Energy consumption optimization method and system for medium-light-intensity obstacle light

Abstract

The invention discloses an energy consumption optimization method and system for a medium-light-intensity obstacle light, and relates to the technical field of obstacle light energy consumption optimization. The method comprises the following steps: carrying out holographic environment data acquisition on a target obstruction light, carrying out adaptive dimming equalization on the obstruction light, and outputting real-time light operation parameters and a real-time illumination mode; after the target obstruction light is switched to the real-time illumination mode, low-power light output control is carried out according to the real-time light operation parameters; constructing an airspace dynamic model; predicting the trajectory of the aircraft in a preset time window, and outputting the dynamic trajectory of the aircraft; if the intersection exists, calculating an intersection time window; triggering the target obstruction light to be switched to a full-power light output mode; and according to the equipment temperature rise characteristic and the component temperature difference characteristic of the target obstruction light in the full-power light output mode, adaptive current compensation is executed. The technical problem that in the prior art, energy consumption of a medium-light-intensity obstacle lamp is high is solved, and the technical effects of reducing energy consumption and prolonging the service life of equipment are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of obstacle lamp energy consumption optimization, and particularly to an energy consumption optimization method and system for medium-intensity obstacle lamps. Background Art

[0002] Medium-intensity obstacle lamps are widely used in warning lighting systems for high-rise buildings, communication towers, wind turbine generators, and other aviation obstacles. Their function is to provide position identification signals for aircraft in the night or low visibility environment to ensure flight safety. To ensure the visual distance and warning effect, existing medium-intensity obstacle lamps usually adopt fixed power or time period switching operation modes. Even when there is no approaching aircraft or the weather conditions are stable, they still maintain high-intensity lighting output, resulting in problems such as waste of electric energy, increased equipment heat load, and reduced service life. Summary of the Invention

[0003] This application provides an energy consumption optimization method and system for medium-intensity obstacle lamps, which solves the technical problem of high energy consumption of medium-intensity obstacle lamps in the prior art.

[0004] In the first aspect of this application, an energy consumption optimization method for medium-intensity obstacle lamps is provided. The method includes: Collecting holographic environmental data of the target obstacle lamp, and performing adaptive dimming balance of the obstacle lamp according to the collection result, and outputting real-time operating parameters and real-time lighting modes, where the target obstacle lamp is a medium-intensity obstacle lamp; after switching the target obstacle lamp to the real-time lighting mode, controlling the low-power light output according to the real-time operating parameters; calling the real-time hierarchical environmental data expansion model radius from the holographic environmental data, and constructing an airspace dynamic model with the ground coordinates of the target obstacle lamp as the center; predicting the aircraft trajectory within a preset time window according to multi-source aviation information, and outputting the aircraft dynamic trajectory; if there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model, calculating the intersection time window based on time extension; triggering the target obstacle lamp to switch to the full-power light output mode with the real-time lighting mode as the mode constraint and the intersection time window as the time constraint; performing adaptive current compensation according to the equipment temperature rise characteristics and component temperature difference characteristics of the target obstacle lamp in the full-power light output mode.

[0005] In the second aspect of this application, an energy consumption optimization system for medium-intensity obstacle lamps is provided. The system includes: The dimming equalization module is used to collect holographic environmental data of the target obstacle light, perform adaptive dimming equalization of the obstacle light according to the collection results, and output real-time operating parameters and real-time lighting modes. Among them, the target obstacle light is a medium-intensity obstacle light; the control module is used to switch the target obstacle light to the real-time lighting mode and then perform low-power light output control according to the real-time operating parameters; the model construction module is used to call the real-time hierarchical environmental data extension model radius from the holographic environmental data and construct an airspace dynamic model with the ground coordinates of the target obstacle light as the center; the trajectory prediction module is used to predict the aircraft trajectory within a preset time window according to multi-source aviation information and output the aircraft dynamic trajectory; the calculation module is used to calculate the intersection time window based on time extension if there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model; the mode triggering module is used to trigger the target obstacle light to switch to the full-power light output mode with the real-time lighting mode as the mode constraint and the intersection time window as the time constraint; the current compensation module is used to perform adaptive current compensation according to the equipment temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: First, collect holographic environmental data of the target obstacle light, perform adaptive dimming equalization of the obstacle light according to the collection results, and output real-time operating parameters and real-time lighting modes. Among them, the target obstacle light is a medium-intensity obstacle light. After switching the target obstacle light to the real-time lighting mode, perform low-power light output control according to the real-time operating parameters. Then, call the real-time hierarchical environmental data extension model radius from the holographic environmental data and construct an airspace dynamic model with the ground coordinates of the target obstacle light as the center. At the same time, predict the aircraft trajectory within a preset time window according to multi-source aviation information and output the aircraft dynamic trajectory. If there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model, calculate the intersection time window based on time extension. Then, trigger the target obstacle light to switch to the full-power light output mode with the real-time lighting mode as the mode constraint and the intersection time window as the time constraint. Finally, perform adaptive current compensation according to the equipment temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode. It solves the technical problem of high energy consumption of medium-intensity obstacle lights in the prior art and achieves the technical effects of reducing energy consumption and extending the equipment life. Description of the Drawings

[0007] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0008] Figure 1 Schematic diagram of the process of an energy consumption optimization method for medium-intensity obstacle lights provided by an embodiment of the present application; Figure 2 Schematic diagram of the structure of an energy consumption optimization system for medium-intensity obstacle lights provided by an embodiment of the present application.

