Control method and system applied to bridge landscape, product and storage medium

Abstract

The invention discloses a control method and system applied to a bridge landscape, a product and a storage medium, and relates to the technical field of bridges. By acquiring the monitoring data of the detection points in real time and comparing the monitoring data with the preset threshold value, the influence of environment change on fountain operation can be found in time. When monitoring data exceeds a threshold value, the monitoring data and historical data are input into the prediction model together, and the change trend of the environment in a period of time in the future can be obtained. And according to the prediction result, an optimal fountain parameter combination is selected from a preset mapping relation table, the optimal fountain parameter combination comprises spraying force, angle, duration, water column shape and the like, and the fountain operation is adjusted in real time according to the optimal fountain parameter combination. And after adjustment, analyzing whether the actual spray amount reaches the expectation or not through image recognition, and if not, continuing monitoring and adjustment. The circulation can ensure that the fountain is always in the optimal working state when the environment changes, and can prevent water from splashing to influence the driving safety.

Description

Technical Field

[0001] The present application relates to the field of bridge technology, and in particular to a control method, system, product and storage medium applied to bridge landscape. Background Art

[0002] With the booming tourism economy, many scenic spots hope to create unique night scenes to attract tourists to visit. As an important hub of urban transportation, bridges not only shoulder the transportation function, but are also often an important window to showcase the city's cultural tourism image. Bridge landscapes are generally divided into two categories: one is to use lights to decorate the bridge structure, and the other is to arrange fountains, water curtains and other waterscapes around the bridge. The two complement each other and jointly create a colorful bridge night scene. For example, Nanx City has built the Jiaxjiang Bridge on x Road into a landscape bridge that integrates bridge deck lighting, digital fountains, and water curtain projection.

[0003] In terms of bridge landscape, a common practice is to arrange digital fountain devices on both sides of the bridge. By presetting parameters such as nozzle angle and spray duration, a dreamlike water curtain can be formed on both sides of the bridge, which complements the bridge deck lights and creates a gorgeous visual feast. Designers usually preset a set of fountain operation parameters based on the geographical location and climate characteristics of the bridge, and the fountain device works periodically according to the preset parameters.

[0004] Digital fountains and water curtain systems installed on bridges face safety challenges under changing environmental conditions, such as increased wind speed, temperature changes or increased humidity. For example, when the wind speed is high, the water may deviate from its original area, causing water to splash onto unintended areas such as sidewalks or driving lanes, thus affecting the safety and comfort of pedestrians and vehicles. Summary of the invention

[0005] The present application provides a control method, system, product and storage medium applied to bridge landscape, which are used to ensure that the fountain is always in the best working state when the environment changes and to avoid splashing water that affects driving safety.

[0006] In the first aspect, the present application provides a control method for bridge landscape, including: obtaining real-time monitoring data of a detection point; when the real-time monitoring data exceeds a preset impact threshold, inputting the real-time monitoring data and historical data into an environmental prediction model to obtain predicted environmental data for a preset time interval; finding a corresponding parameter combination in a preset mapping relationship table according to the predicted environmental data, wherein a series of discrete adjustment values ​​are set for each adjustable parameter in the preset mapping relationship table; adjusting the adjustable parameter combination according to the parameter combination, the adjustable parameter combination including spray intensity, nozzle angle, spray time, nozzle movement speed, nozzle trajectory, and water column shape; after adjusting the adjustable parameter combination, obtaining first image data of a specified area; identifying the amount of water splash data in the first image data; and executing the step of obtaining real-time monitoring data of the detection point when the amount of water splash data is greater than the preset water splash threshold.

[0007] By adopting the above technical solution, by acquiring the monitoring data of the detection point in real time and comparing it with the preset threshold, the impact of environmental changes on the operation of the fountain can be discovered in time. When the monitoring data exceeds the threshold, it is input into the prediction model together with the historical data to obtain the changing trend of the environment in the future. According to the prediction results, the optimal fountain parameter combination is selected from the preset mapping relationship table, including the spray intensity, angle, duration, water column shape, etc., and the fountain operation is adjusted in real time accordingly. After adjustment, image recognition is used to analyze whether the actual amount of water spray meets the expectations. If not, continue to monitor and adjust. Such a cycle can ensure that the fountain is always in the best working state when the environment changes and can avoid splashing water to affect driving safety.

[0008] In combination with some embodiments of the first aspect, in some embodiments, after the step of adjusting the adjustable parameter combination according to the parameter combination, where the adjustable parameter combination includes spray intensity, nozzle angle, spray time, nozzle movement speed, nozzle trajectory, and water column shape, the method also includes: upon receiving an intervention instruction from an operator terminal, readjusting the adjustable parameter combination according to the intervention instruction; after readjusting the adjustable parameter combination, acquiring second image data of a specified area; identifying the data amount of water splash in the second image data; and upon the data amount of the water splash being greater than a preset water splash threshold, feeding back the data amount of the water splash to the operator terminal.

