expulsion signal is activated, the response of the non-target insects continues to be monitored by the optical monitoring device, and if the number of the non-target insects does not significantly decrease within the set time, the intensity of the expulsion signal is increased;

[0057] S54: When the number of non-target insects detected drops below the threshold, or the expulsion effect reaches the expected level within the set time period, the activation of the expulsion signal will be automatically stopped and the normal trapping light spectrum and vibration settings will be restored.

[0058] Optionally, the S6 specifically includes:

[0059] S61: Combined with the real-time monitoring data obtained in S4, the central control unit will With the preset capture target Compare and calculate the achievement rate of the current trapping effect ;when Meet or exceed the set achievement rate threshold When , it is judged that the current trapping effect has met expectations, indicating that the energy consumption optimization mode can be started;

[0060] S62: After starting the energy consumption optimization mode, adjust the working time of the trapping light. Set the current working time of the trapping light to , combined with real-time monitoring data and achievement rate , recalculate the new working hours ;

[0061] S63: Adjust the spectral output of the trap light based on the current ambient light intensity data and achievement rate , adjust each wavelength The spectral output intensity at ;

[0062] S64: After the adjustment is implemented, the system continues to monitor the trapping effect in real time through the optical monitoring equipment in S4. If the trapping effect is significantly reduced under the new working time and spectral output conditions, the system will automatically revert to the previous working mode.

[0063] Beneficial effects of the present invention:

[0064] The present invention significantly improves the efficiency and accuracy of pest trapping by integrating advanced optical monitoring technology and dynamic adjustment mechanism. The system can dynamically adjust the height, spectrum and brightness according to real-time environmental data and pest behavior, thereby attracting target pests in a targeted manner while reducing the accidental attraction of non-target insects. This refined management not only improves the targeting and effectiveness of trapping, but also avoids unnecessary interference with the ecological environment.

[0065] The present invention adopts an energy consumption optimization algorithm to ensure that energy consumption is minimized while maintaining the trapping effect. This energy consumption management strategy not only reduces operating costs, but also helps to reduce environmental impact, meets the needs of sustainable development, and through the application of intelligent control technology, provides a more efficient and environmentally friendly solution for pest management, which significantly improves the application scope and effect of existing pest trapping technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 A schematic diagram of a high-altitude trapping light control method according to an embodiment of the present invention;

[0068] Figure 2 The figure is a schematic diagram of the process of dynamically adjusting the spectral output of a trapping lamp according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0070] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0071] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0072] like Figure 1-Figure 2 As shown, the high-altitude trapping lamp control method based on pest trapping includes the following steps:

[0073] S1: Sensors are deployed at different heights to obtain multi-dimensional environmental parameters including temperature, humidity and light intensity in real time, and environmental analysis algorithms are used to analyze the activity levels of pests to generate height distribution data;

[0074] S2: Based on the height distribution data generated in S1, the height of the trapping light is adjusted so that the light is focused on the height area where the pests are most active, thereby improving the trapping efficiency;

[0075] S3: Based on the light intensity data obtained in S1 and the sensitivity of pests to different spectra, a preset spectrum control algorithm is applied to dynamically adjust the spectral output of the trapping lamp to match the spectral preference of the target pests and reduce the false attraction of non-target insects;

[0076] S4: Optical monitoring equipment is installed at multiple heights to monitor the capture of pests in real time during the trapping process, and a feedback adjustment mechanism is used to adjust the height, spectrum and brightness of the trapping light according to the actual capture data to continuously optimize the trapping effect;

[0077] S5: During the monitoring process of S4, when non-target insects are detected approaching the trapping light, a light source or vibration signal of a predetermined wavelength will be activated to expel the non-target insects, ensuring that only the target pests are effectively trapped;

[0078] S6: Combined with the real-time monitoring data obtained in S4, the energy consumption optimization algorithm is applied to automatically adjust the working time and spectral output of the trapping lamp while ensuring the trapping effect, reduce unnecessary energy consumption, and switch to low power consumption mode to save energy during the off-peak period of pest activity.