[0009] Explanation of reference numerals: dimming balance module 11, control module 12, model construction module 13, trajectory prediction module 14, calculation module 15, mode trigger module 16, current compensation module 17. Specific embodiments

[0010] By providing an energy consumption optimization method and system for medium-intensity obstacle lights, the present application solves the technical problem of high energy consumption of medium-intensity obstacle lights in the prior art.

[0011] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0012] It should be noted that the terms "include" and "have" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0013] Embodiment 1, as Figure 1 shown, the present application provides an energy consumption optimization method for medium-intensity obstacle lights, wherein the method includes: Collect holographic environmental data of the target obstacle light, and perform adaptive dimming balance of the obstacle light according to the collection result, and output real-time light operation parameters and real-time light illumination mode, wherein the target obstacle light is a medium-intensity obstacle light.

[0014] Deploy multiple types of sensors around the target obstacle light (medium-intensity obstacle light), such as a light sensor for real-time monitoring of environmental light intensity and a meteorological sensor for collecting meteorological data; collect holographic environmental data around the target obstacle light through these sensors. Based on the holographic environmental data, match the preset matching light illumination mode mapping relationship library, and determine the adapted real-time light illumination mode and the corresponding real-time light operation parameters (including brightness, frequency, etc.), so as to realize the adaptive dimming balance control of the obstacle light for a complex light environment.

[0015] Furthermore, perform holographic environmental data collection on the target obstacle light, and perform adaptive dimming and equalization of the obstacle light based on the collection results, and output real-time operating parameters and real-time lighting modes. The method includes: Taking the ground coordinate of the target obstacle light as the center, construct an arithmetic radius sequence for circular deployment of the P-layer circular sensor array. Among them, the sensor nodes are integrated with wind speed sensors and transmittance sensors; use the P-layer circular sensor array to perform hierarchical surround environmental data collection to obtain real-time hierarchical environmental data; taking the ground coordinate of the target obstacle light as the origin, deploy H photosensitive sensors at H spatial azimuth angles to complete the configuration of the photosensitive sensor array; perform directional ambient light collection based on the photosensitive sensor array to obtain real-time array illumination data; perform adaptive dimming and equalization of the obstacle light based on the real-time hierarchical environmental data and the real-time array illumination data, and output the real-time operating parameters and real-time lighting modes.

[0016] Preferably, taking the ground coordinate of the target obstacle light as the center, construct a set of radius sequences with equal arithmetic spacing, and deploy a P-layer circular sensor array along this sequence. A number of sensor nodes are evenly distributed on each layer of the array, and each node is integrated with a wind speed sensor and a transmittance sensor to sense the wind flow disturbance and the change of atmospheric transparency at different distances and different azimuths around the obstacle light; through this multi-layer circular sensor structure, realize hierarchical surround collection of environmental parameters and summarize them into real-time hierarchical environmental data, including multi-layer wind speed distribution curves and corresponding light transmittance maps. On the basis of taking the ground coordinate of the target obstacle light as the origin, deploy H equally spaced photosensitive sensors at H set spatial azimuth angles to form a photosensitive sensor array with direction recognition ability, which is used to collect the natural ambient light intensity in each azimuth direction to form real-time array illumination data. This data can be used to analyze the intensity, offset direction and illuminance distribution balance of external natural light sources. Perform adaptive dimming and equalization of the obstacle light based on the real-time hierarchical environmental data and the real-time array illumination data, that is, determine the optimal brightness and frequency parameters required by the target obstacle light under the current environmental conditions, that is, the real-time operating parameters, and the real-time lighting mode (such as high transmittance mode, balanced energy-saving mode, etc.).

[0017] Furthermore, perform adaptive dimming and equalization of the obstacle light based on the real-time hierarchical environmental data and the real-time array illumination data, and output the real-time operating parameters and real-time lighting modes. The method includes: Calculate the wind speed gradient of the real-time hierarchical environmental data to locate the dominant environmental wind speed; use the horizontal distance between the P-layer annular sensor array and the ground coordinates of the target obstacle light as the hierarchical distance weight to perform transmittance hierarchical weighting on the real-time hierarchical environmental data and output the global transmittance; identify the maximum light intensity azimuth of the real-time array illumination data and output the light intensity extreme value; calculate the standard deviation of the real-time array illumination data and output the light intensity equilibrium characteristic; match and locate the real-time illumination mode and real-time operating parameters based on the dominant environmental wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic.

[0018] First, perform a spatial gradient calculation on the wind speed information collected by each annular sensor layer in the real-time hierarchical environmental data, analyze the wind speed change rate between each layer, extract the maximum change direction, and locate the current dominant environmental wind speed to judge the wind disturbance intensity and its main action direction in the current external environment. Second, use the horizontal distance between each P-layer annular sensor array and the ground coordinates of the target obstacle light as the hierarchical distance weight to perform weighted average processing on the transmittance data corresponding to each layer to obtain a global transmittance index with spatial attenuation characteristics, which is used to reflect the current atmospheric light flux propagation ability. Subsequently, based on the real-time array illumination data obtained by the photosensitive sensor array, traverse the H azimuth channels, extract the maximum light intensity direction and its corresponding value, and output the light intensity extreme value; at the same time, calculate the standard deviation of all the illumination values in the H channels as the light intensity equilibrium characteristic, which is used to quantify the uniformity and fluctuation level of the illumination distribution. Finally, use the dominant environmental wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic as input conditions, call the built-in illumination mode mapping model or query the light operation characteristic information library, and determine the currently most suitable real-time illumination mode (such as the direction enhancement mode, equilibrium energy-saving mode, high-transmittance emergency mode, etc.) through rule matching or weight optimization selection, and synchronously output the corresponding real-time operating parameters. The real-time operating parameters include the brightness level (such as high brightness, medium brightness, low brightness) and flashing frequency (such as the number of flashes per minute, flashing rhythm) of the obstacle light.

