A photovoltaic plant area intelligent bird repelling method and system based on a dynamic threshold self-organizing network

Abstract

The application provides a photovoltaic plant intelligent bird repelling method and system based on a dynamic threshold value ad hoc network, and relates to the technical field of bird protection in a photovoltaic plant. The method comprises the following steps: collecting an environmental reference value (S0, L0, T0) in a daily preset period, and taking the mean value after eliminating extreme values; calculating a dynamic threshold value through a formula containing a calibration coefficient based on real-time environmental parameters; generating S 滤波 by sliding window filtering of an infrared signal; generating a primary trigger when S 滤波 continuously exceeds the threshold value and the interval is less than or equal to 1 second; generating a bird repelling instruction when the environmental light intensity change rate ΔL is less than or equal to 5% and the temperature is less than 40°C; and transmitting the bird repelling instruction to an actuator through an ad hoc network, and linking ultrasonic waves and stroboscopic LEDs to repel birds, so that the environmental self-adaptive threshold value, double verification to reduce false positives, regional collaborative coverage and low-power consumption management are realized, and the problems of a large number of blind areas, a high false positive rate and high energy consumption are solved.

Description

Technical Field

[0001] This invention relates to the field of bird protection technology in photovoltaic industrial areas, and in particular to an intelligent bird deterrence method and system for photovoltaic industrial areas based on a dynamic threshold self-organizing network. Background Technology

[0002] Bird control in photovoltaic plant areas faces three major technical bottlenecks: First, the problem of blind spots in coverage. Traditional fixed threshold bird deterrence systems rely on a single detection node and lack a multi-device linkage mechanism, allowing birds to escape to areas without equipment. Second, the problem of environmental interference. Static thresholds cannot adapt to fluctuations in light intensity (such as cloud cover changes) and temperature drift. Interference such as wind blowing leaves leads to a high false alarm rate. Third, the problem of uncontrolled energy consumption. Infrared detectors need to work around the clock, and the daily power consumption reaches 50μA when continuously triggering bird deterrence actions. In solar-powered scenarios, the battery life is ≤3 days on cloudy days.

[0003] Although the existing solution introduces temperature compensation, it does not establish a dynamic threshold adjustment and multi-level verification mechanism, nor does it solve the problem of coordinated driving of the entire plant area. Summary of the Invention

[0004] To address the aforementioned problems in the existing technology, the first aspect of this invention proposes an intelligent bird-repelling method for photovoltaic factory areas based on a dynamic threshold self-organizing network, comprising: Step 1, based on a real-time clock timing signal, during a preset time period each day, continuously collecting multiple sets of infrared signals through a pyroelectric infrared sensor, continuously collecting multiple sets of ambient light intensity and ambient temperature data through an environmental sensor, and taking the arithmetic mean of the remaining values ​​after removing the maximum and minimum values ​​respectively, to generate an infrared signal reference value S0, an ambient light intensity reference value L0, and an ambient temperature reference value T0; Step 2, based on the real-time collected ambient light intensity L 当前 Current ambient temperature T 当前 Given S0, L0, and T0, the dynamic threshold T is calculated using the formula. 动态 : Where k1 and k2 are calibration coefficients; Step 3: Based on the real-time signal from the pyroelectric infrared sensor, a sliding window mean filter is applied to remove outliers that deviate from the window mean by more than a preset proportion. The arithmetic mean of the remaining valid values ​​is then used to generate the filtered signal S. 滤波 ; Step 4, based on S 滤波 With T 动态 When S 滤波 continuously exceeding T 动态 And when the time interval meets the preset conditions, a primary trigger flag is generated; Step 5: Based on the primary trigger flag, obtain the stored historical ambient light intensity L. 基准 The rate of change of ambient light intensity is calculated using a formula. : ; Step 6, based on the primary trigger flag and ,when When the preset range is met, a bird deterrent command is generated by the detector; Step 7: Based on the bird deterrence command, the bird deterrence command is transmitted to the actuator through the self-organizing network communication network to activate the combined bird deterrence action of the ultrasonic generator and the flashing LED.

[0005] In conjunction with the first aspect, in some implementations, the environmental sensor includes a light sensor and a temperature and humidity sensor, and step 1 includes: Step 1-1: Based on the output signal of the light sensor, five sets of light data are continuously acquired. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of light data is used to generate the ambient light intensity reference value L0. The calculation formula is as follows: , where L i This represents the effective light intensity sample value; Steps 1-2: Based on the output signal of the temperature and humidity sensor, five sets of temperature data are continuously acquired. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of temperature data is used to generate the ambient temperature baseline value T0. The calculation formula is as follows: , among which, T i The effective temperature sample value; Steps 1-3: Based on the output signal of the pyroelectric infrared sensor, ten sets of infrared signals are continuously acquired at 200ms intervals. After removing the maximum and minimum values, the arithmetic mean of the remaining eight sets of infrared signal data is taken to generate the infrared signal reference value S0. The calculation formula is as follows: , among which, S i This represents the effective infrared signal sampling value.