[0009] By adopting the above technical solutions, the flexibility and humanization of bridge landscape digital fountain control can be further improved. On the basis of the original automatic parameter adjustment, the system can also receive remote intervention instructions from the operator. When the operator wants to make specific adjustments to the fountain effect based on actual observations or other considerations, he can directly issue instructions, and the system will immediately reset the adjustable parameters as required and monitor the adjustment effect in real time. If the actual amount of water after adjustment does not meet the operator's expectations, the system will provide timely feedback to help the operator make judgments.

[0010] In combination with some embodiments of the first aspect, in some embodiments, after the step of adjusting the adjustable parameter combination according to the parameter combination, wherein the adjustable parameter combination includes spray intensity, nozzle angle, spray time, nozzle movement speed, nozzle trajectory, and water column shape, the method further includes: performing a closing operation when a preset closing condition is reached or a closing instruction is received from an operator terminal; after performing the closing operation, determining the gap between the real-time monitoring data and the predicted environmental data; if the gap exceeds an error threshold, determining the real-time monitoring data as new historical data; and training the environmental prediction model using the new historical data.

[0011] By adopting the above technical solution, after the system controls a fountain operation cycle based on the prediction results, it will compare the actual monitoring data in the cycle with the predicted value and calculate the difference. If the difference exceeds the allowable range, it means that there is a large deviation in this prediction. At this time, the system will mark the measured data of the cycle as new valid historical data for subsequent prediction model retraining. Through this closed-loop mechanism of data labeling and model retraining, the system can continuously accumulate real environmental change data and continuously improve the accuracy of the prediction model.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the step of obtaining real-time monitoring data of the detection point, the method also includes: determining whether the real-time monitoring data meets the preset extreme weather settings; if it meets the preset extreme weather settings, completely closing the bridge landscape; sending a safety alarm message to the bridge display screen so that the bridge display screen displays the safety alarm message.

[0013] By adopting the above technical solutions, the system can determine in real time whether the monitoring data meets the characteristics of extreme weather by presetting extreme weather standards. Once it is determined that extreme weather is approaching, the system will immediately activate the emergency plan and shut down all landscape facilities such as fountains and water curtains to avoid equipment damage. At the same time, safety warnings are issued through bridge display screens to remind passing vehicles to drive carefully. This emergency response can proactively intervene before severe weather causes major impacts, minimizing the risk of damage to landscape facilities and traffic accidents.

[0014] In combination with some embodiments of the first aspect, in some embodiments, before the step of obtaining real-time monitoring data of the detection point, the method also includes: obtaining light distribution data of the bridge landscape lighting; determining the vibration direction of glare and reflected light on the central axis of the bridge based on the light distribution data; adjusting the angle of the polarization element so that the polarization direction of the polarization element is orthogonal to the vibration direction of the glare and reflected light.

[0015] By adopting the above technical solution, the adverse effects of bridge landscape lighting on the driver's sight can be effectively eliminated. First, by collecting bridge light distribution images at different polarization angles, the areas prone to glare and reflection and the corresponding polarization angles are determined. Then, according to the analyzed glare vibration direction, the angle of the polarization filter element is accurately adjusted so that its polarization direction is always orthogonal to the glare. When harmful light undergoes orthogonal polarization, its intensity will be weakened to the greatest extent. In this way, glare and reflection that may affect the driver's sight will be effectively filtered out, making the driving environment safer and more comfortable.

[0016] In combination with some embodiments of the first aspect, in some embodiments, the step of obtaining the light distribution data of the bridge landscape lighting specifically includes: obtaining light intensity distribution images of the bridge landscape lighting at different polarization angles.

[0017] By adopting the above technical solution, the light distribution information of bridge landscape lighting can be accurately and efficiently obtained. Traditional light intensity measurement can only obtain data from a single angle, which is difficult to fully reflect the spatial distribution law of bridge deck light. By improving to multi-angle polarization imaging, the bridge deck light can be fully sampled in different polarization directions to obtain a series of complete light intensity distribution images. These image data not only reflect the overall distribution of light on the bridge deck, but also contain rich polarization attribute information.

[0018] In combination with some embodiments of the first aspect, in some embodiments, the vibration direction of glare and reflected light on the central axis of the bridge is determined based on the light distribution data, specifically including: calculating the difference of images at different polarization angles; determining the area where the difference is greater than the difference threshold as the position of the glare and reflected light; for the glare and reflected light positions, extracting their average light intensity values ​​at different polarization angles; substituting the light intensity value into Malus's law to solve the polarization angle.