[0079] S1 specifically includes:

[0080] S11: Temperature sensors, humidity sensors and light intensity sensors are installed at different heights to obtain temperature, humidity and light intensity parameters in real time. The heights are determined by analyzing the flight altitude range of target pests and the height of crop vegetation. They are usually distributed in the range of 1 to 10 meters above the ground. The specific heights include 1, 3, 5, 7 and 10 meters to cover all levels of pest activities. All sensors transmit the collected data to the central control unit in real time via wireless networks. The collection frequency of each sensor is once per minute to ensure the timeliness and accuracy of environmental parameters.

[0081] S12: After receiving the data transmitted by each height sensor, the central control unit performs preliminary processing of data filtering and outlier exclusion on the temperature, humidity and light intensity data, and stores the processed data in the form of time series in the database of the central control unit;

[0082] S13: The central control unit analyzes the pest activity level through the built-in environmental analysis algorithm, combined with historical environmental data and current environmental data. The environmental analysis algorithm calculates the pest activity intensity value at each height level based on the known reaction rules of pests to temperature, humidity and light intensity;

[0083] S14: Based on the pest activity intensity values ​​analyzed in S13, a height distribution data graph is generated to mark the pest activity intensive areas at each height level. The height distribution data graph is represented by two-dimensional coordinates, with the height as the vertical coordinate and the pest activity intensity value as the horizontal coordinate, so as to intuitively present the pest activity conditions at different height levels. The generated height distribution data graph is updated in real time and transmitted to the trapping light control unit for use in subsequent steps. The above steps deploy sensors at different scientifically determined height positions for precise data collection, analyze the pest activity levels in combination with environmental analysis algorithms, and generate height distribution data, which can effectively identify the intensive areas of pest activity, provide a reliable basis for the precise control of the trapping light, significantly improve the trapping efficiency, and reduce resource waste.

[0084] The calculation of the pest activity intensity values ​​at each height level in S13 specifically includes:

[0085] S131: The acquired historical environmental data and current environmental data are processed by a standardized algorithm, specifically at a high The temperature data at , humidity data is , the light intensity data is , all data are standardized, and the standardized temperature data is , humidity data is , the light intensity data is , its standardized formula is: ; ; ,in, is the historical temperature average, is the historical temperature standard deviation, is the historical humidity average. is the historical humidity standard deviation, is the historical light intensity mean, is the standard deviation of historical light intensity;

[0086] S132: Based on the known responses of different pests to temperature, humidity and light intensity, a preset response function is applied to calculate the pest activity intensity value at each height level. Suppose the pest response function to temperature is , the response function to humidity is , the response function to light intensity is , then at height Pest activity intensity value The calculation formula is:

[0087] ,in, is the weighted coefficient of the effect of temperature on the intensity of pest activity, is the weighted coefficient of the effect of humidity on the intensity of pest activity, is the weighted coefficient of the effect of light intensity on the intensity of pest activity;

[0088] The expression of the temperature response function is: ,in, is the standardized temperature data; is the peak coefficient of temperature response intensity; The ideal temperature for pests that are most sensitive to temperature; is the width parameter of the temperature response curve; exp is the exponential function;

[0089] The response function of humidity is expressed as: ,in, is the standardized humidity data; is the peak coefficient of humidity response intensity; The ideal humidity for pests that are most sensitive to humidity; is the width parameter of the humidity response curve;

[0090] The response function of light intensity is expressed as: ,in, is the standardized light intensity data; is the peak factor of the light intensity response intensity; The ideal light intensity for pests to be most sensitive to light intensity; is the width parameter of the light intensity response curve;

[0091] S133: For data collected by multiple sensors at the same height level, a weighted average algorithm is used to calculate the height The activity intensity values ​​at are weighted averaged, and the number of sensors is , No. Sensors at height The pest activity intensity calculated at , the weight coefficient is , then the calculation formula of the weighted average pest activity intensity value is:

[0092] ,in, For height The final weighted average pest activity intensity value at ;

[0093] S134: The pest activity intensity values ​​at each height level calculated in S133 are Summarize and generate a pest activity intensity curve at different height levels, and generate a height distribution data graph based on this curve as a reference for subsequent steps; the above steps accurately calculate the pest activity intensity value at each height level through standardized processing of historical environmental data and current environmental data, combined with the known reaction rules of pests to temperature, humidity and light intensity, thereby generating a scientific and accurate height distribution data graph, providing a reliable basis for the precise regulation of the trapping lamp, greatly improving the intelligence and trapping efficiency of the system.

