164 results about "Rain intensity" patented technology

The invention discloses a mountain torrent debris flow early warning method and system based on multi-source data comprehensive analysis. And the monitoring system carries out multi-source monitoring on rainfall, material source and mud level change characteristics of the ditch domain. The method is based on double-threshold rainfall intensity parameters, a quantitative analysis model of channel mud level and flow, and a blocking and collapsing mechanism of object source deformation. The threshold value of each element is determined according to the disaster history, a disaster outbreak probability formula is established, and key factor weights are screened through a random forest algorithm. And data preprocessing is carried out through cross validation and dynamic adjustment. And substituting monitoring data into the analysis model, and comprehensively judging the early warning level of the mountain torrent debris flow. And issuing an early warning signal of a corresponding level to the object in the threatened area through the early warning system. After operation, an incremental random forest method is adopted to update the model through online learning, data redisk is carried out, and model threshold correction and parameter inversion analysis are carried out. According to the pre-warning system, a multi-index combined action comprehensive monitoring and pre-warning evaluation system for quantitative analysis is established.

The invention provides an urban road ponding monitoring and drainage system. The urban road ponding monitoring and drainage system comprises a monitoring module which collects ponding depth, water velocity, rainfall intensity and field image data in real time; the initialization configuration module sets parameters such as an accumulated water depth threshold value; the data transmission module encrypts and transmits data to the central control module; the model algorithm optimization module constructs a three-dimensional ponding diffusion model and outputs a predicted ponding depth and an optimized drainage strategy; the central control module generates a drainage pump rotating speed instruction and the like; the drainage execution module dynamically adjusts drainage pump power and a drainage path; the self-checking and fault-tolerant module calculates a health index of drainage equipment and switches redundant equipment; the early warning module sends risk level information; and the interaction module displays information such as a real-time accumulated water thermodynamic diagram. The urban road drainage efficiency can be improved, the water accumulation risk is reduced, and smooth urban traffic and public travel safety are guaranteed.

The invention relates to a method for measuring the toughness of an urban public transport network in extreme rainstorm weather. The method comprises the following steps: acquiring station and line data of the urban public transport network, rainstorm disaster information and passenger flow data; a bus-subway double-layer traffic network is constructed; based on the constructed bus-subway double-layer traffic network, establishing a linear relation between rainstorm rainfall intensity and passenger flow change, and calculating disturbance values of the rainstorm to stations and connecting edges in the network; constructing a bus-subway double-layer traffic network cascade failure model considering passenger flow, and representing a dynamic evolution process of an urban public traffic network in extreme rainstorm weather; and determining a network performance measurement index by using the constructed bus-subway double-layer traffic network cascade failure model, and measuring the toughness level of the urban public traffic network in extreme rainstorm weather. According to the method, the urban public transport network toughness can be accurately measured, and the coping capacity of an urban public transport system in extreme rainstorm weather is improved.

The invention provides a landslide monitoring and early warning method based on air-sky-earthquake integration, and belongs to the technical field of landslide disaster monitoring. Air-sky-ground-earthquake monitoring data are integrated, multi-dimensional parameters such as surface deformation, topographic change, internal strain, crack propagation, rainfall intensity and micro-earthquake activity are covered, the limitation of a single monitoring means is solved, and a space-time complementary three-dimensional monitoring system is formed. According to a data analysis processing result, an early warning response rule is set, an early warning model is constructed through a multi-source data fusion technology in combination with an optimal weighted random forest method and a comprehensive scoring model, real-time evaluation and early warning grade judgment of landslide risks are realized, and visual display of monitoring data is realized. The model is iteratively trained by introducing reward and punishment factors, and weight distribution of different data sources is dynamically adjusted, so that the early warning model has adaptive ability, early warning requirements of long-term slow deformation and short-term accelerated deformation are considered, and the early warning accuracy of the model is improved.