[0019] By adopting the above technical solution, glare reflections can be located with high precision and their polarization angles can be accurately solved. First, the light intensity images at different polarization angles are subjected to difference calculations. Areas with large differences often correspond to the locations where glare reflections occur. Next, the average light intensity values ​​of these areas at each polarization angle are extracted. Finally, these light intensity values ​​are substituted into the mathematical model of Malus's law and solved to obtain the polarization angle of the glare reflection. The entire process uses precise mathematical models and calculations to ensure the high accuracy of glare position determination and polarization angle calculation. This provides a reliable basis for subsequent polarization filtering, so that harmful light can be eliminated to the greatest extent.

[0020] In a second aspect, the present application provides a control system applied to bridge landscape, the control system applied to bridge landscape comprising: 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, the one or more processors call the computer instructions to make the control system applied to bridge landscape perform the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, the present application provides a computer program product comprising instructions, which, when executed on a control system applied to a bridge landscape, enables the control system applied to a bridge landscape to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions, which, when executed on a control system applied to a bridge landscape, causes the control system applied to the bridge landscape to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By acquiring the monitoring data of the detection point in real time and comparing it with the preset threshold, the impact of environmental changes on the operation of the fountain can be discovered in time. When the monitoring data exceeds the threshold, it is input into the prediction model together with the historical data to obtain the trend of environmental changes in the future. According to the prediction results, the optimal fountain parameter combination is selected from the preset mapping relationship table, including the spray intensity, angle, duration, water column shape, etc., and the fountain operation is adjusted in real time accordingly. After adjustment, image recognition is used to analyze whether the actual amount of water spray meets the expectations. If not, continue to monitor and adjust. This cycle can ensure that the fountain is always in the best working condition when the environment changes and can avoid splashing water that affects driving safety.

[0024] 2. The system determines in real time whether the monitoring data meets the characteristics of extreme weather by presetting extreme weather standards. Once it is determined that extreme weather is approaching, the system immediately activates the emergency plan and shuts down all landscape facilities such as fountains and water curtains to avoid equipment damage. At the same time, it also issues safety warnings through the bridge display screen to remind passing vehicles to drive carefully. This emergency response can proactively intervene before severe weather causes major impacts, minimizing the risk of damage to landscape facilities and traffic accidents.

[0025] 3. It can effectively eliminate the adverse effects of bridge landscape lighting on the driver's sight. First, by collecting bridge light distribution images at different polarization angles, determine the areas prone to glare and reflection and the corresponding polarization angles. Then, according to the analyzed glare vibration direction, accurately adjust the angle of the polarization filter element so that its polarization direction is always orthogonal to the glare. When harmful light undergoes orthogonal polarization, its intensity will be weakened to the greatest extent. In this way, glare and reflection that may affect the driver's sight will be effectively filtered out, making the driving environment safer and more comfortable. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a control method applied to bridge landscape in an embodiment of the present application; Figure 2 is another flow chart of the control method applied to bridge landscape in an embodiment of the present application; Figure 3 is another flow chart of the control method applied to bridge landscape in an embodiment of the present application; Figure 4 It is a schematic diagram of an exemplary hardware structure of a control system applied to bridge landscape in an embodiment of the present application. DETAILED DESCRIPTION

[0027] 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 and appended claims of the present application, the singular expressions "one", "a kind of", "said", "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 and includes any or all possible combinations of one or more listed items.

[0028] 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.

[0029] See also Figure 1 , Figure 1 It is a flow chart of a control method applied to bridge landscape in an embodiment of the present application; S101, obtaining real-time monitoring data of the detection point; Among them, detection points refer to sensors deployed in the surrounding environment of the bridge to collect environmental data, such as temperature and humidity sensors, anemometers, light intensity sensors, etc.

[0030] In some embodiments, a timed active reporting method is adopted, where each sensor node actively reports the real-time collected environmental data to the control system applied to the bridge landscape through wireless communication according to a preset time interval. There is no need for polling of the control system applied to the bridge landscape, and the efficiency is higher when the communication volume is small.

[0031] In other embodiments, an event-triggered reporting method is used to set a change threshold of environmental parameters at key sensor nodes. When the parameter change exceeds the threshold, the node actively initiates communication with the control system applied to the bridge landscape and reports abnormal data. After receiving the report, the control system applied to the bridge landscape actively polls other nodes to obtain complete real-time data, which can reduce the communication frequency.

[0032] It is understandable that the actual data collection system is generally a combination of multiple communication methods. Normally, low-frequency scheduled reporting is used with a stable status. Once an abnormality occurs, event triggering and active polling are initiated to obtain full real-time data in a timely manner, balancing communication efficiency and data timeliness.

[0033] In some embodiments, the real-time monitoring data is wind speed.

[0034] S102: When the real-time monitoring data exceeds a preset impact threshold, the real-time monitoring data and historical data are input into an environmental prediction model to obtain predicted environmental data for a preset time interval; The environmental prediction model refers to a mathematical model based on a machine learning algorithm, which is obtained by training historical environmental data and is used to predict the changing trend of environmental parameters in the future.

