Photovoltaic plant intelligent bird repelling method and system based on dynamic threshold ad hoc network

Abstract

The invention provides a photovoltaic plant intelligent bird repelling method and system based on a dynamic threshold ad hoc network, and relates to the technical field of photovoltaic plant bird protection. The method comprises the following steps: acquiring environment reference values (S0, L0, T0) in a preset time period every day, removing extreme values, and then taking a mean value; calculating a dynamic threshold value through a formula containing a calibration coefficient based on the real-time environment parameters; performing sliding window filtering on the infrared signal to generate S filtering; when S filtering continuously exceeds the threshold value and the interval is less than or equal to 1 second, primary triggering is generated; the environment light intensity change rate delta L is less than or equal to 5% and the temperature is lt; generating a bird repelling instruction at 40 DEG C; a bird repelling instruction is transmitted to an actuator through an ad hoc network, ultrasonic waves and stroboscopic LEDs are linked to repel birds, an environment self-adaptive threshold value, double-verification false alarm reduction, regional collaborative coverage and low-power-consumption management are achieved, and the problems that the number of blind areas is large, the false alarm rate is high and energy consumption is large are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of bird protection in photovoltaic plant areas, and in particular to an intelligent bird-repelling method and system for photovoltaic plant areas based on a dynamic threshold self-organizing network. Background Art

[0002] Bird protection in photovoltaic plants faces three major technical bottlenecks: First, coverage blind spots. Traditional fixed-threshold bird repellent systems rely on a single detection node and lack a multi-device linkage mechanism, allowing birds to escape to equipment-free areas. Second, environmental interference. Static thresholds cannot adapt to fluctuations in light intensity (such as changes in cloud cover) and temperature drift. Interference from wind-blown leaves leads to a high false alarm rate. Third, uncontrolled energy consumption. Infrared probes need to work around the clock, and the average daily power consumption when continuously triggering bird repellent action is 50μA. In a solar-powered scenario, the battery life on cloudy days is ≤3 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 expulsion across the entire plant. Summary of the Invention

[0004] In response to the above-mentioned problems existing in the prior art, the first aspect of the present invention proposes an intelligent bird-repellent method for photovoltaic plants based on a dynamic threshold self-organizing network, comprising: step 1, based on a timing signal of a real-time clock, continuously collecting multiple sets of infrared signals through a pyroelectric infrared sensor and continuously collecting multiple sets of ambient light intensity and ambient temperature data through an environmental sensor during a preset time period every day, and taking the arithmetic average 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 current ambient light intensity L collected in real time 当前 、Current ambient temperature T 当前 And S0, L0, T0, calculate the dynamic threshold T through the formula 动态 : , where k1 and k2 are calibration coefficients; Step 3: Based on the real-time signal of the pyroelectric infrared sensor, the sliding window mean filter is used to remove abnormal values ​​that deviate from the window mean by more than a preset ratio, and the arithmetic mean of the remaining effective values ​​is taken to generate the filtered signal S 滤波 ; Step 4, based on S 滤波 With T 动态 , when S 滤波 Continuously exceed T 动态 And when the time interval meets the preset conditions, a primary trigger mark is generated; Step 5: Based on the primary trigger mark, obtain the stored historical ambient light intensity L 基准 , calculate the ambient light intensity change rate by the formula : ; Step 6, based on the primary trigger mark and ,when When the preset range is met, the detector generates a bird-repelling instruction; Step 7: Based on the bird-repelling instruction, the bird-repelling instruction is transmitted to the actuator through the ad hoc network communication network, activating the combined bird-repelling action of the ultrasonic generator and the strobe 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, continuously obtain five sets of light data. After removing the maximum and minimum values, take the arithmetic average of the remaining three sets of light data to generate the ambient light intensity reference value L0. The calculation formula is: , where L i is the effective light intensity sampling value; In step 1-2, based on the output signal of the temperature and humidity sensor, five sets of temperature data are continuously obtained. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of temperature data is taken to generate the ambient temperature reference value T0. The calculation formula is: , where T i is the effective temperature sampling value; In 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: , where S i is the valid 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, generate a digital signal through analog-to-digital conversion; Step 3-2: Based on five consecutive digital signals, after removing the abnormal values ​​that deviate from the current window mean by more than 20%, the arithmetic mean of the remaining effective values ​​is taken to generate the filtered signal S 滤波 , the calculation formula is: , where n is the effective sampling number after removing outliers, and n>3, S i is the valid digital signal sampling 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 Exceed T three times in a row 动态, and the three sampling intervals are ≤ 1 second, a primary trigger mark is generated; Step 6 includes: Step 6-1, based on the primary trigger mark and ,when ≤5% and T 当前 When the temperature is less than 40℃, a bird-repelling instruction 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 primary trigger.

