Wireless control method for LED illumination, dimming device, medium and product

Abstract

The invention discloses a wireless control method for LED illumination, a dimming device, a medium and a product, and relates to the technical field of electric illumination, and the method comprises the steps: obtaining tunnel illumination control parameters; dividing the tunnel entrance area into an entrance section, a buffer section and a basic section according to the tunnel parameters, and determining a plurality of illumination control subareas; calculating the brightness adaptation time of a vehicle driver based on the external brightness value and the vehicle passing speed, and generating an illumination gradient curve from the entrance section to the buffer section and the basic section; according to the illumination gradient curve, determining a target illumination value of each illumination control zone; converting the target illumination value into an LED driving parameter, and issuing the LED driving parameter to an LED driving circuit of each illumination control subarea; and collecting actual illumination data of each illumination control subarea, and regenerating an illumination gradient curve when the actual illumination data exceeds a preset target range or the external brightness value changes. By implementing the method, tunnel illumination can be adjusted based on illumination changes when the weather changes drastically, and driving safety is guaranteed.

Description

Technical Field

[0001] The present application relates to the field of electric lighting technology, and in particular to a wireless control method, dimming device, medium and product of LED lighting. Background Art

[0002] With the continuous expansion of the highway network, the safety and reliability requirements of tunnel lighting systems are increasing. Especially at the entrance of the tunnel, due to the huge difference between the natural light outside and the light environment inside the tunnel, drivers are prone to temporary visual disharmony, which poses a serious threat to driving safety. At the same time, the changes in the intensity of external light under different weather conditions and at different times further exacerbate the complexity of this problem.

[0003] In the related art, the tunnel entrance section adopts a time-divided fixed-value lighting scheme. This scheme pre-sets several fixed lighting modes, such as day mode, cloudy mode and night mode, and switches the corresponding lighting modes at different time periods. Each lighting mode presets a fixed number of lamps to be turned on and power output value, and the mode is switched at a predetermined time point by a controller to achieve lighting control of the entrance section.

[0004] However, fixed lighting modes are difficult to adapt to the continuous changes in external light, especially when the weather changes drastically, the preset lighting mode often lags behind actual needs. Summary of the invention

[0005] The present application provides a wireless control method, dimming device, medium and product of LED lighting, which are used to adjust tunnel lighting based on light changes when the weather changes drastically to ensure driving safety.

[0006] In a first aspect, the present application provides a wireless control method for LED lighting, which is applied to a dimming device, and the method includes: obtaining tunnel lighting control parameters; the tunnel lighting control parameters include external brightness values, tunnel parameters and vehicle travel speeds; according to the tunnel parameters, the tunnel entrance area is divided into an entrance section, a buffer section and a basic section, and a plurality of lighting control partitions are determined; based on the external brightness value and the vehicle travel speed, the brightness adaptation time of the vehicle driver is calculated, and an illumination gradient curve from the entrance section to the buffer section and the basic section is generated; according to the illumination gradient curve, the target illumination value of each lighting control partition is determined respectively; the target illumination value is converted into an LED drive parameter, and sent to the LED drive circuit of each lighting control partition through a wireless communication module; the actual illumination data of each lighting control partition is collected, and when the actual illumination data exceeds the preset target range or the external brightness value changes, the illumination gradient curve is regenerated.

[0007] In the above embodiment, the dimming device achieves precise control of tunnel lighting by acquiring tunnel lighting control parameters, dynamically dividing lighting areas based on these parameters, calculating the driver's brightness adaptation time, and generating an illumination gradient curve. By real-time acquisition of illumination data and timely adjustment when the data is abnormal or the external brightness changes, the real-time and accuracy of lighting control is ensured, effectively improving the safety of tunnel lighting.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the steps of dividing the tunnel entrance area into an entrance section, a buffer section and a basic section according to tunnel parameters, and determining multiple lighting control partitions specifically include: determining the tunnel full length data and lane width data according to the tunnel parameters; dividing the tunnel entrance area into an entrance section, a buffer section and a basic section according to the tunnel full length data; determining multiple lighting control partitions according to the segmentation type and lane width data of the tunnel entrance area.

[0009] In the above embodiment, the dimming device realizes accurate zoning based on the physical characteristics of the tunnel through detailed analysis of the tunnel parameters, determines the lighting zoning through the lane width data, ensures the pertinence and rationality of the lighting control, and improves the lighting effect.

[0010] In combination with some embodiments of the first aspect, in some embodiments, based on the external brightness value and the vehicle travel speed, the brightness adaptation time of the vehicle driver is calculated, and the steps of generating the illumination gradient curve from the entrance section to the buffer section and the basic section specifically include: determining the initial visual brightness adaptation value of the vehicle driver when entering the tunnel according to the external brightness value; calculating the adaptation time threshold of the vehicle driver from light adaptation to dark adaptation based on the vehicle travel speed; using an exponential attenuation model, combining the initial visual brightness adaptation value and the adaptation time threshold, to generate the driver's visual brightness adaptation curve; based on the visual brightness adaptation curve, determining the illumination gradient curve from the entrance section to the buffer section and the basic section.

[0011] In the above embodiment, the dimming device calculates the initial visual brightness adaptation value and the adaptation time threshold, and uses an exponential decay model to generate a driver's visual brightness adaptation curve, thereby achieving an accurate simulation of the driver's visual adaptation process and ensuring that the lighting gradient conforms to the adaptation characteristics of the human eye.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the step of calculating the adaptation time threshold of the vehicle driver from light adaptation to dark adaptation based on the vehicle travel speed specifically includes: obtaining the traffic flow data and vehicle type distribution data at the tunnel entrance; performing time series analysis on the traffic flow data to identify traffic flow characteristics including peak periods and trough periods; based on the vehicle type distribution data, classifying and counting the vehicles according to passenger cars, buses and trucks to obtain vehicle type characteristics; collecting the real-time travel speed of each type of vehicle to obtain speed distribution characteristics; and determining the average time threshold of the driver's visual adaptation based on the traffic flow characteristics, vehicle type characteristics and speed distribution characteristics.