[0035] In some embodiments, the training process of the environment prediction model is as follows: The training set should contain historical environmental monitoring data with a long span, and then divide the historical environmental monitoring data into multiple time windows, each of which contains sequence data of a fixed length. For each time window, select the first part as input data and the second part as validation data. The input data is used to train the model, and the validation data is used to evaluate the prediction performance of the model.

[0036] S103, finding a corresponding parameter combination in a preset mapping relationship table according to the predicted environment data, wherein a series of discrete adjustment values ​​are set for each adjustable parameter in the preset mapping relationship table; The preset mapping relationship table refers to a data structure pre-set in the system, which is used to establish the correspondence between environmental parameters and adjustable parameters of the fountain. It contains the value combinations of various adjustable parameters of the fountain for different environmental conditions. A series of discrete adjustment values ​​means that for each adjustable parameter (such as the spray angle), a number of discrete optional values ​​are pre-set, and when adjusting the parameters, you can choose from these discrete values ​​instead of continuous full-range adjustment.

[0037] In some embodiments, the predicted environmental data obtained by the environmental prediction model is matched with the environmental conditions in the preset mapping relationship table. A set of environmental parameters closest to the predicted environment is found, and a combination of pre-set fountain adjustable parameters under this set of environmental parameters is extracted. These parameters include nozzle angle, spray duration, water column shape, etc., all of which have several discrete optional values ​​set in advance. The system only needs to select the closest one from these discrete values ​​as the target value for this adjustment, avoiding the control difficulties that may be caused by continuous adjustment.

[0038] In some embodiments, the designer or debugger manually designs multiple groups of optimal fountain parameter combinations under typical environmental conditions based on previous practice summary, and fills in the mapping relationship table. When adjustment is required, the system can obtain the corresponding discrete adjustment value through simple condition matching and table lookup operation.

[0039] S104, adjusting an adjustable parameter combination according to the parameter combination, the adjustable parameter combination including spray intensity, nozzle angle, spray time, nozzle movement speed, nozzle trajectory, and water column shape; Among them, the spray force indicates the pressure provided by the water pump to the nozzle, which affects the height and dispersion range of the water column; the nozzle angle indicates the angle between the elevation of the nozzle and the ground, which affects the inclination direction of the water column; the spray time indicates the duration of the opening of a single nozzle; the nozzle movement speed indicates the movement speed of the nozzle; the nozzle trajectory indicates the spatial movement path of the mobile nozzle; the water column shape indicates the size of the water column.

[0040] S105, after adjusting the adjustable parameter combination, obtaining first image data of the designated area; The designated area refers to a certain area around the fountain where the amount of water spray needs to be monitored, such as a side close to a road, etc. The first image data refers to a digital image reflecting the real-time status of the designated area obtained by collecting images of the designated area after parameter adjustment.

[0041] In some embodiments, after the fountain parameters are adjusted and stabilized for a period of time (such as 30 seconds), the system will send a collection instruction to the on-site video surveillance equipment such as a high-definition camera, and specify the target area for collection, such as the road area within 5 meters on the east side of the fountain.

[0042] S106, identifying the amount of water splash data in the first image data; The number of water splashes refers to the number of pixels or the coverage area of ​​water mist, water droplets, etc. in the image that reflect the amount of water splashes.

[0043] In some embodiments, a traditional image processing algorithm based on threshold segmentation is used to binary the image into foreground (water splash) and background by setting thresholds for features such as color and texture. Then, the binary image is subjected to connected domain analysis and pixel counting to obtain the quantitative features of the water splash area.

[0044] S107. When the amount of the splash data is greater than a preset splash threshold, execute the step of obtaining real-time monitoring data of the detection point.

[0045] This step is a secondary judgment of the fountain adjustment effect, the purpose of which is to avoid excessive water splashes caused by excessive adjustment or sudden changes in the environment, which may affect the safety of vehicles and pedestrians. It forms a closed loop with the primary judgment based on environmental parameters in S102 to jointly control the dynamic adjustment process of the fountain effect.

[0046] It can be seen that by acquiring the monitoring data of the detection point in real time and comparing it with the preset threshold, the impact of environmental changes on the operation of the fountain can be discovered in time. When the monitoring data exceeds the threshold, it is input into the prediction model together with the historical data to obtain the changing trend of the environment in the future. According to the prediction results, the optimal fountain parameter combination is selected from the preset mapping relationship table, including the spray intensity, angle, duration, water column shape, etc., and the fountain operation is adjusted in real time accordingly. After adjustment, image recognition is used to analyze whether the actual amount of water spray meets the expectations. If not, continue to monitor and adjust. This cycle can ensure that the fountain is always in the best working condition when the environment changes and can avoid splashing water to affect driving safety.