[0008] In combination with the first aspect, in some implementations, the power supply modules of the pyroelectric infrared sensor, environmental sensor, detector and actuator switch the power supply mode based on the light intensity detection result. When the light intensity detection result meets the light intensity threshold condition, the power is supplied by solar energy, otherwise it is supplied by a lithium battery; wherein, the solar power supply unit of the detector realizes charging and discharging control through the power management circuit, and the solar power supply unit of the actuator controls the power on and off state through the MOSFET switching circuit.

[0009] In conjunction with the first aspect, in some implementations, low power consumption management is further included, specifically including: Controlling the detector to enter a deep sleep mode based on the timing signal and shutting down the main control circuit of the detector; Based on the standby signal, the actuator is controlled to disconnect the MOSFET switch circuit, so that the ultrasonic generator and the strobe LED are powered off; Based on the bird-repelling command, the MOSFET switch circuit is turned on to activate the ultrasonic generator and the strobe LED; Based on the timer control, the ultrasonic generator and strobe LED will automatically shut down after working for 5 seconds.

[0010] In conjunction with the first aspect, in some implementations, a temperature compensation operation is further included, specifically including: When T 当前 When the temperature is ≤-20℃, the preheating circuit is started; 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 ad hoc communication network in step 7 includes: Search surrounding networks based on network discovery request frames sent by newly added devices; Receive a 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 ID and security key are verified based on the network coordinator to complete the configuration of the ad hoc communication network.

[0012] In a second aspect, the present invention provides a photovoltaic plant intelligent bird repellent system based on a dynamic threshold self-organizing network. The system adopts the method provided in any of the above embodiments, and the system includes: Detection module, including pyroelectric infrared sensor and environmental sensor, used to collect infrared signal, ambient light intensity and ambient temperature data; The processing module is connected to the detection module and has a built-in dynamic threshold algorithm for generating the infrared signal reference value S0, the ambient light intensity reference value L0 and the ambient temperature reference value T0, and calculating the dynamic threshold value T 动态 , and perform multi-level trigger verification to generate bird-repelling instructions; The communication module is connected to the processing module and adopts the self-organizing network protocol to transmit the bird-repelling instructions; The actuator is connected to the communication module and includes an ultrasonic generator and a strobe LED, and is used to receive bird-repelling instructions and perform bird-repelling actions.

[0013] Compared with the prior art, the present invention has the following advantages: Step 1 takes the arithmetic mean value after eliminating abnormal values ​​in a preset period, generates the infrared signal reference value S0, the ambient light intensity reference value L0 and the ambient temperature reference value T0, eliminates the single sampling deviation, provides a reliable environmental baseline for the dynamic threshold, and reduces the risk of false alarms from the source. Step 2 introduces calibration coefficients k1 and k2, and converts the current ambient light intensity L 当前 and the current ambient temperature T 当前 The deviation from the reference value is quantified as a dynamic threshold T 动态 , so that the threshold value can be automatically adjusted with light / temperature fluctuations, solving the problem of fixed threshold value failure when the environment changes suddenly. Step 3 removes abnormal values ​​from the real-time signal of the pyroelectric infrared sensor to generate an anti-interference filter signal S 滤波 , to avoid false operation caused by transient noise. Steps 4 to 6 are based on S 滤波 With T 动态 Continuous exceeding of thresholds (primary trigger) combined with verification of the ambient light intensity change rate ΔL (secondary trigger) double-filters interference such as windblown leaves. Automatically raising the threshold at high temperatures further suppresses false alarms. Step 7 synchronizes the bird repellent command to multiple actuators via the ad hoc communication network, activating the combined repellent action of the ultrasonic generator and strobe LED, creating a coordinated regional repellent and eliminating coverage blind spots.

[0014] In summary, steps 1 to 3 build the foundation for environmental adaptive detection, steps 4 to 6 compress the false alarm space through dual verification of signals and environment, and step 7 relies on self-organizing networks to achieve low-power wide-area coverage. As a whole, the system maintains a high detection rate and a low false alarm rate in complex environments, while reducing energy loss caused by invalid triggering. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0016] Figure 1 The figure shows a flow chart of an intelligent bird-repelling method for a photovoltaic plant area based on a dynamic threshold self-organizing network provided by an embodiment of the present invention.