[0013] In the above embodiment, the dimming device analyzes multi-dimensional data such as vehicle flow and vehicle type distribution, identifies traffic characteristics, and calculates a more accurate driver's visual adaptation time threshold, thereby improving the scientificity and adaptability of lighting control.

[0014] In combination with some embodiments of the first aspect, in some embodiments, before the step of obtaining the tunnel lighting control parameters, the method also includes: grouping and numbering the LED lamps in each lighting control zone and assigning communication addresses to determine multiple groups of LED lamps; collecting initial electrical parameters of each group of LED lamps; the initial electrical parameters include rated power, dimming range and current gain coefficient; and determining the driving parameters of the LED lamps based on the initial electrical parameters and the dimming characteristic curve of the LED lamps.

[0015] In the above embodiment, the dimming device establishes a complete lamp control system by grouping and numbering LED lamps and collecting parameters, so that the dimming is more accurate.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after collecting actual illuminance data of each lighting control zone and regenerating the illuminance gradient curve when the actual illuminance data exceeds a preset target range or the external brightness value changes, the method also includes: determining the illuminance timing change characteristics of each lighting control zone based on the actual illuminance data; determining the illuminance drift trend based on historical illuminance data and the illuminance timing change characteristics; and adjusting the LED drive parameters when it is determined based on the illuminance drift trend that the actual illuminance data exceeds a preset target range after a preset interval time.

[0017] In the above embodiment, the dimming device realizes predictive adjustment of lighting parameters by analyzing the time-series variation characteristics and drift trend of illumination, thereby improving the foresight and stability of the system.

[0018] In combination with some embodiments of the first aspect, in some embodiments, when it is determined based on the illuminance drift trend that the actual illuminance data exceeds a preset target range after a preset interval time, after the step of adjusting the LED driving parameters, the method also includes: collecting illuminance timing data and energy consumption data of each lighting control partition, and calculating the lighting index score; recording the dimming curve during the illuminance correction process, and extracting dimming characteristic parameters; generating a lighting performance evaluation report based on the lighting index score and dimming characteristic parameters, combined with historical operation data.

[0019] In the above embodiment, the dimming device generates a performance evaluation report by collecting illumination time series data and energy consumption data, thereby achieving comprehensive monitoring and evaluation of the operating status of the lighting system, enabling continuous optimization of the system and improving system adaptability.

[0020] In a second aspect, an embodiment of the present application provides a dimming device, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the dimming device to perform the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer program product comprising instructions, and when the above-mentioned computer program product runs on a dimming device, the above-mentioned dimming device executes the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions. When the instructions are executed on a dimming device, the dimming device executes the method described in the first aspect and any possible implementation manner of the first aspect.

[0023] It can be understood that the dimming device provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the method provided in the embodiment of the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Due to the adoption of a comprehensive control method based on external brightness value, tunnel parameters and vehicle speed, and the dynamic adjustment of LED driving parameters combined with the illumination gradient curve, it is possible to achieve real-time precise control and adaptive adjustment of tunnel lighting, effectively solving the problem that the fixed lighting mode in the existing technology cannot adapt to the continuous changes in external light, thereby achieving a precise match between the lighting environment and the driver's visual adaptation characteristics, and improving driving safety and lighting system reliability.

[0025] 2. Due to the use of time series analysis of traffic flow data and identification of traffic flow characteristics, combined with vehicle type distribution statistics and real-time traffic speed collection, and comprehensive consideration of the operating characteristics of different vehicle types, it is possible to accurately calculate the driver's visual adaptation time threshold that conforms to actual traffic conditions, effectively solving the problem in the existing technology that the preset value of visual adaptation time is too single and cannot adapt to complex traffic environments, thereby realizing a more accurate lighting control strategy and ensuring the safe passage of different types of vehicles under various traffic conditions.

[0026] 3. Since the timing change characteristics are analyzed based on actual illumination data, the illumination drift trend is predicted in combination with historical data, and the LED drive parameters are adjusted in advance when it is predicted that the illumination is about to exceed the target range, the predictive adjustment and active control of the lighting system can be realized, which effectively solves the problem of passive lag of lighting control and inability to respond to environmental changes in time in the existing technology, thereby realizing intelligent pre-control and smooth transition of the lighting system, and improving the stability and reliability of the system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the wireless control method of LED lighting in the embodiment of the present application; Figure 2 is another flow chart of the wireless control method for LED lighting in an embodiment of the present application; Figure 3 It is a schematic diagram of a physical device structure of a dimming device in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification of the present application, the singular expressions "one", "a kind of", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more of the listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] For ease of understanding, the application scenarios of the embodiments of the present application are introduced below.

[0031] In a certain highway network, a newly built 3.2-kilometer two-way four-lane tunnel was put into use, and traffic accidents occasionally occurred. Especially in summer with frequent thunderstorms, the external light intensity changes dramatically, from sunny to rainy, and the fixed lighting mode in the tunnel cannot be adjusted in time. When the driver enters the tunnel from a dark environment at a speed of 90km / h, the human eye cannot quickly adapt to the brightness change, which easily causes temporary blurred vision, causing the driver to misjudge the road conditions ahead and cause an accident.

