Energy consumption optimization method and system for medium intensity obstruction light

Abstract

The application discloses an energy consumption optimization method and system for a medium-intensity obstruction light, and relates to the technical field of obstruction light energy consumption optimization.The method comprises the following steps: collecting holographic environment data of a target obstruction light, and performing adaptive light adjustment and equalization of the obstruction light, to output real-time light operation parameters and a real-time light mode; after the target obstruction light is switched to the real-time light mode, low-power light output control is performed according to the real-time light operation parameters; an airspace dynamic model is constructed; aircraft trajectory prediction in a preset time window is performed, to output an aircraft dynamic trajectory; if there is an intersection, an intersection time window is calculated; the target obstruction light is triggered to be switched to a full-power light output mode; adaptive current compensation is performed according to equipment temperature rise characteristics and component temperature difference characteristics of the target obstruction light in the full-power light output mode.The technical problem of high energy consumption of a medium-intensity obstruction light in the prior art is solved, and the technical effects of reducing energy consumption and prolonging equipment life are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of obstacle light energy consumption optimization, and particularly relates to an energy consumption optimization method and system for medium-intensity obstacle light. BACKGROUND

[0002] Medium-intensity obstacle light is widely used in warning lighting systems of high-rise buildings, communication towers, wind turbine generators and other aviation obstacles. Its function is to provide position identification signals for aircraft in night or low-visibility environments to ensure flight safety. In order to ensure the visible distance and warning effect, the existing medium-intensity obstacle light usually adopts a fixed power or time period switching operation mode. Even in the case of no aircraft approaching or stable weather conditions, high-intensity lighting output is still maintained, resulting in problems such as waste of electric energy, increase of equipment thermal load and reduction of service life. SUMMARY

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

[0004] In a first aspect, the present application provides an energy consumption optimization method for medium-intensity obstacle light, which comprises:

[0005] Holographic environment data of the target obstacle light is collected, and adaptive dimming balancing of the obstacle light is performed according to the collection result, to output real-time light operation parameters and a real-time light mode. The target obstacle light is a medium-intensity obstacle light. After the target obstacle light is switched to the real-time light mode, low-power light output control is performed according to the real-time light operation parameters. Real-time hierarchical environment data extension model radius is called from the holographic environment data, and a space dynamic model is constructed with the ground coordinates of the target obstacle light as the center. Aircraft trajectory prediction in a preset time window is performed according to multi-source aviation information, to output an aircraft dynamic trajectory. If the aircraft dynamic trajectory and the space dynamic model have an intersection, an intersection time window is calculated based on time extension. The real-time light mode is taken as a mode constraint, and the intersection time window is taken as a time constraint, to trigger the target obstacle light to switch to a full-power light output mode. Adaptive current compensation is performed according to the device temperature rise characteristics and the component temperature difference characteristics of the target obstacle light in the full-power light output mode.

[0006] In a second aspect, the present application provides an energy consumption optimization system for medium-intensity obstacle light, which comprises:

[0007] The light modulation balancing module is used for holographic environment data collection of a target obstruction light and adaptive light modulation balancing of the obstruction light according to the collection result, and outputs real-time light operation parameters and a real-time light mode, wherein the target obstruction light is a medium-intensity obstruction light; the control module is used for low-power light output control according to the real-time light operation parameters after the target obstruction light is switched to the real-time light mode; the model construction module is used for calling a real-time hierarchical environment data expansion model radius from the holographic environment data, and constructing a space dynamic model with the ground coordinates of the target obstruction light as the center; the trajectory prediction module is used for aircraft trajectory prediction in a preset time window according to multi-source aviation information, and outputs an aircraft dynamic trajectory; the calculation module is used for calculating an intersection time window based on time extension if the aircraft dynamic trajectory intersects with the space dynamic model; the mode triggering module is used for triggering the target obstruction light to switch to a full-power light output mode with the real-time light mode as a mode constraint and the intersection time window as a time constraint; and the current compensation module is used for adaptive current compensation according to the device temperature rise characteristics and the component temperature difference characteristics of the target obstruction light in the full-power light output mode.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] Firstly, holographic environment data of a target obstruction light is collected, and adaptive light modulation balancing of the obstruction light is performed according to the collection result, and real-time light operation parameters and a real-time light mode are output, wherein the target obstruction light is a medium-intensity obstruction light. After the target obstruction light is switched to the real-time light mode, low-power light output control is performed according to the real-time light operation parameters. Then, a real-time hierarchical environment data expansion model radius is called from the holographic environment data, and a space dynamic model is constructed with the ground coordinates of the target obstruction light as the center. Meanwhile, aircraft trajectory prediction in a preset time window is performed according to multi-source aviation information, and an aircraft dynamic trajectory is output. If the aircraft dynamic trajectory intersects with the space dynamic model, an intersection time window is calculated based on time extension. Then, the target obstruction light is triggered to switch to a full-power light output mode with the real-time light mode as a mode constraint and the intersection time window as a time constraint. Finally, adaptive current compensation is performed according to the device temperature rise characteristics and the component temperature difference characteristics of the target obstruction light in the full-power light output mode. The technical problem of high energy consumption of the medium-intensity obstruction light in the prior art is solved, and the technical effects of reducing energy consumption and prolonging the service life of the equipment are achieved. BRIEF DESCRIPTION OF DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0011] Figure 1 A flow chart of an energy consumption optimization method for a medium-intensity obstruction beacon is provided for the embodiments of the present application;

[0012] Figure 2 A system structure diagram of an energy consumption optimization system for a medium-intensity obstruction beacon is provided for the embodiments of the present application.