[0019] Furthermore, matching and locating the real-time illumination mode and real-time operating parameters based on the dominant environmental wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic, the method includes: Traverse the light operation characteristic information library according to the dominant environmental wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic to obtain the initial light operation parameters and the real-time illumination mode; call the light intensity direction angle of the light intensity extreme value; compensate the initial light operation parameters according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle, and output the real-time operating parameters.

[0020] The system uses the ambient dominant wind speed, global transmittance, extreme light intensity, and light intensity equilibrium characteristics as multi-dimensional input features, and calls the pre-constructed light operation feature information library. This library records the corresponding lighting control strategies under different environmental combination conditions. Through traversal and matching operations, the feature combination item closest to the current environment is extracted, and a set of initial light operation parameters (including brightness, current level, flicker frequency, etc.) and their corresponding real-time lighting modes (such as diffusion mode, directional enhancement mode, energy-saving equilibrium mode, etc.) are determined. The system obtains the light intensity direction angle corresponding to the extreme light intensity at the current moment from the photosensitive sensor array. This direction angle represents the spatial direction of the strongest light source or reflection source in the current natural environment, and is used to assist in judging the azimuthal characteristics of external light interference or light source enhancement areas. The system calls the device direction angle of the target obstacle light (i.e., the actual physical installation orientation of the obstacle light) and calculates the real-time angle deviation between it and the above light intensity direction angle; if this angle deviation exceeds the preset threshold, it indicates that the current lighting direction of the obstacle light is misaligned with the main direction of external light, which may lead to unbalanced lighting effects or decreased energy consumption efficiency. Based on this angle deviation, the system retrieves the matching compensation coefficient and compensation logic strategy in the compensation mapping table, and dynamically adjusts the initial light operation parameters: including performing directional enhancement compensation on the brightness level, or making adaptive fine-tuning on the flicker frequency, etc. Finally, the real-time light operation parameters coordinated with the current spatial lighting structure are output, improving the energy efficiency performance and direction response ability of the obstacle light in a complex light environment.

[0021] Furthermore, before compensating the initial light operation parameters according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle and outputting the real-time light operation parameters, it includes: Interactively obtain multiple sample compensation coefficients, multiple sample compensation logics for multiple sample deviation angles; aggregate the multiple sample compensation coefficients with a preset compensation coefficient deviation scale to obtain M sample compensation coefficients, M groups of sample deviation angles, and M groups of sample compensation logics; construct M angle deviation ranges according to the angle fluctuation thresholds of the M groups of sample deviation angles; extract M standard compensation logics according to the recurrence frequencies of the M groups of sample compensation logics; associatively map and store the M sample compensation coefficients, M angle deviation ranges, and M standard compensation logics to construct the compensation mapping relationship library.

[0022] Through experiments, multiple sample compensation coefficients and multiple sample compensation logics corresponding to multiple sample deviation angles are interactively obtained. Here, the sample deviation angle represents the spatial angle between the device direction angle and the light intensity direction angle. The sample compensation coefficient is used to quantify the parameter adjustment amplitude, and the sample compensation logic is used to define the adjustment strategy (such as brightness gain, frequency perturbation, or maintaining the current state). The system standardizes the obtained sample compensation coefficients and aggregates and classifies them according to a preset compensation coefficient deviation scale (such as a fixed ratio ladder or a statistical clustering interval), thereby obtaining M types of sample compensation coefficients, and corresponding combinations are made with the corresponding M groups of sample deviation angles and M groups of sample compensation logics to form a preliminary parameter set. The system sets an angle fluctuation threshold based on the variation range of the M groups of sample deviation angles and the possible perturbation levels in actual applications, and constructs M angle deviation ranges, each range covering a typical deviation response interval for quickly locating the current deviation section in actual applications. The system counts the recurrence frequencies of each compensation logic in the corresponding deviation angle range in the sample library to determine its adaptation stability and representativeness, and selects the most representative compensation strategy under each angle range to extract and form M standard compensation logics. By associating and mapping the M types of sample compensation coefficients, the M angle deviation ranges, and the M standard compensation logics one by one and storing them in a structured manner, a compensation mapping relationship library is constructed.

[0023] Furthermore, compensating the initial light operation parameters according to the angle deviation between the device direction angle and the light intensity direction angle of the target obstacle light, and outputting the real-time light operation parameters. The method includes: Calculating the real-time angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle; using the real-time angle deviation to retrieve and output the real-time compensation coefficient and the real-time compensation logic in the compensation mapping relationship library; using the real-time compensation coefficient to perform light intensity compensation on the initial light operation parameters, and using the real-time compensation logic to perform associated trigger enhancement on the initial light operation parameters, and outputting the real-time light operation parameters.

[0024] The system calculates the real-time angle deviation between the device direction angle (i.e., its physical installation or beam projection direction) of the target obstacle light and the light intensity direction angle (the azimuth angle corresponding to the extreme value of the light intensity in the current environment detected by the photosensitive sensor array). The real-time angle deviation is used to measure the deviation degree between the lighting direction of the obstacle light and the main direction of natural light.