[0032] In the related art, the lighting control of the tunnel entrance can be achieved by adopting a fixed lighting mode based on time segmentation and a simple dimming solution triggered by a preset threshold. The following introduces the scenario of using the wireless control method of LED lighting in the related art.

[0033] In a highway tunnel, a fixed-value lighting control system based on time periods is used. The system presets three fixed lighting schemes: day mode (8:00-17:00), dusk mode (17:00-19:00) and night mode (19:00-8:00 the next day). The lighting intensity of each time period is a pre-set fixed value, such as 2000 lux at the entrance section and 1000 lux at the buffer section in day mode. However, during a rainstorm, the external light dropped from 5000 lux to 800 lux within 10 minutes, while the lighting system still maintained a high illumination state in day mode, causing serious light pollution and energy waste, and the driver would experience visual discomfort.

[0034] The wireless control method for LED lighting in the embodiment of the present application is used to achieve continuous and smooth adjustment of lighting intensity through multi-dimensional parameter collection and algorithm calculation, which not only ensures driving safety but also improves energy efficiency. The following describes the scenarios in which the wireless control method for LED lighting in the present application is used.

[0035] In a highway tunnel, an LED intelligent lighting system based on this application is installed. The system arranges a high-precision light sensor network in the tunnel entrance area to monitor the changes in external brightness in real time. When a change in external light is detected, the system immediately calculates a new illumination gradient curve. For example, when a thunderstorm comes, the system detects that the external brightness drops from 8000 lux to 3000 lux. It immediately calculates the visual adaptation time required by the driver of 2.3 seconds based on the current average speed of 70 km / h, automatically generates a new illumination gradient curve, and completes the parameter adjustment of all lighting partitions within 0.3 seconds, ensuring a smooth transition of the driver's visual experience.

[0036] It can be seen that the wireless control method of LED lighting in the embodiment of the present application can not only realize the dynamic adjustment of tunnel lighting, but also effectively solve the visual adaptation problems and energy waste problems caused by the traditional fixed mode, thereby achieving the improvement of safety, comfort and energy saving.

[0037] For ease of understanding, the following describes the process of the method provided by this implementation in combination with the above scenario. Figure 1 , which is a flow chart of the wireless control method of LED lighting in an embodiment of the present application.

[0038] S101. Obtain tunnel lighting control parameters.

[0039] Among them, tunnel lighting control parameters represent a set of key parameters used to control the operation of the tunnel lighting system, including external brightness value, tunnel parameters and vehicle speed; external brightness value refers to the natural light intensity at the entrance of the tunnel, usually in lux; tunnel parameters are used to represent the physical characteristics of the tunnel, including geometric parameters such as tunnel length, width, height, etc.; vehicle speed refers to the actual driving speed of motor vehicles passing through the tunnel, usually in kilometers per hour (km / h).

[0040] The dimming device needs to obtain tunnel lighting control parameters during the initialization or operation of the tunnel lighting system. Specifically, the dimming device first collects the external brightness value at the tunnel entrance in real time through the light sensor, reads the preset tunnel parameters from the tunnel management system database, and obtains the actual speed of the current vehicle through the speed detector, and integrates these data into a complete control parameter set.

[0041] In some embodiments, the process of acquiring tunnel lighting control parameters can be implemented in a variety of ways: optionally, multiple light sensors arranged at the tunnel entrance collect external brightness data, filter the collected data to eliminate interference, calculate the average value to obtain the external brightness value, read the tunnel parameters from the database, and collect the vehicle speed through the geomagnetic detector; optionally, the external brightness data is assisted by weather forecast data, the tunnel parameters are extracted from the construction drawings, and the vehicle speed is obtained using a high-speed speed measurement system. It is understandable that other sensor combinations can also be used to obtain control parameters, which are not limited here.

[0042] S102. Divide the tunnel entrance area into an entrance section, a buffer section, and a basic section according to tunnel parameters, and determine a plurality of lighting control zones.

[0043] The entrance section refers to an area near the entrance of the tunnel, which is used to achieve the lighting transition from the external environment to the inside of the tunnel. The buffer section refers to the transition area after the entrance section, which is used to further adjust the lighting level. The basic section refers to the standard lighting area inside the tunnel. The lighting control partition refers to an independent control unit divided according to lighting needs, and each partition has independent illumination control capabilities.

[0044] After obtaining the tunnel parameters, the dimming device needs to reasonably segment the tunnel entrance area. Specifically, the dimming device first determines the length of the entrance section based on the total length of the tunnel, usually 1.5-2 times the height of the tunnel, and then determines the length of the buffer section, which is generally 1-1.5 times the length of the entrance section. The remaining part is divided into basic sections. After that, based on the length and width data of each section, each section is divided into several lighting control partitions, and the size of each partition is determined according to the lighting uniformity requirements.

[0045] It should be noted that, for ease of understanding, this application mainly discusses the lighting control at the entrance, and the lighting control at the exit can be mirrored based on the entrance to optimize the lighting control out of the tunnel.

[0046] In some embodiments, tunnel partitioning can be achieved in a variety of ways: optionally, the theoretical partition length is calculated according to the tunnel cross-sectional shape, and the actual lamp installation position is considered to make corrections, the number of lateral partitions is determined in combination with the number of lanes, and finally the partition number is generated; optionally, a three-dimensional model of the tunnel is established using computer-aided design software, optical simulation analysis is performed, and the partition scheme is optimized based on the simulation results. It is understandable that other engineering calculation methods can also be used to achieve partitioning, which is not limited here.

[0047] S103: Based on the external brightness value and the vehicle travel speed, the brightness adaptation time of the vehicle driver is calculated, and an illumination gradient curve from the entrance section to the buffer section and the basic section is generated.