[0047] refer to Figure 2 , Figure 2 is another flow chart of the control method applied to bridge landscape in an embodiment of the present application; After step S104, step S105, step S201, and step S205 may be executed.

[0048] S201, when receiving an intervention instruction from an operator terminal, readjusting the adjustable parameter combination according to the intervention instruction; Among them, the operator terminal refers to a computer device with human-computer interaction functions used by human operators, such as PCs, tablets, mobile phones, etc.

[0049] The principle and process of this step are the same as those of step S104. The relevant principles and processes can refer to step S104 and will not be repeated here.

[0050] S202, after re-adjusting the adjustable parameter combination, obtaining second image data of the designated area; Acquiring the second image data of the designated area is used to determine whether the effect of the manual adjustment meets expectations.

[0051] The principle and process of this step are the same as those of step S105. The relevant principles and processes can refer to step S105 and will not be repeated here.

[0052] S203, identifying the data amount of the splash in the second image data; The principle and process of this step are the same as those of step S106. The relevant principles and processes can refer to step S106 and will not be repeated here.

[0053] S204: When the data volume of the splash is greater than a preset splash threshold, the data volume of the splash is fed back to the operator terminal.

[0054] The preset water splash threshold refers to the upper limit of the number of safe and beautiful water splashes that is preset based on fountain design requirements and actual experience. When the actual amount of water splashes detected exceeds the threshold, it means that the manual adjustment may not be ideal, and a prompt needs to be issued to the operator to draw attention.

[0055] It can be seen that the flexibility and humanization of bridge landscape digital fountain control can be further improved. On the basis of the original automatic parameter adjustment, the system can also receive remote intervention instructions from the operator. When the operator wants to make specific adjustments to the fountain effect based on actual observations or other considerations, he can directly issue instructions, and the system will immediately reset the adjustable parameters as required and monitor the adjustment effect in real time. If the actual amount of water after adjustment does not meet the operator's expectations, the system will promptly provide feedback to help the operator make judgments.

[0056] In other embodiments; S205, executing a closing operation when a preset closing condition is met or a closing instruction from an operator terminal is received; The preset shutdown condition refers to the specific environmental state or time node at which the fountain should be shut down, which is predefined during system design. The shutdown instruction refers to the control command issued by the operator to the control system through the terminal device to stop the fountain operation.

[0057] The shutdown operation is the process in which the control system performs a series of actions to safely and orderly stop the operation of the fountain equipment, such as shutting down the water pump, disconnecting the power supply of the colored lights, resetting parameter settings, etc.

[0058] This step can be performed at a specific moment in the automatic control process, or it can be triggered by the operator at any time according to actual needs. In any case, closing marks the end of a complete fountain working cycle.

[0059] Specifically, when the external environment reaches the preset shutdown conditions, such as reaching the set shutdown time, the control system will automatically start the shutdown process. The system first issues a shutdown command to all execution units, controls the water pump to stop discharging water, the solenoid valve to cut off the water supply, the colored lights to turn off the discharge, etc., and then monitors the status feedback of each unit to confirm that they have completely stopped working. When receiving the shutdown command from the operator, the system also executes a similar shutdown process, but it needs to first perform a security check on the command to confirm the legitimacy of its source to prevent interference from malicious commands. After the shutdown is completed, the system automatically records the shutdown time and the environmental parameters at that time for subsequent data analysis and model optimization.

[0060] S206, after executing the closing operation, determining the difference between the real-time monitoring data and the predicted environmental data; It should be noted that in step S102, the predicted environmental data is generated based on the current real-time monitoring data. Specifically, when the real-time monitoring data exceeds a preset threshold, the system inputs these real-time monitoring data into the trained environmental prediction model to obtain the predicted environmental data for a period of time in the future. This means that the predicted environmental data is an extension and prediction of the current real-time monitoring data in the future. In step S206, the system compares and analyzes the real-time monitoring data with the previously generated predicted environmental data. The real-time monitoring data here is synchronized with the predicted environmental data in time, that is, the start time of the predicted environmental data is consistent with the time point of the real-time monitoring data.

[0061] S207: if the difference exceeds the error threshold, determine the real-time monitoring data as new historical data; It should be noted that "real-time monitoring data" is mentioned many times in the full text, but its specific meaning and expression form are different in different steps, such as different time (step S102 and step S206), and different data dimensions. The real-time monitoring data in step S206 is the data at a certain point in time, and the real-time monitoring data in step S207 is a data set within a time period.

[0062] S208: Use new historical data to train the environment prediction model.

[0063] The principle and process of this step are the same as those of step S102. The relevant principles and processes can be referred to step S102 and will not be repeated here.

[0064] It can be seen that after the system controls a fountain operation cycle based on the prediction results, it will compare the actual monitoring data in the cycle with the predicted value and calculate the difference. If the difference exceeds the allowable range, it means that there is a large deviation in this prediction. At this time, the system will mark the measured data of the cycle as new valid historical data for subsequent prediction model retraining. Through this closed-loop mechanism of data labeling and model retraining, the system can continuously accumulate real environmental change data and continuously improve the accuracy of the prediction model.