[0017] Figure 2 FIG. 4 is a flow chart of a dynamic threshold algorithm provided by an embodiment of the present invention.

[0018] Figure 3 FIG2 is an architecture diagram of a detector and an actuator provided by an embodiment of the present invention.

[0019] Figure 4 Shown is a schematic diagram of photovoltaic plant deployment provided by an embodiment of the present invention.

[0020] Figure 5 FIG. 1 is a timing diagram of power consumption management provided by an embodiment of the present invention.

[0021] Figure 6 FIG2 is a schematic structural diagram of a photovoltaic plant intelligent bird-repelling system based on a dynamic threshold self-organizing network provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

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

[0024] Example 1 like Figures 1 to 4As shown, the present invention proposes an intelligent bird-repellent method for photovoltaic plants based on a dynamic threshold self-organizing network, comprising: step 1, based on a timing signal of a real-time clock, continuously collecting multiple sets of infrared signals through a pyroelectric infrared sensor and continuously collecting multiple sets of ambient light intensity and ambient temperature data through an environmental sensor during a preset time period every day, and taking the arithmetic average 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 current ambient light intensity L collected in real time 当前 、Current ambient temperature T 当前 And S0, L0, T0, calculate the dynamic threshold T through the formula 动态 : , where k1 and k2 are calibration coefficients; Step 3: Based on the real-time signal of the pyroelectric infrared sensor, the sliding window mean filter is used to remove abnormal values ​​that deviate from the window mean by more than a preset ratio, and the arithmetic mean of the remaining effective values ​​is taken to generate the filtered signal S 滤波 ; Step 4, based on S 滤波 With T 动态 , when S 滤波 Continuously exceed T 动态 And when the time interval meets the preset conditions, a primary trigger mark is generated; Step 5: Based on the primary trigger mark, obtain the stored historical ambient light intensity L 基准 , calculate the ambient light intensity change rate by the formula : ; Step 6, based on the primary trigger mark and ,when When the preset range is met, the detector generates a bird-repelling instruction; Step 7: Based on the bird-repelling instruction, the bird-repelling instruction is transmitted to the actuator through the ad hoc network communication network, activating the combined bird-repelling action of the ultrasonic generator and the strobe LED.

[0025] The core of the intelligent bird repellent method for photovoltaic plants based on a dynamic threshold ad hoc network lies in reducing false alarm rates through an environmentally adaptive mechanism and leveraging the ad hoc network to achieve collaborative bird repellent. This method first collects environmental baseline values ​​during a predetermined daily period (e.g., 3:00 a.m., when bird activity is at its lowest). A pyroelectric infrared sensor continuously collects multiple infrared signals at 200ms intervals, while an environmental sensor simultaneously collects ambient light intensity and temperature data. By removing the maximum and minimum values ​​from each data set and calculating the arithmetic mean of the remaining values, the infrared signal baseline value S0, the ambient light intensity baseline value L0, and the ambient temperature baseline value T0 are generated. This design eliminates single-shot sampling bias, provides a reliable environmental baseline for the dynamic threshold, and reduces the risk of false alarms caused by environmental fluctuations.

[0026] When working in real time, the dynamic threshold T 动态 The calculation integrates the deviation between the current environmental parameters and the reference value. 动态 The formula, where calibration coefficients k1=0.2 and k2=0.15 were determined through experimental optimization, quantifies the impact of light intensity fluctuations (such as cloud cover) and temperature drift (such as sensor baseline shift caused by scorching sun) on the threshold, allowing the system to automatically adapt to diurnal and seasonal changes and addressing the issue of fixed thresholds failing under sudden environmental changes.

[0027] The signal processing stage uses sliding window mean filtering to enhance anti-interference performance: the real-time signal of the pyroelectric infrared sensor is continuously sampled, and abnormal values ​​(such as instantaneous electromagnetic noise) that deviate from the window mean by more than a preset ratio (such as 20%) are eliminated. The arithmetic mean of the remaining effective values ​​generates the filtered signal S 滤波 This will prevent the trigger from misoperation due to transient interference such as wind blowing leaves. The trigger mechanism is designed for multi-level verification: the primary trigger requires S 滤波 Continuously exceed T 动态 The time interval is ≤ 1 second (e.g., three consecutive samplings) to ensure that the signal continuity is consistent with bird activity characteristics. Secondary verification calculates the ambient light intensity change rate ΔL based on the primary trigger marker. A bird repellent command is generated only when ΔL ≤ 5% and the temperature is within the specified limit. This dual verification mechanism reduces false alarms due to disturbances such as wind blowing through leaves.