[0048] The brightness adaptation time refers to the time required for the driver's vision to switch from light adaptation to dark adaptation. The illuminance gradient curve refers to the function curve that describes the change law of lighting intensity from the tunnel entrance to the basic section, which is used to guide the operation of the lighting control system.

[0049] The dimming device needs to calculate the appropriate lighting transition plan based on the current external environment and traffic conditions. Specifically, the dimming device first determines the initial visual state of the driver when entering the tunnel based on the external brightness value, then calculates the time required for the vehicle to pass through each section based on the current vehicle speed, and determines the required brightness adaptation time based on the dark adaptation characteristics of the human eye. Based on these parameters, a mathematical model is used to generate a continuous illumination gradient curve from the entrance section to the basic section.

[0050] In some embodiments, the illumination gradient curve can be generated in a variety of ways: optionally, an exponential decay model is used to calculate the illumination value of each point, an interpolation algorithm is applied to generate a smooth curve, and curve parameters are optimized; optionally, a neural network model is used to input parameters such as external brightness and vehicle speed, and the optimal illumination change curve is trained and predicted. It is understandable that other mathematical models can also be used to generate the illumination gradient curve, which is not limited here.

[0051] It should be noted that the exponential decay model is used to describe the visual change process of the driver from light adaptation to dark adaptation. When training the exponential decay model, it is necessary to collect training data through large-scale driver visual adaptation experiments, including visual adaptation process data of drivers of different ages under various lighting conditions. The experiment measures the change in visual perception of the driver when entering a low-brightness environment (50-500 lux) from a high-brightness environment (5000-20000 lux). The training data of the exponential decay model includes: initial brightness value, target brightness value, measured visual perception values ​​at multiple time points during the adaptation process, driver age, etc. The least squares method is used to optimize the model parameters to minimize the mean square error between the model prediction value and the measured value. The exponential decay model is constructed based on the mathematical formula V(t)=V0*e^(-kt)+C, where V(t) represents the visual brightness perception value at time t, V0 is the initial visual brightness value, k is the attenuation coefficient related to the vehicle speed, and C is the brightness value of the final stable state. The exponential decay model also includes an age correction coefficient α and an environmental factor correction coefficient β to form a complete description of the visual adaptation characteristics. By inputting the external brightness value (obtained through the light sensor), vehicle speed data (obtained through the vehicle speed monitor) and driver characteristics in real time, the exponential decay model can output a complete visual brightness adaptation curve to guide the generation of the lighting gradient curve.

[0052] S104: Determine the target illumination value of each lighting control zone according to the illumination gradient curve.

[0053] The target illuminance value indicates the lighting intensity value that each lighting control zone needs to achieve. The illuminance calculation needs to consider lighting quality parameters such as lighting uniformity and appearance ratio.

[0054] The dimming device needs to convert the continuous illuminance gradient curve into discrete partition control parameters. Specifically, the dimming device first determines the spatial position of each lighting control partition, then takes the illuminance value of the corresponding position on the illuminance gradient curve, considers the uniformity requirements within the partition, calculates the target illuminance value of the partition, and ensures smooth illuminance transition between adjacent partitions.

[0055] In some embodiments, the target illumination value can be determined in a variety of ways: optionally, the theoretical illumination value of the partition center point is calculated, and the lamp arrangement is considered to make corrections, and the lighting quality index is verified to obtain the final target value; optionally, a lighting mathematical model is established, and the superposition effect of multiple lamps is considered, and the target illumination value is obtained by optimization calculation. It is understandable that other optimization algorithms can also be used to determine the target illumination value, which is not limited here.

[0056] S105 , converting the target illumination value into LED driving parameters, and sending the parameters to the LED driving circuits of each lighting control partition through the wireless communication module.

[0057] Among them, LED driving parameters refer to the electrical parameters that control the output luminous flux of LED lamps, including driving current, duty cycle, etc. The wireless communication module refers to the communication device used to realize data transmission between the controller and the driving circuit. The LED driving circuit is used to perform actual current regulation control.

[0058] The dimming device needs to convert the illumination control instruction into specific execution parameters. Specifically, the dimming device first converts the target illumination value into the corresponding electrical parameters according to the electro-optical conversion characteristic curve of the LED lamp, and then packages these parameters into control instructions and sends them to the LED drive circuits of each partition through the wireless communication network. After receiving the instructions, the drive circuit performs the corresponding dimming operation.

[0059] In some embodiments, the conversion and distribution of driving parameters can be achieved in a variety of ways: optionally, a database of illumination-current correspondence is established, basic parameters are obtained by table lookup, temperature compensation is considered, and instructions are issued through the MQTT protocol; optionally, a PWM dimming algorithm is used to calculate driving parameters, communication encryption is performed, and control instructions are transmitted using the Zigbee network. It is understandable that other communication methods and control algorithms can also be used to implement parameter distribution, which is not limited here.

[0060] S106, collecting actual illumination data of each lighting control zone, and regenerating an illumination gradient curve when the actual illumination data exceeds a preset target range or an external brightness value changes.

[0061] The actual illuminance data indicates the current measured illuminance value of the lighting control partition. The preset target range refers to the allowable illuminance deviation range, which is usually set to ±10% of the target value. Illuminance monitoring is used to achieve closed-loop control and timely adjustment.

[0062] The dimming device needs to continuously monitor the operating status of the lighting system and respond. Specifically, the dimming device collects illuminance data in real time through illuminance sensors distributed in each control zone, compares the collected data with the preset target range, and monitors the changes in the external brightness value. When an abnormal illuminance or a change in the external environment is detected, the generation process of the illuminance gradient curve is re-executed to achieve dynamic adjustment of lighting parameters.