[0094] Adjusting the height of the trapping light in S2 specifically includes:

[0095] S21: By analyzing the height distribution data generated in S1, identify the target height area with the highest pest activity intensity, specifically select the pest activity intensity value in the height distribution data graph Reaching the preset threshold The height interval above is recorded as to range, where and They represent the lower and upper altitudes of the areas with the most intensive pest activities;

[0096] S22: According to the upper and lower limit heights of the target height area and , use the optimal height calculation formula to determine the adjustment height of the trapping light , optimal height The calculation formula is:

[0097] ,in, Adjust the height for optimum so that the trap light can provide maximum coverage of the area with the most intense pest activity;

[0098] S23: The optimal height calculated in S22 As the working height of the trap light, the trap light is adjusted to the height by controlling the drive system. , let the light focus on the height area where the target pests are most active to improve the trapping efficiency; the above steps determine and adjust the working height of the trapping light through precise analysis of the height distribution data graph and combined with the optimal height calculation formula, so that the light can accurately cover the height area where the pests are most active, thereby significantly improving the effectiveness of pest trapping and enhancing the overall intelligent control level of the system.

[0099] S3 specifically includes:

[0100] S31: Light intensity data obtained from S1 After preprocessing, compared with historical lighting data Compare to evaluate the current ambient lighting conditions and calculate the deviation between the current light intensity and the historical light average , the formula is: ,in, is the relative deviation between the current light intensity and the historical average light intensity; The absolute value of exceeds the preset trigger threshold When , then the spectrum control algorithm is started to dynamically adjust the spectrum output of the trapping lamp;

[0101] S32: Conduct spectral preference analysis of target pests. According to the known sensitivity of target pests to spectra of different wavelengths, establish a spectral response model of target pests. This model is based on experimental data and literature, and is used to define the response intensity of target pests to light of different wavelengths. The response intensity data of light of different wavelengths are integrated into the spectral preference curve of target pests, which indicates the trapping effectiveness of target pests under different spectral conditions.

[0102] S33: In parallel with the spectral preference analysis of target pests, a spectral repulsion model for non-target insects is established. This model is used to identify and define the repulsion of non-target insects to spectra of different wavelengths, also based on experimental and literature data, and to generate spectral sensitivity curves for non-target insects to ensure that when adjusting the spectral output, the attraction of non-target insects is minimized;

[0103] S34: Based on the spectral preference curve of target pests in S32 and the spectral sensitivity curve of non-target insects in S33, combined with the current ambient light intensity, a dynamic spectral control scheme is generated to determine the spectral range and intensity that the trapping lamp should output under the current conditions, so as to maximize the attraction effect of target pests and reduce the misattraction of non-target insects;

[0104] S35: According to the spectrum control scheme generated in S34, the spectrum output is dynamically adjusted by adjusting the light source combination and spectrum distribution of the trapping lamp. The control scheme will respond to the changes in ambient light and the activities of target pests and non-target insects in real time, ensuring that the trapping lamp can output the most suitable spectrum combination under different conditions to improve the trapping effect. The above steps generate and adjust the spectrum output scheme in real time through the analysis and preprocessing of light intensity data, combined with the spectral sensitivity of target pests and non-target insects, so that the trapping lamp can accurately attract target pests under different environmental conditions and reduce the misattraction of non-target insects, thereby significantly improving the effectiveness and accuracy of trapping.