[0006] In conjunction with the first aspect, in some implementations, step 3 includes: Step 3-1: Based on the real-time signal output by the pyroelectric infrared sensor at 200ms intervals, a digital signal is generated through analog-to-digital conversion; Step 3-2: Based on five consecutive sets of digital signals, after removing outliers that deviate from the current window mean by more than 20%, the arithmetic mean of the remaining valid values ​​is used to generate the filtered signal S. 滤波 The calculation formula is: Where n is the number of valid samples after removing outliers, and n > 3, S i The effective digital signal sample value.

[0007] In conjunction with the first aspect, in some implementations, step 4 includes: based on S 滤波 With T 动态 When S 滤波 Exceeding T three times in a row 动态When the interval between the three samplings is ≤1 second, a primary trigger flag is generated; Step 6 includes: Step 6-1, based on the primary trigger flag and ,when ≤5% and T 当前 When the temperature is below 40℃, a bird deterrent command is generated; Step 6-2, when T 当前 When the temperature is ≥40℃, the dynamic threshold is increased to 1.1×T. 动态 Then re-verify the initial trigger.

[0008] In conjunction with the first aspect, in some implementations, the power supply modules of the pyroelectric infrared sensor, environmental sensor, detector, and actuator switch power supply modes based on the light intensity detection results. When the light intensity detection results meet the light intensity threshold condition, power is supplied by solar energy; otherwise, power is supplied by lithium battery. Among them, the solar power supply unit of the detector realizes charging and discharging control through a power management circuit, and the solar power supply unit of the actuator controls the on and off states through a MOSFET switching circuit.

[0009] In conjunction with the first aspect, some implementations also include low-power management, specifically including: The detector enters a deep sleep mode based on a timing signal, shutting down the detector's main control circuit. The standby signal controls the actuator to disconnect the MOSFET switching circuit, thereby de-energizing the ultrasonic generator and the strobe LED. The MOSFET switching circuit is activated based on the bird deterrence command, which in turn activates the ultrasonic generator and the flashing LED. Based on timer control, the ultrasonic generator and the flashing LED will automatically turn off after working continuously for 5 seconds.

[0010] In conjunction with the first aspect, some implementation methods also include temperature compensation operations, specifically including: When T 当前 When the temperature is ≤-20℃, the preheating circuit is activated; When T 当前 When the temperature is ≥40℃, the dynamic threshold is increased by 10% to generate the updated T. 动态 .

[0011] In conjunction with the first aspect, in some implementations, the configuration of the self-organizing network communication network in step 7 includes: Search for surrounding networks based on network discovery request frames sent by newly added devices; Receive the response frame corresponding to the request frame, and obtain the network ID and security key based on the response frame; Send an association request to the network coordinator based on the network ID and security key; The network coordinator verifies the network ID and security key to complete the configuration of the ad hoc network communication network.

[0012] Secondly, the present invention provides an intelligent bird-repelling system for photovoltaic factory areas based on a dynamic threshold self-organizing network. The system adopts the method provided in any of the above embodiments, and the system includes: The detection module includes a pyroelectric infrared sensor and an environmental sensor, used to collect infrared signals, ambient light intensity, and ambient temperature data; The processing module, connected to the detection module, has a built-in dynamic threshold algorithm used to generate infrared signal reference value S0, ambient light intensity reference value L0, and ambient temperature reference value T0, and to calculate the dynamic threshold T. 动态 And execute multi-level trigger verification to generate bird deterrence commands; The communication module is connected to the processing module and uses an ad hoc network protocol to transmit bird-scaring commands. The actuator, connected to the communication module, includes an ultrasonic generator and a strobe LED, used to receive bird-repelling commands and perform bird-repelling actions.