[0065] In actual use, digital fountains and water curtain equipment on bridges and their electronic control systems are extremely vulnerable to damage in extreme weather events such as storms, thunderstorms, etc. In addition, strong winds and heavy rains may cause water splashes to spread over a large area, increasing the risk of accidents.

[0066] Therefore, in some embodiments, step S101 further includes: S209, determining whether the real-time monitoring data meets the preset extreme weather setting; Among them, the preset extreme weather settings refer to the parameter thresholds of various severe weather conditions, such as maximum wind speed, which are pre-defined during system design based on the actual use environment of the bridge landscape.

[0067] This step is continuously executed after the fountain is turned on. The purpose is to promptly detect extreme weather that may threaten the safe operation of the bridge and provide a decision-making basis for the next emergency risk avoidance action.

[0068] S210, if the preset extreme weather setting is met, completely close the bridge landscape; S211. Sending a safety alarm message to a bridge display screen so that the bridge display screen displays the safety alarm message.

[0069] It can be seen that the system determines in real time whether the monitoring data meets the characteristics of extreme weather by presetting extreme weather standards. Once it is determined that extreme weather is approaching, the system immediately activates the emergency plan and shuts down all landscape facilities such as fountains and water curtains to avoid equipment damage. At the same time, it also issues safety warnings through the bridge display screen to remind passing vehicles to drive carefully. This emergency response can proactively intervene before severe weather causes major impacts, minimizing the risk of damage to landscape facilities and traffic accidents.

[0070] In some embodiments, the decorative lighting of the bridge landscape may interfere with the vision of drivers on the bridge. In particular, in fog, rain or snow, the reflected light may cause blurred vision and increase the risk of traffic accidents.

[0071] Therefore, before step S101, the following steps are also included: S301, obtaining light distribution data of the bridge landscape lighting; Light distribution data is a physical quantity that characterizes the light intensity distribution of these lamps in space. It is usually presented in the form of images or curves, reflecting the changes in the intensity of light in different directions.

[0072] Specifically, after the bridge lights are turned on, the system controls a dedicated radiometer or illuminance meter to measure the radiation flux or illuminance value of light in a specific band at different positions and angles on the bridge deck and the guardrails on both sides, and obtains a set of discrete observation data. Then, the system maps these observation data to the three-dimensional model of the bridge according to the spatial position, and uses the interpolation algorithm to estimate the light intensity values ​​at other positions, and finally forms a continuous light intensity distribution image. The image usually shows the light intensity gradient in the form of pseudo-color or contour lines, which intuitively reflects the light and dark distribution everywhere. The spatial resolution and sensitivity of the image can be flexibly set according to actual needs to balance the calculation efficiency and result accuracy.

[0073] In a specific embodiment, S3011, obtain light intensity distribution images of the bridge landscape lighting at different polarization angles.

[0074] The polarization angle is the angle between the vibration direction of light and a reference direction (such as the horizontal direction), which is used to describe the vibration characteristics of polarized light. Different types of light sources, such as sunlight, light bulbs, reflectors, etc., usually have different polarization characteristics. By changing the receiving polarization angle of the detector, the size of the polarization component of light in different directions can be obtained.

[0075] This sub-step is one of the specific implementations of step S301, and uses the polarization characteristics of light to obtain richer light distribution information. In the application, by analyzing the difference in light intensity at different polarization angles, the type and source of glare can be determined, providing a more targeted strategy for subsequent glare reduction.

[0076] Specifically, when acquiring light distribution data, a polarizer is installed in front of the radiometer or illuminometer so that it only receives light in a specific vibration direction, and the polarizer is rotated with the motor to scan various polarization angles in the range of 0-180°. At each angle position, the sensor measures a light intensity distribution image, reflecting the distribution characteristics of polarized light in that direction. A set of distribution images with different polarization angles is obtained to form a data cube, preparing for subsequent reflected light analysis. The angular interval for acquiring polarization images can be determined based on the trade-off between equipment accuracy and computational efficiency, usually between 5-30°. The scanning process can be performed continuously, or several key angles can be selected to complete it in batches.

[0077] In some embodiments, the acquisition of bridge lighting light distribution can be achieved in a variety of ways: Optionally, an imaging light intensity distribution measurement system is used to obtain brightness images of different positions on the bridge deck using an array CCD camera. The image coordinates are mapped to actual space coordinates through registration and calibration, and the luminous flux value of each pixel is calculated using a photometric inversion algorithm to synthesize the illumination distribution map of the entire bridge. The array camera can work continuously at a fixed position, or be controlled by a pan / tilt to image at different angles in batches.