[0025] The system uses the real-time angle deviation as the retrieval condition and quickly queries in the pre-constructed compensation mapping relationship library (Table 1) to extract the real-time compensation coefficient and real-time compensation logic that match the current deviation range. Among them, the compensation coefficient is used to quantitatively adjust parameters such as brightness, current, or illumination range; the compensation logic defines the enhanced strategy for parameter linkage, such as synchronously increasing the flicker frequency, enabling directional light-emitting components, adjusting the beam projection width, etc. Based on the compensation coefficient, the system proportionally amplifies the brightness level, current output, or other illumination intensity-related parameters in the initial light operation parameters, and executes the corresponding directional control strategy according to the compensation logic, such as enhancing the beam in a specific direction, weakening the backlight interference area, calling the direction rotation mechanism, etc., and finally outputs the real-time light operation parameters that match the current ambient light structure to achieve adaptive light emission control and energy consumption optimization under directional interference.

[0026] Table 1

[0027] After switching the target obstacle light to the real-time illumination mode, low-power light output control is performed according to the real-time light operation parameters.

[0028] After switching the target obstacle light to the real-time illumination mode, the system performs low-power light output control according to the real-time light operation parameters (including brightness level, current gear, flicker frequency, etc.) output by the previous environmental perception and dimming balance. Specifically, the system adjusts the light-emitting state of the medium-intensity obstacle light to the energy-saving operation state corresponding to the current real-time illumination mode through the lamp control unit.

[0029] Call the real-time hierarchical environmental data extension model radius from the holographic environmental data, and construct an airspace dynamic model centered on the ground coordinates of the target obstacle light.

[0030] The system extracts the wind speed, transmittance, and meteorological stability parameters of each layer of sensors at the current moment from the acquired holographic environmental data, analyzes the disturbance degree and propagation characteristics at different spatial levels, and evaluates the dynamic response range of the aircraft affected by the environment accordingly. Based on the analysis results, the system performs a model radius expansion operation on the sensing space around the obstacle light. This radius is not a fixed value but is dynamically adjusted according to the real-time environmental state. For example, in the case of increasing wind speed, decreasing transmittance, or enhanced meteorological disturbance, the system will expand the coverage radius of the sensing model to expand the ability to predict the deviation trajectory of potential aircraft; in a stable environment with balanced lighting, the system maintains the basic model radius to ensure processing efficiency and energy-saving goals. Subsequently, taking the ground coordinates of the light intensity obstacle light in the target as the center point and combining the dynamic radius parameter, a three-dimensional airspace dynamic model is constructed. This model is usually a cylinder, sphere, or irregular semi-closed space body, and the coverage range covers a certain height above the obstacle light (such as the minimum safe flight height) and the extension radius of the horizontal plane. The three-dimensional airspace dynamic model is not only used to record the effective lighting influence range of the current obstacle light but also serves as a spatial reference benchmark for flight trajectory prediction and intersection judgment.

[0031] Predict the trajectory of the aircraft within a preset time window based on multi-source aviation information and output the dynamic trajectory of the aircraft.

[0032] By accessing multi-source aviation information such as ADS-B data, flight schedules, and flight status platforms, extract flight parameters of the aircraft such as the current position, speed, heading, and altitude; combine the ground coordinates of the target obstacle light and the current environmental wind speed gradient, map the aircraft's motion state to the polar coordinate system or three-dimensional space, and perform trajectory extrapolation prediction based on a simplified flight dynamics model; at the same time, introduce airspace control information to avoid no-fly zones for the predicted path and generate a high-confidence aviation trajectory; finally, extract the trajectory segments that fall within the preset time window and output them as the dynamic trajectory of the aircraft.

[0033] Furthermore, predicting the trajectory of the aircraft within a preset time window based on multi-source aviation information and outputting the dynamic trajectory of the aircraft, the method includes: Access civil aviation broadcast data, and parse and output multiple aviation real-time associated data based on the pre-stored flight schedule and the civil aviation broadcast data; calculate and output the real-time wind speed gradient according to the real-time hierarchical environmental data; after converting the multiple aviation real-time associated data to the polar coordinate system centered on the ground coordinates of the target obstacle light, use the real-time wind speed gradient as the lateral acceleration correction feature to predict the dynamic behavior of the aircraft in the polar coordinate system and output multiple initial dynamic trajectories; interactively obtain airspace control information to perform no-fly zone path avoidance prediction on the multiple initial dynamic trajectories and output multiple high-confidence aviation trajectories; segment the aircraft's dynamic trajectory that falls within the preset time window from the multiple high-confidence aviation trajectories.

[0034] The system accesses civil aviation broadcast data (such as ADS - B, Mode - S, etc.), and combines with the pre - stored local flight schedule database to fuse and analyze information such as the flight number, flight altitude, speed, heading, geographical location, etc. of the current aircraft, generating multiple real - time aviation correlation data with time and space attributes. The system calls the wind speed measurement values of each layer in the real - time hierarchical environmental data, calculates the wind speed change rate for different spatial altitude segments, and outputs the real - time wind speed gradient within the current airspace. This gradient information is used to simulate the lateral offset trend of the aircraft affected by wind disturbance at different altitude layers. By mapping and transforming the real - time aviation correlation data into a polar coordinate system constructed with the ground coordinates of the target obstacle light as the origin, the relative position and heading of the aircraft are established in this coordinate system; the wind speed gradient is introduced as a lateral acceleration correction feature into the aircraft motion model, and the behavior simulation of the aircraft based on simplified dynamics and flight path propagation is carried out to generate multiple initial dynamic trajectories, representing the predicted flight paths under unconstrained airspace conditions. The system interacts with the air traffic control platform or the aviation supervision database to obtain airspace control information (such as no - fly zone boundaries, temporary restricted areas, etc.), and embeds it into the flight path prediction model to perform no - fly zone avoidance optimization calculations on the initial dynamic trajectories to obtain multiple high - confidence aviation trajectories that meet the constraint conditions. Trajectory segments that are likely to enter the dynamic model of the target obstacle light airspace within the set preset time window (such as the next 30 seconds, 60 seconds) are extracted from the high - confidence aviation trajectories to form the aircraft dynamic trajectory corresponding to the current moment, providing a spatio - temporal input basis for subsequent airspace intersection judgment and obstacle light power response control.