[0013] Compared with existing technologies, the beneficial effects of this invention are as follows: Step 1 generates an infrared signal reference value S0, an ambient light intensity reference value L0, and an ambient temperature reference value T0 by taking the arithmetic mean after removing outliers within a preset time period. This eliminates single sampling bias, provides a reliable environmental baseline for dynamic thresholds, and reduces the risk of false alarms from the source. Step 2 introduces calibration coefficients k1 and k2 to adjust the current ambient light intensity L0. 当前 and the current ambient temperature T 当前 The deviation from the benchmark value is quantified into a dynamic threshold T. 动态 This allows the threshold to automatically adjust with fluctuations in light / temperature, solving the problem of fixed thresholds failing under sudden environmental changes. Step 3 involves outlier removal from the real-time signal of the pyroelectric infrared sensor to generate an anti-interference filtered signal S. 滤波 This avoids malfunctions triggered by transient noise. Steps 4 to 6 are based on S 滤波 With T 动态 The continuous over-threshold judgment (primary trigger) is combined with the ambient light intensity change rate ΔL verification (secondary trigger) to double filter interference such as wind blowing leaves. At high temperatures, the threshold is automatically increased to further suppress false alarms. Step 7 synchronizes the bird deterrence command to multiple actuators through the self-organizing network communication network, activating the combined bird deterrence action of the ultrasonic generator and the flashing LED to form regional coordinated bird deterrence and eliminate coverage blind spots.

[0014] In summary, steps 1 to 3 establish the foundation for environment-adaptive detection, steps 4 to 6 compress the false alarm space through dual verification of signals and environment, and step 7 achieves low-power wide-area coverage by relying on self-organizing networks. Overall, the system maintains a high detection rate and a low false alarm rate in complex environments, while reducing energy consumption caused by invalid triggers. Attached Figure Description

[0015] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0016] Figure 1 The diagram shown is a flowchart of an intelligent bird control method for photovoltaic plant areas based on a dynamic threshold self-organizing network, according to an embodiment of the present invention.

[0017] Figure 2 The diagram shown is a flowchart of a dynamic threshold algorithm provided in an embodiment of the present invention.

[0018] Figure 3 The diagram shown is an architecture diagram of a detector and actuator provided in an embodiment of the present invention.

[0019] Figure 4 The diagram shown is a schematic diagram of a photovoltaic plant deployment according to an embodiment of the present invention.

[0020] Figure 5 The figure shown is a power management timing diagram provided in an embodiment of the present invention.

[0021] Figure 6 The diagram shown is a structural schematic of a photovoltaic factory area intelligent bird control system based on a dynamic threshold self-organizing network provided by an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0023] The specific embodiments of the present invention will be described below.

[0024] Example 1 like Figures 1 to 4As shown, this invention proposes an intelligent bird control method for photovoltaic factory areas based on dynamic threshold self-organizing networks, including: Step 1, based on the timing signal of a real-time clock, during a preset time period each day, multiple sets of infrared signals are continuously collected by a pyroelectric infrared sensor, and multiple sets of ambient light intensity and ambient temperature data are continuously collected by an environmental sensor. The maximum and minimum values ​​are removed respectively, and the arithmetic mean of the remaining values ​​is taken to generate an infrared signal reference value S0, an ambient light intensity reference value L0, and an ambient temperature reference value T0. Step 2, based on the real-time collected ambient light intensity L 当前 Current ambient temperature T 当前 Given S0, L0, and T0, the dynamic threshold T is calculated using the formula. 动态 : Where k1 and k2 are calibration coefficients; Step 3: Based on the real-time signal from the pyroelectric infrared sensor, a sliding window mean filter is applied to remove outliers that deviate from the window mean by more than a preset proportion. The arithmetic mean of the remaining valid values ​​is then used to generate the filtered signal S. 滤波 ; Step 4, based on S 滤波 With T 动态 When S 滤波 continuously exceeding T 动态 And when the time interval meets the preset conditions, a primary trigger flag is generated; Step 5: Based on the primary trigger flag, obtain the stored historical ambient light intensity L. 基准 The rate of change of ambient light intensity is calculated using a formula. : ; Step 6, based on the primary trigger flag and ,when When the preset range is met, a bird deterrent command is generated by the detector; Step 7: Based on the bird deterrence command, the bird deterrence command is transmitted to the actuator through the self-organizing network communication network to activate the combined bird deterrence action of the ultrasonic generator and the flashing LED.

[0025] The core of the intelligent bird control method for photovoltaic power plants based on a dynamic threshold self-organizing network lies in reducing the false alarm rate through an environmental adaptive mechanism and achieving collaborative bird control through the self-organizing network. The method first collects environmental baseline values ​​during a preset time period each day (e.g., 3:00 AM, a low point for bird activity): a pyroelectric infrared sensor continuously collects multiple sets of infrared signals at 200ms intervals, while an environmental sensor simultaneously collects ambient light intensity and ambient temperature data. By removing the maximum and minimum values ​​from each set of data and calculating the arithmetic mean of the remaining values, a baseline value S0 for the infrared signal, a baseline value L0 for the ambient light intensity, and a baseline value T0 for the ambient temperature are generated. This design eliminates single-sample bias, provides a reliable environmental baseline for the dynamic threshold, and reduces the risk of false alarms caused by environmental fluctuations from the source.