[0105] S32 specifically includes:

[0106] S321: Based on experimental data and literature, obtain the response data of target pests under different wavelength spectra. Suppose the wavelength of the spectrum is (in, Representative wavelengths), at each wavelength Next, record the activity intensity data of target pests ; Preprocess these data, remove outliers, and standardize the activity intensity data. The standardized data is recorded as , the standardized formula is: ,in, and are the minimum and maximum response intensity values ​​of the target pests at all wavelengths, respectively;

[0107] S322: Establish a spectral response model of target pests by fitting the standardized spectral response data. Specifically, set the spectral wavelength response of target pests The response function of the response intensity is , the response function is fitted with a Gaussian function, and the model of the response intensity is expressed as: ,in, is the peak factor of the response intensity, The wavelength that the target pests are most sensitive to. is the standard deviation of the response function, which is used to indicate the width of the response. is an exponential function, which is defined as a natural number (approximately equal to 2.718) as the base exponential function;

[0108] S323: Using the spectral response model established in S322, calculate the theoretical response intensity of the target pest at each wavelength , the formula is: ,in, Wavelength for target pests Theoretical response intensity value;

[0109] S324: All wavelengths Theoretical response intensity value under Integrate and plot the spectral preference curve of the target pest, with the vertical axis being the response intensity value , the horizontal axis is the wavelength ; This curve is used to intuitively indicate the preference of target pests under different wavelength spectra and provide a basis for subsequent spectrum regulation;

[0110] The above steps accurately define the response intensity of target pests to spectra of different wavelengths through experimental data collection, establishment and standardization of spectral response models, and generate scientific spectral preference curves, which provide an accurate basis for the spectral regulation of trapping lamps, can more effectively attract target pests and improve trapping effects.

[0111] The steps of establishing the spectral repulsion model for non-target insects in S33 are the same as the above steps.

[0112] S34 specifically includes:

[0113] S341: According to the spectral preference curve of the target pest generated in S32, determine the spectral range to which the target pest is most sensitive in the current environment ,in, and Spectral preference curves The upper target pest response intensity value is greater than the set threshold The minimum and maximum wavelength values ​​are expressed as follows:

[0114] ; ;

[0115] S342: According to the spectral sensitivity curve of the non-target insects generated in S33, the spectral range initially determined in S341 is corrected; the specific method is to identify the sensitive wavelengths of the non-target insects within the spectral range. , the response intensity corresponding to these wavelengths is greater than the set threshold of the non-target insect repellent curve , these sensitive wavelengths are eliminated to reduce the attraction to non-target insects. The formula is expressed as: ,in, and is the corrected spectral range;

[0116] S343: Combine the current ambient light intensity data and the corrected spectral range to calculate the trapping light at each wavelength The spectral output intensity at , where the spectral intensity is proportional to the response intensity of the target pests and inversely proportional to the ambient light intensity. The formula is: ,in, For the trapping light at wavelength The spectral output intensity at is the proportional coefficient used to adjust the overall spectral intensity output level, Wavelength for target pests The response strength, is the light intensity in the current environment;

[0117] S344: Each wavelength calculated in S343 The spectral intensity The spectral control scheme is integrated and generated to determine the specific spectral output of the trapping lamp under current conditions, that is, the output intensity of each wavelength spectrum within the corrected spectral range, so as to maximize the attraction effect of the target pests while reducing the misattraction of non-target insects.

[0118] S4 specifically includes:

[0119] S41: Optical monitoring equipment is installed at different heights to collect image data to obtain the number and type of pests entering the range of the trapping light; the collected image data is transmitted to the central control unit in real time, and the pests are automatically classified and counted through image recognition algorithms;

[0120] S42: The central control unit uses the built-in image recognition algorithm to analyze the image data collected by the optical monitoring equipment to extract the number and type of pests actually captured. The number of captures at , type is ; and compare with the preset target capture quantity and type to calculate the capture deviation value. The formula is:

[0121] ; ,in, is the deviation between the actual capture quantity and the target quantity, is the deviation between the actual captured species and the target species;

[0122] S43: Deviation value based on actual captured data and , a feedback adjustment mechanism is applied to adjust the height, spectrum and brightness of the trapping light in real time;

[0123] The principle of the feedback adjustment mechanism is:

[0124] when When it is positive, it means that the actual number of captures is lower than expected. In this case, the height of the trapping light can be adjusted. and spectral output To improve capture efficiency;

