Scientific methods, systems, equipment and media for bird deterrence using shock wave energy fields

Abstract

This invention relates to a scientific method, system, device, and medium for bird deterrence using shock wave energy fields. The method includes acquiring monitoring data and corresponding environmental illuminance information of the target protected area; adaptively fusing the monitoring data based on the environmental illuminance information to obtain bird behavioral characteristics; determining bird behavior categories and intervention priorities based on the bird behavioral characteristics, and performing a risk quantification assessment based on the monitoring data, bird behavior categories, and intervention priorities to obtain a risk assessment result; determining shock wave parameters based on the risk assessment result and a preset response matrix, and then controlling the shock wave generating unit to output a shock wave energy field based on the shock wave parameters. This invention improves the sustainability of bird deterrence.

Description

Technical Field

[0001] This invention belongs to the technical field of bird behavior intervention, and in particular relates to a scientific method, system, device and medium for bird repelling using shock wave energy fields. Background Technology

[0002] Currently, power facilities such as transmission lines, substations, and photovoltaic power stations are often located in open outdoor environments, making it common for birds to stop, circle, approach, perch, or nest in these areas. Bird activity can easily cause line tripping, decreased insulation performance, equipment contamination, and increased operational risks. Power facility protection scenarios are also characterized by large areas, significant diurnal environmental changes, rapid changes in bird activity patterns, and high requirements for continuous operation.

[0003] Existing methods for repelling birds from power facilities typically rely on on-site monitoring results to trigger bird-repelling devices and drive birds away according to preset intervention methods. In practical applications, this type of method is prone to problems such as the intervention basis being too rough and the repelling intensity not matching the bird's activity state. This results in weak repelling targeting, unstable continuous effects, and birds easily adapting under repeated intervention conditions, thereby affecting the protective effect of power facilities. Summary of the Invention

[0004] The purpose of this invention is to provide a scientific method, system, device and medium for bird repelling using shock wave energy fields, so as to solve the technical problem that existing bird repelling methods are not targeted and sustainable due to their crude intervention basis.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: In a first aspect, the present invention provides a scientific method for bird deterrence using shock wave energy fields, the method comprising: Acquire monitoring data and corresponding environmental illuminance information for the target protected area; The monitoring data is adaptively fused based on the environmental illumination information to obtain bird behavioral characteristics; Based on the bird behavior characteristics, bird behavior categories and intervention priorities are determined, and risk quantification assessment is performed based on the monitoring data, bird behavior categories, and intervention priorities to obtain risk assessment results; The shock wave parameters are determined based on the risk assessment results and the preset response matrix, and then the shock wave generating unit is controlled to output the shock wave energy field based on the shock wave parameters.

[0006] By adopting the above technical solutions, and by acquiring monitoring data of the target protection area and corresponding environmental illuminance information, the appearance, movement, and acoustic status of birds can be simultaneously monitored under different lighting conditions, thus providing a stable data foundation for subsequent behavior analysis and intervention decisions. By adaptively fusing the monitoring data based on environmental illuminance information, bird behavioral characteristics can be obtained, improving the matching degree of different modal information in day and night scenarios, thereby enhancing the completeness and robustness of bird behavior representation. By determining bird behavior categories and intervention priorities based on bird behavioral characteristics and conducting risk quantification assessments, risk assessment results can be obtained, distinguishing the risk level and intervention urgency corresponding to different bird activities, thereby reducing ineffective deterrence and improving the targeting of interventions. By determining shock wave parameters based on risk assessment results and a preset response matrix, and controlling the shock wave energy field output of the shock wave generating unit, the shock wave output can be adapted to the current risk state, thereby improving the accuracy and sustainability of bird deterrence effects.

[0007] In one example, the present invention can be further configured as follows: acquiring monitoring data of the target protected area and corresponding environmental illuminance information includes: Acquire visible light and infrared images of the target protected area to obtain visual monitoring data; The radar echo of the target protection area is acquired to obtain motion monitoring data; Acoustic data of the target protected area is obtained to obtain acoustic monitoring data; The visual monitoring data, the motion monitoring data, and the acoustic monitoring data are summarized to obtain the monitoring data. Obtain the ambient illuminance information corresponding to the target protection area.

[0008] By adopting the above technical solutions, and by acquiring visible light and infrared images, radar echoes, and acoustic data, and combining them with environmental illumination information to form monitoring data, it is possible to coordinate the perception of bird activities within the target protection area from multiple dimensions of vision, motion, and acoustics, thereby improving the ability to detect bird activities and the reliability of monitoring under all-weather conditions.

[0009] In one example, the present invention can be further configured as follows: the adaptive fusion of the monitoring data based on the environmental illumination information to obtain bird behavioral characteristics includes: Visual feature vectors are extracted from the visible light and infrared images; motion feature vectors are extracted from the radar echoes; acoustic feature vectors are extracted from the acoustic data. The fusion weights corresponding to the visual feature vector, the motion feature vector, and the acoustic feature vector are determined based on the ambient illumination information. The visual feature vector, the motion feature vector, and the acoustic feature vector are adaptively fused based on the fusion weights to obtain the bird behavior features.

[0010] By adopting the above technical solution, visual feature vectors, motion feature vectors and acoustic feature vectors are extracted separately, and adaptive fusion is performed after determining the fusion weights based on environmental illumination information. This enables the unified mapping of bird appearance changes, flight changes and call changes into comprehensive behavioral features, thereby improving the recognition accuracy of bird activity status in complex scenes.