[0028] Ultimately, the bird-repelling command is transmitted to the actuator via an ad hoc communication network (such as LoRaWAN or Zigbee Mesh), activating a combined ultrasonic generator and strobe LED to repel the bird. This multimodal repelling design, combining random ultrasonic frequency variation with strobe light, combined with the ad hoc network to trigger synchronized multi-node action, forms a regional repelling network, preventing birds from adapting to a single stimulus and maintaining a high repelling success rate over the long term.

[0029] Multiple nodes work synchronously to form a regional coordinated expulsion network, eliminating blind spots in photovoltaic plant coverage. This comprehensive approach utilizes a five-layer closed-loop technology: environmental baseline construction, dynamic threshold adjustment, signal filtering, multi-level verification, and self-organizing network linkage. This approach maintains high detection rates and low false alarm rates in complex environments, while also reducing ineffective energy consumption.

[0030] This embodiment of the present invention uses baseline initialization and a dynamic threshold formula to adapt the system to light and temperature fluctuations, reducing false alarm rates at the source. Sliding window filtering suppresses transient interference. Dual verification of continuous threshold exceeding and light intensity stability eliminates spurious signals. Self-organizing network command distribution enables regional coordinated bird repellent. Ultimately, this system maintains a high detection rate while maintaining a low false alarm rate and reducing average daily power consumption.

[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, continuously obtain five sets of light data. After removing the maximum and minimum values, take the arithmetic average of the remaining three sets of light data to generate the ambient light intensity reference value L0. The calculation formula is: , where L i is the effective light intensity sampling value; In step 1-2, based on the output signal of the temperature and humidity sensor, five sets of temperature data are continuously obtained. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of temperature data is taken to generate the ambient temperature reference value T0. The calculation formula is: , where T i is the effective temperature sampling value; In 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: , where S i is the valid infrared signal sampling value.

[0032] In other embodiments, the pyroelectric infrared sensor can be replaced with a 24 GHz millimeter wave radar, which detects the flying speed of birds through the Doppler effect. The detection distance is increased to 30 meters and the false alarm rate is low in rainy days.

[0033] In the embodiment of the present invention, a differentiated sampling strategy balances data accuracy and processing efficiency; an extreme value elimination mechanism resists occasional interference; and non-volatile storage and deviation checking 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, generate a digital signal through analog-to-digital conversion; Step 3-2: Based on five consecutive digital signals, after removing the abnormal values ​​that deviate from the current window mean by more than 20%, the arithmetic mean of the remaining effective values ​​is taken to generate the filtered signal S 滤波 , the calculation formula is: , where n is the effective sampling number after removing outliers, and n>3, S i is the valid digital signal sampling value.

[0035] The pyroelectric infrared sensor outputs an analog signal at a fixed 200ms interval, which is converted to a digital signal by an analog-to-digital converter for subsequent processing. A sliding window mean filter uses five data sets as a window (covering a 1-second period) and calculates the arithmetic mean of the data within the window in real time as a reference. Any sample value that deviates from this mean by more than a preset percentage (e.g., 20%) is identified as an outlier (e.g., caused by electromagnetic noise or small, non-bird moving objects) and is rejected.

[0036] For example, n > 3 is required to ensure statistical significance. For example, within the window, the five sample values ​​are [102, 105, 30, 108, 103] (unit: mV), with a mean of 89.6. After removing the outlier value "30" that deviates by more than 20% (i.e., < 71.68 or > 107.52), the mean of the remaining four values ​​is 104.5 mV. This design effectively suppresses transient interference while preserving the characteristics of the bird's sustained activity signal.

[0037] In the embodiment of the present invention, the sliding window dynamically updates the benchmark to adapt to the slow change of the signal; the 20% deviation threshold accurately isolates abnormal pulses; the effective sampling number constraint ensures the statistical validity of the filtering result, so that S 滤波 Truly reflect the bird activity signals.