[0063] The following is a more detailed description of the process of the method provided by this implementation. Figure 2 , is another flow chart of the wireless control method of LED lighting in an embodiment of the present application.

[0064] S201. Obtain tunnel lighting control parameters.

[0065] Referring to step S101 , the dimming device obtains tunnel lighting control parameters.

[0066] In some embodiments, the dimming device first groups the LED lamps in each lighting control zone, assigns group numbers and communication addresses, and determines multiple groups of LED lamps; collects the initial electrical parameters of each group of LED lamps; the initial electrical parameters include rated power, dimming range, and current gain coefficient; and determines the driving parameters of the LED lamps based on the initial electrical parameters and the dimming characteristic curve of the LED lamps.

[0067] Among them, lighting control partition refers to the independent lighting control area divided in the tunnel. LED lamps refer to light-emitting diode lighting devices used for tunnel lighting. Group number is used to indicate the logical grouping relationship of lamps. Communication address indicates the unique identification of each lamp in the network. Initial electrical parameters refer to the basic working characteristics of lamps, including rated power, dimming range and current gain coefficient. Dimming characteristic curve indicates the corresponding relationship between input and output of LED lamps.

[0068] The dimming device needs to establish a lamp control system during the system initialization phase. Specifically, the dimming device first physically locates and groups the LED lamps in the tunnel, assigns a unique communication address to each lamp, and then collects the electrical parameters of each group of lamps, including rated power value, dimming range, and current gain characteristics. Based on these parameters and the dimming characteristic curve of the lamp, the optimal drive control parameters are calculated.

[0069] In some embodiments, the initialization configuration of the lamp control parameters can be implemented in a variety of ways: optionally, scanning physical addresses, establishing grouping schemes, testing communication links, collecting electrical parameters, and generating control tables; optionally, importing lamp layout diagrams, automatically assigning addresses, measuring operating characteristics, establishing parameter models, and optimizing drive configurations. It is understandable that other configuration methods can also be used to implement the initialization of the lamp control system, which is not limited here.

[0070] S202. Divide the tunnel entrance area into an entrance section, a buffer section, and a basic section according to tunnel parameters, and determine a plurality of lighting control partitions.

[0071] Referring to step S102 , the dimming device determines a plurality of lighting control zones.

[0072] In some embodiments, the dimming device determines the total length data of the tunnel and the lane width data based on the tunnel parameters; divides the tunnel entrance area into an entrance section, a buffer section and a basic section based on the total length data of the tunnel; and determines multiple lighting control partitions based on the segmentation type and lane width data of the tunnel entrance area.

[0073] Among them, tunnel parameters represent the basic data describing the physical characteristics of the tunnel. The tunnel full length data refers to the actual length of the tunnel. The lane width data is used to represent the lateral dimensions of the lane. The entrance section, buffer section and basic section represent the three functional areas of the tunnel entrance area.

[0074] When designing lighting zones, the dimming device needs to be reasonably divided based on the physical characteristics of the tunnel. Specifically, the dimming device first extracts the full-length data and lane width information from the tunnel parameters, determines the length of the entrance section, buffer section and basic section according to the full-length data in accordance with the standard ratio, and then combines the lane width data and the lighting demand characteristics of each section to divide multiple independent lighting control zones to ensure the lighting uniformity and controllability of each zone.

[0075] S203: Determine an initial visual brightness adaptation value of the vehicle driver when entering the tunnel according to the external brightness value.

[0076] The initial visual brightness adaptation value indicates the visual brightness perception level of the driver's eyes when entering the tunnel. The external brightness value refers to the ambient light intensity at the entrance of the tunnel, in lux. Visual brightness adaptation refers to the process of human eyes adapting to different brightness environments, including dark adaptation and light adaptation.

[0077] After acquiring external brightness data, the dimming device needs to determine the driver's initial visual state. Specifically, the dimming device first collects real-time brightness data at the tunnel entrance, considers the human eye's perception of different brightness levels, and combines the physiological optical model to calculate the driver's visual brightness adaptation level before entering the tunnel. This value will serve as an important reference for subsequent lighting control.

[0078] In some embodiments, the initial visual brightness adaptation value can be determined in a variety of ways: optionally, collecting multi-point brightness data, performing data smoothing, applying the Weber-Fechner law to calculate the visual perception value, and taking age factors into account for correction; optionally, establishing a human eye vision model, inputting environmental parameters, predicting the visual adaptation state through a neural network, and verifying it in combination with experimental data. It is understandable that other physiological optical models can also be used to determine the initial adaptation value, which is not limited here.

[0079] S204: Calculate an adaptation time threshold for the vehicle driver from light adaptation to dark adaptation based on the vehicle travel speed.

[0080] Among them, light adaptation to dark adaptation refers to the process of human eyes adapting from a high-brightness environment to a low-brightness environment. The adaptation time threshold refers to the shortest time required to complete visual adaptation. The vehicle speed is used to indicate the actual speed of vehicles passing through the tunnel entrance area.

[0081] The dimming device needs to calculate the appropriate visual adaptation time according to the current traffic conditions. Specifically, the dimming device first analyzes the traffic flow data and vehicle type distribution characteristics, combines the actual speed of different types of vehicles, calculates the time it takes for vehicles to pass through the tunnel entrance area, and then determines the shortest time threshold required for the driver to switch from light adaptation to dark adaptation based on the physiological characteristics of dark adaptation of the human eye.

[0082] In some embodiments, the calculation of the adaptation time threshold can be achieved in a variety of ways: optionally, collecting traffic flow data, identifying traffic characteristics, calculating the average travel time, determining the basic threshold in combination with the safety factor, and making corrections based on weather factors; optionally, establishing a traffic flow model, simulating the vehicle operation status, analyzing the driver's visual changes, and optimizing the calculation of the adaptation time. It is understandable that other traffic analysis methods can also be used to determine the adaptation time threshold, which is not limited here.