[0035] If there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model, calculate the intersection time window based on time extension.

[0036] If there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model, the system analyzes the interaction process between the trajectory and the model based on the time extension strategy and calculates the intersection time window. Specifically, the system uses the airspace dynamic model constructed with the target obstacle light as the center as a three - dimensional space boundary reference, traverses the spatial position points of each predicted time step in the aircraft dynamic trajectory, and determines whether the position point falls within the airspace model range. When the trajectory first enters the airspace dynamic model, record the corresponding predicted time point as the intersection entry time; continue to judge the subsequent trajectory points until the trajectory point leaves the model boundary, and record the corresponding time point at this time as the intersection exit time. Thus, a closed intersection time window is formed, that is, the time interval during which the aircraft predicted trajectory spatially coincides with the obstacle light airspace model within the preset time window.

[0037] Trigger the target obstacle light to switch to the full - power light output mode with the real - time lighting mode as the mode constraint and the intersection time window as the time constraint.

[0038] The system determines whether the current obstacle light has the ability to switch and the switching path (e.g., switching from the directional low-power mode to the full-view high-power mode) according to the real-time lighting mode. If the current mode allows upward switching, the mode switching behavior is incorporated into the execution judgment process. When the current system clock reaches the start time of the intersection time window, the system immediately triggers the obstacle light control unit to execute the power scheduling instruction and adjusts the optical operation parameters to the full-power state (full-power light output mode), including: increasing the brightness level to the maximum, increasing the light-emitting angle coverage range, and adjusting the flashing frequency to meet the aviation warning standard requirements (such as flashing 60 times per minute, etc.).

[0039] Perform adaptive current compensation according to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode.

[0040] After the target obstacle light enters the full-power light output mode, the system performs adaptive current compensation control according to its temperature rise characteristics and component temperature difference characteristics during operation. Specifically, by monitoring the temperature changes of multiple heating modules inside the obstacle light in real time, the overall temperature rise rate and local temperature difference extreme values of the device are extracted and used as input parameters to map to a preset temperature difference-current compensation relationship model to obtain the corresponding current compensation ratio and compensation logic. The system dynamically adjusts the drive current output accordingly and combines the PID current control strategy to achieve fine adjustment of the lighting current, effectively controlling the heat load, preventing overheating, and extending the service life of the device while ensuring that the output brightness of the obstacle light meets the aviation safety requirements.

[0041] Furthermore, perform adaptive current compensation according to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode. The methods include: Perform multi-module temperature rise monitoring on the target obstacle light to obtain multiple time-series temperature rise sequences; calculate the extreme value of the temperature rise speed gradient of the multiple time-series temperature rise sequences as the device temperature rise characteristic; calculate the extreme value of the temperature difference across the multiple time-series temperature rise sequences as the component temperature difference characteristic; map the device temperature rise characteristic and the component temperature difference characteristic to a temperature difference-current compensation table to locate the real-time current compensation ratio and real-time current compensation logic; apply the real-time current compensation ratio and real-time current compensation logic to the PID current dynamic control.

[0042] First, perform multi-module temperature rise monitoring on multiple key thermal units inside the target obstacle lamp, including but not limited to the LED lighting module, drive power supply, heat dissipation module, reflective cavity, etc. By deploying acquisition devices such as thermocouples and digital temperature sensors, collect the temperature changes of each monitoring point in the time series respectively to form multiple time-series temperature rise sequences. Then, analyze and process the multiple time-series temperature rise sequences. Calculate the first derivative of the temperature change with respect to time for each sequence, and extract the extreme value of the temperature rise speed gradient (such as the maximum positive slope or the steepest growth rate) as the device temperature rise characteristic of the obstacle lamp under the current operating state, which is used to reflect the overall thermal rise dynamic trend and response intensity. At the same time, the system performs cross-sequence comparison calculations on each time-series sequence at the same time node, extracts the extreme value of the temperature difference between different modules to form the component temperature difference characteristic, which is used to determine the local thermal imbalance state, heat dissipation lag or potential thermal abnormality. Subsequently, use the above temperature rise characteristics and temperature difference characteristics as double input parameters, map them to the pre-constructed temperature difference-current compensation table, retrieve the matching item in Table 2 to obtain the real-time current compensation ratio (such as ±5%, ±10%, current limit 50%, etc.) that matches the current thermal state and the corresponding real-time current compensation logic (such as continuous peak shaving and current limiting, short-term overclocking protection, segmented current sharing strategy, etc.). Finally, the system inputs the real-time current compensation ratio and compensation logic into the PID current dynamic controller to perform closed-loop control and adjustment on the current LED drive current, and adjust the output power in real time to ensure that, on the premise of meeting the full-power warning requirements, an active response to excessive temperature rise or excessive temperature difference is achieved, ensuring the thermal stability of the system and extending the service life of the device.