[0011] In one example, the present invention can be further configured as follows: determining the bird behavior category and intervention priority based on the bird behavior characteristics, and performing a risk quantification assessment based on the monitoring data, the bird behavior category, and the intervention priority to obtain a risk assessment result, including: Based on the aforementioned bird behavioral characteristics, behavioral discrimination information representing the bird's activity status is extracted; The bird behavior category is determined based on the behavior discrimination information, and the intervention priority is determined based on the bird behavior category; Risk assessment information characterizing the risk of bird activity is extracted from the monitoring data; The risk is quantitatively assessed based on the risk assessment information, the bird behavior category, and the intervention priority to obtain the risk assessment result.

[0012] By adopting the above technical solution, by extracting behavioral discrimination information that characterizes bird activity status, determining bird behavior categories and intervention priorities, and extracting risk assessment information that characterizes bird activity risk and then conducting risk quantification assessment, the original monitoring results can be transformed into risk assessment results that can be directly used for intervention decisions. This provides a clear risk basis for subsequent shock wave parameter selection and improves the rationality of decision-making.

[0013] In one example, the present invention can be further configured as follows: determining the bird behavior category based on the behavior discrimination information, and determining the intervention priority based on the bird behavior category, includes: Extract instantaneous velocity, acceleration, trajectory curvature, dwell time, and trajectory direction relationship from the behavior discrimination information; The instantaneous velocity, acceleration, trajectory curvature, dwell time, and trajectory pointing relationship are matched with preset behavior discrimination conditions to obtain the corresponding behavior discrimination results; The bird behavior category is determined based on the behavior discrimination results; The intervention priority is determined based on the bird behavior category.

[0014] By adopting the above technical solution, and by extracting instantaneous speed, acceleration, trajectory curvature, dwell time and trajectory direction relationship from behavior discrimination information, and matching them with preset behavior discrimination conditions to determine bird behavior categories and intervention priorities, it is possible to more accurately distinguish different activity states such as approaching attack, circling reconnaissance, brief passing by and continuous stay, so as to keep the intervention intensity consistent with the behavioral risk and improve the accuracy of driving away birds.

[0015] In one example, the present invention can be further configured as follows: the risk quantification assessment based on the risk assessment information, the bird behavior category, and the intervention priority, to obtain the risk assessment result, includes: Based on the risk assessment information, extract the real-time distance of birds, the number of birds in the flock, and the cumulative stay time; Bird species are identified based on the monitoring data, and species hazard weights are determined based on the identified bird species. Determine the attenuation factor of historical intervention effects based on historical intervention records; A risk coefficient is obtained by comprehensively processing the real-time distance of the birds, the number of birds, the cumulative stay time, the species hazard weight, the historical intervention effect decay factor, and the intervention priority. The corresponding intervention mode is determined based on the risk coefficient, and the risk assessment result is obtained based on the risk coefficient and the intervention mode.

[0016] By adopting the above technical solution, and by extracting real-time distance, flock size, and cumulative stay time of birds, and combining the species hazard weight corresponding to the bird species and the historical intervention effect decay factor for comprehensive processing, a risk coefficient and intervention mode can be obtained. This can uniformly quantify spatial proximity, flock size, stay intensity, species differences, and historical intervention impact, thereby avoiding homogeneous driving away of birds in different risk scenarios and improving the objectivity of risk assessment.

[0017] In one example, the present invention can be further configured as follows: determining the shock wave parameters based on the risk assessment results and a preset response matrix, and then controlling the shock wave generating unit to output a shock wave energy field based on the shock wave parameters, includes: Extract risk coefficients and intervention models from the risk assessment results; The corresponding set of parameter combinations is determined in the preset response matrix according to the intervention mode; The target parameter combination is obtained by filtering the parameter combination set based on the risk coefficient. The shock wave parameters are determined based on the target parameter combination; The shock wave generating unit is controlled to output the shock wave energy field according to the shock wave parameters.

[0018] By adopting the above technical solution, by extracting risk coefficients and intervention modes from risk assessment results, and by determining the parameter combination set in the preset response matrix, selecting the target parameter combination and shock wave parameters, and then controlling the shock wave generation unit to output the shock wave energy field, it is possible to select output parameters that are more compatible with the current risk state based on historical response relationships, thereby reducing the blindness of parameter selection and improving the effectiveness of shock wave intervention.

[0019] In a second aspect, the present invention provides a shock wave energy field scientific bird deterrence system, the system comprising: The monitoring and acquisition module is used to acquire monitoring data and corresponding environmental illuminance information of the target protection area; The feature fusion module is used to adaptively fuse the monitoring data based on the environmental illumination information to obtain bird behavioral characteristics; The assessment and judgment module is used to determine the bird behavior category and intervention priority based on the bird behavior characteristics, and to perform a risk quantification assessment based on the monitoring data, the bird behavior category and the intervention priority to obtain the risk assessment result; The parameter output module is used to determine the shock wave parameters based on the risk assessment results and the preset response matrix, and then control the shock wave generating unit to output the shock wave energy field based on the shock wave parameters.

[0020] By adopting the above technical solutions, and by acquiring monitoring data of the target protection area and corresponding environmental illuminance information, the appearance, movement, and acoustic status of birds can be simultaneously monitored under different lighting conditions, thus providing a stable data foundation for subsequent behavior analysis and intervention decisions. By adaptively fusing the monitoring data based on environmental illuminance information, bird behavioral characteristics can be obtained, improving the matching degree of different modal information in day and night scenarios, thereby enhancing the completeness and robustness of bird behavior representation. By determining bird behavior categories and intervention priorities based on bird behavioral characteristics and conducting risk quantification assessments, risk assessment results can be obtained, distinguishing the risk level and intervention urgency corresponding to different bird activities, thereby reducing ineffective deterrence and improving the targeting of interventions. By determining shock wave parameters based on risk assessment results and a preset response matrix, and controlling the shock wave energy field output of the shock wave generating unit, the shock wave output can be adapted to the current risk state, thereby improving the accuracy and sustainability of bird deterrence effects.