[0083] It should be noted that the traffic flow model is used to predict the traffic flow characteristics of the tunnel entrance area and provide a basis for lighting control. The traffic flow model collects at least one year of tunnel traffic history data during training, including time series data such as vehicle flow, vehicle model distribution, and traffic speed. The training data also includes external factors such as weather conditions and holiday information. The LSTM (Long Short-Term Memory) neural network architecture is adopted. The input features include historical traffic data sequences and external factors, and the output is the traffic forecast value for the future period. The network parameters are optimized by minimizing the difference between the prediction error and the true value. The traffic flow model adopts a multi-layer LSTM network structure, including an input layer (processing multi-dimensional traffic characteristics), an LSTM layer (capturing time series characteristics), a fully connected layer, and an output layer. The traffic flow model can simultaneously predict multiple traffic parameters such as vehicle flow, average vehicle speed, and vehicle model distribution. The traffic flow model can continuously input real-time traffic monitoring data and output traffic condition forecasts for the next 5-15 minutes, including vehicle flow change trends, speed distribution forecasts, etc., which are used to adjust the lighting control strategy in advance.

[0084] In some embodiments, the dimming device obtains the traffic flow data and vehicle type distribution data at the tunnel entrance; performs time series analysis on the traffic flow data to identify traffic flow characteristics including peak and trough periods; based on the vehicle type distribution data, classifies and counts the vehicles according to passenger cars, buses and trucks to obtain vehicle type characteristics; collects the real-time travel speed of each type of vehicle to obtain speed distribution characteristics; and determines the average time threshold for the driver's visual adaptation based on the traffic flow characteristics, vehicle type characteristics and speed distribution characteristics.

[0085] Among them, traffic flow characteristics are used to represent the temporal distribution of traffic flow; vehicle type characteristics refer to the statistical characteristics of vehicle types; and speed distribution characteristics represent the actual driving speed distribution of various types of vehicles.

[0086] The dimming device needs to comprehensively analyze traffic characteristics when determining the visual adaptation time. Specifically, the dimming device first collects real-time traffic flow and vehicle type data at the tunnel entrance, performs time series analysis on the traffic flow to identify peak and trough characteristics, and classifies and counts vehicle types. Combined with the real-time speed data of various types of vehicles, a complete traffic characteristic model is established, and finally the driver's visual adaptation time threshold that conforms to the actual situation is calculated.

[0087] S205 , using an exponential decay model, combining the initial visual brightness adaptation value and the adaptation time threshold, to generate a driver's visual brightness adaptation curve.

[0088] The exponential decay model is a mathematical model that describes the process of human visual brightness adaptation. The visual brightness adaptation curve is a function curve that characterizes the change of the driver's visual perception ability over time. The model parameters include variables such as initial brightness value, decay coefficient and time constant.

[0089] After obtaining the initial adaptation value and time threshold, the dimming device needs to establish a complete visual adaptation process model. Specifically, the dimming device first selects a suitable exponential decay function according to the physiological characteristics of human vision, takes the initial visual brightness adaptation value as the starting point of the function, determines the decay rate with the adaptation time threshold, and generates a continuous curve describing the driver's visual adaptation process through mathematical calculation.

[0090] In some embodiments, the generation of the visual brightness adaptation curve can be achieved in a variety of ways: optionally, an exponential function model is set, initial parameters are input, the adaptation values ​​at key time points are calculated, an interpolation algorithm is used to generate a smooth curve, and the rationality of the curve is verified; optionally, a polynomial fitting model is established, the function coefficients are determined in combination with experimental data, the curve shape is optimized, and the fitting accuracy is evaluated. It is understandable that other mathematical models can also be used to generate the adaptation curve, which is not limited here.

[0091] S206: Determine the illumination gradient curve from the entrance segment to the buffer segment and the basic segment based on the visual brightness adaptation curve.

[0092] The illumination gradient curve shows the changing pattern of lighting intensity in each section of the tunnel. The entrance section to the buffer section refers to the transition area of ​​tunnel lighting. The basic section lighting refers to the standard lighting level in the tunnel.

[0093] The dimming device needs to convert the driver's visual adaptation characteristics into an actual lighting control curve. Specifically, the dimming device first analyzes the changing characteristics of the visual brightness adaptation curve, combines the length parameters of each section of the tunnel, establishes the corresponding relationship between visual adaptation and lighting requirements, and finally generates a continuous illumination gradient curve from the entrance section to the buffer section and the basic section.

[0094] In some embodiments, the determination of the illumination gradient curve can be achieved in a variety of ways: optionally, analyzing visual adaptation characteristics, determining key control points, calculating illumination requirements at each point, applying a curve fitting algorithm, and generating a smooth transition curve; optionally, establishing a light environment model, considering tunnel structural characteristics, optimizing illumination distribution, and generating a segmented control curve. It is understandable that other lighting design methods can also be used to determine the gradient curve, which is not limited here.

[0095] S207: Determine the target illumination value of each lighting control zone according to the illumination gradient curve.

[0096] Referring to step S104 , the dimming device determines a target illumination value.

[0097] S208: Convert the target illumination value into LED driving parameters, and send them to the LED driving circuits of each lighting control partition through the wireless communication module.

[0098] Referring to step S105 , the dimming device determines LED driving parameters and performs circuit control.

[0099] S209, collecting actual illumination data of each lighting control zone, and regenerating an illumination gradient curve when the actual illumination data exceeds a preset target range or the external brightness value changes.

[0100] Referring to step S106 , the dimming device regenerates the illumination gradient curve.