[0125] when When it is a negative value, it means that the captured non-target species exceed expectations, so by reducing the corresponding spectral wavelength Output intensity to repel non-target pests;

[0126] The specific adjustment formula is as follows:

[0127] Height adjustment formula: ,in, The height of the trapping light after adjustment. is the current height, is the height adjustment factor;

[0128] Spectrum adjustment formula: ,in, is the adjusted spectral intensity, is the current spectrum intensity, is the spectrum adjustment coefficient;

[0129] S44: Increase the brightness of the trap light when the actual number of captures is lower than expected and the target is still not reached after spectrum adjustment. , the trapping effect is enhanced by increasing the brightness, the formula is: ,in, is the adjusted brightness, is the current brightness, is the brightness adjustment coefficient; the above steps install optical monitoring equipment at different heights to monitor and analyze pest capture data in real time, and combine the feedback adjustment mechanism to dynamically adjust the height, spectrum and brightness of the trapping lamp according to the actual capture data, so that the working state of the trapping lamp is optimized in real time, ensuring efficient trapping of pests.

[0130] S5 specifically includes:

[0131] S51: The optical monitoring device installed in S4 captures the insect activities around the trapping light in real time. When the system detects that the type and number of non-target insects exceed the set threshold, the expulsion mechanism is immediately triggered; The number of non-target insects detected at ,like When (where is the preset number threshold), the expulsion procedure is initiated;

[0132] S52: Based on the spectral repulsion curve of non-target insects in S33, a light source or vibration signal of a predetermined wavelength is selected for expulsion; specifically, the wavelength of the light source expulsion signal should fall within the wavelength range to which non-target insects are most sensitive, while the frequency of the vibration repellent signal It should be within the range that non-target insects are most sensitive to vibration; the activation rule of the expulsion signal is: if the spectral expulsion signal is selected, the corresponding wavelength is activated The light source has an output intensity of , the formula is: ,in, is the intensity coefficient of the expelling light source, For non-target insects If the vibration expulsion signal is selected, the activation frequency is The source of vibration;

[0133] S53: After the expulsion signal is activated, the reaction of non-target insects continues to be monitored by the optical monitoring device. If the number of non-target insects does not decrease significantly within the set time, the intensity of the expulsion signal is increased; the specific adjustment formula is: or ,in, is the increase in light intensity, is the amount of vibration frequency adjustment until the number of non-target insects is significantly reduced or reaches the set target value;

[0134] S54: When the number of non-target insects is monitored to drop below the threshold, or the expulsion effect reaches the expected level within the set time period, the activation of the expulsion signal is automatically stopped, and the normal spectrum and vibration settings of the trapping lamp are restored to maintain energy optimization; the above steps identify the types and numbers of non-target insects in real time, and activate the light source or vibration signal of the predetermined wavelength for precise expulsion. The system can effectively reduce the misattraction of non-target insects, ensure that the trapping lamp focuses on capturing target pests, improve the accuracy of the trapping effect, and restore to normal in time after expulsion, thereby achieving efficient energy management.

[0135] S6 specifically includes:

[0136] S61: Combined with the real-time monitoring data obtained in S4, the central control unit will With the preset capture target Compare and calculate the achievement rate of the current trapping effect , the formula is: ,in, is the achievement rate; Meet or exceed the set achievement rate threshold When , it is judged that the current trapping effect has met expectations, indicating that the energy consumption optimization mode can be started;

[0137] S62: After starting the energy consumption optimization mode, adjust the working time of the trapping light. Set the current working time of the trapping light to , combined with real-time monitoring data and achievement rate , recalculate the new working hours , the formula is: ,in, is the target achievement rate. If the actual number of captures greatly exceeds the target number (i.e. Much greater than ), then appropriately reduce the working hours to save energy;

[0138] S63: Adjust the spectral output of the trap light based on the current ambient light intensity data and achievement rate , adjust each wavelength The spectral output intensity at , the optimization calculation formula of spectral output intensity is: ,in, is the adjusted spectral output intensity, To achieve the best light intensity, ensuring the necessary trapping effect is maintained while optimizing energy consumption;