[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 Exceed T three times in a row 动态 , and the three sampling intervals are ≤ 1 second, a primary trigger mark is generated; Step 6 includes: Step 6-1, based on the primary trigger mark and ,when ≤5% and T 当前 When the temperature is less than 40℃, a bird-repelling instruction 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 primary trigger.

[0039] The generation of the primary trigger mark must meet two conditions: first, the filtered signal S 滤波 Exceeds the dynamic threshold T three times in a row 动态 (Reflecting signal persistence), and secondly, the interval between three samples is ≤ 1 second (matching the flight speed of birds). For example, with a sampling interval of 200ms, three consecutive threshold crossings take only 400ms, allowing the capture of fast-moving targets.

[0040] Secondary verification focuses on environmental coupling factors: After the primary trigger mark is generated, the system calculates the ambient light intensity change rate ΔL. If ΔL ≤ 5% and the current temperature T 当前<40℃ is considered as a valid trigger. Light stability verification (ΔL≤5%) can eliminate false alarms caused by rapid cloud movement or device shadows; temperature conditions can avoid false triggering of sensors in high temperatures. Extreme high temperature scenarios (T 当前 ≥40℃) with a protection mechanism: the dynamic threshold is increased to 1.1×T 动态 This compensates for sensor baseline drift caused by high temperature.

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

[0042] In combination with the first aspect, in some implementations, the power supply modules of the pyroelectric infrared sensor, environmental sensor, detector and actuator switch the power supply mode based on the light intensity detection result. When the light intensity detection result meets the light intensity threshold condition, the power is supplied by solar energy, otherwise it is supplied by a lithium battery; wherein, the solar power supply unit of the detector realizes charging and discharging control through the power management circuit, and the solar power supply unit of the actuator controls the power on and off state through the 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 (e.g., when there is sufficient daylight), the system automatically switches to solar power mode; otherwise, it switches to lithium battery power mode. The detector's solar power supply unit uses a power management circuit to control charging and discharging. This circuit incorporates an MPPT maximum power point tracking algorithm to improve photoelectric conversion efficiency and provides overcharge / over-discharge protection. The actuator's solar power supply unit uses a MOSFET switching circuit to control its on / off state. When the bird repellent command is not activated, the MOSFET is in the off state, completely disconnecting the actuator circuit from power, with standby power consumption ≤5μA. Upon receiving the bird repellent command, the MOSFET turns on instantaneously, activating the ultrasonic generator and strobe LED.

[0044] In other embodiments, a wind-solar complementary power supply system may be used, and a micro wind turbine may be added to cope with continuous rainy weather.

[0045] In the embodiment of the present invention, dual-mode switching of solar energy and lithium batteries 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 combination with the first aspect, in some implementations, low power consumption management is further included, specifically including: Controlling the detector to enter a deep sleep mode based on the timing signal and shutting down the main control circuit of the detector; Based on the standby signal, the actuator is controlled to disconnect the MOSFET switch circuit, so that the ultrasonic generator and the strobe LED are powered off; Based on the bird-repelling command, the MOSFET switch circuit is turned on to activate the ultrasonic generator and the strobe LED; Based on the timer control, the ultrasonic generator and strobe LED will automatically shut down after working for 5 seconds.

[0047] refer to Figure 5 , Initialization phase (0s): When the time reaches 0s, the MCU is awakened and starts 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 actual sampling operations and transmits the collected data to the data processing module.

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

[0050] Threshold calculation and judgment stage (0.6s-1s): The trigger judgment module calculates the dynamic threshold between 0.6s and 0.8s and judges the trigger condition between 0.8s and 1s.

[0051] Specifically, low-power management achieves energy consumption optimization through a hierarchical sleep strategy. Based on the timing signal generated by the real-time clock, the detector is controlled to enter deep sleep mode during non-monitoring periods: the main MCU switches to Stop 2 mode, shuts down all peripheral circuits, and only keeps the RTC real-time clock running. At this time, the power consumption is ≤2μA. The standby signal controls the actuator to disconnect the internal MOSFET switch circuit, completely powering off the ultrasonic generator and strobe LED. When the bird-repelling command is generated, the detector transmits the command to the actuator through the self-organizing network communication network, triggering its MOSFET switch circuit to turn on, activating the ultrasonic generator (working current 15mA) and strobe LED (drive 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 an embodiment of the present invention, the deep sleep mode compresses the detector energy consumption 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 system's average daily power consumption, thereby reducing the annual operation and maintenance frequency of a thousand-acre photovoltaic plant.