The invention discloses a slope deformation monitoring system applied to a power transmission and transformation project, relates to the technical field of slope deformation monitoring, realizes high-precision slope displacement calculation by fusing optical fiber voltage signals and Beidou positioning data, constructs an inclination angle prediction model by combining historical inclination angle data, and introduces residual analysis to identify a structure deviation trend. The system dynamically calculates soil stress attenuation based on pore water pressure data, generates a threshold value correction factor driven by a softening coefficient, and then adaptively adjusts a displacement acceleration early warning threshold value to realize adaptation to different geological states. A closed-loop risk identification mechanism is established by monitoring double indexes of displacement acceleration and inclination angle prediction residual error, and the method has the advantages of being timely in response, high in identification precision, low in false alarm rate and the like, and is particularly suitable for power transmission and transformation scenes with complex geological conditions and large rainfall intensity changes.

The invention relates to the technical field of strategy optimization, and discloses a regional weather prediction method and system based on a meteorological large model, and the method comprises the steps: obtaining a terrain influence weight matrix; inputting into a spatial distribution feature model, outputting an optimized spatial distribution feature set, and realizing space-time registration through Kriging interpolation to obtain a spatial distribution feature set of local weather; extracting a seasonal change trend, and executing deviation correction to obtain a deviation correction coefficient; updating the weight matrix and performing coupling calculation to generate a coupling parameter set; generating a prediction result according to the coupling parameter set, and if the precision is lower than a threshold value, generating computing resource configuration; combining the resource configuration, the updating weight matrix and the spatial feature set to carry out weather prediction to obtain a prediction result; and finally, generating a rainfall intensity distribution diagram, performing differentiation correction, and outputting a regional weather prediction result. The method can achieve the high-precision prediction of the weather in the complex region.

The invention discloses a microwave link-weather radar combined rainfall inversion method based on Z-R relation adaptive adjustment, and the method comprises the steps: defining a related parameter set of microwave link rainfall estimation and weather radar reflectivity measurement in observation time, and carrying out the matching and space-time averaging processing, and obtaining rainfall intensity-radar reflectivity characteristics; fitting a radar reflectivity-rainfall intensity relation within observation time by using a least square method based on the rainfall intensity-radar reflectivity characteristics; according to the radar reflectivity-rainfall intensity relation sample of the known position, calculating the spatial distribution of the radar reflectivity-rainfall intensity relation in the research area by using an inverse distance weighted interpolation method; and according to the spatial distribution of the radar reflectivity-rainfall intensity relationship within the observation time and the average reflectivity factor measured by the radar, calculating to obtain a spatial distribution result of the accumulated rainfall within the observation time. According to the invention, the accuracy of regional rainfall monitoring is effectively improved.

The invention discloses a short temporary rainfall intensity prediction and identification method based on space-time composite attention, and the method comprises the following steps: obtaining an IMERG satellite rainfall data set, and carrying out the data construction and marking of a target region; establishing a space-time composite attention network, accessing an MFGA module and a TSMA module layer by layer, and performing non-negative activation on output to ensure physical interpretability; proposing a C-DWABP loss function, performing direction asymmetrical penalty aiming at a pixel-level prediction error, and introducing a grading weight mapped according to a real rainfall intensity grade at the same time; based on the output, intensity classification is carried out through a microthresholding ordered layer, and learnable threshold stability training is set; generating a forecast product, and obtaining an hour-by-hour precipitation grid in future 1-6 hours and a corresponding intensity identification result; according to the method, the precision of short temporary rainfall intensity prediction is improved, the false alarm rate is reduced, and a heavy rainfall event is effectively identified.

The invention discloses a rainstorm ground waterlogging prediction method, device, equipment and product, and relates to the technical field of urban waterlogging prediction.The rainstorm ground waterlogging prediction method comprises the steps that ephemeris and ground observation station data are obtained, the atmospheric moisture delay amount and the high-altitude water vapor conversion factor are calculated respectively, the historical water vapor content is calculated, and the future atmospheric precipitable water amount is predicted; rainfall time distribution data are obtained through rainstorm intensity decomposition; calculating the rainwater overflow amount of the catchment area in combination with the water discharge amount time distribution data of the urban drainage pipe network; and iterative calculation is carried out by using a digital elevation model grid to obtain the waterlogging depth, and waterlogging early warning information is sent out. By constraining the total rainfall amount, the rainfall amount can be effectively constrained by predicting the precipitable water amount based on the satellite ephemeris; the underground pipe network drainage is restrained, and a water flow condition in a pipe channel is simulated by adopting an SWMM model; and finally, the waterlogging accumulated water volume is calculated, constraint verification is carried out on each link of urban waterlogging, and relatively high precision and relatively long timeliness are ensured.