[0043] Table 2

[0044] Furthermore, according to the device temperature rise characteristic and component temperature difference characteristic of the target obstacle lamp in the full-power light output mode, perform adaptive current compensation. After that, it includes: Collect the device temperature drop characteristic of the target obstacle lamp; trigger the fan for heat dissipation according to the deviation between the device temperature drop characteristic and the preset time-varying threshold of temperature drop.

[0045] After performing adaptive current compensation based on the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode, the system continuously collects the device temperature drop characteristics of the key components of the obstacle light (such as LED modules, drive power supplies, heat dissipation substrates, etc.) gradually decreasing from the peak temperature during their operation, forming a temperature-time drop curve to reflect the current heat energy release efficiency and passive heat dissipation ability. Subsequently, the system compares and analyzes the collected temperature drop characteristics with the pre-set time-varying temperature drop threshold, which can be dynamically set according to factors such as device type, heat capacity, and ambient temperature, to determine whether the temperature drop rate is lower than the system's safe cooling requirement. When it is detected that the actual temperature drop rate is lower than the preset threshold, it indicates that the passive heat dissipation of the obstacle light is insufficient, there is local heat accumulation or poor heat release, and the system then triggers the active fan heat dissipation mechanism, starts the integrated air cooling module, and improves the heat exchange efficiency around the device by enhancing air convection to quickly reduce the component temperature and prevent thermal runaway, performance drift, or material aging.

[0046] In summary, the embodiments of the present application at least have the following technical effects: First, holographic environmental data of the target obstacle light is collected, and adaptive dimming balance of the obstacle light is performed according to the collection results, and real-time light operation parameters and real-time illumination modes are output. Among them, the target obstacle light is a medium-intensity obstacle light. After switching the target obstacle light to the real-time illumination mode, low-power light output control is performed according to the real-time light operation parameters. Then, the radius of the real-time hierarchical environmental data expansion model is called from the holographic environmental data, and an airspace dynamic model is constructed with the ground coordinates of the target obstacle light as the center. At the same time, the aircraft trajectory is predicted within a preset time window according to multi-source aviation information, and the aircraft dynamic trajectory is output. If there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model, the intersection time window is calculated based on time extension. Then, with the real-time illumination mode as the mode constraint and the intersection time window as the time constraint, the target obstacle light is triggered to switch to the full-power light output mode. Finally, adaptive current compensation is performed according to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode. The technical problem of high energy consumption of medium-intensity obstacle lights in the prior art is solved, and the technical effects of reducing energy consumption and extending the device life are achieved.

[0047] Embodiment 2, based on the same inventive concept as the method for optimizing the energy consumption of a medium-intensity obstacle light in the foregoing embodiment, as Figure 2 shown, the present application provides a system for optimizing the energy consumption of a medium-intensity obstacle light, wherein the system includes: The dimming equalization module 11 is used to collect holographic environmental data for the target obstacle light, perform adaptive dimming equalization of the obstacle light according to the collection results, and output real-time operating parameters and real-time illumination modes. Among them, the target obstacle light is a medium-intensity obstacle light; the control module 12 is used to control the low-power light output according to the real-time operating parameters after switching the target obstacle light to the real-time illumination mode; the model construction module 13 is used to call the real-time hierarchical environmental data expansion model radius from the holographic environmental data, and construct an airspace dynamic model with the ground coordinates of the target obstacle light as the center; the trajectory prediction module 14 is used to predict the aircraft trajectory within a preset time window according to multi-source aviation information, and output the aircraft dynamic trajectory; the calculation module 15 is used to calculate the intersection time window based on time extension if there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model; the mode trigger module 16 is used to trigger the target obstacle light to switch to the full-power light output mode with the real-time illumination mode as the mode constraint and the intersection time window as the time constraint; the current compensation module 17 is used to perform adaptive current compensation according to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode.

[0048] Further, the current compensation module 17 is used to execute the following method: Monitor the temperature rise of multiple modules of the target obstacle light to obtain multiple sequential temperature rise sequences; calculate the extreme value of the temperature rise speed gradient of the multiple sequential temperature rise sequences as the device temperature rise characteristic; calculate the extreme value of the temperature difference across sequences from the multiple sequential temperature rise sequences as the component temperature difference characteristic; map the device temperature rise characteristic and the component temperature difference characteristic to a temperature difference-current compensation table to locate the real-time current compensation ratio and the real-time current compensation logic; apply the real-time current compensation ratio and the real-time current compensation logic to the PID current dynamic control.

[0049] Further, the dimming equalization module 11 is used to execute the following method: Construct an arithmetic radius sequence with the ground coordinates of the target obstacle light as the center for the circular deployment of the P-layer circular sensor array, where the sensor nodes are integrated with wind speed sensors and transmittance sensors; use the P-layer circular sensor array to perform hierarchical surrounding environmental data collection to obtain real-time hierarchical environmental data; deploy H photosensitive sensors at H spatial azimuth angles with the ground coordinates of the target obstacle light as the origin to complete the configuration of the photosensitive sensor array; perform directional ambient light collection based on the photosensitive sensor array to obtain real-time array illumination data; perform adaptive dimming equalization of the obstacle light according to the real-time hierarchical environmental data and the real-time array illumination data, and output the real-time operating parameters and the real-time illumination mode.

[0050] Further, the dimming equalization module 11 is used to execute the following method: Perform wind speed gradient calculation on the real-time hierarchical environment data to locate the dominant environmental wind speed; use the horizontal distance between the P-layer annular sensor array and the ground coordinates of the target obstacle light as the hierarchical distance weight to perform transmittance hierarchical weighting on the real-time hierarchical environment data and output the global transmittance; perform maximum light intensity azimuth recognition on the real-time array illumination data and output the light intensity extreme value; perform standard deviation calculation on the real-time array illumination data and output the light intensity equilibrium characteristic; match and locate the real-time illumination mode and real-time operating parameters based on the dominant environmental wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic.