[0021] In a third aspect, the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the aforementioned shock wave energy field scientific bird-repelling method.

[0022] In a fourth aspect, the present invention provides a storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the aforementioned shock wave energy field scientific bird-repelling method. Attached Figure Description

[0023] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart of a scientific bird-repelling method using shock wave energy fields in an embodiment of the present invention; Figure 2 This is a structural block diagram of the shock wave energy field scientific bird deterrence system in an embodiment of the present invention; Figure 3 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0024] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0025] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0026] Example 1 like Figure 1 As shown, this invention discloses a scientific method for repelling birds using shock wave energy fields, specifically including the following steps: S10: Obtain monitoring data and corresponding environmental illuminance information for the target protection area.

[0027] Specifically, bird activity sensing operations are continuously performed within the target protection area. Raw observation information that can characterize the location, movement status, appearance and call characteristics of birds is collected simultaneously from the coverage area. At the same time as collecting raw observation information, the brightness and illumination changes of the current area are obtained to form monitoring data and environmental illumination information corresponding to the current bird activity in the protection area. This facilitates subsequent differentiated analysis and intervention of bird activities according to daytime, nighttime and different visibility conditions.

[0028] S20: Adaptive fusion of monitoring data based on environmental illumination information to obtain bird behavioral characteristics.

[0029] Specifically, after acquiring monitoring data, instead of directly and independently judging single modal data, the reliability and contribution ratio of data from different sources are adjusted in conjunction with the current ambient illumination information. This makes the representation of shape contour, size change and gray distribution of visible light images more prominent under bright conditions, and the representation of target presence, movement trend and trajectory change of infrared images and radar echoes more prominent under low illumination conditions. At the same time, acoustic data is introduced to supplement the representation of call spectrum and rhythm changes. After completing the normalization processing and weighted fusion of different modal data, the output is a bird behavior feature that can comprehensively represent the bird activity status.

[0030] S30: Determine bird behavior categories and intervention priorities based on bird behavior characteristics, and conduct a risk quantification assessment based on monitoring data, bird behavior categories, and intervention priorities to obtain risk assessment results.

[0031] Specifically, behavioral state analysis is performed on bird behavior characteristics to determine whether the current target belongs to a high-risk behavior of approaching critical equipment, reconnaissance behavior around critical areas, short-term transit behavior, or continuous stay behavior. Then, the intervention priority is determined according to the intervention urgency corresponding to different categories. At the same time, risk quantification assessment is performed by combining information from monitoring data that can characterize the spatial relationship between the target and critical equipment, the stay status, and the group size. The behavior category, intervention priority, and monitoring status are combined into risk assessment results that can be used for intervention decision-making, so that matching shock wave parameter combinations can be selected according to risk level in subsequent steps.

[0032] S40: Determine the shock wave parameters based on the risk assessment results and the preset response matrix, and then control the shock wave generation unit to output the shock wave energy field based on the shock wave parameters.

[0033] Specifically, risk level and pattern information corresponding to the intervention decision are extracted from the risk assessment results. Candidate parameter regions corresponding to the current intervention mode are searched in the preset response matrix. Shock wave parameters for the current intervention are determined within the candidate parameter regions. The determined shock wave parameters are then sent to the shock wave generation unit. The energy control circuit, pulse generation module, and transducer generate a shock wave energy field with target sound pressure level, fundamental frequency, and pulse sequence according to the corresponding parameter relationship. This causes the shock wave energy field to physically disturb and behaviorally drive away birds within the target protection area.

[0034] In one embodiment, step S10, namely acquiring monitoring data of the target protection area and corresponding environmental illuminance information, includes: S11: Acquire visible light and infrared images of the target protection area to obtain visual monitoring data.

[0035] Specifically, multispectral visual sensors are used to continuously collect image information within the target protection area. The visible light camera is used to collect information on the bird's appearance outline, feather color, target size, and spatial distribution under daytime and normal visibility conditions. The infrared thermal imaging component is used to collect the target's thermal radiation outline and thermal imaging coordinate information under nighttime, backlight, or low visibility conditions. The visible light images and infrared images acquired at the same time are then stored in a unified time sequence to form visual monitoring data that can jointly characterize the bird's appearance and thermal features.

[0036] S12: Acquire radar echoes from the target protection area to obtain motion monitoring data.

[0037] Specifically, within the target protection area, a microwave radar detector is used to continuously scan the airspace and the area surrounding key equipment, outputting echo information corresponding to bird targets. From the echo information, information related to distance, speed, azimuth changes, and trajectory evolution is extracted to form motion monitoring data that can characterize the bird's approach process, flight trend, and motion continuity. Radar detection is not affected by light or general weather changes and can stably perceive distant and small moving targets, providing a foundation for subsequent motion feature extraction.

[0038] S13: Acquire acoustic data of the target protection area to obtain acoustic monitoring data.

[0039] Specifically, within the target protection area, a microphone array is used to collect bird calls, pulse sounds, and changes in the environmental sound field. The output is acoustic waveform information and frequency domain information corresponding to bird activities. The content reflecting the intensity of calls, frequency distribution, pulse intervals, and temporal rhythms is compiled into acoustic monitoring data so that acoustic changes can still be used to assist in judging the species, number, and activity status of birds when visual monitoring is obstructed or interfered with by low light.

[0040] S14: Summarize the visual monitoring data, motion monitoring data, and acoustic monitoring data to obtain the monitoring data.