[0139] S64: After the adjustment is implemented, the system continues to monitor the trapping effect in real time through the optical monitoring equipment in S4. If the trapping effect decreases significantly under the new working time and spectral output conditions, , the system will automatically revert to the previous working mode and re-evaluate the optimization plan. If the energy consumption optimization effect is significant, the current parameters will be recorded for subsequent operations. The above steps combine real-time monitoring data and apply energy consumption optimization algorithms to dynamically adjust the working time and spectral output of the trapping lamp. The system can minimize energy consumption and improve energy utilization efficiency while ensuring the trapping effect, thereby realizing the intelligent and energy-saving optimization of the trapping process, effectively extending the service life of the equipment and reducing operating costs.

[0140] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0141] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A high-altitude trapping lamp control method based on pest trapping, characterized in that: The following steps are involved: S1: Sensors are deployed at different heights to obtain multi-dimensional environmental parameters including temperature, humidity and light intensity in real time, and environmental analysis algorithms are used to analyze the activity levels of pests to generate height distribution data; S2: Based on the height distribution data generated in S1, adjust the height of the trapping light so that the light is focused on the height area where pest activities are most intensive; S3: Based on the light intensity data obtained in S1 and the sensitivity of pests to different spectra, a preset spectrum control algorithm is applied to dynamically adjust the spectral output of the trapping light to match the spectral preference of the target pests and reduce the misattraction of non-target insects, including: S31: Light intensity data obtained from S1 After preprocessing, compared with historical lighting data Compare to evaluate the current ambient lighting conditions and calculate the deviation between the current light intensity and the historical light average ;when The absolute value of exceeds the preset trigger threshold When , then the spectrum control algorithm is started to dynamically adjust the spectrum output of the trapping lamp; S32: Spectral preference analysis of target pests is performed, and according to the known sensitivity of target pests to spectra of different wavelengths, a spectral response model of target pests is established to define the response intensity of target pests to light of different wavelengths, and the response intensity data of light of different wavelengths are integrated into a spectral preference curve of target pests; S33: In parallel with the spectral preference analysis of target pests, a spectral repulsion model for non-target insects is established to identify and define the repulsion of non-target insects to spectra of different wavelengths and generate a spectral sensitivity curve for non-target insects; S34: Based on the spectral preference curve of the target pest in S32 and the spectral sensitivity curve of the non-target insect in S33, combined with the current ambient light intensity, a dynamic spectral control scheme is generated to determine the spectral range and intensity that the trapping lamp should output under the current conditions; S35: According to the spectrum control scheme generated in S34, the spectrum output is dynamically adjusted by adjusting the light source combination and spectrum distribution of the trapping lamp; The S32 specifically includes: S321: Based on experimental data and literature, obtain the response data of target pests under different wavelength spectra. Suppose the wavelength of the spectrum is , at each wavelength Record the activity intensity data of target pests ; S322: Establish a spectral response model of target pests by fitting the standardized spectral response data. Specifically, set the spectral wavelength response of target pests The response function of the response intensity is , the response function is fitted with a Gaussian function, and the model of the response intensity is expressed as: ,in, is the peak factor of the response intensity, The wavelength that the target pests are most sensitive to. is the standard deviation of the response function, is an exponential function; S323: Using the spectral response model established in S322, calculate the theoretical response intensity of the target pest at each wavelength , the formula is: ,in, Wavelength for target pests Theoretical response intensity value; S324: All wavelengths Theoretical response intensity value under Integrate and plot the spectral preference curve of the target pest, with the vertical axis being the response intensity value , the horizontal axis is the wavelength ; S4: Optical monitoring equipment is installed at multiple heights to monitor the capture of pests in real time during the trapping process, and a feedback adjustment mechanism is used to adjust the height, spectrum and brightness of the trapping light according to the actual capture data; S5: During the monitoring process of S4, when non-target insects are detected approaching the trapping light, a light source or vibration signal of a predetermined wavelength will be activated to expel the non-target insects; S6: Combined with the real-time monitoring data obtained in S4, the energy consumption optimization algorithm is applied to automatically adjust the working time and spectral output of the trapping lamp while ensuring the trapping effect, and switch to low power consumption mode to save energy during the off-peak period of pest activity.