[0051] Further, the trajectory prediction module 14 is used to execute the following method: Access civil aviation broadcast data, and parse and output multiple aviation real-time correlation data based on the pre-stored flight schedule and the civil aviation broadcast data; calculate and output the real-time wind speed gradient according to the real-time hierarchical environment data; after converting the multiple aviation real-time correlation data to a polar coordinate system centered on the ground coordinates of the target obstacle light, use the real-time wind speed gradient as the lateral acceleration correction feature to predict the dynamic behavior of the aircraft in the polar coordinate system and output multiple initial dynamic trajectories; interactively obtain airspace control information to perform no-fly zone path avoidance prediction on the multiple initial dynamic trajectories and output multiple high-confidence aviation trajectories; segment the dynamic trajectory of the aircraft falling within the preset time window from the multiple high-confidence aviation trajectories.

[0052] Further, the dimming equilibrium module 11 is used to execute the following method: Based on the dominant environmental wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic, traverse the light operation feature information library to obtain the initial light operation parameters and the real-time illumination mode; call the light intensity direction angle of the light intensity extreme value; compensate the initial light operation parameters according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle, and output the real-time light operation parameters.

[0053] Further, the dimming equilibrium module 11 is used to execute the following method: Calculate the real-time angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle; use the real-time angle deviation to retrieve and output the real-time compensation coefficient and real-time compensation logic in the compensation mapping relationship library; use the real-time compensation coefficient to perform light intensity compensation on the initial light operation parameters, and use the real-time compensation logic to perform associated trigger enhancement on the initial light operation parameters, and output the real-time light operation parameters.

[0054] Further, the dimming equilibrium module 11 is used to execute the following method: Interactively obtain multiple sample compensation coefficients and multiple sample compensation logics for multiple sample deviation angles; preset a compensation coefficient deviation scale to aggregate the multiple sample compensation coefficients to obtain M types of sample compensation coefficients, M groups of sample deviation angles, and M groups of sample compensation logics; construct M angular deviation ranges according to the angular fluctuation thresholds of the M groups of sample deviation angles; extract M standard compensation logics according to the recurrence frequencies of the M groups of sample compensation logics; and associatively map and store the M types of sample compensation coefficients, M angular deviation ranges, and M standard compensation logics to construct the compensation mapping relationship library.

[0055] Further, the current compensation module 17 is used to execute the following method: Collect the device temperature drop characteristics of the target obstacle lamp; trigger the fan for heat dissipation according to the deviation between the device temperature drop characteristics and the preset time-varying temperature drop threshold.

[0056] It should be noted that the above sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above describes specific embodiments of this specification. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0057] The above are only the preferred embodiments of the present application and are not used to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

[0058] This specification and the drawings are only exemplary descriptions of the present application and are considered to have covered any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. An energy consumption optimization method for medium-intensity obstacle lights, characterized in that, The method includes: Performing holographic environmental data acquisition on a target obstacle light, and performing adaptive dimming equalization of the obstacle light according to the acquisition results, and outputting real-time light operation parameters and a real-time light illumination mode, where the target obstacle light is a medium-intensity obstacle light; After switching the target obstacle light to the real-time light illumination mode, performing low-power light output control according to the real-time light operation parameters; Calling a real-time hierarchical environmental data expansion model radius from the holographic environmental data, and constructing an airspace dynamic model with the ground coordinates of the target obstacle light as the center; Predicting the aircraft trajectory within a preset time window based on multi-source aviation information, and outputting the aircraft dynamic trajectory; If there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model, calculating an intersection time window based on time extension; Triggering the target obstacle light to switch to the full-power light output mode with the real-time light illumination mode as the mode constraint and the intersection time window as the time constraint; Performing adaptive current compensation according to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode.

2. The energy consumption optimization method for medium-intensity obstacle lights according to claim 1, characterized in that, Performing adaptive current compensation according to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full-power light output mode, the method includes: Performing multi-module temperature rise monitoring on the target obstacle light to obtain multiple sequential temperature rise sequences; Calculating the extreme value of the temperature rise speed gradient of the multiple sequential temperature rise sequences as the device temperature rise characteristic; Calculating the extreme value of the temperature difference across sequences from the multiple sequential temperature rise sequences as the component temperature difference characteristic; Mapping the device temperature rise characteristic and the component temperature difference characteristic to a temperature difference - current compensation table to locate the real-time current compensation ratio and the real-time current compensation logic; Applying the real-time current compensation ratio and the real-time current compensation logic to PID current dynamic control.

3. The energy consumption optimization method for medium-intensity obstacle lights as described in claim 1, characterized in that Performing holographic environmental data acquisition on a target obstacle light, and performing adaptive dimming equalization of the obstacle light according to the acquisition results, and outputting real-time light operation parameters and a real-time light illumination mode, the method includes: Constructing an arithmetic radius sequence with the ground coordinates of the target obstacle light as the center of the circle for circular deployment of a P-layer circular sensor array, where the sensor nodes are integrated with a wind speed sensor and a transmittance sensor; Using the P-layer circular sensor array to perform hierarchical surround environmental data acquisition to obtain real-time hierarchical environmental data; Deploying H photosensitive sensors at H spatial azimuth angles with the ground coordinates of the target obstacle light as the origin to complete the configuration of the photosensitive sensor array; Performing directional ambient light acquisition based on the photosensitive sensor array to obtain real-time array illumination data; Performing adaptive dimming equalization of the obstacle light according to the real-time hierarchical environmental data and the real-time array illumination data, and outputting the real-time light operation parameters and the real-time light illumination mode.