The invention discloses a wind turbine generator voiceprint self-adaptive detection method, system and device and a storage medium, and belongs to the technical field of wind power, and the method comprises the steps: collecting a voiceprint signal, raindrop diameter, environment humidity, environment temperature and atmospheric pressure of a wind turbine generator in real time through a sensor array; temperature and humidity coupling correction parameters are calculated based on the environment humidity, and real-time air density is obtained through correction according to an air density correction formula by means of the environment humidity, the environment temperature and the atmospheric pressure; constructing a rain intensity noise spectrum mapping model based on the raindrop diameter and the real-time air density in combination with a raindrop vertical fragmentation merging effect compensation algorithm; performing rain noise suppression on the voiceprint signal of the wind turbine generator by adopting a depth spectrum subtraction algorithm in combination with the rain intensity noise spectrum mapping model and the dynamic suppression factor to obtain a clean voiceprint signal; and matching the clean voiceprint signal with a preset wind turbine generator fault voiceprint feature library to complete wind turbine generator voiceprint adaptive detection.

The invention relates to a rainfall observation method and device, a computer system and a medium, and solves the problem of high-reliability observation of regional rainfall. The method comprises the following steps: firstly, adopting reanalysis data and earth system mode output data to construct a first deep learning model of satellite inversion rainfall so as to reconstruct a lattice long-series rainfall data set; then, taking the rainfall attenuation information of the historical period as input, obtaining a rainfall simulation series of the corresponding historical period through different rainfall attenuation and rainfall intensity models, determining regional rainfall under the different rainfall attenuation and rainfall intensity models through a weighted link method, and preferably selecting an optimal rainfall attenuation and rainfall intensity model through long-series lattice rainfall data of the historical period; furthermore, a second deep learning model is constructed by adopting satellite inversion data and rainfall data inverted by a rainfall attenuation and rainfall intensity model, real-time correction of regional precipitation is realized, finally, real-time rainfall information of the region is deduced by adopting the optimal rainfall attenuation and rainfall intensity model and taking a real-time mobile signal as input, and the regional average precipitation corrected in real time is obtained.

The invention discloses an extreme rainfall intensity potential intelligent forecasting method based on optimized physical factors. The method comprises the following steps: preparing numerical mode forecasting data for training an extreme rainfall intensity potential intelligent forecasting model; rainfall observation data used for training of the extreme rainfall intensity potential intelligent forecasting model are prepared; calculating a physical diagnostic quantity based on a numerical pattern; constructing forecasting factors of the extreme rainfall intensity intelligent forecasting model; carrying out sensitivity analysis on the forecasting factors and carrying out preliminary screening; carrying out dimension reduction processing on the forecasting factors; constructing a fuzzy matching observation label of a space-time neighborhood; constructing an optimal extreme rain intensity balance sample training set; performing data cleaning and standardized preprocessing; constructing an extreme rainfall intensity intelligent forecasting model and optimizing key parameters; intelligent forecasting and forecasting effect evaluation are carried out. According to the method, the problems of magnitude underestimation and falling area deviation in the extreme rainfall intensity forecast in the next three days in the existing numerical mode are solved.