[0026] In real-time operation, the dynamic threshold T 动态 The calculation integrates the deviation between current environmental parameters and baseline values. Specifically, it uses T... 动态 The formula, where calibration coefficients k1=0.2 and k2=0.15, were determined through experimental optimization. This formula quantifies the impact of light intensity fluctuations (such as cloud cover) and temperature drift (such as sensor baseline shift caused by intense sunlight) on the threshold, enabling the system to automatically adapt to day-night and seasonal changes, and solving the problem of fixed threshold failure during sudden environmental changes.

[0027] The signal processing stage employs a sliding window mean filter to enhance anti-interference capability: Real-time signals from the pyroelectric infrared sensor are continuously sampled, and outliers (such as transient electromagnetic noise) that deviate from the window mean by more than a preset proportion (e.g., 20%) are removed. The arithmetic mean of the remaining effective values ​​generates the filtered signal S. 滤波 This measure avoids accidental triggering caused by momentary disturbances such as wind blowing leaves. The triggering mechanism is designed with multi-level verification: the primary triggering requirement S... 滤波 continuously exceeding T 动态 Furthermore, the time interval is ≤1 second (e.g., 3 consecutive samplings) to ensure that the signal continuity matches the characteristics of bird activity; the secondary verification is based on the calculation of the ambient light intensity change rate ΔL using the primary trigger marker. A bird deterrent command is only generated when ΔL ≤5% and the temperature does not exceed the limit. This dual verification mechanism reduces the false alarm rate caused by interference such as wind blowing leaves.

[0028] Ultimately, the bird-repelling command is transmitted to the actuator via an ad-hoc network communication network (such as LoRaWAN or Zigbee Mesh), activating a combined bird-repelling action of the ultrasonic generator and strobe LEDs. Employing a multimodal deterrence design that combines random frequency variation of ultrasonic waves with strobe light interference, and triggering synchronized actions of multiple nodes through an ad-hoc network, a regional deterrence encirclement is formed, preventing birds from adapting to a single stimulus and maintaining a high long-term deterrence success rate.

[0029] Multi-node synchronous operation forms a regional collaborative driving and encirclement network, eliminating coverage blind spots in photovoltaic plant areas. The overall method adopts a five-layer technical closed loop of environmental baseline construction, dynamic threshold adjustment, signal filtering, multi-level verification, and self-organizing network linkage to maintain a high detection rate and low false alarm rate in complex environments, while reducing ineffective energy consumption.

[0030] This invention employs a baseline initialization and dynamic threshold formula to adapt the system to light / temperature fluctuations, reducing the false alarm rate at the source. Sliding window filtering suppresses transient interference; dual verification of continuous threshold exceedance and light intensity stability eliminates false signals; and self-organizing network command distribution enables regional collaborative bird deterrence. Ultimately, while ensuring a high detection rate, the false alarm rate is low, and daily power consumption is reduced.

[0031] In conjunction with the first aspect, in some implementations, the environmental sensor includes a light sensor and a temperature and humidity sensor, and step 1 includes: Step 1-1: Based on the output signal of the light sensor, five sets of light data are continuously acquired. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of light data is used to generate the ambient light intensity reference value L0. The calculation formula is as follows: , where L i This represents the effective light intensity sample value; Steps 1-2: Based on the output signal of the temperature and humidity sensor, five sets of temperature data are continuously acquired. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of temperature data is used to generate the ambient temperature baseline value T0. The calculation formula is as follows: , among which, T i The effective temperature sample value; Steps 1-3: Based on the output signal of the pyroelectric infrared sensor, ten sets of infrared signals are continuously acquired at 200ms intervals. After removing the maximum and minimum values, the arithmetic mean of the remaining eight sets of infrared signal data is taken to generate the infrared signal reference value S0. The calculation formula is as follows: , among which, S i This represents the effective infrared signal sampling value.

[0032] In other embodiments, the pyroelectric infrared sensor can be replaced with a 24 GHz millimeter-wave radar that detects bird flight speed through the Doppler effect, increasing the detection range to 30 meters and reducing the false alarm rate in rainy weather.

[0033] In this embodiment of the invention, the differentiated sampling strategy balances data accuracy and processing efficiency; the extreme value elimination mechanism resists occasional interference; and non-volatile storage and bias verification ensure the reliability of baseline data, providing a solid foundation for dynamic threshold calculation.