[0013] Legend: dimming equalization module 11, control module 12, model construction module 13, trajectory prediction module 14, calculation module 15, mode triggering module 16, current compensation module 17. DETAILED DESCRIPTION

[0014] The present application provides an energy consumption optimization method and system for a medium-intensity obstruction beacon, solving the technical problem of high energy consumption of a medium-intensity obstruction beacon in the prior art.

[0015] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0016] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion, for example, a process, method, system, product or server comprising a series of steps or units need not be limited to only those steps or units clearly listed, but can include other steps or modules not clearly listed or inherent to these processes, methods, products or devices.

[0017] Embodiment one, as shown in the present application, an energy consumption optimization method for a medium-intensity obstruction beacon is provided, wherein the method comprises: Figure 1

[0018] Holographic environment data of the target obstruction beacon is collected, and adaptive dimming equalization of the obstruction beacon is performed according to the collection results, outputting real-time light operation parameters and real-time light modes, wherein the target obstruction beacon is a medium-intensity obstruction beacon.

[0019] A plurality of types of sensors are deployed around the target obstruction beacon (medium-intensity obstruction beacon), such as light sensors for real-time monitoring of ambient light intensity, and weather sensors for collecting weather data; holographic environment data around the target obstruction beacon is collected through these sensors. Based on the holographic environment data, a pre-set matching light mode mapping relationship library is matched to determine the adaptive real-time light mode and the corresponding real-time light operation parameters (including brightness, frequency, etc.), thereby realizing adaptive dimming equalization control of the obstruction beacon to complex light environment.​

[0020] Further, the target obstruction light is collected with holographic environmental data, and the obstruction light adaptive light adjustment and equalization are carried out according to the collection results, and the real-time light operation parameters and real-time light mode are output, the method comprising:

[0021] The ground coordinates of the target obstruction light are taken as the center, a sequence of equal-difference radii is constructed, and a P-layer ring-shaped sensor array is deployed in a ring shape, wherein the sensor nodes are integrated with wind speed sensors and transmittance sensors; the P-layer ring-shaped sensor array is used for hierarchical surrounding environmental data collection to obtain real-time hierarchical environmental data; H photosensitive sensors are deployed at H spatial azimuth angles with the ground coordinates of the target obstruction light as the origin, and a photosensitive sensor array is configured; directional environmental light is collected based on the photosensitive sensor array to obtain real-time array illumination data; the obstruction light adaptive light adjustment and equalization are carried out according to the real-time hierarchical environmental data and real-time array illumination data, and the real-time light operation parameters and real-time light mode are output.

[0022] Preferably, the ground coordinates of the target obstruction light are taken as the center, a sequence of radii with equal-difference intervals is constructed, and a P-layer ring-shaped sensor array is deployed along the sequence, a plurality of sensor nodes are uniformly distributed on each layer array, each node is integrated with a wind speed sensor and a transmittance sensor, and is used for sensing wind flow disturbance and atmospheric transparency changes at different distances and different azimuths around the obstruction light; through the multi-layer ring-shaped sensor structure, hierarchical surrounding environmental data collection is realized, and the real-time hierarchical environmental data are summarized, including multi-layer wind speed distribution curves and corresponding light transmittance maps. Based on the ground coordinates of the target obstruction light as the origin, H equally spaced photosensitive sensors are deployed at H spatial azimuth angles to form a photosensitive sensor array with direction recognition capability, which is used for collecting natural environmental light intensity in each azimuth direction to form real-time array illumination data, which can be used to analyze the intensity, offset direction and illumination distribution uniformity of external natural light sources. Based on the real-time hierarchical environmental data and real-time array illumination data, the obstruction light adaptive light adjustment and equalization are carried out, that is, the optimal brightness and frequency parameters required by the target obstruction light under the current environmental conditions are determined, that is, the real-time light operation parameters and the real-time light mode (such as high-transmittance mode, equalization energy-saving mode, etc.).

[0023] Further, the obstruction light adaptive light adjustment and equalization are carried out according to the real-time hierarchical environmental data and real-time array illumination data, and the real-time light operation parameters and real-time light mode are output, the method comprising:

[0024] perform wind speed gradient calculation on the real-time hierarchical environment data to locate an environment dominant wind speed; perform transmittance hierarchical weighting on the real-time hierarchical environment data by taking the horizontal distance between the P-layer annular sensor array and the ground coordinates of the target obstruction light as a hierarchical distance weight, and output global transmittance; perform maximum light intensity azimuth identification on the real-time array illumination data, and output a light intensity extreme value; perform standard deviation calculation on the real-time array illumination data, and output a light intensity balance characteristic; and match and locate the real-time illumination mode and real-time light operation parameters according to the environment dominant wind speed, global transmittance, light intensity extreme value and light intensity balance characteristic.

[0025] First, spatial gradient calculation is performed on the wind speed information collected by each annular sensor layer in the real-time hierarchical environment data, the wind speed change rate between each layer is analyzed, the maximum change direction is extracted and the current environment dominant wind speed is located, which is used to judge the wind disturbance intensity and its main action direction in the current external environment. Secondly, the horizontal distance between each P-layer annular sensor array and the ground coordinates of the target obstruction light is taken as a hierarchical distance weight, and the corresponding transmittance data of each layer is weighted and averaged 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, the maximum light intensity direction and its corresponding value are extracted by traversing H azimuth channels, and the light intensity extreme value is output; at the same time, the standard deviation of all illumination values of the H channels is calculated as the light intensity balance characteristic, which is used to quantify the uniformity and fluctuation level of the light distribution. Finally, the environment dominant wind speed, global transmittance, light intensity extreme value and light intensity balance characteristic are taken as input conditions, the built-in illumination mode mapping model or the light operation characteristic information library is called, and the current most suitable real-time illumination mode (such as direction enhancement mode, balanced energy saving mode, high transmittance emergency mode, etc.) is determined through rule matching or weight optimization selection, and the corresponding real-time light operation parameters are output synchronously, including the brightness level (such as high brightness, medium brightness, low brightness) and the flashing frequency (such as the number of flashes per minute, the flashing rhythm) of the obstruction light.