The system comprises a water storage container and a control system, a partition plate and a moving plate connected with a driving mechanism are arranged in the water storage container, a sensor system of the control system is used for monitoring state parameters of the moving plate and the water supply flow of the water storage container, and after the target rainfall intensity is determined, the target rainfall intensity is determined; the controller is used for obtaining state estimation of the moving plate based on the state space model and the state parameters of the moving plate, calculating real-time rainfall intensity by combining the water supply flow of the water storage container, and dynamically controlling the driving mechanism to operate in a closed-loop mode with the target of reducing the error between the target rainfall intensity and the real-time rainfall intensity. The movable plate is driven to move relative to the partition plate to adjust the water outlet area, rainfall holes of the water storage container discharge water to simulate rainfall for an irrigation test, dynamic response continuous adjustment of simulated rainfall intensity can be achieved, natural rainfall scenes of different rainfall intensities and modes can be reproduced in a high-precision mode, a reliable test platform is provided for agricultural irrigation research, design is flexible, and the test efficiency is high. The operability is high.

The invention discloses an offshore floating type low-altitude waveguide all-weather detection method and system, and relates to the technical field of marine environment monitoring and electronic information engineering.The method comprises the steps that the current weather condition is judged according to a rain intensity sensor, a miniature weather station, a visibility sensor and an infrared cloud measurement sensor; obtaining a temperature and humidity value range according to the current weather condition, and adding liquid water for correction according to the weather condition; a simulated brightness temperature is obtained according to a MonoRTM model by combining an air pressure profile constructed by sea surface air pressure and a pressure height formula; designing a multi-objective genetic inversion algorithm, constructing an objective function, and when the objective function obtains a minimum value, obtaining an inverted atmospheric parameter profile group; and according to the atmospheric parameter profile group, calculating an atmospheric refractive index profile, judging whether a low-altitude waveguide occurs or not, and uploading a result to a shore station data management center. According to the invention, the atmospheric absorption coefficient is corrected according to different weathers, and all-weather and high-precision monitoring of the low-altitude waveguide on the offshore floating platform is realized.

The present invention provides an automotive air-conditioning performance detection device, which relates to the technical field of automotive air-conditioning performance detection. It includes a detection chamber. A working cavity is opened in the detection chamber, and a partition plate is fixedly installed in the working cavity. The partition plate can divide the working cavity into a liquid storage cavity and a detection chamber arranged vertically. A plurality of water outlet holes are opened on the partition plate, and a plurality of piston rods are slidably installed in the liquid storage cavity. The present invention provides an automotive air-conditioning performance detection device. By setting the detection chamber, partition plate, piston rod, scraping rod and driving mechanism, it can simulate rainy days to realize the function detection of the vehicle's air conditioner during rainy driving. At the same time, it can clean the water outlet holes and the bottom water outlets of the water outlet holes, ensure the size of the simulated raindrops, thus ensure the simulation of different rain intensities, reduce the insufficient water output caused by the blockage of the water outlet holes, resulting in the decrease of the simulated rain intensity and affecting the result of the automotive air-conditioning performance detection, and ensure the accuracy of the detection result.

The invention provides a Ka-band radar echo attenuation correction method and system based on artificial intelligence, and relates to the technical field of radars. Comprising the following steps: acquiring horizontal reflectivity factor data detected by a radar and rainfall intensity data at a corresponding observation moment; constructing a reflectivity factor attenuation correction model set; according to the rainfall intensity data, inputting the horizontal reflectivity factor data into a corresponding reflectivity factor attenuation correction model in a reflectivity factor attenuation correction model set to obtain a horizontal reflectivity factor attenuation correction result, the reflectivity factor attenuation correction model is a deep learning model obtained by training historical radar horizontal reflectivity factor samples based on different rain intensity conditions. According to the method, the problems of relatively large error and uncertainty of a correction result caused by limitation of a traditional empirical formula method in the prior art are solved.