[0034] In conjunction with the first aspect, in some implementations, step 3 includes: Step 3-1: Based on the real-time signal output by the pyroelectric infrared sensor at 200ms intervals, a digital signal is generated through analog-to-digital conversion; Step 3-2: Based on five consecutive sets of digital signals, after removing outliers that deviate from the current window mean by more than 20%, the arithmetic mean of the remaining valid values ​​is used to generate the filtered signal S. 滤波 The calculation formula is: Where n is the number of valid samples after removing outliers, and n > 3, S i The effective digital signal sample value.

[0035] The pyroelectric infrared sensor outputs analog signals at fixed intervals of 200ms, which are then converted into digital signals by an analog-to-digital converter for subsequent processing. The sliding window mean filter uses five sets of data as a window unit (covering a 1-second duration), calculating the arithmetic mean of the data within the window in real time as a reference. Any sampled value that deviates from this mean by more than a preset percentage (e.g., 20%) is considered an outlier (e.g., caused by electromagnetic noise or small non-bird moving targets) and is discarded.

[0036] Where n>3 to ensure statistical significance, for example, the five sampled values ​​within the window are [102, 105, 30, 108, 103] (unit: mV), with a mean of 89.6. After removing the outlier "30" that deviates by more than 20% (i.e., <71.68 or >107.52), the mean of the remaining four groups is taken as 104.5mV. This design can effectively suppress transient interference while preserving the characteristics of continuous bird activity signals.

[0037] In this embodiment of the invention, the sliding window dynamically updates the benchmark to adapt to gradual signal changes; a 20% deviation from the threshold precisely isolates abnormal pulses; and the effective sampling number constraint ensures the statistical validity of the filtering results, making S 滤波 It accurately reflects the signals of bird activity.

[0038] In conjunction with the first aspect, in some implementations, step 4 includes: based on S 滤波 With T 动态 When S 滤波 Exceeding T three times in a row 动态 When the interval between the three samplings is ≤1 second, a primary trigger flag is generated; Step 6 includes: Step 6-1, based on the primary trigger flag and ,when ≤5% and T 当前 When the temperature is below 40℃, a bird deterrent command is generated; Step 6-2, when T 当前 When the temperature is ≥40℃, the dynamic threshold is increased to 1.1×T. 动态 Then re-verify the initial trigger.

[0039] The generation of the primary trigger flag requires two conditions to be met: first, the filtered signal S 滤波 Exceeding the dynamic threshold T three times in a row 动态 (This reflects signal continuity) and secondly, the sampling interval between the three samples is ≤1 second (matching the flight speed of birds). For example, sampling at a 200ms interval, three consecutive exceedances of the threshold only require 400ms, which can capture fast-moving targets.

[0040] Secondary verification focuses on environmental coupling factors: After generating the primary trigger flag, the system calculates the rate of change of ambient light intensity ΔL. If ΔL ≤ 5% and the current temperature T 当前A temperature below 40℃ is considered a valid trigger. Light stability verification (ΔL≤5%) eliminates false alarms caused by rapidly moving clouds or shadows cast by the device; temperature conditions prevent sensor mis-triggers at high temperatures. Extreme high-temperature scenarios (T...) 当前 (≥40℃) has a protection mechanism: the dynamic threshold is raised to 1.1×T 动态 The primary trigger was then re-verified. This action compensates for sensor baseline drift caused by high temperatures.

[0041] In this embodiment of the invention, continuous exceeding of thresholds and a 1-second timing constraint ensure the characteristics of bird activity signals; light intensity change rate verification isolates interference from sudden environmental changes; and adaptive high-temperature threshold enhances system robustness. The three-level decision chain (signal persistence - environmental stability - temperature adaptability) keeps the overall false alarm rate at a low level.

[0042] In conjunction with the first aspect, in some implementations, the power supply modules of the pyroelectric infrared sensor, environmental sensor, detector, and actuator switch power supply modes based on the light intensity detection results. When the light intensity detection results meet the light intensity threshold condition, power is supplied by solar energy; otherwise, power is supplied by lithium battery. Among them, the solar power supply unit of the detector realizes charging and discharging control through a power management circuit, and the solar power supply unit of the actuator controls the on and off states through a MOSFET switching circuit.

[0043] Specifically, the power supply modules for the pyroelectric infrared sensor, environmental sensor, detector, and actuator adaptively switch energy supply modes based on ambient light intensity. When the light intensity detection result meets a preset threshold condition (such as sufficient daylight), the system automatically switches to solar power supply mode; otherwise, it switches to lithium battery power supply mode. The solar power supply unit of the detector achieves charging and discharging control through a power management circuit. This circuit includes an MPPT (maximum power point tracking) algorithm to improve photoelectric conversion efficiency and has overcharge / over-discharge protection functions. The solar power supply unit of the actuator is controlled by a MOSFET switching circuit. When the bird deterrence command is not activated, the MOSFET is in the off state, completely de-energizing the actuator circuit, with standby power consumption ≤5μA; upon receiving a bird deterrence command, the MOSFET is instantaneously turned on, activating the ultrasonic generator and the strobe LED.