[0026] Further, according to the environment dominant wind speed, global transmittance, light intensity extreme value and light intensity balance characteristic, the real-time illumination mode and real-time light operation parameters are matched and located, and the method comprises:

[0027] According to the environment dominant wind speed, global transmittance, light intensity extreme value and light intensity balance characteristic, the light operation characteristic information library is traversed to obtain initial light operation parameters and the real-time illumination mode; the light intensity direction angle of the light intensity extreme value is called; the initial light operation parameters are compensated according to the angle deviation between the device direction angle of the target obstruction light and the light intensity direction angle, and the real-time light operation parameters are output.

[0028] The system takes the environmental dominant wind speed, global transmittance, light intensity extreme value and light intensity balance characteristics as multi-dimensional input features, calls a pre-constructed light operation feature information library which records corresponding light control strategies under different environmental combination conditions, extracts the closest feature combination item to the current environment through traversal matching operation, and determines a set of initial light operation parameters (including brightness, current level, flicker frequency, etc.) and their corresponding real-time light mode (such as diffusion mode, directional enhancement mode, energy balance mode, etc.). The system obtains the light intensity direction angle corresponding to the light intensity extreme value at the current time from the photosensitive sensor array, which 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 orientation characteristics of external light interference or light source enhancement area. The system calls the device direction angle of the target obstacle light (i.e. the actual physical installation direction of the obstacle light), and calculates the real-time angle deviation between it and the above-mentioned light intensity direction angle; if the angle deviation exceeds the preset threshold, it means that the current lighting direction of the obstacle light is not aligned with the main direction of external light, which may lead to uneven light effect or energy efficiency decline. Based on the angle deviation, the system retrieves the matching compensation coefficient and compensation logic strategy in the compensation mapping table, dynamically adjusts the initial light operation parameters, including directional enhancement compensation for brightness level or adaptive fine-tuning for flicker frequency, etc., and finally outputs real-time light operation parameters coordinated with the current spatial light structure, improving the energy efficiency performance and directional response ability of the obstacle light in complex light environment.

[0029] Further, the initial light operation parameters are compensated according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle, and the real-time light operation parameters are output, and before that, the method comprises:

[0030] interactively obtaining a plurality of sample compensation coefficients and a plurality of sample compensation logics of a plurality of sample deviation angles; presetting a compensation coefficient deviation scale to aggregate the plurality of sample compensation coefficients, obtaining M sample compensation coefficients, M groups of sample deviation angles and M groups of sample compensation logics; constructing M angle deviation ranges according to the angle fluctuation threshold of the M groups of sample deviation angles; extracting M standard compensation logics according to the recurrence frequency of the M groups of sample compensation logics; associatively storing the M sample compensation coefficients, M angle deviation ranges and M standard compensation logics to construct the compensation mapping relationship library.

[0031] The system obtains multiple sample compensation coefficients and multiple sample compensation logics corresponding to multiple sample deviation angles through experiments, wherein the sample deviation angle represents the spatial included 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 disturbance, 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 proportion ladder or a statistical clustering interval), thereby obtaining M sample compensation coefficients, and corresponding M groups of sample deviation angles and M groups of sample compensation logics are combined to form a preliminary parameter set. The system sets an angle fluctuation threshold according to the variation range of the M groups of sample deviation angles and the disturbance level that may occur in actual application, thereby constructing M angle deviation ranges, each range covering a typical deviation response interval, which is used to quickly locate the current deviation belonging to the section in actual application. The system counts the recurrence frequency 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 M standard compensation logics. By one-to-one association mapping and structured storage of the M sample compensation coefficients, the M angle deviation ranges, and the M standard compensation logics, a compensation mapping relationship library is constructed.

[0032] Further, the method for compensating the initial light operation parameter according to the angle deviation between the device direction angle and the light intensity direction angle of the target obstruction light and outputting the real-time light operation parameter comprises:

[0033] calculating the real-time angle deviation between the device direction angle of the target obstruction light and the light intensity direction angle; retrieving and outputting real-time compensation coefficients and real-time compensation logics from the compensation mapping relationship library using the real-time angle deviation; performing light intensity compensation on the initial light operation parameter using the real-time compensation coefficients, and performing associated trigger enhancement on the initial light operation parameter using the real-time compensation logics, and outputting the real-time light operation parameter.

[0034] The system calculates the real-time angle deviation between the device direction angle (i.e. the physical installation or beam projection direction) of the target obstruction light and the light intensity direction angle (the azimuth angle corresponding to the light intensity extreme value in the current environment detected by the photosensitive sensing array), and the real-time angle deviation is used to measure the deviation degree between the obstruction light illumination direction and the main direction of natural light.

[0035] The system takes the real-time angle deviation as a search condition, and performs a quick query in a pre-constructed compensation mapping relationship library (Table 1) to extract a real-time compensation coefficient and a 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 enhancement strategy of parameter linkage, such as synchronously increasing the flicker frequency, enabling the directional light-emitting component, 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 a specific directional beam, weakening a backward interference light area, calling a directional rotation mechanism, etc., finally outputs the real-time light operation parameters that match the current ambient light structure, and realizes adaptive light-emitting control and energy consumption optimization under directional interference.

[0036] Table 1

[0037]

[0038] After switching the target obstruction light to the real-time lighting mode, low-power light output control is performed according to the real-time light operation parameters.

[0039] After switching the target obstruction light to the real-time lighting mode, the system performs low-power light output control according to the real-time light operation parameters (including brightness level, current position, flicker frequency, etc.) output by the previous environmental perception and light balancing. Specifically, the system adjusts the light-emitting state of the medium-intensity obstruction light to the energy-saving operation state corresponding to the current real-time lighting mode through the light control unit.