[0041] Specifically, visual monitoring data, motion monitoring data, and acoustic monitoring data acquired within the same target protection area and the same observation period are correlated and linked in time to form a unified data set among visible light images, infrared images, radar echoes, and acoustic waveforms. The unified data set is then organized according to the target area, acquisition time, and data source to obtain monitoring data that comprehensively reflects the appearance, motion, and acoustic status of birds, providing a unified input for subsequent multimodal feature extraction and risk assessment.

[0042] S15: Obtain the ambient illuminance information corresponding to the target protection area.

[0043] Specifically, while collecting monitoring data, the current ambient brightness status of the target protection area is obtained, and the current state of the area in daylight, dusk, night, or low-light scene is determined based on the changes in ambient brightness. The numerical results reflecting the brightness and illuminance change trend are then output as ambient illuminance information, which is used to adaptively adjust the weight distribution relationship of visual features, motion features, and acoustic features in the fusion process.

[0044] In one embodiment, step S20, namely, adaptively fusing the monitoring data based on environmental illumination information to obtain bird behavioral characteristics, includes: S21: Extract visual feature vectors from visible light and infrared images; extract motion feature vectors from radar echoes; extract acoustic feature vectors from acoustic data.

[0045] Specifically, visual feature vectors V for characterizing the appearance and spatial contours of birds are extracted from visible light and infrared images. t Visual feature vector V t This includes target size *s*, shape complexity *c*, and grayscale distribution entropy *h*. Target size *s* characterizes the area or scale variation of the target in the image; shape complexity *c* characterizes the complexity of the contour boundary; and grayscale distribution entropy *h* characterizes the discreteness of the pixel grayscale distribution within the target region. A motion feature vector *M* representing the flight state is extracted from the radar echo. t Motion feature vector M t This includes instantaneous velocity v, acceleration a, and trajectory curvature k, where instantaneous velocity v characterizes the rate of displacement change of the target at the current moment, acceleration a characterizes the intensity of the velocity change, and trajectory curvature k characterizes the degree of curvature of the flight path. An acoustic feature vector A is extracted from the acoustic data to characterize the call rhythm and sound field changes. t Acoustic eigenvector A t It includes the frequency domain energy distribution E(f) and the pulse interval Δτ, where E(f) represents the acoustic energy distribution at different frequency positions, and Δτ represents the time interval between adjacent acoustic pulses.

[0046] S22: Determine the fusion weights corresponding to the visual feature vector, motion feature vector, and acoustic feature vector based on the ambient illumination information.

[0047] Specifically, based on ambient illumination information, it is determined which type of perception information is more suitable for the current scene. Under high illumination conditions, the weight of visual feature vectors in the fusion process is increased, so that target size, shape complexity, and grayscale distribution entropy play a dominant role in behavior judgment. Under low illumination or nighttime conditions, the weight of infrared-related visual information and radar motion information in the fusion process is increased, while acoustic feature vectors are kept as supplementary weights to participate in the fusion, so that stable fusion results can be generated with a more suitable feature ratio under different environmental conditions.

[0048] S23: Adaptive fusion of visual feature vectors, motion feature vectors, and acoustic feature vectors based on fusion weights to obtain bird behavior features.

[0049] Specifically, for the visual feature vector V t Motion feature vector M t Harmony acoustic eigenvector A t Perform normalization mapping N(·) separately, then follow the fusion formula. We perform a weighted summation to obtain the bird behavioral characteristic F. t Where α is the visual feature weight, β is the motion feature weight, and γ is the acoustic feature weight, and satisfying α+β+γ=1, N(V t N(M) represents the result after normalization of the visual feature vector. t N(A) represents the result after normalization of the motion feature vector. t F represents the result of normalizing the acoustic eigenvectors. t This represents the fused bird behavior characteristics. This fusion method maps appearance, movement, and call rhythm into the same feature representation space to output a comprehensive feature result for subsequent behavior discrimination.

[0050] In one embodiment, in step S30, the bird behavior category and intervention priority are determined based on the bird's behavioral characteristics, and a risk quantification assessment is performed based on monitoring data, bird behavior category, and intervention priority to obtain the risk assessment result, including: S31: Extract behavioral discrimination information that characterizes the activity status of birds based on their behavioral characteristics.

[0051] Specifically, the behavioral characteristics of birds are analyzed to extract discriminative information that reflects the current activity status of birds. This includes changes in the target's speed, acceleration, trajectory curvature, duration of stay, size changes, and spatial orientation relationship between the flight trajectory and key equipment over continuous observation periods. This allows the behavioral discrimination information to simultaneously characterize whether the bird is in a state of rapid approach, reconnaissance by flying around, short-term passing, or continuous stay, providing a direct basis for subsequent determination of behavioral categories.

[0052] S32: Determine bird behavior categories based on behavior discrimination information, and determine intervention priorities based on bird behavior categories.

[0053] Specifically, the behavior discrimination information is matched with the preset behavior discrimination conditions. If the behavior is high-speed approach with increased acceleration and movement toward key equipment, it is judged as a high-risk approach behavior. If the behavior is flying around the key area and staying for a certain duration, it is judged as a medium-risk reconnaissance behavior. If the behavior is passing through with significant speed and minimal path curvature, it is judged as a low-risk passing behavior. If the target size changes little and the dwell time increases continuously, it is judged as a continuous dwelling behavior. Then, the intervention priority is output according to the mapping relationship between the behavior category and the preset priority, so that high-risk approach behavior and continuous dwelling behavior correspond to higher priority, reconnaissance behavior corresponds to medium priority, and passing behavior corresponds to lower priority.

[0054] S33: Extract risk assessment information that characterizes the risk of bird activity based on monitoring data.