[0044] In other embodiments, a wind-solar hybrid power supply system can be used, with the addition of micro wind turbines to cope with continuous rainy weather.

[0045] In this embodiment of the invention, the dual-mode switching between solar energy and lithium battery ensures energy sustainability; the MPPT algorithm optimizes solar energy utilization; the MOSFET switching circuit achieves zero standby power consumption of the actuator; and the overall power supply architecture enables the device to maintain a long battery life even in the absence of sunlight.

[0046] like Figure 5As shown, in conjunction with the first aspect, some implementations also include low-power management, specifically including: The detector enters a deep sleep mode based on a timing signal, shutting down the detector's main control circuit. The standby signal controls the actuator to disconnect the MOSFET switching circuit, thereby de-energizing the ultrasonic generator and the strobe LED. The MOSFET switching circuit is activated based on the bird deterrence command, which in turn activates the ultrasonic generator and the flashing LED. Based on timer control, the ultrasonic generator and the flashing LED will automatically turn off after working continuously for 5 seconds.

[0047] refer to Figure 5 Initialization phase (0s): When time reaches 0s, the MCU is woken up and begins to initialize the system and related parameters.

[0048] Sensor sampling phase (0s-0.4s): From 0s to 0.2s, the pyroelectric infrared sensor prepares for sampling; from 0.2s to 0.4s, the pyroelectric infrared sensor performs the actual sampling operation and transmits the collected data to the data processing module.

[0049] Data processing phase (0.4s-0.6s): During the time period from 0.4s to 0.6s, the data processing module performs analog-to-digital conversion and sliding window filtering on the received sampled data, and then transmits the processed data to the trigger judgment module.

[0050] Threshold calculation and judgment phase (0.6s-1s): The trigger judgment module calculates the dynamic threshold from 0.6s to 0.8s and judges the trigger conditions from 0.8s to 1s.

[0051] Specifically, low-power management optimizes energy consumption through a tiered sleep strategy. Based on a timing signal generated by a real-time clock, the detector enters a deep sleep mode during non-monitoring periods: the main control MCU switches to Stop 2 mode, shutting down all peripheral circuits and retaining only the RTC real-time clock, at which point power consumption is ≤2μA. A standby signal controls the actuator to disconnect its internal MOSFET switching circuit, completely de-energizing the ultrasonic generator and strobe LED. When a bird-repelling command is generated, the detector transmits the command to the actuator via a self-organizing network, triggering its MOSFET switching circuit to turn on, activating the ultrasonic generator (operating current 15mA) and the strobe LED (driving current 20mA) to perform a combined bird-repelling action. The duration of the action is precisely controlled by a hardware timer; after 5 seconds, the actuator automatically shuts down and returns to the power-off standby state.

[0052] In this embodiment of the invention, the deep sleep mode reduces the energy consumption of the detector to the microampere level; the actuator power-off standby design eliminates static power consumption; the timed shutdown mechanism avoids energy waste; and the hierarchical control strategy reduces the average daily power consumption of the system, thereby reducing the annual operation and maintenance frequency of photovoltaic power plants covering thousands of acres.

[0053] In conjunction with the first aspect, some implementation methods also include temperature compensation operations, specifically including: When T 当前 When the temperature is ≤-20℃, the preheating circuit is activated; When T 当前 When the temperature is ≥40℃, the dynamic threshold is increased by 10% to generate the updated T. 动态 .

[0054] Temperature compensation provides a dual protection mechanism against extreme weather conditions. When the ambient temperature T... 当前 When the temperature is ≤-20℃, the system automatically activates the preheating circuit: the PTC ceramic heating element raises the temperature of the pyroelectric infrared sensor to the operating range (-10℃~50℃) within 2 seconds, avoiding signal distortion caused by low temperature. When T 当前 When the temperature is ≥40℃, the processing module will increase the dynamic threshold by 10% to generate an updated T. 动态 This compensates for sensor baseline drift caused by high temperatures.

[0055] In this embodiment of the invention, low-temperature preheating ensures the measurement accuracy of the sensor in frigid environments; high-temperature threshold enhancement suppresses thermal noise interference; and a dual compensation mechanism enables the system to maintain stable detection performance within an ambient temperature range of -20℃ to 50℃, thereby improving environmental adaptability.