[0040] The real-time hierarchical environmental data extension model radius is called from the holographic environmental data, and a space dynamic model is constructed with the ground coordinates of the target obstruction light as the center.

[0041] The system extracts the wind speed, transmittance and meteorological stability parameters of each layer sensor at the current time 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. According to the analysis result, the system performs model radius expansion operation on the perception space around the obstacle light, and the 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 increasing meteorological disturbance, the system will expand the coverage radius of the perception model to expand the prediction ability of the potential aircraft deviation trajectory; in the case of stable environment and balanced light, the system maintains the basic model radius to ensure processing efficiency and energy saving goal. Subsequently, taking the ground coordinates of the target light intensity obstacle light as the center point, and combining the dynamic radius parameter, a three-dimensional airspace dynamic model is constructed, which is usually a cylinder, a sphere or an irregular semi-closed space body, covering a certain height above the obstacle light (such as the minimum safe flight height) and the horizontal extension radius. The three-dimensional airspace dynamic model not only records the current effective light intensity influence range of the obstacle light, but also serves as a spatial reference benchmark for flight trajectory prediction and intersection judgment.

[0042] According to the multi-source aviation information, the aircraft trajectory within a preset time window is predicted, and the aircraft dynamic trajectory is output.

[0043] By accessing ADS-B data, flight plans, flight status platforms and other multi-source aviation information, the current position, speed, heading, height and other flight parameters of the aircraft are extracted; combined with the ground coordinates of the target obstacle light and the current environmental wind speed gradient, the aircraft motion state is mapped to polar coordinates or three-dimensional space, and trajectory extrapolation prediction is carried out based on a simplified flight dynamics model; at the same time, airspace control information is introduced to avoid no-fly zones on the predicted path, generating high-confidence aircraft trajectories; finally, the trajectory segment falling within the preset time window is extracted and output as the aircraft dynamic trajectory.

[0044] Further, according to the multi-source aviation information, the aircraft trajectory within a preset time window is predicted, and the aircraft dynamic trajectory is output, the method comprising:

[0045] Accessing civil aviation broadcast data, and based on the pre-stored flight schedule and the civil aviation broadcast data, outputting a plurality of aviation real-time associated data; calculating and outputting real-time wind speed gradient according to the real-time hierarchical environmental data; converting the plurality of aviation real-time associated data to a polar coordinate system with the ground coordinates of the target obstacle light as the center, and taking the real-time wind speed gradient as a lateral acceleration correction feature, predicting the aircraft dynamics behavior in the polar coordinate system, and outputting a plurality of initial dynamic trajectories; obtaining airspace control information interactively to avoid no-fly zone path prediction on the plurality of initial dynamic trajectories, and outputting a plurality of high-confidence aircraft trajectories; segmenting the aircraft dynamic trajectory falling within the preset time window from the plurality of high-confidence aircraft trajectories.

[0046] The system accesses civil aviation broadcast data (such as ADS-B, Mode-S, etc.), and combines with the locally pre-stored flight schedule database to fuse and analyze the flight number, flight altitude, speed, heading, geographical position and other information of the current aircraft, and generate multiple aviation real-time correlation data containing time and space attributes. The system calls the wind speed measurement values in the real-time hierarchical environmental data to calculate the wind speed variation rate in different spatial height sections, and outputs the real-time wind speed gradient in the current airspace. This gradient information is used to simulate the lateral deviation trend of the aircraft affected by wind disturbance in different height layers. By mapping and converting the aviation real-time 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 trajectory propagation is performed to generate multiple initial dynamic trajectories representing the predicted flight path under the condition of unrestricted airspace. The system interacts with the air traffic control platform or aviation regulation 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 calculation on the initial dynamic trajectory to obtain multiple high-confidence aviation trajectories that meet the constraint conditions and have high reliability. From the high-confidence aviation trajectories, the trajectory segment that may enter the target obstacle light airspace dynamic model within a set preset time window (such as 30 seconds, 60 seconds in the future) is extracted to form the aircraft dynamic trajectory corresponding to the current time, providing time and space input basis for subsequent airspace intersection judgment and obstacle light power response control.

[0047] If the aircraft dynamic trajectory intersects with the airspace dynamic model, the intersection time window is calculated based on time extension.

[0048] If the aircraft dynamic trajectory intersects with the airspace dynamic model, the system analyzes the interaction process of the trajectory and the model based on the time extension strategy, and calculates the intersection time window. Specifically, the system takes the airspace dynamic model constructed with the target obstacle light as the center as the three-dimensional space boundary reference, traverses the spatial position points of each prediction time step in the aircraft dynamic trajectory, and judges whether the position point falls within the airspace model range. When the trajectory first enters the airspace dynamic model, the corresponding prediction time point is recorded as the intersection entry time. Continue to judge the subsequent trajectory points until the trajectory point leaves the model boundary, and record the time point corresponding to this time as the intersection exit time. In this way, a closed intersection time window is formed, that is, the time interval in which the aircraft predicted trajectory spatially coincides with the obstacle light airspace model within the preset time window.

[0049] Trigger the target obstacle light to switch to the full-power light output mode with the real-time light mode as the mode constraint and the intersection time window as the time constraint.

[0050] The system determines whether the current obstruction light has switchable ability and switching path (e.g. from directional low-power mode to full-view high-power mode) according to real-time light mode. If the current mode allows upward switching, the mode switching behavior is included in the execution judgment process. When the current system clock reaches the start time of the intersection time window, the system immediately triggers the obstruction light control unit to execute the power scheduling instruction, and adjusts the light running parameters to the full-power state (full-power light output mode), including: increasing the brightness level to the maximum, increasing the light angle coverage, and adjusting the flashing frequency to the aviation warning standard requirement (e.g. 60 times per minute).