4. The energy consumption optimization method for medium-intensity obstacle lights according to claim 3, wherein Performing adaptive dimming equalization of the obstacle light according to the real-time hierarchical environmental data and the real-time array illumination data, and outputting the real-time light operation parameters and the real-time light illumination mode, the method includes: Calculating the wind speed gradient of the real-time hierarchical environmental data to locate the environmental dominant wind speed; Take the horizontal distance between the P-layer annular sensor array and the ground coordinates of the target obstacle light as the hierarchical distance weight, perform transmittance hierarchical weighting on the real-time hierarchical environment data, and output the global transmittance; Identify the azimuth of the maximum light intensity for the real-time array illumination data and output the light intensity extreme value; Calculate the standard deviation of the real-time array illumination data and output the light intensity equilibrium characteristic; Match and locate the real-time illumination mode and real-time operating parameters based on the environmental dominant wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic.

5. The energy consumption optimization method for medium-intensity obstacle lights according to claim 4, characterized in that, Predict the aircraft trajectory within a preset time window based on multi-source aviation information and output the aircraft dynamic trajectory. The method includes: Access civil aviation broadcast data and parse and output multiple aviation real-time association data based on the pre-stored flight schedule and the civil aviation broadcast data; Calculate and output the real-time wind speed gradient based on the real-time hierarchical environment data; After converting the multiple aviation real-time association data to a polar coordinate system centered on the ground coordinates of the target obstacle light, use the real-time wind speed gradient as the lateral acceleration correction feature to perform aircraft dynamic behavior prediction in the polar coordinate system and output multiple initial dynamic trajectories; Interactively obtain airspace control information to perform no-fly zone path avoidance prediction on the multiple initial dynamic trajectories and output multiple high-confidence aviation trajectories; Segment the aircraft dynamic trajectory falling within the preset time window from the multiple high-confidence aviation trajectories.

6. The energy consumption optimization method for medium-intensity obstacle lights according to claim 4, characterized in that Match and locate the real-time illumination mode and real-time operating parameters based on the environmental dominant wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic. The method includes: Traverse the light operation feature information library based on the environmental dominant wind speed, global transmittance, light intensity extreme value, and light intensity equilibrium characteristic to obtain the initial light operation parameters and the real-time illumination mode; Call the light intensity direction angle of the light intensity extreme value; Compensate the initial light operation parameters according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle, and output the real-time light operation parameters.

7. The energy consumption optimization method for medium-intensity obstacle lights according to claim 6, characterized in that Compensate the initial light operation parameters according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle, and output the real-time light operation parameters. The method includes: Calculate the real-time angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle; Retrieve and output the real-time compensation coefficient and real-time compensation logic in the compensation mapping relationship library using the real-time angle deviation; Perform light intensity compensation on the initial light operation parameters using the real-time compensation coefficient, and perform associated trigger enhancement on the initial light operation parameters using the real-time compensation logic, and output the real-time light operation parameters.

8. The energy consumption optimization method for medium-intensity obstacle lights according to claim 7, characterized in that, Before compensating the initial light operation parameters according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle and outputting the real-time light operation parameters, the method includes: Interactively obtain multiple sample compensation coefficients and multiple sample compensation logics for multiple sample deviation angles; Preset a compensation coefficient deviation scale to aggregate the multiple sample compensation coefficients to obtain M types of sample compensation coefficients, M groups of sample deviation angles, and M groups of sample compensation logics; Construct M angle deviation ranges according to the angle fluctuation threshold of the M groups of sample deviation angles; Extract M standard compensation logics according to the recurrence frequency of the M - group sample compensation logics; Associate and map to store the M sample compensation coefficients, M angular deviation ranges, and M standard compensation logics, and construct the compensation mapping relationship library.

9. The energy consumption optimization method for medium-intensity obstacle lights according to claim 2, characterized in that According to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full - power light output mode, perform adaptive current compensation. After that, the method includes: Collect the device temperature drop characteristics of the target obstacle light; Trigger the fan cooling according to the deviation between the device temperature drop characteristics and the preset temperature drop time - varying threshold.

10. An energy consumption optimization system for medium-intensity obstacle lights, characterized in that, For implementing an energy consumption optimization method for a medium - intensity obstacle light according to any one of claims 1 - 9, the system includes: A dimming equalization module, configured to collect holographic environmental data of the target obstacle light, and perform adaptive dimming equalization of the obstacle light according to the collection result, and output real - time light operation parameters and real - time lighting modes, where the target obstacle light is a medium - intensity obstacle light; A control module, configured to control the low - power light output according to the real - time light operation parameters after switching the target obstacle light to the real - time lighting mode; A model construction module, configured to call the real - time hierarchical environmental data expansion model radius from the holographic environmental data, and construct an airspace dynamic model with the ground coordinates of the target obstacle light as the center; A trajectory prediction module, configured to predict the aircraft trajectory within a preset time window according to multi - source aviation information, and output the aircraft dynamic trajectory; A calculation module, configured to calculate the intersection time window based on time extension if there is an intersection between the aircraft dynamic trajectory and the airspace dynamic model; A mode trigger module, configured to trigger the target obstacle light to switch to the full - power light output mode with the real - time lighting mode as the mode constraint and the intersection time window as the time constraint; A current compensation module, configured to perform adaptive current compensation according to the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in the full - power light output mode.

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