[0055] Specifically, basic assessment content directly related to risk quantification is extracted from monitoring data, including the spatial distance between birds and key equipment, the number of bird flocks appearing in the target area at the same time, the cumulative stay time corresponding to the same bird or the same target trajectory, information that can reflect the bird species characteristics, and historical records related to the previous intervention time, so that the risk assessment information covers spatial proximity, group size, stay intensity, species harm level, and historical intervention decay status.

[0056] S34: Conduct a quantitative risk assessment based on risk assessment information, bird behavior categories, and intervention priorities to obtain risk assessment results.

[0057] Specifically, risk assessment information, along with behavior categories and intervention priorities, is input into the risk quantification assessment process. First, risk factors of different dimensions are standardized and characterized. Then, each risk factor is weighted and combined to obtain a risk coefficient that reflects the risk level of bird activity at the current moment. Based on the risk range that the risk coefficient falls into, the corresponding intervention mode is determined. Finally, the risk coefficient and the intervention mode are output as the risk assessment result, which is used to select the corresponding shock wave parameter combination from the preset response matrix.

[0058] In one embodiment, step S32, namely determining the bird behavior category based on behavior discrimination information and determining the intervention priority based on the bird behavior category, includes: S321: Extract instantaneous velocity, acceleration, trajectory curvature, dwell time, and trajectory direction relationship from behavior discrimination information.

[0059] Specifically, the same bird target is temporally correlated in continuous observation frames. Instantaneous velocity is calculated based on the position change and time interval between adjacent moments. Acceleration is calculated based on the velocity difference and time interval between adjacent moments. Trajectory curvature is calculated based on the degree of local turning change formed by continuous trajectory points. Dwell time is determined based on the cumulative duration of the target's continuous presence in the critical area. Trajectory pointing relationship is determined by the relationship between the target's trajectory extension direction and the position of the critical equipment. This allows the output results to fully reflect the target's approach speed, acceleration intensity, path curvature, dwell time, and whether it is approaching the critical equipment.

[0060] S322: Match instantaneous velocity, acceleration, trajectory curvature, dwell time and trajectory direction with preset behavior discrimination conditions to obtain the corresponding behavior discrimination result.

[0061] Specifically, instantaneous velocity, acceleration, trajectory curvature, dwell time, and trajectory pointing relationship are input into preset behavior discrimination conditions for comparison. When the instantaneous velocity is greater than a preset velocity threshold, the acceleration is greater than a preset acceleration threshold, and the trajectory points to critical equipment, the behavior discrimination result corresponding to a dive attack is output. When the instantaneous velocity is within a preset circling speed range and the dwell time is greater than a preset dwell time threshold, the behavior discrimination result corresponding to circling reconnaissance is output. When the instantaneous velocity meets the short-term transit condition and the trajectory curvature is less than a preset curvature threshold, the behavior discrimination result corresponding to a brief pass-through is output. When the target size changes by less than 5% in consecutive frames and the dwell time reaches a preset dwelling condition, the behavior discrimination result corresponding to nest building or roosting is output.

[0062] S323: Determine the bird behavior category based on the behavior discrimination results.

[0063] Specifically, the behavior discrimination results are classified and mapped. Results that meet the diving attack condition are classified as diving attack category, results that meet the circling reconnaissance condition are classified as circling reconnaissance category, results that meet the brief pass-through condition are classified as brief pass-through category, and results that meet the nesting or roosting condition are classified as nesting or roosting category, so as to obtain bird behavior category outputs that correspond one-to-one with the current monitored object.

[0064] S324: Determine intervention priorities based on bird behavior categories.

[0065] Specifically, bird behavior categories are mapped to pre-established priority relationships. Dive attack category corresponds to the highest priority P1, nesting or roosting category corresponds to continuous intervention priority P1, circling and reconnaissance category corresponds to medium priority P2, and short-term passing category corresponds to negligible or low priority P3. The priority results obtained from the mapping are then output as intervention priorities so as to reflect the urgency of intervention corresponding to different categories in the risk quantification assessment and subsequent parameter screening process.

[0066] In one embodiment, step S34 involves a risk quantification assessment based on risk assessment information, bird behavior categories, and intervention priorities to obtain risk assessment results, including: S341: Extract real-time distances, flock sizes, and cumulative dwell time of birds based on risk assessment information.

[0067] Specifically, the current spatial distance between the target and the key equipment is read from the risk assessment information as the real-time distance of the birds. The number of individual birds in the target protection area within the same observation window is counted as the flock size. The cumulative stay time is determined according to the cumulative time from the start time of the target's continuous stay to the current time, so that subsequent quantitative calculations can reflect the current risk from three dimensions: spatial proximity, flock size, and intensity of continuous stay.

[0068] S342: Identify bird species based on monitoring data and determine species hazard weights based on the identified bird species.

[0069] Specifically, bird species are identified by combining image features, thermal imaging features, motion status and acoustic features in the monitoring data, and the identified bird species are matched with a preset species hazard weight table to obtain the corresponding species hazard weight. Eagles can be matched with a higher hazard weight, and sparrows can be matched with a lower hazard weight, so that the potential threat level of different species to power facilities can be reflected in the form of weights in the risk quantification process.

[0070] S343: Determine the attenuation factor of historical intervention effects based on historical intervention records.

[0071] Specifically, the time interval Δt between the current moment and the last shock wave intervention is extracted from historical intervention records, and then the effect decay formula of historical intervention is applied. Calculate the historical intervention effect decay factor, where η history The factor represents the decay factor of the historical intervention effect at the current moment, where λ represents the decay coefficient, used to characterize how quickly the historical intervention effect weakens over time, and Δt represents the time interval since the last intervention. This factor enables the risk quantification process to consider the residual effects of previous interventions after they decay over time.