[0051] According to the device temperature rise characteristics and component temperature difference characteristics of the target obstruction light in the full-power light output mode, adaptive current compensation is performed.

[0052] After the target obstruction light enters the full-power light output mode, the system performs adaptive current compensation control according to the temperature rise characteristics and component temperature difference characteristics during its operation. Specifically, by monitoring the temperature changes of multiple heat generating modules inside the obstruction light in real time, the overall temperature rise rate and local temperature difference extreme value are extracted and used as input parameters to map to the preset temperature difference-current compensation relationship model to obtain the corresponding current compensation ratio and compensation logic. The system dynamically adjusts the driving current output, and combines the PID current control strategy to realize fine adjustment of the lighting current, ensuring that the output brightness of the obstruction light meets the aviation safety requirements, while effectively controlling the heat load, preventing overheating, and prolonging the service life of the device.

[0053] Further, according to the device temperature rise characteristics and component temperature difference characteristics of the target obstruction light in the full-power light output mode, adaptive current compensation is performed, and the method comprises:

[0054] The target obstruction light is subjected to multi-module temperature rise monitoring to obtain multiple time-series temperature rise sequences; the temperature rise speed gradient extreme value of the multiple time-series temperature rise sequences is calculated as the device temperature rise characteristics; the temperature difference extreme value is calculated from the multiple time-series temperature rise sequences as the component temperature difference characteristics; the device temperature rise characteristics and component temperature difference characteristics are mapped to the temperature difference-current compensation table to locate the real-time current compensation ratio and real-time current compensation logic; and the real-time current compensation ratio and real-time current compensation logic are applied to the PID current dynamic control.

[0055] Firstly, the internal multiple key thermal units of the target obstruction light are monitored for multi-module temperature rise, including but not limited to LED light-emitting module, driving power supply, heat dissipation module, and reflective cavity, etc. Through the arrangement of thermocouple, digital temperature sensor and other collection devices, the temperature changes of each monitoring point in time sequence are collected respectively to form multiple time sequence temperature rise sequences. Then, the multiple time sequence temperature rise sequences are analyzed and processed, the first derivative of the temperature change with time is calculated for each sequence, and the extreme value (such as the maximum positive slope or the steepest speed) of the temperature rise speed gradient is extracted as the equipment temperature rise feature under the current running state of the obstruction light, which is used to reflect the overall thermal rise dynamic trend and response strength. At the same time, the system performs cross-sequence comparison calculation of each time sequence at the same time node, extracts the temperature difference extreme value between different modules, forms the component temperature difference feature, and is used to judge the local thermal imbalance state, heat dissipation lag or potential thermal abnormality. Subsequently, the above temperature rise feature and temperature difference feature are taken as double input parameters, mapped to the pre-constructed temperature difference-current compensation table, the matching items are retrieved in Table 2, the real-time current compensation proportion (such as ±5%, ±10%, current limiting 50% etc.) and the corresponding real-time current compensation logic (such as continuous peak clipping current limiting, short-time overclocking protection, segmented current sharing strategy, etc.) matching the current thermal state are obtained. Finally, the system inputs the real-time current compensation proportion and compensation logic into the PID current dynamic controller to perform closed-loop control and adjustment on the current of the LED driving current, adjusts the output power in real time, ensures to meet the full-power warning demand, realizes the active response to the too fast temperature rise or too large temperature difference, guarantees the thermal stability of the system and prolongs the service life of the device.

[0056] Table 2

[0057]

[0058] Further, according to the equipment temperature rise feature and the component temperature difference feature of the target obstruction light in the full-power light output mode, adaptive current compensation is performed, and then, including:

[0059] Collecting the equipment temperature drop feature of the target obstruction light; triggering the fan heat dissipation according to the deviation of the equipment temperature drop feature from the preset temperature drop time-varying threshold.

[0060] After adaptive current compensation is performed according to the device temperature rise characteristic and the component temperature difference characteristic of the target obstruction light in the full-power light output mode, the system continuously collects the device temperature drop characteristic of the key components (such as the LED module, the driving power supply, the heat dissipation substrate, etc.) of the obstruction light in the process of gradually reducing from the peak temperature, forms a temperature-time drop curve, and reflects the current heat release efficiency and passive heat dissipation capacity. Subsequently, the system compares and analyzes the collected temperature drop characteristic with the pre-set temperature drop time-varying threshold, which can be dynamically set according to factors such as device type, heat capacity, and environmental temperature, and is used to determine whether the temperature drop rate is lower than the system safety cooling requirement. When it is detected that the actual temperature drop rate is lower than the pre-set threshold, it indicates that the passive heat dissipation of the obstruction light is insufficient, and there is a situation of local heat accumulation or poor heat release. Therefore, the system triggers the active fan heat dissipation mechanism, starts the integrated air cooling module, enhances the heat exchange efficiency around the device through air convection, rapidly reduces the component temperature, and prevents thermal runaway, performance drift, or material aging.

[0061] In summary, the embodiments of the present application have at least the following technical effects:

[0062] Firstly, holographic environmental data of the target obstruction light is collected, and adaptive dimming balancing of the obstruction light is performed according to the collection result, to output real-time light running parameters and a real-time light mode. The target obstruction light is a medium-intensity obstruction light. After the target obstruction light is switched to the real-time light mode, low-power light output control is performed according to the real-time light running parameters. Then, a real-time hierarchical environmental data extension model radius is called from the holographic environmental data, and a space dynamic model is constructed with the ground coordinates of the target obstruction light as the center. At the same time, aircraft trajectory prediction in a preset time window is performed according to multi-source aviation information, to output an aircraft dynamic trajectory. If the aircraft dynamic trajectory intersects with the space dynamic model, a time window of intersection is calculated based on time extension. Then, the target obstruction light is triggered to switch to the full-power light output mode, with the real-time light mode as a mode constraint and the time window of intersection as a time constraint. Finally, adaptive current compensation is performed according to the device temperature rise characteristic and the component temperature difference characteristic of the target obstruction light in the full-power light output mode. The technical problem of high energy consumption of the medium-intensity obstruction light in the prior art is solved, and the technical effects of reducing energy consumption and prolonging the service life of the device are achieved.