[0101] S210: Determine the illumination time series variation characteristics of each lighting control partition based on the actual illumination data.

[0102] Among them, the illumination time series variation characteristics represent the law of illumination variation over time in the lighting control partition. The actual illumination data refers to the measured illumination intensity value collected by the sensor. The time series characteristics include variation trend, periodicity and fluctuation range.

[0103] The dimming device needs to dynamically analyze the operating status of the lighting system. Specifically, the dimming device first collects the historical illumination data of each lighting control partition, extracts the characteristic parameters of illumination change through time series analysis method, including short-term fluctuation characteristics and long-term change trends, and establishes a mathematical description of the operating status of the lighting system.

[0104] S211. Determine the illumination drift trend based on historical illumination data and illumination time series variation characteristics.

[0105] The illuminance drift trend indicates the degree of deviation between the actual output of the lighting system and the target value and its development direction. Historical illuminance data refers to the illuminance records stored during the operation of the system.

[0106] The dimming device needs to predict the performance change trend of the lighting system. Specifically, the dimming device first integrates the historical illumination data and the current time series change characteristics, calculates the drift direction and rate of the illumination value through the trend analysis algorithm, evaluates the stability of the lighting system, and predicts possible abnormal conditions.

[0107] In some embodiments, the prediction of the illuminance drift trend can be achieved in a variety of ways: optionally, collecting historical data, establishing a trend model, calculating drift parameters, evaluating development trends, and generating warning information; optionally, applying a regression analysis method, fitting a drift curve, predicting future states, and determining a warning threshold. It is understandable that other prediction methods can also be used to analyze the drift trend, which is not limited here.

[0108] It should be noted that the trend model is used to predict the performance change trend of the lighting system and realize predictive maintenance. The trend model needs to collect the operating data of the lighting system during training, including the measured illuminance value of each partition, ambient temperature, operating time, energy consumption data, etc. The training data also includes information such as the aging characteristics and maintenance records of LED lamps. The model is trained using a time series prediction algorithm, and the optimization goal is to minimize the illuminance prediction deviation while considering the timeliness and accuracy of the warning. The trend model combines multiple regression and time series analysis methods to establish a mathematical model of illuminance change, which includes trend terms (reflecting long-term changes), periodic terms (reflecting environmental impacts) and random terms (reflecting sudden changes). The trend model also integrates the lamp life prediction sub-model and the energy efficiency evaluation sub-model. By continuously inputting real-time illuminance monitoring data, operating parameters and environmental data, the trend model can output illuminance change trend prediction, abnormal warning information and maintenance suggestions to support predictive maintenance of the lighting system.

[0109] S212: When it is determined based on the illuminance drift trend that the actual illuminance data exceeds a preset target range after a preset interval time, adjust LED driving parameters.

[0110] The preset interval time represents the time span predicted by the system. The preset target range refers to the allowable illumination deviation range. LED drive parameter adjustment refers to the compensation control of the lighting output.

[0111] The dimming device needs to implement preventive adjustments based on the prediction results. Specifically, the dimming device first predicts the illumination value at a certain point in the future based on the illumination drift trend. When the predicted value may exceed the target range, the required compensation amount is calculated in advance, and the active correction of the lighting output is achieved by adjusting the LED driving parameters. In some embodiments, the pre-adjustment of LED driving parameters can be achieved in a variety of ways: optionally, calculating the prediction deviation, determining the compensation strategy, generating adjustment instructions, executing parameter correction, and verifying the adjustment effect; optionally, establishing a predictive control model, optimizing the compensation parameters, implementing progressive adjustments, and monitoring the system response. It is understandable that other control strategies can also be used to achieve parameter adjustment, which is not limited here.

[0112] In some embodiments, the dimming device also collects the illumination timing data and energy consumption data of each lighting control zone, calculates the lighting index score; records the dimming curve during the illumination correction process, and extracts the dimming characteristic parameters; generates a lighting performance evaluation report based on the lighting index score and dimming characteristic parameters, combined with historical operation data.

[0113] Among them, illumination time series data refers to the record of lighting intensity changes over time. Energy consumption data refers to the power consumption of the lighting system. The lighting index score is used to represent the comprehensive performance evaluation of the lighting system. The dimming characteristic parameters refer to the key parameters that describe the illumination adjustment process. The performance evaluation report represents the comprehensive analysis results of the system operation status.

[0114] The dimming device needs to be evaluated during system operation. Specifically, the dimming device continuously collects illumination change data and energy consumption data of each lighting zone, calculates the performance index score of the lighting system through data analysis, and records the changes in control parameters during the illumination adjustment process. Finally, combined with historical operation data, a performance evaluation report is generated to provide a basis for system optimization.

[0115] In some embodiments, the performance evaluation of the lighting system can be achieved in a variety of ways: optionally, collecting operating data, calculating performance indicators, analyzing dimming characteristics, evaluating system status, and generating analysis reports; optionally, establishing an evaluation model, processing historical data, extracting key features, optimizing scoring methods, and outputting evaluation results. It is understandable that other evaluation methods can also be used to achieve the performance analysis of the lighting system, which is not limited here.

[0116] In the embodiment of the present application, due to the adoption of real-time monitoring of external brightness, intelligent execution of lighting control based on the driver's visual adaptation model, and combination of LED zone dimming technology and predictive maintenance strategy, it is possible to achieve continuous dynamic adjustment of tunnel lighting intensity and fault warning, effectively solving the problems of delayed response, energy waste, passive maintenance, etc. of traditional fixed lighting mode when dealing with sudden changes in external light, thereby achieving improved driving safety, optimized lighting comfort and improved energy utilization efficiency.