The utility model relates to the technical field of test boxes, in particular to a rain test box, which comprises a box body, a water spraying nozzle arranged at the upper part in the box body, a liftable partition plate arranged in the box body, a rotatable rotating plate arranged on the partition plate, vertical plates oppositely arranged on the rotating plate, a rotatable rod body arranged between the vertical plates and a gear arranged on the rod body, a supporting frame is arranged on the gear, a containing frame used for containing experiment articles is arranged on the supporting frame, a driving assembly used for driving the gear to rotate is arranged on the rotating plate, a water collecting cavity is formed in the bottom in the box body, a water pump is arranged in the water collecting cavity, and a water pipe connected with the water spraying nozzle is arranged on the water pump. The gear is driven by the driving assembly to rotate, so that the experiment article in the placing frame is inclined, the raining test can be carried out on the obliquely placed experiment article, the raining intensity test can be carried out on a plurality of positions on the experiment article by adjusting the rotation angle of the placing frame, and the test effect is improved.

The invention discloses a rainfall measurement method and device and electronic equipment, and relates to the technical field of meteorological monitoring. The method comprises the steps of obtaining a first count value of a first range tipping bucket corresponding to a first rainfall sensing quantity in a first time period, and obtaining a second count value of a second range tipping bucket corresponding to a second rainfall sensing quantity in the first time period, the second rainfall sensing quantity being greater than the first rainfall sensing quantity; judging whether the second count value of the second range tipping bucket is increased in the first time period or not; in response to increment of the second count value, performing zero clearing and weight counting on the first count value of the first range tipping bucket; and determining a target rainfall based on the first count value and the second count value after the zero-clearing weightometer. According to the invention, the resolution of rainfall measurement and the compatibility of different rain intensity ranges can be improved.

The invention discloses a flood discharge atomization rainfall intensity prediction method based on fog and rain liquid drop distribution. The method comprises the following steps: acquiring fog and rain images and environmental parameters of a flood discharge area; extracting effective round spot data of fog drops and raindrops; extracting droplet deformation characteristics, constructing a fluid constraint matrix, enhancing deformation critical characteristics, decoupling flow characteristics, reconstructing a physical deformation mode, evaluating droplet stability and correcting droplet volume; and calculating the spatial distribution of the rainfall intensity based on the corrected droplet particle size data. According to the method, through a technical route of combining deformation feature extraction, flow characteristic decoupling and physical modal reconstruction, accurate description of dynamic deformation of flood discharge atomization rainfall droplets under the action of water-gas turbulence in a complex environment is realized, and the prediction precision of rainfall intensity and range of a flood discharge atomization area is improved.

The invention relates to the technical field of meteorological monitoring, and discloses a rainfall early warning method and system based on a weather radar, and the method comprises the steps: obtaining weather radar body sweeping arrival base data and rainfall station observation data, carrying out the alignment, carrying out the meshing of the radar base data, and obtaining the grid echo data; constructing a quasi-vertical profile to determine the height range and uncertainty of the melting layer, and carrying out weighted bright band correction on echoes in the melting layer to obtain corrected echo data; determining rainfall type partitions and performing inversion to obtain a radar rainfall intensity field; according to the rainfall station data and the radar rainfall intensity field, station residual data is obtained, a space deviation field is obtained, and finally a calibration rainfall intensity field is obtained; determining an accumulated precipitation field of each member according to the calibrated rainfall field; and obtaining an over-threshold probability published by early warning according to the accumulated precipitation field of each member, and outputting precipitation early warning information when a probability threshold is continuously met. According to the invention, the rainfall intensity overestimation and false alarm jitter are reduced, and the accuracy and stability of short temporary rainfall early warning are improved.

The invention relates to the technical field of meteorology and hydrology, and discloses a quantitative rainfall estimation method and system based on multi-source data correction radar echoes, and the method comprises the steps: collecting the multi-source data, such as rainfall station actually measured rainfall data, elevation data, hydrometric station flow, radar reflectivity, soil humidity and environmental attributes, in a target region; a Z-R relation parameter of each radar sampling grid is dynamically calibrated by combining a collaborative Kriging interpolation and physical constraint hybrid neural network model, and a radar reflectivity correction parameter of each grid is calculated by using a difference between rainfall station observation data and radar data; in real-time application, based on the corrected radar reflectivity and the calibrated Z-R parameter, the rainfall intensity of each grid is inverted, and the precision of quantitative rainfall estimation is improved.