[0063] Embodiment two, based on the same inventive concept as the energy consumption optimization method for a medium-intensity obstruction light in the foregoing embodiment, as shown in Figure 2 The present application provides an energy consumption optimization system for a medium-intensity obstruction light, wherein the system comprises:

[0064] The light modulation balancing module 11 is configured to collect holographic environment data of the target obstruction light, and perform adaptive light modulation balancing of the obstruction light according to the collection result, and output real-time light operation parameters and a real-time light mode, wherein the target obstruction light is a medium-intensity obstruction light; the control module 12 is configured to, after switching the target obstruction light to the real-time light mode, perform low-power light output control according to the real-time light operation parameters; the model construction module 13 is configured to call a real-time hierarchical environment data expansion model radius from the holographic environment data, and construct a space dynamic model with the ground coordinates of the target obstruction light as the center; the trajectory prediction module 14 is configured to perform aircraft trajectory prediction within a preset time window according to multi-source aviation information, and output an aircraft dynamic trajectory; the calculation module 15 is configured to, if the aircraft dynamic trajectory intersects with the space dynamic model, calculate an intersection time window based on time extension; the mode triggering module 16 is configured to trigger the target obstruction light to switch to a full-power light output mode, with the real-time light mode as a mode constraint and the intersection time window as a time constraint; and the current compensation module 17 is configured to perform adaptive current compensation according to the device temperature rise characteristics and the component temperature difference characteristics of the target obstruction light in the full-power light output mode.

[0065] Further, the current compensation module 17 is configured to perform the following method:

[0066] The target obstruction light is subjected to multi-module temperature rise monitoring to obtain a plurality of time-series temperature rise sequences; a temperature rise speed gradient extreme value of the plurality of time-series temperature rise sequences is calculated as the device temperature rise characteristics; a temperature difference extreme value is calculated from the plurality of time-series temperature rise sequences across sequences as the component temperature difference characteristics; the device temperature rise characteristics and the component temperature difference characteristics are mapped to a temperature difference-current compensation table to locate a real-time current compensation ratio and a real-time current compensation logic; and the real-time current compensation ratio and the real-time current compensation logic are applied to PID current dynamic control.

[0067] Further, the light modulation balancing module 11 is configured to perform the following method:

[0068] A target obstruction light is subjected to multi-module temperature rise monitoring to obtain a plurality of time-series temperature rise sequences; a temperature rise speed gradient extreme value of the plurality of time-series temperature rise sequences is calculated as the device temperature rise characteristics; a temperature difference extreme value is calculated from the plurality of time-series temperature rise sequences across sequences as the component temperature difference characteristics; the device temperature rise characteristics and the component temperature difference characteristics are mapped to a temperature difference-current compensation table to locate a real-time current compensation ratio and a real-time current compensation logic; and the real-time current compensation ratio and the real-time current compensation logic are applied to PID current dynamic control.

[0069] Further, the light adjustment and balance module 11 is configured to perform the following method:

[0070] The wind speed gradient of the real-time hierarchical environment data is calculated to locate the environment dominant wind speed; the horizontal distance between the P-layer annular sensor array and the target obstacle light ground coordinate is taken as the hierarchical distance weight, the real-time hierarchical environment data is weighted by the transmittance hierarchy, and the global transmittance is output; the maximum light intensity direction of the real-time array illumination data is identified, and the light intensity extreme value is output; the standard deviation of the real-time array illumination data is calculated, and the light intensity balance characteristic is output; the real-time light mode and the real-time light operation parameter are matched and located according to the environment dominant wind speed, the global transmittance, the light intensity extreme value and the light intensity balance characteristic.

[0071] Further, the trajectory prediction module 14 is configured to perform the following method:

[0072] Access the civil aviation broadcast data, and output a plurality of 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 environment data; convert the plurality of aviation real-time associated data to the polar coordinate system with the target obstacle light ground coordinate as the center, take the real-time wind speed gradient as the lateral acceleration correction feature, and predict the aircraft dynamics behavior in the polar coordinate system to output a plurality of initial dynamic trajectories; obtain airspace control information interactively to avoid the no-fly zone path prediction on the plurality of initial dynamic trajectories, and output a plurality of high-confidence aviation trajectories; segment the aircraft dynamic trajectory falling within the preset time window from the plurality of high-confidence aviation trajectories.

[0073] Further, the light adjustment and balance module 11 is configured to perform the following method:

[0074] According to the environment dominant wind speed, the global transmittance, the light intensity extreme value and the light intensity balance characteristic, the initial light operation parameter and the real-time light mode are obtained by traversing the light operation feature information library; the light intensity direction angle of the light intensity extreme value is called; the initial light operation parameter is compensated according to the angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle, and the real-time light operation parameter is output.

[0075] Further, the light adjustment and balance module 11 is configured to perform the following method:

[0076] The real-time angle deviation between the device direction angle of the target obstacle light and the light intensity direction angle is calculated; the real-time compensation coefficient and the real-time compensation logic are retrieved from the compensation mapping relationship library according to the real-time angle deviation; the initial light operation parameter is compensated by the real-time compensation coefficient, and the initial light operation parameter is associated with the trigger enhancement by the real-time compensation logic, and the real-time light operation parameter is output.