[0117] The dimming device in the embodiment of the present invention is described below from the perspective of hardware processing. Figure 3 , is a schematic diagram of a physical device structure of a dimming device in an embodiment of the present application.

[0118] It should be noted that Figure 3 The structure of the dimming device shown is only an example and should not bring any limitation to the function and scope of use of the embodiment of the present invention.

[0119] like Figure 3As shown, the dimming device includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method described in the above embodiment. In the RAM 303, various programs and data required for system operation are also stored. The CPU 301, the ROM 302 and the RAM 303 are connected to each other through the bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0120] The following components are connected to the I / O interface 305: an input section 306 including an audio input device, a button switch, etc.; an output section 307 including a liquid crystal display (LCD) and an audio output device, an indicator light, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0121] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0122] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0123] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings.

[0124] Specifically, the dimming device of this embodiment includes a processor and a memory. The memory stores a computer program. When the computer program is executed by the processor, the wireless control method of LED lighting provided in the above embodiment is implemented.

[0125] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the dimming device described in the above embodiment; or may exist independently without being assembled into the dimming device. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of the dimming device, the dimming device implements the wireless control method of LED lighting provided in the above embodiment.

[0126] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0127] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0128] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A wireless control method for LED lighting, characterized in that: Applied to a dimming device, the method comprises: Acquiring tunnel lighting control parameters; the tunnel lighting control parameters include external brightness value, tunnel parameters and vehicle travel speed; According to the tunnel parameters, the tunnel entrance area is divided into an entrance section, a buffer section and a basic section, and a plurality of lighting control zones are determined; Based on the ambient brightness value and the vehicle passing speed, the brightness adaptation time of the vehicle driver is calculated, and an illumination gradient curve from the entrance section to the buffer section and the basic section is generated; Determining the target illumination value of each lighting control zone according to the illumination gradient curve; Convert the target illumination value into LED driving parameters, and send them to the LED driving circuits of each lighting control partition through a wireless communication module; The actual illumination data of each lighting control partition is collected, and when the actual illumination data exceeds a preset target range or the external brightness value changes, an illumination gradient curve is regenerated.

2. The method according to claim 1, characterized in that The step of dividing the tunnel entrance area into an entrance section, a buffer section and a basic section according to the tunnel parameters, and determining a plurality of lighting control zones specifically includes: Determine tunnel length data and lane width data according to the tunnel parameters; According to the tunnel full-length data, the tunnel entrance area is divided into an entrance section, a buffer section and a basic section; A plurality of lighting control zones are determined according to the segment type of the tunnel entrance area and the lane width data.

3. The method according to claim 1, characterized in that The step of calculating the brightness adaptation time of the vehicle driver based on the external brightness value and the vehicle passing speed, and generating the illumination gradient curve from the entrance section to the buffer section and the basic section specifically includes: Determining, according to the ambient brightness value, an initial visual brightness adaptation value of the vehicle driver when entering the tunnel; Calculating, based on the vehicle speed, an adaptation time threshold for the vehicle driver from light adaptation to dark adaptation; Using an exponential decay model, combining the initial visual brightness adaptation value and the adaptation time threshold, to generate a driver's visual brightness adaptation curve; Based on the visual brightness adaptation curve, an illumination gradient curve from the entrance section to the buffer section and the basic section is determined.

4. The method according to claim 3, characterized in that The step of calculating the adaptation time threshold of the vehicle driver from light adaptation to dark adaptation based on the vehicle passing speed specifically includes: Obtain traffic flow data and vehicle type distribution data at the tunnel entrance; Performing time series analysis on the traffic flow data to identify traffic flow characteristics including peak periods and trough periods; Based on the vehicle type distribution data, the vehicles are classified and counted according to passenger cars, buses and trucks to obtain vehicle type characteristics; Collect the real-time speed of various vehicles and obtain the speed distribution characteristics; An average time threshold of the driver's visual adaptation is determined according to the traffic flow characteristics, the vehicle type characteristics and the speed distribution characteristics.

5. The method according to claim 1, characterized in that Before the step of obtaining the tunnel lighting control parameters, the method further includes: Group and number the LED lamps in each lighting control zone and assign communication addresses to determine multiple groups of LED lamps; Collecting initial electrical parameters of each group of LED lamps; the initial electrical parameters include rated power, dimming range and current gain coefficient; Based on the initial electrical parameters and the dimming characteristic curve of the LED lamp, driving parameters of the LED lamp are determined.

6. The method according to claim 1, characterized in that After the step of collecting the actual illuminance data of each lighting control partition and regenerating the illuminance gradient curve when the actual illuminance data exceeds a preset target range or the external brightness value changes, the method further includes: Based on the actual illumination data, determining the illumination time-series variation characteristics of each of the lighting control partitions; Determine the illumination drift trend according to the historical illumination data and the illumination time series variation characteristics; When it is determined based on the illuminance drift trend that the actual illuminance data exceeds a preset target range after a preset interval time, the LED driving parameters are adjusted.

7. The method according to claim 6, characterized in that After the step of adjusting the LED driving parameters when it is determined based on the illuminance drift trend that the actual illuminance data exceeds a preset target range after a preset interval time, the method further includes: Collecting illumination time series data and energy consumption data of each lighting control zone, and calculating the lighting index score; Record the dimming curve during illumination correction and extract dimming characteristic parameters; A lighting performance evaluation report is generated based on the lighting index score and the dimming characteristic parameters in combination with historical operation data.

8. A dimming device, characterized in that: The dimming device comprises: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors call the computer instructions so that the dimming device executes the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the dimming device, the dimming device is caused to perform the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product runs on a dimming device, the dimming device is enabled to perform the method according to any one of claims 1 to 7.

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