[0078] Optionally, a scanning light intensity distribution measurement system is used, using a single-point illuminance meter or spectrometer to mechanically scan different sections of the bridge to obtain a series of discrete observation values, and then a spatial interpolation algorithm is used to construct a continuous distribution surface. The scanning path can be pre-planned and precisely controlled by a stepper motor. After a certain number of single-point measurement values ​​are accumulated, the overall light distribution can be estimated in real time.

[0079] It can be seen that the light distribution information of bridge landscape lighting can be accurately and efficiently obtained. Traditional light intensity measurement can only obtain data from a single angle, which is difficult to fully reflect the spatial distribution law of bridge deck light. By improving to multi-angle polarization imaging, the bridge deck light can be fully sampled in different polarization directions to obtain a series of complete light intensity distribution images. These image data not only reflect the overall distribution of light on the bridge deck, but also contain rich polarization attribute information.

[0080] S302, determining the vibration direction of glare and reflected light on the central axis of the bridge according to the light distribution data; Specifically, S3021, calculating the difference of images at different polarization angles; The intensity images obtained at different polarization angles are subtracted to generate a series of difference images. The size of the difference reflects the relative change of light intensity in different polarization directions. The larger the difference, the higher the polarization degree of the reflected light at that position, which is a potential glare source. The difference calculation can be achieved by simple pixel subtraction, or by using complex digital image processing algorithms, such as differential Gaussian, LOG, etc., to extract the difference in texture and edge features.

[0081] S3022, determining the area where the difference is greater than the difference threshold as the location of the glare and reflected light; The difference image is binarized, and pixels whose difference exceeds a specific threshold are extracted to obtain candidate glare areas. The setting of the threshold needs to comprehensively consider factors such as the intensity level of landscape lighting, the evaluation criteria for glare, and the signal-to-noise ratio of the image. It can be estimated by empirical formulas or learned from historical data using statistical methods. The extraction results may form multiple discrete areas, which require morphological filtering for denoising or connected domain analysis.

[0082] S3023. For the glare and reflected light positions, extract the average light intensity values ​​at different polarization angles; The light intensity characteristics of the glare area in different polarization images are further analyzed, and the average light intensity value at each angle is calculated. The average light intensity is the weighted average of the pixel values ​​in the area, which can suppress local noise and reflect the overall brightness level. The weight can be normalized by area, or spatial distance weighting can be introduced to highlight the role of the center position. The relationship curve between the average light intensity and the polarization angle quantitatively reflects the polarization characteristics of the reflected light and provides a criterion for determining the direction of the reflected vibration.

[0083] S3024. Substitute the light intensity value into Malus's law to solve the polarization angle.

[0084] The law of reflection and the polarization formula are used to establish an analytical relationship between light intensity and angle, and the key parameters of the polarization characteristics are solved. Specifically, according to the law of reflection, the normal of the reflection surface, the incident light and the reflected light are coplanar, and the reflection angle is equal to the incident angle. Malus's law gives a nonlinear functional relationship between the reflected light intensity and the incident angle, refractive index and polarization angle. By fitting the average light intensity value sequence to the function model, the estimated values ​​of the incident angle and refractive index can be obtained. Furthermore, combined with the known direction vector of the incident light, the normal direction vector of the polarization plane of the reflected light at that location can be analytically calculated.

[0085] It can be seen that the glare reflection can be located with high precision and its polarization angle can be accurately solved. First, the light intensity images at different polarization angles are differenced, and the areas with large differences often correspond to the locations where the glare reflection occurs. Next, the average light intensity values ​​of these areas at each polarization angle are extracted. Finally, these light intensity values ​​are substituted into the mathematical model of Malus's law and solved to obtain the polarization angle of the glare reflection. The entire process uses precise mathematical models and calculations to ensure the high accuracy of glare position determination and polarization angle calculation. This provides a reliable basis for subsequent polarization filtering, so that harmful light can be eliminated to the greatest extent.

[0086] S303, adjusting the angle of the polarization element so that the polarization direction of the polarization element is orthogonal to the vibration direction of the glare and the reflected light.

[0087] Among them, polarizing elements refer to optical devices that can selectively transmit or reflect light in a specific vibration direction and block light in other directions, such as polarizers and polarizing prisms, and are often used in the field of glare suppression. The polarization direction of a polarizing element refers to the light vibration direction corresponding to its maximum transmittance. When the polarization direction is orthogonal to the light vibration direction, the damping of the light beam is the greatest, which helps to filter out glare.

[0088] In a specific embodiment, the obtained reflected polarization angle is converted into a target angle of the polarization element, and an angle control instruction is generated. The actuator drives the polarizer to rotate around the optical axis and tracks and adjusts to the target angle in real time.