[0077] Further, the light modulation balancing module 11 is configured to perform the following method:

[0078] The plurality of sample compensation coefficients and the plurality of sample compensation logics are obtained by interaction, the plurality of sample compensation coefficients are aggregated according to a preset compensation coefficient deviation scale, M sample compensation coefficients, M sets of sample deviation angles and M sets of sample compensation logics are obtained, M angle deviation ranges are constructed according to the angle fluctuation threshold of the M sets of sample deviation angles, M standard compensation logics are extracted according to the recurrence frequency of the M sets of sample compensation logics, the M sample compensation coefficients, the M angle deviation ranges and the M standard compensation logics are stored by association mapping, and the compensation mapping relationship library is constructed.

[0079] Further, the current compensation module 17 is configured to perform the following method:

[0080] The device temperature drop characteristics of the target obstacle light are collected, and the fan cooling is triggered according to the deviation of the device temperature drop characteristics from a preset temperature drop time-varying threshold.

[0081] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above-mentioned embodiments of the present application are described. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or may be advantageous.

[0082] The above-mentioned only for the preferred embodiments of the present application, and not to limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application, should be included in the protection scope of the present application.

[0083] The present application and the drawings are only exemplary description of the present application, and are considered to cover any and all modifications, changes, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various modifications and changes to the present application without departing from the scope of the present application. Thus, if these modifications and changes of the present application belong to the scope of the present application and its equivalents, the present application intends to include these modifications and changes.

Claims

1. A method for optimizing energy consumption for medium-intensity obstruction lights, characterized in that, The method includes: Holographic environmental data is collected from the target obstacle lights, and adaptive dimming and equalization of the obstacle lights are performed based on the collection results. Real-time light operation parameters and real-time lighting modes are output, where the target obstacle lights are medium-intensity obstacle lights. After switching the target obstacle light to the real-time illumination mode, low-power light output control is performed based on the real-time light operation parameters. The model radius is expanded by calling real-time hierarchical environmental data from the holographic environmental data, and a dynamic airspace model is constructed with the ground coordinates of the target obstacle light as the center. Based on multi-source aviation information, predict the aircraft trajectory within a preset time window and output the dynamic trajectory of the aircraft. If the aircraft's dynamic trajectory intersects with the airspace dynamic model, the intersection time window is calculated based on the time extension. Using the real-time illumination mode as a mode constraint and the intersection time window as a time constraint, the target obstacle light is triggered to switch to full-power light output mode; Based on the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in full power light output mode, adaptive current compensation is performed. The method involves acquiring holographic environmental data of the target obstacle lights, performing adaptive dimming and equalization of the obstacle lights based on the acquisition results, and outputting real-time light operation parameters and real-time illumination modes. Using the ground coordinates of the target obstacle light as the center, an arithmetic radius sequence is constructed for the circular deployment of a P-layer ring sensor array, in which the sensor nodes integrate wind speed sensors and transmittance sensors. The P-layer ring sensor array is used to perform hierarchical surround environmental data acquisition to obtain real-time hierarchical environmental data. Using the ground coordinates 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; Directional ambient light is collected based on the photosensitive sensor array to obtain real-time array illumination data; Based on the real-time hierarchical environmental data and real-time array illumination data, adaptive dimming and equalization of the obstacle lights are performed, and the real-time light operation parameters and real-time illumination mode are output. The system extracts wind speed, transmittance, and meteorological stability parameters of each sensor layer at the current moment from the acquired holographic environmental data, analyzes the degree of disturbance and propagation characteristics at different spatial levels, and assesses the dynamic response range of the aircraft affected by the environment. Based on the analysis results, the system performs a model radius expansion calculation on the perception space around the obstruction lights. This radius is not a fixed value, but is dynamically adjusted according to the real-time environmental conditions.

2. The energy consumption optimization method for medium-intensity obstruction lights as described in claim 1, characterized in that, Based on the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in full-power light output mode, adaptive current compensation is performed, the method comprising: Multi-module temperature rise monitoring of the target obstacle lights was performed to obtain multiple time-series temperature rise sequences. Calculate the extreme values ​​of the temperature rise rate gradient of the multiple time-series temperature rise sequences, and use them as the temperature rise characteristics of the equipment; The extreme values ​​of temperature difference are calculated across the multiple time-series temperature rise sequences and used as the temperature difference characteristics of the component. Map the equipment temperature rise characteristics and component temperature difference characteristics to a temperature difference-current compensation table to locate the real-time current compensation ratio and real-time current compensation logic. The real-time current compensation ratio and real-time current compensation logic are applied to PID current dynamic control.

3. The energy consumption optimization method for medium-intensity obstruction lights as described in claim 1, characterized in that, Based on the real-time hierarchical environmental data and real-time array illumination data, adaptive dimming equalization of obstacle lights is performed, and the real-time light operation parameters and real-time illumination mode are output. The method includes: Wind speed gradients are calculated from the real-time hierarchical environmental data to pinpoint the dominant wind speed in the environment. The horizontal distance between the P-layer ring sensor array and the ground coordinates of the target obstacle light is used as the layer distance weight to perform transmittance layer weighting on the real-time layer environmental data, and the global transmittance is output. The maximum light intensity azimuth is identified from the real-time array illumination data, and the extreme light intensity value is output. The standard deviation of the real-time array illumination data is calculated, and the light intensity equalization characteristics are output. Based on the dominant wind speed, global transmittance, extreme light intensity, and light intensity balance characteristics of the environment, the real-time illumination mode and real-time light operation parameters are matched and located.