[0053] In conjunction with the first aspect, in some implementations, a temperature compensation operation is further included, specifically including: When T 当前 When the temperature is ≤-20℃, the preheating circuit is started; 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 operation provides a dual protection mechanism for extreme climate environments. 当前 When the temperature is ≤-20℃, the system automatically starts the preheating circuit: the PTC ceramic heater raises the temperature of the pyroelectric infrared sensor to the working range (-10℃~50℃) within 2 seconds to avoid signal distortion caused by low temperature. 当前 When the temperature is ≥40℃, the processing module increases the dynamic threshold by 10% to generate an updated T 动态 , to compensate for the sensor baseline drift caused by high temperature.

[0055] In the embodiment of the present invention, low-temperature preheating ensures the measurement accuracy of the sensor in severe cold environments; the high-temperature threshold is improved to suppress thermal noise interference; and the dual compensation mechanism enables the system to maintain stable detection performance in the ambient temperature range of -20℃~50℃, thereby improving environmental adaptability.

[0056] In conjunction with the first aspect, in some implementations, the configuration of the ad hoc communication network in step 7 includes: Search surrounding networks based on network discovery request frames sent by newly added devices; Receive a 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 ID and security key are verified based on the network coordinator to complete the configuration of the ad hoc communication network.

[0057] Specifically, the configuration process for the ad hoc communication network is based on a mesh architecture without a central node. After a new device is powered on, it first sends a network discovery request frame to search for surrounding networks. After receiving the request, existing nodes in the network return a response frame containing 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 verifying the legitimacy of the network ID and security key, the network coordinator assigns a network address to the new device and synchronizes the communication channel parameters, completing the device's network entry. After network capacity expansion, any detector can broadcast bird-repelling commands to actuators within the network, enabling cross-regional linkage.

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

[0059] Example 2 like Figure 6 As shown, in a second aspect, the present invention provides a photovoltaic plant intelligent bird-repellent system based on a dynamic threshold self-organizing network. The system adopts the method provided in any of the above embodiments, and the system includes: Detection module, including pyroelectric infrared sensor and environmental sensor, used to collect infrared signal, ambient light intensity and ambient temperature data; The processing module is connected to the detection module and has a built-in dynamic threshold algorithm for generating the infrared signal reference value S0, the ambient light intensity reference value L0 and the ambient temperature reference value T0, and calculating the dynamic threshold value T 动态 , and perform multi-level trigger verification to generate bird-repelling instructions; The communication module is connected to the processing module and adopts the self-organizing network protocol to transmit the bird-repelling instructions; The actuator is connected to the communication module and includes an ultrasonic generator and a strobe LED, and is used to receive bird-repelling instructions and perform bird-repelling actions.

[0060] The system corresponds to the method provided in the above embodiment 1, and will not be described in detail here.

[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than 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 they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A photovoltaic plant intelligent bird repellent method based on dynamic threshold self-organizing network, characterized in that: include: Step 1: Based on the timing signal of the real-time clock, during a preset time period each day, a pyroelectric infrared sensor is used to continuously collect multiple sets of infrared signals, and an environmental sensor is used to continuously collect multiple sets of ambient light intensity and ambient temperature data. The maximum and minimum values ​​are removed respectively, and the arithmetic average 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 current ambient light intensity L collected in real time 当前 、Current ambient temperature T 当前 And S0, L0, T0, calculate the dynamic threshold T through the formula 动态 : , where k1 and k2 are calibration coefficients; Step 3: Based on the real-time signal of the pyroelectric infrared sensor, the sliding window mean filter is used to remove abnormal values ​​that deviate from the window mean by more than a preset ratio, and the arithmetic mean of the remaining effective values ​​is taken to generate the filtered signal S 滤波 ; Step 4, based on S 滤波 With T 动态 , when S 滤波 Continuously exceed T 动态 And when the time interval meets the preset conditions, a primary trigger mark is generated; Step 5: Based on the primary trigger mark, obtain the stored historical ambient light intensity L 基准 , calculate the ambient light intensity change rate by the formula : ; Step 6, based on the primary trigger mark and ,when When the preset range is met, the detector generates a bird-repelling instruction; Step 7: Based on the bird-repelling instruction, the bird-repelling instruction is transmitted to the actuator through the ad hoc network communication network to activate the combined bird-repelling action of the ultrasonic generator and the strobe LED.