[0056] In conjunction with the first aspect, in some implementations, the configuration of the self-organizing network communication network in step 7 includes: Search for surrounding networks based on network discovery request frames sent by newly added devices; Receive the response frame corresponding to the request frame, and obtain the network ID and security key based on the response frame; Send an association request to the network coordinator based on the network ID and security key; The network coordinator verifies the network ID and security key to complete the configuration of the ad hoc network communication network.

[0057] Specifically, the configuration process of the ad-hoc communication network is implemented based on the centerless Mesh architecture. After a new device is powered on, it first sends a network discovery request frame to search for surrounding networks; after a node that has already joined the network receives the request, it returns a response frame, which contains key parameters such as the network ID and security key; based on the response frame information, the new device sends an association request to the network coordinator; after the network coordinator verifies the legitimacy of the network ID and security key, it allocates a network address to the new device and synchronizes communication channel parameters, completing the device's network access. After network expansion, any detector can broadcast bird repelling instructions to actuators in the network, realizing cross-regional linkage.

[0058] In the embodiment of the present invention, the centerless architecture improves system reliability; security key verification guarantees network access security; the dynamic networking mechanism supports plug-and-play of devices; the multi-hop relay function realizes full-coverage communication for a thousand-mu plant area, reducing signal blind spots.

[0059] Example 2 as Figure 6 shown, in a second aspect, the present invention provides an intelligent bird repelling system for photovoltaic plant areas based on dynamic threshold ad-hoc network, the system adopts the method provided by any of the above embodiments, and the system comprises: a detection module, comprising a pyroelectric infrared sensor and an environmental sensor, configured to collect infrared signals, ambient light intensity and ambient temperature data; a processing module, connected to the detection module, with a built-in dynamic threshold algorithm, configured to generate an infrared signal reference value S0, an ambient light intensity reference value L0 and an ambient temperature reference value T0, and calculate a dynamic threshold T 动态 , and execute multi-level trigger verification to generate a bird repelling instruction; a communication module, connected to the processing module, which adopts an ad-hoc network protocol to transmit bird repelling instructions; an actuator, connected to the communication module, comprising an ultrasonic generator and a strobe LED, configured to receive the bird repelling instruction and execute a bird repelling action.

[0060] The system corresponds to the method provided in the foregoing Example 1, and will not be repeated one by one herein.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention, rather than limiting it; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solution recorded in the foregoing embodiments, or perform equivalent replacement on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solution depart from the technical solution of the embodiments of the present invention.

Claims

1. A method for intelligent bird control in photovoltaic factory areas based on dynamic threshold self-organizing networks, characterized in that, include: Step 1: Based on the timing signal of the real-time clock, during the preset time period each day, multiple sets of infrared signals are continuously collected by the pyroelectric infrared sensor, and multiple sets of ambient light intensity and ambient temperature data are continuously collected by the environmental sensor. After removing the maximum and minimum values ​​respectively, the arithmetic mean of the remaining values ​​is taken to generate the infrared signal reference value S0, the ambient light intensity reference value L0 and the ambient temperature reference value T0. Step 2, based on the real-time collected ambient light intensity L 当前 Current ambient temperature T 当前 Given S0, L0, and T0, the dynamic threshold T is calculated using the formula. 动态 : Where k1 and k2 are calibration coefficients, k1=0.2 and k2=0.15; Step 3: Based on the real-time signal from the pyroelectric infrared sensor, a sliding window mean filter is applied to remove outliers that deviate from the window mean by more than a preset proportion. The arithmetic mean of the remaining valid values ​​is then used to generate the filtered signal S. 滤波 ; Step 4, based on S 滤波 With T 动态 When S 滤波 continuously exceeding T 动态 And when the time interval meets the preset conditions, a primary trigger flag is generated; Step 5: Based on the primary trigger flag, obtain the stored historical ambient light intensity L. 基准 The rate of change of ambient light intensity ∆L is calculated using the formula: ; Step 6: Based on the primary trigger marker and ∆L, when ∆L meets the preset range, generate a bird deterrent command through the detector; Step 7: Based on the bird deterrence command, the bird deterrence command is transmitted to the actuator through the self-organizing network communication network to activate the combined bird deterrence action of the ultrasonic generator and the flashing LED. Step 4 includes: based on S 滤波 With T 动态 When S 滤波 Exceeding T three times in a row 动态 When the interval between the three samplings is ≤1 second, a primary trigger flag is generated; Step 6 includes: Step 6-1, based on the primary trigger flag and ∆L, when ∆L≤5% and T 当前 When the temperature is below 40℃, a bird deterrent command is generated; Step 6-2, when T 当前 When the temperature is ≥40℃, the dynamic threshold is increased to 1.1×T. 动态 The initial trigger was then re-verified; The method also includes temperature compensation operations, specifically including: When T 当前 When the temperature is ≤-20℃, the preheating circuit is activated; When T 当前 When the temperature is ≥40℃, the dynamic threshold is increased by 10% to generate the updated T. 动态 .