4. The energy consumption optimization method for medium-intensity obstruction lights as described in claim 3, characterized in that, The method includes predicting aircraft trajectories within a preset time window based on multi-source aviation information and outputting the dynamic trajectory of the aircraft. Access civil aviation broadcast data, and parse and output multiple real-time aviation-related data based on pre-stored flight schedules and the civil aviation broadcast data; The real-time wind speed gradient is calculated and output based on the real-time hierarchical environmental data. After converting the multiple real-time aviation correlation data into a polar coordinate system centered on the ground coordinates of the target obstruction light, the real-time wind speed gradient is used as a lateral acceleration correction feature to predict the aircraft dynamic behavior in the polar coordinate system and output multiple initial dynamic trajectories. The system interactively obtains airspace control information to predict no-fly zone path avoidance for the multiple initial dynamic trajectories and outputs multiple high-confidence aviation trajectories. The aircraft dynamic trajectory is segmented from the multiple high-confidence aviation trajectories and falls within the preset time window.

5. The energy consumption optimization method for medium-intensity obstruction lights as described in claim 3, characterized in that, Based on the dominant environmental wind speed, global transmittance, extreme light intensity, and light intensity balance characteristics, the real-time illumination mode and real-time light operation parameters are matched and located. The method includes: Based on the dominant wind speed, global transmittance, extreme light intensity, and light intensity balance characteristics of the environment, the initial light operation parameters and the real-time illumination mode are obtained by traversing the light operation characteristic information database. The light intensity direction angle that calls the extreme light intensity value; The initial light operation parameters are compensated based on the angular deviation between the device orientation angle and the light intensity orientation angle of the target obstacle light, and the real-time light operation parameters are output.

6. The energy consumption optimization method for medium-intensity obstruction lights as described in claim 5, characterized in that, The method includes compensating for the initial light operation parameters based on the angular deviation between the device orientation angle and the light intensity orientation angle of the target obstacle light, and outputting the real-time light operation parameters. Calculate the real-time angular deviation between the device orientation angle of the target obstacle light and the light intensity orientation angle; The real-time angle deviation is used to retrieve and output the real-time compensation coefficient and real-time compensation logic from the compensation mapping relationship database; The initial optical operating parameters are compensated for using the real-time compensation coefficient, and the initial optical operating parameters are enhanced by association triggering using the real-time compensation logic. The real-time optical operating parameters are then output.

7. The energy consumption optimization method for medium-intensity obstruction lights as described in claim 6, characterized in that, The method first compensates for the initial light operating parameters based on the angular deviation between the device orientation angle and the light intensity orientation angle of the target obstacle light, and then outputs the real-time light operating parameters. Prior to this, the method includes: Interactively obtain multiple sample compensation coefficients and multiple sample compensation logic for multiple sample deviation angles; The multiple sample compensation coefficients are aggregated using a preset compensation coefficient deviation scale to obtain M types of sample compensation coefficients, M sets of sample deviation angles, and M sets of sample compensation logic. Based on the angle fluctuation threshold of the M sets of sample deviation angles, construct M angle deviation ranges; Based on the recurrence frequency of the compensation logic in the M groups of samples, extract M standard compensation logics; The association mapping stores the compensation coefficients of the M types of samples, the M angular deviation ranges, and the M standard compensation logics, thus constructing the compensation mapping relationship library.

8. The energy consumption optimization method for medium-intensity obstruction lights as described in claim 2, characterized in that, Based on the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in full-power light output mode, adaptive current compensation is performed. Then, the method includes: Collect temperature drop characteristics of the target obstacle lights; The fan is triggered to dissipate heat based on the deviation between the device's temperature drop characteristics and the preset time-varying temperature drop threshold.

9. An energy consumption optimization system for medium-intensity obstruction lights, characterized in that, The system is used to implement the energy consumption optimization method for a medium-intensity obstruction lamp according to any one of claims 1-8, the system comprising: The dimming equalization module is used to collect holographic environmental data of the target obstacle light, and perform adaptive dimming equalization of the obstacle light based on the collection results, outputting real-time light operation parameters and real-time lighting mode. 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 illumination mode and then control the low-power light output according to the real-time light operation parameters. The model building module is used to call real-time hierarchical environmental data from the holographic environmental data to expand the model radius, and to build a dynamic airspace 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 based on multi-source aviation information and output the dynamic trajectory of the aircraft. The calculation module is used to calculate the intersection time window based on time extension if the dynamic trajectory of the aircraft intersects with the airspace dynamic model. The mode triggering module is used to trigger the target obstacle light to switch to 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 is used to perform adaptive current compensation based on the device temperature rise characteristics and component temperature difference characteristics of the target obstacle light in full power light output mode. The method involves acquiring holographic environmental data of the target obstacle lights, performing adaptive dimming and equalization of the obstacle lights based on the acquisition results, and outputting real-time light operation parameters and real-time illumination modes. Using the ground coordinates of the target obstacle light as the center, an arithmetic radius sequence is constructed for the circular deployment of a P-layer ring sensor array, in which the sensor nodes integrate wind speed sensors and transmittance sensors. The P-layer ring sensor array is used to perform hierarchical surround environmental data acquisition to obtain real-time hierarchical environmental data. Using the ground coordinates 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; Directional ambient light is collected based on the photosensitive sensor array to obtain real-time array illumination data; Based on the real-time hierarchical environmental data and real-time array illumination data, adaptive dimming and equalization of the obstacle lights are performed, and the real-time light operation parameters and real-time illumination mode are output. The system extracts wind speed, transmittance, and meteorological stability parameters of each sensor layer at the current moment from the acquired holographic environmental data, analyzes the degree of disturbance and propagation characteristics at different spatial levels, and assesses the dynamic response range of the aircraft affected by the environment. Based on the analysis results, the system performs a model radius expansion calculation on the perception space around the obstruction lights. This radius is not a fixed value, but is dynamically adjusted according to the real-time environmental conditions.

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