[0072] S344: The risk coefficient is obtained by comprehensively processing data such as real-time bird distance, flock size, cumulative stay time, species hazard weight, historical intervention effect decay factor, and intervention priority.

[0073] Specifically, the real-time distance of birds, flock size, cumulative stay time, species hazard weight, and historical intervention effect attenuation factor are input into the risk assessment function. A comprehensive calculation is performed to obtain the risk coefficient R.t , where R t The risk coefficient at time t is represented by w1, w2, w3, w4, and w5, which represent the weighting coefficients corresponding to different risk items, respectively. t d represents the real-time distance between birds and critical equipment. safe N represents the safe distance threshold. t N represents the current flock size. max t represents the maximum number of historical observations. stay T represents the total time a single bird spends. crit δ represents the critical dwell threshold. species η represents the species hazard weight. history This represents the historical intervention effect decay factor, which increases the impact of high-risk behaviors on the overall outcome when intervention priority is high, so that the risk coefficient more accurately reflects the actual threat level in the current scenario.

[0074] S345: Determine the corresponding intervention mode based on the risk coefficient, and obtain the risk assessment result based on the risk coefficient and the intervention mode.

[0075] Specifically, the risk coefficient is compared with a preset decision threshold; when R... t When R < 0.3, it is determined to be in non-intervention mode; when 0.3 ≤ R t When R < 0.6, it is determined to be an early warning mode and corresponds to a low-frequency, low-intensity shock wave. t When the value is ≥0.6, it is determined to be an enhanced driving mode and a high-frequency, high-intensity shock wave that allows for adaptive adjustment. The risk coefficient and the corresponding intervention mode are then output together to form the risk assessment result at the current moment.

[0076] In one embodiment, step S40, namely determining the shock wave parameters based on the risk assessment results and the preset response matrix, and then controlling the shock wave generating unit to output the shock wave energy field based on the shock wave parameters, includes: S41: Extract risk coefficients and intervention models from risk assessment results.

[0077] Specifically, numerical risk coefficients and pattern-based intervention results used for parameter selection are separated from the risk assessment results. The risk coefficients reflect the overall risk intensity of the current target, while the intervention patterns determine whether to select a low-intensity warning parameter region or a high-intensity enhanced drive parameter region from the preset response matrix, thus establishing an input basis for subsequent parameter combination selection.

[0078] S42: Determine the corresponding set of parameter combinations in the preset response matrix according to the intervention mode.

[0079] Specifically, a two-dimensional response matrix M is pre-constructed based on historical intervention response levels, specifying frequency and sound pressure levels. The matrix rows correspond to frequency levels, and the matrix columns correspond to sound pressure levels. Matrix elements can be configured according to... Perform the calculation, where M ij This represents the average response value corresponding to the i-th frequency level and the j-th sound pressure level, and K represents the cumulative number of historical interventions for this parameter combination. This represents the response rate obtained when the parameter combination is used for the kth time. In the current step, the retrieval area of ​​the matrix is ​​limited according to the intervention mode. If several pre-modes are warning modes, the corresponding parameter combination set is determined in the low-frequency and low-intensity region. If several pre-modes are enhanced driving modes, the corresponding parameter combination set is determined in the high-frequency and high-intensity region.

[0080] S43: Filter the set of parameter combinations based on the risk coefficient to obtain the target parameter combination.

[0081] Specifically, within the parameter combination set, the candidate combinations are optimized by incorporating risk coefficients, which can be done according to the parameter optimization decision formula. Perform the filtering, where This represents the combination of target parameters obtained through filtering. Indicates the target frequency range. Indicates the target sound pressure level. This represents the response value of the corresponding parameter combination in the response matrix. This indicates the number of times this parameter combination has been used in history. λ represents the total number of times all parameter combinations have been used in history, and λ represents the frequency of use penalty coefficient. By introducing a frequency of use penalty term on the basis of the response value, the screening results can maintain the effectiveness of the intervention while avoiding long-term repeated use of the same combination, which may cause birds to adapt.

[0082] S44: Determine the shock wave parameters based on the target parameter combination.

[0083] Specifically, the target parameter combination is mapped to the specific shock wave parameters required for the current intervention, including sound pressure level, fundamental frequency, pulse duration, pulse interval, and working cycle. The sound pressure level is used to characterize the intensity of the output shock wave, the fundamental frequency is used to characterize the center of the shock wave spectrum, the pulse duration is used to characterize the duration of a single action, the pulse interval is used to characterize the time interval between adjacent pulses, and the working cycle is used to characterize the proportion of pulse output per unit time. The above parameters are matched according to different risk modes, so that the parameters in the early warning mode are biased towards low intensity and short-term warning, and the parameters in the enhanced driving mode are biased towards high intensity and variable combinations.

[0084] S45: Controls the output of the shock wave energy field of the shock wave generating unit according to the shock wave parameters.

[0085] Specifically, the shock wave parameters are sent to the parameter adjustment section in the shock wave generating unit. The energy control circuit adjusts and stabilizes the input electrical energy. Then, the pulse generation module generates a high-voltage electrical pulse according to the target frequency, target pulse width, and target sequence relationship. Finally, the transducer drives the high-voltage electrical pulse to convert it into a corresponding sound pressure wave output, thereby forming a shock wave energy field that matches the current shock wave parameters. The energy control circuit can provide an instantaneous pulse voltage sufficient to support the shock wave output, and the pulse generation module can output an adjustable electrical pulse sequence. The transducer concentrates the energy onto the target protection area through the directional propagation effect of the acoustic cavity to achieve directional repulsion of birds.