2. The method for intelligent bird repelling in photovoltaic plant area based on dynamic threshold self-organizing network according to claim 1, characterized in that: 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, continuously obtain five sets of light data. After removing the maximum and minimum values, take the arithmetic average of the remaining three sets of light data to generate the ambient light intensity reference value L0. The calculation formula is: , where L i is the effective light intensity sampling value; In step 1-2, based on the output signal of the temperature and humidity sensor, five sets of temperature data are continuously obtained. After removing the maximum and minimum values, the arithmetic mean of the remaining three sets of temperature data is taken to generate the ambient temperature reference value T0. The calculation formula is: , where T i is the effective temperature sampling value; In 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: , where S i is the valid infrared signal sampling value.

3. The method for intelligent bird repelling in photovoltaic plant area based on dynamic threshold self-organizing network 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, generate a digital signal through analog-to-digital conversion; Step 3-2: Based on five consecutive digital signals, after removing the abnormal values ​​that deviate from the current window mean by more than 20%, the arithmetic mean of the remaining effective values ​​is taken to generate the filtered signal S 滤波 , the calculation formula is: , where n is the effective sampling number after removing outliers, and n>3, S i is the valid digital signal sampling value.

4. The method for intelligent bird repelling in photovoltaic plant area based on dynamic threshold self-organizing network according to claim 1, characterized in that: Step 4 includes: Based on S 滤波 With T 动态 , when S 滤波 Exceed T three times in a row 动态 , and the three sampling intervals are ≤ 1 second, a primary trigger mark is generated; Step 6 includes: Step 6-1, based on the primary trigger mark and ,when ≤5% and T 当前 When the temperature is less than 40℃, a bird-repelling instruction 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 primary trigger.

5. The method for intelligent bird repelling in photovoltaic plant area based on dynamic threshold self-organizing network according to claim 1, characterized in that: The power supply modules of the pyroelectric infrared sensor, environmental sensor, detector and actuator switch the power supply mode based on the light intensity detection results. When the light intensity detection result meets the light intensity threshold condition, power is supplied by solar energy; otherwise, power is supplied by lithium batteries. Among them, the solar power supply unit of the detector realizes charge and discharge control through the power management circuit, and the solar power supply unit of the actuator controls the power on and off state through the MOSFET switching circuit.

6. The method for intelligent bird repelling in photovoltaic plant area based on dynamic threshold self-organizing network according to claim 5, characterized in that: It also includes low power management, including: Controlling the detector to enter a deep sleep mode based on the timing signal and shutting down the main control circuit of the detector; Based on the standby signal, the actuator is controlled to disconnect the MOSFET switch circuit, so that the ultrasonic generator and the strobe LED are powered off; Based on the bird-repelling command, the MOSFET switch circuit is turned on to activate the ultrasonic generator and the strobe LED; Based on the timer control, the ultrasonic generator and strobe LED will automatically shut down after working for 5 seconds.

7. The method for intelligent bird repelling in photovoltaic plant area based on dynamic threshold self-organizing network according to claim 1, characterized in that: Also included are temperature compensation operations, specifically: When T 当前 When the temperature is ≤-20℃, the preheating circuit is started; When T 当前 When the temperature is ≥40℃, the dynamic threshold is increased by 10% to generate the updated T 动态 .

8. The method for intelligent bird repelling in photovoltaic plant area based on dynamic threshold self-organizing network according to claim 1, characterized in that: The configuration of the ad hoc communication network in step 7 includes: Search surrounding networks based on network discovery request frames sent by newly added devices; Receive a 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 ID and security key are verified based on the network coordinator to complete the configuration of the ad hoc communication network.

9. A photovoltaic plant intelligent bird repellent system based on dynamic threshold self-organizing network, characterized in that: The system adopts the method according to any one of claims 1 to 8, and the system includes: Detection module, including pyroelectric infrared sensor and environmental sensor, used to collect infrared signal, ambient light intensity and ambient temperature data; The processing module is connected to the detection module and has a built-in dynamic threshold algorithm for generating the infrared signal reference value S0, the ambient light intensity reference value L0 and the ambient temperature reference value T0, and calculating the dynamic threshold value T 动态 , and perform multi-level trigger verification to generate bird-repelling instructions; The communication module is connected to the processing module and adopts the self-organizing network protocol to transmit the bird-repelling instructions; The actuator is connected to the communication module and includes an ultrasonic generator and a strobe LED, and is used to receive bird-repelling instructions and perform bird-repelling actions.

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