[0089] It can be seen that the adverse effects of bridge landscape lighting on the driver's sight can be effectively eliminated. First, by collecting bridge light distribution images at different polarization angles, the areas prone to glare and reflection and the corresponding polarization angles are determined. Then, according to the analyzed glare vibration direction, the angle of the polarization filter element is accurately adjusted so that its polarization direction is always orthogonal to the glare. When harmful light undergoes orthogonal polarization, its intensity will be weakened to the greatest extent. In this way, glare and reflection that may affect the driver's sight will be effectively filtered out, making the driving environment safer and more comfortable.

[0090] The following introduces an exemplary control system 400 applied to bridge landscape provided by an embodiment of the present application. Figure 4 Schematic diagram of an exemplary hardware structure of a control system 400 applied to bridge landscape provided in an embodiment of the present application.

[0091] In some embodiments, the control system 400 applied to bridge landscape is a computer device or the control system 400 applied to bridge landscape includes a computer device. The computer device includes a processor, a memory and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers through a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, the method in the embodiment of the present application is implemented.

[0092] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0093] 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.

[0094] 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.

[0095] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0096] 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 control method applied to bridge landscape, characterized in that: include: Obtain real-time monitoring data of detection points; When the real-time monitoring data exceeds a preset impact threshold, the real-time monitoring data and historical data are input into an environmental prediction model to obtain predicted environmental data for a preset time interval; Finding a corresponding parameter combination in a preset mapping relationship table according to the predicted environment data, wherein a series of discrete adjustment values ​​are set for each adjustable parameter in the preset mapping relationship table; Adjusting the adjustable parameter combination according to the parameter combination, wherein the adjustable parameter combination includes spray intensity, nozzle angle, spray time, nozzle movement speed, nozzle trajectory, and water column shape; After adjusting the adjustable parameter combination, obtaining first image data of the designated area; identifying the amount of water splash data in the first image data; When the amount of the splash data is greater than a preset splash threshold, the step of obtaining the real-time monitoring data of the detection point is performed.

2. The method according to claim 1, characterized in that After the step of adjusting the adjustable parameter combination according to the parameter combination, wherein the adjustable parameter combination includes spray intensity, nozzle angle, spray time, nozzle movement speed, nozzle trajectory, and water column shape, the method further includes: When receiving an intervention instruction from an operator terminal, readjusting the adjustable parameter combination according to the intervention instruction; After re-adjusting the adjustable parameter combination, obtaining second image data of the designated area; identifying the amount of water splash data in the second image data; When the data amount of the splash is greater than a preset splash threshold, the data amount of the splash is fed back to the operator terminal.

3. The method according to claim 1, characterized in that: After the step of adjusting the adjustable parameter combination according to the parameter combination, wherein the adjustable parameter combination includes spray intensity, nozzle angle, spray time, nozzle movement speed, nozzle trajectory, and water column shape, the method further includes: When the preset closing condition is met or a closing instruction is received from the operator terminal, the closing operation is executed; After executing the closing operation, determining the difference between the real-time monitoring data and the predicted environmental data; If the difference exceeds the error threshold, the real-time monitoring data is determined as new historical data; The environmental prediction model is trained using new historical data.

4. The method according to claim 1, characterized in that: After the step of obtaining the real-time monitoring data of the detection point, the method further includes: Determining whether the real-time monitoring data meets the preset extreme weather settings; If the extreme weather conditions are met, the bridge view is completely closed; The safety alarm information is sent to a bridge display screen, so that the bridge display screen displays the safety alarm information.

5. The method according to claim 1, characterized in that Before the step of acquiring the real-time monitoring data of the detection point, the method further includes: Acquiring light distribution data of the bridge landscape lighting; Determining the vibration direction of glare and reflected light on the central axis of the bridge according to the light distribution data; The angle of the polarizing element is adjusted so that the polarization direction of the polarizing element is orthogonal to the vibration direction of the glare light and the reflected light.

6. The method according to claim 5, characterized in that The step of obtaining the light distribution data of the bridge landscape lighting specifically includes: Obtain light intensity distribution images of the bridge landscape lighting at different polarization angles.

7. The method according to claim 6, characterized in that Determining the vibration direction of glare and reflected light on the central axis of the bridge according to the light distribution data specifically includes: Calculate the difference of images at different polarization angles; The area where the difference is greater than the difference threshold is determined as the location of the glare and reflected light; For the glare and reflected light positions, extract the average light intensity values ​​at different polarization angles; Substitute the light intensity value into Malus's law to solve for the polarization angle.

8. A control system applied to bridge landscape, characterized in that: The control system applied to bridge landscape 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 control system applied to bridge landscape to execute the method described in any one of claims 1 to 7.

9. A computer program product comprising instructions, characterized in that When the computer program product is run on a control system applied to a bridge landscape, the control system applied to a bridge landscape is enabled to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a control system applied to a bridge landscape, the control system applied to a bridge landscape executes the method according to any one of claims 1 to 7.

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