The invention relates to the technical field of intelligent traffic, and discloses a traffic operation state sensing method and system, computer equipment and a storage medium, and the method comprises the following steps: S1, multi-modal data collection: collecting multi-source data through a roadside meteorological station, a millimeter wave radar and an anti-fog camera, the multi-source data comprising meteorological parameters, vehicle motion trails and video streams; s2, meteorological parameter dynamic compensation: dynamically calculating a weather sensitivity coefficient based on real-time meteorological data, the meteorological data including visibility, rainfall intensity and road surface temperature; s3, performing deep learning visual compensation; s4, performing multi-scale risk prediction; and S5, edge 5G real-time early warning is carried out. According to the method, through chained processing of meteorological parameter dynamic compensation and deep learning visual compensation, the influence of climate on traffic perception is quantified, visual errors caused by weather are dynamically compensated, the traffic operation state is rapidly and accurately perceived under the complex climate condition, the traffic safety and the traffic efficiency are improved, and the vehicle prediction accuracy is improved.

The invention discloses a mountain torrent early warning rainfall threshold dynamic adjustment method and system, and relates to the technical field of hydrological early warning, and the method comprises the steps: obtaining basic rainfall data and a basic early warning threshold of a target region; according to the basic rainfall data, performing calculation to obtain a multi-factor correction factor; the multi-factor correction factors comprise an early-stage wettability correction factor, a rainfall intensity correction factor and a rain pattern mode correction factor; calculating to obtain a comprehensive correction factor according to the multi-factor correction factor; according to the comprehensive correction factor and the basic early warning threshold value, calculating to obtain a dynamic early warning threshold value; the dynamic early warning threshold value comprises a ready transfer dynamic early warning threshold value and an immediate transfer dynamic early warning threshold value; and determining a rainfall early warning level according to the dynamic early warning threshold and the real-time rainfall. According to the invention, the early warning threshold can be dynamically adjusted according to the real-time working condition, and the accuracy and timeliness of mountain torrent early warning are improved.

The invention provides a gate pump station water level prediction method based on microwave link rain measurement data, and belongs to the field of microwave signal processing and hydrological application. The method comprises the steps of collecting data of a gate pump station; utilizing the collected microwave link attenuation time sequence data to invert regional rainfall intensity; processing the inverted regional rainfall intensity together with the upstream and downstream water levels of the gate pump station, the gate opening height and the pump operation state into multi-input training data; constructing a multi-input single-output water level prediction model; training the water level prediction model by using the training data; and using the trained water level prediction model to predict the water level of the gate pump station. According to the method, key factors influencing the water level change of the gate pump station are fully considered, a water level prediction model based on LSTM + Attention is designed, and accurate prediction of the upstream water level of the gate pump station can be achieved.

The invention discloses a porous asphalt pavement gap distribution uniformity and drainage performance testing method. A porous asphalt pavement needing to be tested is divided into a plurality of test road sections; detecting the water seepage conditions of n measuring points in the transverse direction h and the longitudinal direction z of the test road section by adopting a pavement water seepage instrument; driving the rainfall simulation device into a test road section; before testing, the rainfall simulation device is calibrated, the uniform spraying effect of the rainfall simulation device is ensured, the minimum rainfall intensity can be simulated and measured, and meanwhile all interfaces are checked to ensure tight connection; performing water seepage condition retest on the test road section by using a rainfall simulation device, and selecting m test points; and uniformly analyzing gap distribution of the test road section. According to the method, firstly, a road surface runoff scene can be truly simulated, the problem of lateral seepage interference is solved, the overall water seepage condition of a road section can be accurately evaluated, and the pavement water seepage qualification misjudgment rate is reduced; meanwhile, the construction segregation degree is revealed through the data difference between the water seepage instrument (point) and the rainfall simulation (surface). The method is high in operability, convenient to understand and real and reliable in data, and is a simple, convenient and visual test method.