[0086] Example 2 like Figure 2 As shown, based on the same inventive concept as the above embodiments, the present invention also provides a shock wave energy field scientific bird deterrence system, comprising: The monitoring and acquisition module is used to acquire monitoring data and corresponding environmental illuminance information of the target protection area; The feature fusion module is used to adaptively fuse monitoring data based on environmental illumination information to obtain bird behavioral characteristics; The assessment and judgment module is used to determine the bird behavior category and intervention priority based on the bird's behavioral characteristics, and to conduct a risk quantification assessment based on monitoring data, bird behavior category and intervention priority to obtain the risk assessment result; The parameter output module is used to determine the shock wave parameters based on the risk assessment results and the preset response matrix, and then control the shock wave generating unit to output the shock wave energy field based on the shock wave parameters.

[0087] Optionally, the monitoring acquisition module includes: The visual acquisition submodule is used to acquire visible light and infrared images of the target protected area to obtain visual monitoring data; The motion acquisition submodule is used to acquire radar echoes from the target protection area to obtain motion monitoring data; The acoustic acquisition submodule is used to acquire acoustic data of the target protected area and obtain acoustic monitoring data; The data aggregation submodule is used to aggregate visual monitoring data, motion monitoring data, and acoustic monitoring data to obtain monitoring data; The illuminance acquisition submodule is used to acquire the ambient illuminance information corresponding to the target protection area.

[0088] Optionally, the feature fusion module includes: The feature extraction submodule is used to extract visual feature vectors from visible light and infrared images; extract motion feature vectors from radar echoes; and extract acoustic feature vectors from acoustic data. The weight determination submodule is used to determine the fusion weights corresponding to the visual feature vector, motion feature vector and acoustic feature vector based on the ambient illumination information. The fusion generation submodule is used to adaptively fuse visual feature vectors, motion feature vectors, and acoustic feature vectors based on fusion weights to obtain bird behavior features.

[0089] Optionally, the evaluation and judgment module includes: The behavior extraction submodule is used to extract behavioral discrimination information that represents the activity status of birds based on their behavioral characteristics. The priority determination submodule is used to determine the bird behavior category based on behavior discrimination information, and to determine the intervention priority based on the bird behavior category; The risk extraction submodule is used to extract risk assessment information that characterizes the risk of bird activity based on monitoring data. The quantitative assessment submodule is used to conduct quantitative risk assessment based on risk assessment information, bird behavior categories, and intervention priorities to obtain risk assessment results.

[0090] Optionally, the behavior extraction submodule includes: The state extraction unit is used to extract instantaneous velocity, acceleration, trajectory curvature, dwell time, and trajectory pointing relationship from behavior discrimination information; The condition matching unit is used to match instantaneous velocity, acceleration, trajectory curvature, dwell time and trajectory pointing relationship with preset behavior discrimination conditions to obtain the corresponding behavior discrimination result; The category determination unit is used to determine the bird behavior category based on the behavior discrimination results; Priority determination unit, used to determine intervention priorities based on bird behavior categories.

[0091] Optional, the quantitative evaluation submodule includes: The risk extraction unit is used to extract real-time distance, flock size, and cumulative dwell time of birds based on risk assessment information. The species identification unit is used to identify bird species based on monitoring data and determine the species hazard weight based on the identified bird species. The attenuation determination unit is used to determine the attenuation factor of historical intervention effects based on historical intervention records; The coefficient calculation unit is used to comprehensively process data such as real-time bird distance, flock size, cumulative stay time, species hazard weight, historical intervention effect decay factor, and intervention priority to obtain the risk coefficient. The results generation unit is used to determine the corresponding intervention mode based on the risk coefficient, and to obtain the risk assessment results based on the risk coefficient and the intervention mode.

[0092] Optionally, the parameter output module includes: The results extraction submodule is used to extract risk coefficients and intervention patterns from risk assessment results; The matrix matching submodule is used to determine the corresponding set of parameter combinations in the preset response matrix according to the intervention mode; The combination filtering submodule is used to filter the set of parameter combinations based on the risk coefficient to obtain the target parameter combination; The parameter determination submodule is used to determine the shock wave parameters based on the target parameter combination; The energy field output submodule is used to control the output of the shock wave energy field by the shock wave generating unit according to the shock wave parameters.

[0093] Example 3 like Figure 3 As shown, the present invention also provides an electronic device 100 for realizing a scientific bird-repelling method using shock wave energy fields; The electronic device 100 includes a memory 101, at least one processor 102, a computer program 103 stored in the memory 101 and executable on at least one processor 102, and at least one communication bus 104.

[0094] The memory 101 can be used to store computer program 103. The processor 102 implements the steps of the shock wave energy field scientific bird deterrence method of Embodiment 1 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101.

[0095] The memory 101 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created based on the use of the electronic device 100 (such as audio data), etc. In addition, the memory 101 may include non-volatile memory, such as hard disk, RAM, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0096] At least one processor 102 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 102 may be a microprocessor or any conventional processor. Processor 102 is the control center of electronic device 100, connecting various parts of electronic device 100 via various interfaces and lines.

[0097] The memory 101 in the electronic device 100 stores multiple instructions to implement a scientific bird-repelling method using shock wave energy fields, and the processor 102 can execute multiple instructions to achieve the following: Acquire monitoring data and corresponding environmental illuminance information for the target protected area; Bird behavioral characteristics are obtained by adaptively fusing monitoring data based on environmental illumination information. Bird behavior categories and intervention priorities are determined based on bird behavior characteristics, and risk quantification assessment is conducted based on monitoring data, bird behavior categories, and intervention priorities to obtain risk assessment results; The shock wave parameters are determined based on the risk assessment results and the preset response matrix, and then the shock wave energy field is output by the shock wave generating unit according to the shock wave parameters.