2. The high-altitude trapping lamp control method based on pest trapping according to claim 1 is characterized in that: The S1 specifically includes: S11: Install temperature sensors, humidity sensors and light intensity sensors at different heights to obtain temperature, humidity and light intensity parameters in real time. The heights are determined by analyzing the flight altitude range of target pests and the height of crop vegetation. The specific altitudes include 1 meter, 3 meters, 5 meters, 7 meters and 10 meters to cover all levels of pest activities. All sensors transmit the collected data to the central control unit in real time via a wireless network. The collection frequency of each sensor is once per minute. S12: After receiving the data transmitted by each height sensor, the central control unit performs preliminary processing of data filtering and outlier exclusion on the temperature, humidity and light intensity data, and stores the processed data in the form of time series in the database of the central control unit; S13: The central control unit analyzes the pest activity level by combining historical environmental data and current environmental data through a built-in environmental analysis algorithm. The environmental analysis algorithm calculates the pest activity intensity value at each height level based on the known reaction rules of pests to temperature, humidity and light intensity; S14: Generate a height distribution data graph based on the pest activity intensity value obtained by the analysis in S13, which is used to mark the pest activity intensive areas at each height level. The height distribution data graph is represented by a two-dimensional coordinate, with the height as the vertical coordinate and the pest activity intensity value as the horizontal coordinate.

3. The high-altitude trapping lamp control method based on pest trapping according to claim 2 is characterized in that: The S13 specifically includes: S131: Processing the acquired historical environmental data and current environmental data through a standardized algorithm; S132: Based on the known responses of different pests to temperature, humidity and light intensity, a preset response function is applied to calculate the pest activity intensity value at each height level. Suppose the pest response function to temperature is , the response function to humidity is , the response function to light intensity is , then at height Pest activity intensity value The calculation formula is: ,in, is the weighted coefficient of the effect of temperature on the intensity of pest activity, is the weighted coefficient of the effect of humidity on the intensity of pest activity, is the weighted coefficient of the effect of light intensity on the intensity of pest activity; The expression of the temperature response function is: ,in, is the standardized temperature data; is the peak coefficient of temperature response intensity; The ideal temperature for pests that are most sensitive to temperature; is the width parameter of the temperature response curve; exp is the exponential function; The response function of humidity is expressed as: ,in, is the standardized humidity data; is the peak coefficient of humidity response intensity; The ideal humidity for pests that are most sensitive to humidity; is the width parameter of the humidity response curve; The response function of light intensity is expressed as: ,in, is the standardized light intensity data; is the peak factor of the light intensity response intensity; The ideal light intensity for pests to be most sensitive to light intensity; is the width parameter of the light intensity response curve; S133: For data collected by multiple sensors at the same height level, a weighted average algorithm is used to calculate the height The activity intensity values ​​at are weighted averaged, and the number of sensors is , No. Sensors at height The pest activity intensity calculated at , the weight coefficient is , then the calculation formula of the weighted average pest activity intensity value is: ,in, For height The final weighted average pest activity intensity value at ; S134: The pest activity intensity values ​​at each height level calculated in S133 are Summarize and generate pest activity intensity curves at different height levels.

4. The high-altitude trapping lamp control method based on pest trapping according to claim 3 is characterized in that: The S2 specifically includes: S21: By analyzing the height distribution data generated in S1, identify the target height area with the highest pest activity intensity, specifically select the pest activity intensity value in the height distribution data graph Reaching the preset threshold The height interval above is recorded as to range, where and They represent the lower and upper altitudes of the areas with the most intensive pest activities; S22: According to the upper and lower limit heights of the target height area and , use the optimal height calculation formula to determine the adjustment height of the trapping light ; Optimal height The calculation formula is: ,in, Adjust the height for optimum so that the trap light can provide maximum coverage of the area with the most intense pest activity; S23: The optimal height calculated in S22 As the working height of the trap light, the trap light is adjusted to the height by controlling the drive system. , so that the light is focused on the height area where the target pest activity is most intensive.