The invention provides a road toughness evaluation method and device based on landslide volume simulation and a storage medium. The road toughness evaluation method comprises the following steps: acquiring a road network, historical rainfall data, landslide influence factors, landslide simulation parameters, a landslide hidden danger point database and emergency rescue resources of a target area; determining target rainfall intensity according to the historical rainfall data, calculating slope stability of the target area under the target rainfall intensity according to the landslide influence factors, and determining a potential sliding soil body distribution area according to the slope stability; calculating the road burying volume of each road section in the road network by each landslide hidden danger point under the target rainfall intensity according to the potential sliding soil body distribution area and the landslide simulation parameters; and constructing an emergency rescue recovery time model for the road burying volume of each road section according to the emergency rescue resources and each landslide hidden danger point, wherein the model allocates resources to each road section according to a preset resource allocation method and calculates the traffic recovery time of each road section.

The application discloses a signal interference strategy generation method and device based on deep learning, and a medium, and relates to the technical field of signal interference. The method comprises the following steps: calculating initial path rain attenuation values corresponding to reference level sampling data and real-time level sampling data; filtering a wet antenna attenuation component of the real-time level sampling data through digital filtering based on the initial path rain attenuation values, and determining pure path rain attenuation values of each communication link; inverting the pure path rain attenuation values to obtain path average rain intensities corresponding to each communication link; performing spatial interpolation optimization on a preset interference area to determine a two-dimensional rainfall intensity distribution map; calculating signal propagation time delay of an interference target ray track to obtain interference target corrected coordinates; and determining an interference strategy corresponding to the interference target through link interference parameter calculation and interference window prediction. The application solves the technical problem that the signal interference strategy in the prior art cannot meet the dynamic requirements of an interference signal link in a rainfall environment.

The present invention discloses a method for inverting rainfall intensity levels. First, radar images under different rainfall intensities are collected offline, a suitable rainfall detection area is selected, and the corresponding wavenumber energy spectrum image is obtained by using two-dimensional discrete Fourier transform (2D-DFT). The characteristic parameters of the energy spectrum images under different rainfall intensities are extracted and fed into the constructed GA-BPNN model for training to obtain a model that meets the experimental requirements. Then, the radar image to be detected is selected, and its wavenumber energy spectrum image and characteristic parameters are calculated. Finally, the characteristic parameters are fed into the GA-BPNN model obtained offline to obtain the rainfall intensity level of the image to be detected. The present invention realizes the requirement of real-time acquisition of marine rainfall information during ship navigation and offshore operations.

The invention relates to a rain sensor for motor vehicles that precisely detects rain intensity and dirt accumulation on the windshield. The sensor uses modulated light beams emitted by LEDs or laser diodes and guided through the windshield. Changes caused by raindrops or dirt are detected by photodetectors and analyzed by a control unit consisting of a computer system with a CPU and memory. The control unit processes the signals and derives measured values ​​for the probability of rain and the windshield's attenuation. In addition, the sensor supports encrypted communication, software updates, and integration into modern connected vehicle systems. Its modular design allows for adaptation to various vehicle models and environmental conditions. The rain sensor is future-proof and ready for integration into intelligent and autonomous vehicle systems, ensuring high precision and reliability under diverse weather conditions.

The invention discloses a rainfall intensity detection method and device bearing raindrop falling strike, and the method comprises the following steps: setting a sliding time window, collecting rainfall data, processing the rainfall data based on the sliding time window, and obtaining optimized rainfall data; impact kinetic energy of the optimized precipitation data is obtained based on a piezoelectric sensor, and the impact kinetic energy is converted into an electric signal; calculating a voltage value based on the electric signal, and comparing the voltage value with a set voltage threshold value to obtain a voltage difference value; setting a weight coefficient attenuation model based on the voltage difference value, and matching different weight coefficients for the precipitation data in the sliding time window based on the weight coefficient attenuation model; calculating rainfall intensity information of different time periods based on different weight coefficients; rainfall data are acquired at intervals by setting a sliding window, and weight coefficients of different windows are dynamically adjusted through a weight coefficient attenuation model, so that rainfall intensity information is accurately analyzed.