[0098] Example 4 If the modules / units integrated in the electronic device 100 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or system capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, and read-only memory (ROM).

[0099] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A system that specifies functions in one or more boxes.

[0101] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including an instruction set implemented in a process. Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0102] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0103] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A scientific bird-repelling method using shock wave energy fields, characterized in that, The method includes: Acquire monitoring data and corresponding environmental illuminance information for the target protected area; The monitoring data is adaptively fused based on the environmental illumination information to obtain bird behavioral characteristics; Based on the bird behavior characteristics, bird behavior categories and intervention priorities are determined, and risk quantification assessment is performed based on the monitoring data, bird behavior categories, and intervention priorities to obtain risk assessment results; The shock wave parameters are determined based on the risk assessment results and the preset response matrix, and then the shock wave generating unit is controlled to output the shock wave energy field based on the shock wave parameters.

2. The scientific bird-repelling method using shock wave energy fields according to claim 1, characterized in that, The acquisition of monitoring data and corresponding environmental illuminance information of the target protection area includes: Acquire visible light and infrared images of the target protected area to obtain visual monitoring data; The radar echo of the target protection area is acquired to obtain motion monitoring data; Acoustic data of the target protected area is obtained to obtain acoustic monitoring data; The visual monitoring data, the motion monitoring data, and the acoustic monitoring data are summarized to obtain the monitoring data. Obtain the ambient illuminance information corresponding to the target protection area.

3. The scientific bird-repelling method using shock wave energy fields according to claim 2, characterized in that, The adaptive fusion of the monitoring data based on the environmental illumination information to obtain bird behavioral characteristics includes: Visual feature vectors are extracted from the visible light and infrared images; motion feature vectors are extracted from the radar echoes; acoustic feature vectors are extracted from the acoustic data. The fusion weights corresponding to the visual feature vector, the motion feature vector, and the acoustic feature vector are determined based on the ambient illumination information. The visual feature vector, the motion feature vector, and the acoustic feature vector are adaptively fused based on the fusion weights to obtain the bird behavior features.

4. The scientific bird-repelling method using shock wave energy fields according to claim 1, characterized in that, The process involves determining bird behavior categories and intervention priorities based on the bird's behavioral characteristics, and conducting a risk quantification assessment based on the monitoring data, the bird behavior categories, and the intervention priorities to obtain risk assessment results, including: Based on the aforementioned bird behavioral characteristics, behavioral discrimination information representing the bird's activity status is extracted; The bird behavior category is determined based on the behavior discrimination information, and the intervention priority is determined based on the bird behavior category; Risk assessment information characterizing the risk of bird activity is extracted from the monitoring data; The risk is quantitatively assessed based on the risk assessment information, the bird behavior category, and the intervention priority to obtain the risk assessment result.

5. The scientific bird-repelling method using shock wave energy fields according to claim 4, characterized in that, The step of determining the bird behavior category based on the behavior discrimination information and determining the intervention priority based on the bird behavior category includes: Extract instantaneous velocity, acceleration, trajectory curvature, dwell time, and trajectory direction relationship from the behavior discrimination information; The instantaneous velocity, acceleration, trajectory curvature, dwell time, and trajectory pointing relationship are matched with preset behavior discrimination conditions to obtain the corresponding behavior discrimination results; The bird behavior category is determined based on the behavior discrimination results; The intervention priority is determined based on the bird behavior category.

6. The scientific bird-repelling method using shock wave energy fields according to claim 4, characterized in that, The risk quantification assessment based on the risk assessment information, the bird behavior category, and the intervention priority, to obtain the risk assessment result, includes: Based on the risk assessment information, extract the real-time distance of birds, the number of birds in the flock, and the cumulative stay time; Bird species are identified based on the monitoring data, and species hazard weights are determined based on the identified bird species. Determine the attenuation factor of historical intervention effects based on historical intervention records; A risk coefficient is obtained by comprehensively processing the real-time distance of the birds, the number of birds, the cumulative stay time, the species hazard weight, the historical intervention effect decay factor, and the intervention priority. The corresponding intervention mode is determined based on the risk coefficient, and the risk assessment result is obtained based on the risk coefficient and the intervention mode.

7. The scientific bird-repelling method using shock wave energy fields according to claim 1, characterized in that, The step of determining shock wave parameters based on the risk assessment results and a preset response matrix, and then controlling the shock wave generating unit to output a shock wave energy field based on the shock wave parameters, includes: Extract risk coefficients and intervention models from the risk assessment results; The corresponding set of parameter combinations is determined in the preset response matrix according to the intervention mode; The target parameter combination is obtained by filtering the parameter combination set based on the risk coefficient. The shock wave parameters are determined based on the target parameter combination; The shock wave generating unit is controlled to output the shock wave energy field according to the shock wave parameters.

8. A scientific bird-repelling system using shock wave energy fields, characterized in that, The system includes: The monitoring and acquisition module is used to acquire monitoring data and corresponding environmental illuminance information of the target protection area; The feature fusion module is used to adaptively fuse the monitoring data based on the environmental illumination information to obtain bird behavioral characteristics; The assessment and judgment module is used to determine the bird behavior category and intervention priority based on the bird behavior characteristics, and to perform a risk quantification assessment based on the monitoring data, the bird behavior category and the intervention priority to obtain the risk assessment result; The parameter output module is used to determine the shock wave parameters based on the risk assessment results and the preset response matrix, and then control the shock wave generating unit to output the shock wave energy field based on the shock wave parameters.

9. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the scientific bird-repelling method using shock wave energy fields as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction that, when executed by a processor, implements the scientific bird-repelling method using shock wave energy fields as described in any one of claims 1 to 7.

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