2. The intelligent bird-repelling method for photovoltaic factory areas based on dynamic threshold self-organizing networks according to claim 1, characterized in that, The environmental sensors include light sensors and temperature and humidity sensors. Step 1 includes: Step 1-1: Based on the output signal of the light sensor, five sets of light data are continuously acquired. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of light data is used to generate the ambient light intensity reference value L0. The calculation formula is as follows: , where L i This represents the effective light intensity sample value; Steps 1-2: Based on the output signal of the temperature and humidity sensor, five sets of temperature data are continuously acquired. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of temperature data is used to generate the ambient temperature baseline value T0. The calculation formula is as follows: , among which, T i The effective temperature sample value; Steps 1-3: Based on the output signal of the pyroelectric infrared sensor, ten sets of infrared signals are continuously acquired at 200ms intervals. After removing the maximum and minimum values, the arithmetic mean of the remaining eight sets of infrared signal data is used to generate the infrared signal reference value S0. The calculation formula is as follows: , of which S i This represents the effective infrared signal sampling value.

3. The intelligent bird-repelling method for photovoltaic factory areas based on dynamic threshold self-organizing networks according to claim 1, characterized in that, Step 3 includes: Step 3-1: Based on the real-time signal output by the pyroelectric infrared sensor at 200ms intervals, a digital signal is generated through analog-to-digital conversion; Step 3-2: Based on five consecutive sets of digital signals, after removing outliers that deviate from the current window mean by more than 20%, the arithmetic mean of the remaining valid values ​​is used to generate the filtered signal S. 滤波 The calculation formula is: Where n is the number of valid samples after removing outliers, and n > 3, S i The effective digital signal sample value.

4. The intelligent bird-repelling method for photovoltaic factory areas based on dynamic threshold self-organizing networks according to claim 1, characterized in that, The power supply modules for the pyroelectric infrared sensor, environmental sensor, detector, and actuator switch power supply modes based on the light intensity detection results. When the light intensity detection results meet the light intensity threshold conditions, the device is powered by solar energy; otherwise, it is powered by a lithium battery. The solar power supply unit of the detector is controlled by a power management circuit for charging and discharging, while the solar power supply unit of the actuator is controlled by a MOSFET switching circuit for power on / off states.

5. The intelligent bird-repelling method for photovoltaic factory areas based on dynamic threshold self-organizing networks according to claim 4, characterized in that, It also includes low-power management, specifically including: The detector enters a deep sleep mode based on a timing signal, shutting down the detector's main control circuit. The standby signal controls the actuator to disconnect the MOSFET switching circuit, thereby de-energizing the ultrasonic generator and the strobe LED. The MOSFET switching circuit is activated based on the bird deterrence command, which in turn activates the ultrasonic generator and the flashing LED. Based on timer control, the ultrasonic generator and the flashing LED will automatically turn off after working continuously for 5 seconds.

6. The intelligent bird-repelling method for photovoltaic factory areas based on dynamic threshold self-organizing networks according to claim 1, characterized in that, Step 7, configuring the ad hoc network communication network, includes: Search for surrounding networks based on network discovery request frames sent by newly added devices; Receive the response frame corresponding to the request frame, and obtain the network ID and security key based on the response frame; Send an association request to the network coordinator based on the network ID and security key; The network coordinator verifies the network ID and security key to complete the configuration of the ad hoc network communication network.

7. A smart bird-repelling system for photovoltaic factory areas based on a dynamic threshold self-organizing network, characterized in that, The system employs the method described in any one of claims 1 to 6, the system comprising: The detection module includes a pyroelectric infrared sensor and an environmental sensor, used to collect infrared signals, ambient light intensity, and ambient temperature data; The processing module, connected to the detection module, has a built-in dynamic threshold algorithm used to generate infrared signal reference value S0, ambient light intensity reference value L0, and ambient temperature reference value T0, and to calculate the dynamic threshold T. 动态 And execute multi-level trigger verification to generate bird deterrence commands; The communication module is connected to the processing module and uses an ad hoc network protocol to transmit bird-scaring commands. The actuator, connected to the communication module, includes an ultrasonic generator and a strobe LED, used to receive bird-repelling commands and perform bird-repelling actions.

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