5. The high-altitude trapping lamp control method based on pest trapping according to claim 1 is characterized in that: The S34 specifically includes: S341: According to the spectral preference curve of the target pest generated in S32, determine the spectral range to which the target pest is most sensitive in the current environment ,in, and Spectral preference curves The upper target pest response intensity value is greater than the set threshold The minimum and maximum wavelength values ​​are expressed as follows: ; ; S342: According to the spectral sensitivity curve of the non-target insects generated in S33, the spectral range initially determined in S341 is corrected; the specific method is to identify the sensitive wavelengths of the non-target insects within the spectral range. , the response intensity corresponding to the wavelength is greater than the set threshold of the non-target insect repellent curve , remove sensitive wavelengths to reduce the attraction to non-target insects, the formula is expressed as: ,in, and is the corrected spectral range; S343: Combine the current ambient light intensity data and the corrected spectral range to calculate the trapping light at each wavelength The spectral output intensity at , where the spectral intensity is proportional to the response intensity of the target pests and inversely proportional to the ambient light intensity. The formula is: ,in, For the trapping light at wavelength The spectral output intensity at is the proportional coefficient used to adjust the overall spectral intensity output level, Wavelength for target pests The response strength, is the light intensity in the current environment; S344: Each wavelength calculated in S343 The spectral intensity The integrated generation of a spectral control scheme is used to determine the specific spectral output of the trapping light under current conditions, i.e., within the corrected spectral range.

6. The high-altitude trapping lamp control method based on pest trapping according to claim 1 is characterized in that: The S4 specifically includes: S41: Install optical monitoring equipment at different heights to collect image data to obtain the number and type of pests entering the range of the trap light; S42: The central control unit uses a built-in image recognition algorithm to analyze the image data collected by the optical monitoring device, extract the number and type of pests actually captured, and compare it with the preset target capture number and type to calculate the capture deviation value; S43: Based on the deviation value of the actual captured data, the height, spectrum and brightness of the trapping light are adjusted in real time using a feedback adjustment mechanism; S44: Increase the brightness of the trap light when the actual number of captures is lower than expected and the target is still not reached after spectrum adjustment. , enhancing the trapping effect by increasing the brightness.

7. The high-altitude trapping lamp control method based on pest trapping according to claim 1 is characterized in that: The S5 specifically includes: S51: The optical monitoring device installed in S4 captures the insect activities around the trapping light in real time. When the system detects that the type and number of non-target insects exceed the set threshold, the expulsion mechanism is immediately triggered; S52: based on the spectral repulsion curve of non-target insects in S33, selecting a light source or vibration signal of a predetermined wavelength to expel the non-target insects; S53: After the expulsion signal is activated, the response of the non-target insects continues to be monitored by the optical monitoring device, and if the number of the non-target insects does not significantly decrease within the set time, the intensity of the expulsion signal is increased; S54: When the number of non-target insects detected drops below the threshold, or the expulsion effect reaches the expected level within the set time period, the activation of the expulsion signal will be automatically stopped and the normal trapping light spectrum and vibration settings will be restored.

8. The high-altitude trapping lamp control method based on pest trapping according to claim 1 is characterized in that: The S6 specifically includes: S61: Combined with the real-time monitoring data obtained in S4, the central control unit will With the preset capture target Compare and calculate the achievement rate of the current trapping effect ;when Meet or exceed the set achievement rate threshold When , it is judged that the current trapping effect has met expectations, indicating that the energy consumption optimization mode can be started; S62: After starting the energy consumption optimization mode, adjust the working time of the trapping light, and set the current working time of the trapping light to , combined with real-time monitoring data and achievement rate , recalculate the new working hours ; S63: Adjust the spectral output of the trap light based on the current ambient light intensity data and achievement rate , adjust each wavelength The spectral output intensity at ; S64: After the adjustment is implemented, the system continues to monitor the trapping effect in real time through the optical monitoring equipment in S4. If the trapping effect is significantly reduced under the new working time and spectral output conditions, the system will automatically revert to the previous working mode.

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