187 results about "Echo intensity" patented technology

Provided is an automatic hail identification method based on radar image spatial mapping, including: obtaining a base reflectivity radar image; grading radar echoes using intensity values represented by different colors, and detecting radar center coordinates; performing spatial mapping, and establishing a dictionary for radar echo intensity in a new radar image space; after expanding the dictionary, transforming V-shaped notch and TBSS characteristics behind an original radar strong echo area into a standard rectangle and a triangle behind a strong echo in the new radar image space; determining whether there is a V-shaped notch and TBSS according to whether there is a standard rectangle or a triangle behind the strong echo; and if so, marking in the original radar image and calculating a position where hail occurs. A rapid and accurate method is provided for automation of hail monitoring and early warning and elimination of continuous high-intensity analysis pressure of forecasters.

The embodiment of the invention provides a radar echo extrapolation prediction method and system based on a test time training strategy. According to the embodiment of the invention, the method comprises the steps: carrying out the time axis calibration and space grid alignment processing of a radar echo historical collection sequence collected by an atmosphere detection system, and generating radar echo sequence data with time-space consistency; constructing an echo evolution relevance representation model based on the data, and generating an echo evolution dependency graph and a multi-step extrapolation initial condition set; then introducing a test time training strategy to carry out adaptive prediction processing, and adjusting edge weight parameters in real time to obtain a radar echo multi-step extrapolation prediction sequence with time dynamic characteristics; and finally, according to the sequence, extracting an echo intensity change characteristic and a space movement track rule, and combining historical climate cycle evolution data to generate a climate evolution trend description set containing an echo intensity trend curve and a path offset vector so as to realize more accurate climate evolution prediction and weather forecast.

The invention relates to a lightning potential forecasting method and system based on a random forest. The method comprises the following steps: (1) collecting and preprocessing multi-source meteorological data; (2) feature extraction: cloud picture texture and shape features are extracted from satellite data, and echo intensity, top height and vertical development speed features are extracted from radar data; (3) constructing and optimizing a model; and (4) early warning thunder and lightning. The method has the advantages that the random forest serves as a typical representation of the ensemble learning algorithm, and the core of the random forest is to integrate prediction results of a plurality of decision trees. According to the integration mode based on Bagging, multi-dimensional feature information can be fully integrated, and the overfitting problem which is likely to happen to a single decision tree is effectively restrained. In a thunder and lightning potential forecasting scene, the algorithm can accurately capture a complex nonlinear relationship between meteorological elements and thunder and lightning potential by adaptively learning association between a large amount of historical meteorological data and thunder and lightning events, so that the forecasting accuracy is remarkably improved.

The invention relates to the technical field of ultrasonic detection, and discloses an ultrasonic-based weld defect detection method and system.The method comprises the steps that a historical database is established, ultrasonic echo signals are traversed in the historical database, a reuse defect strategy or an ultrasonic verification strategy is determined according to the traversal result, and when the reuse defect strategy or the ultrasonic verification strategy is determined, the ultrasonic verification strategy is determined; determining a first ultrasonic result based on the echo delay and the echo intensity, determining a second ultrasonic result based on the ultrasonic echo signal and the ultrasonic feature model, determining whether the weld joint to be detected has defects or not according to the first ultrasonic result and the second ultrasonic result, and performing Fourier transform on the ultrasonic echo signal to obtain the weld joint to be detected. The defect type of the weld joint to be detected is determined based on the ultrasonic characteristic spectrogram, the attenuation result is determined based on the three-dimensional model and the metal sample and written into the simulation database of the simulation environment, the defect type is verified based on the relation between the ultrasonic characteristic spectrogram and the simulation spectrum curve, and the reliability and stability of ultrasonic detection are ensured.

The invention discloses an acoustic Doppler flow velocity measurement method and system, and the method comprises the steps: generating an emission parameter combination adaptive to a current hydrological environment according to the depth characteristics and precision requirements of a target water area; original echo signals are collected based on the emission parameter combination, and a three-dimensional flow velocity vector of temperature compensation is output; inputting the three-dimensional flow velocity vector into the dynamic segmentation network to generate a layered flow velocity distribution model; calling a layered flow velocity distribution model, fusing fluxgate compass azimuth data to carry out flow direction compensation, triggering a deviation correction algorithm when equipment inclination exceeds a limit, and outputting absolute flow velocity distribution of pose calibration; and according to absolute flow velocity distribution and echo intensity dynamic range constraint, calculating an error interval of each depth unit, and outputting a final flow velocity profile with confidence identification. According to the embodiment of the invention, the environmental adaptability and data reliability of flow velocity measurement can be improved.

The invention discloses a pipeline detection device and method based on phased array ultrasonic waves, and relates to the technical field of pipeline detection. The pipeline detection device based on phased array ultrasonic waves comprises a shell with an opening in the lower portion and a phased array ultrasonic detector installed in the shell, an arc-shaped filter plate is fixedly connected to the upper portion of a strip-shaped discharging groove in an embedded mode, and a scraping and collecting mechanism used for scraping and collecting a coated coupling agent in time after detection is completed is arranged on the right portion of an inner cavity of the shell. According to the invention, the coupling agent is uniformly coated on the surface of the pipeline in a thickness-constant manner through the self-extrusion coating mechanism, the consistency of acoustic impedance in a welding seam or a detection area is ensured, the stability of ultrasonic echo intensity is improved, and a detection blind area caused by coating missing is avoided, so that the detection accuracy and reliability are improved; couplant can be scraped and collected in time after detection, the retention time of the couplant on the surface of the pipeline is shortened, solidification residues are effectively prevented, and the surface quality of the pipeline is protected.

The present invention discloses a radar monitoring and early warning method for open-pit mine slope stability, which relates to the technical field of geological disaster monitoring and early warning. It is used to solve the problem that existing slope radar monitoring is greatly affected by electromagnetic interference and is difficult to achieve accurate and stable real-time early warning. By obtaining the position information of the radar and the mine edge to be measured and generating a monitoring distance, the echo intensity is measured to calculate the initial reflectivity, and the radar deployment position is dynamically adjusted according to the required echo intensity. After updating the position information, multiple time periods are set to send radar signals of different frequencies. At the same time, the number of wireless devices and power supply fluctuations in the area are monitored, and the voltage spikes are extracted by using the power fluctuations of the wireless devices. The electromagnetic interference intensity is comprehensively analyzed in combination with the number of devices. The reflection change score is integrated based on the multi-frequency echo signal. The current reflectivity is calculated based on the radar echo according to the score screening standard, and compared with the initial reflectivity to determine whether an alarm is issued, thereby significantly improving the real-time and reliability of the slope instability early warning.

The invention provides a monitoring method and system for the conveying state of grain capable of being washed based on multi-mode sensing. Multi-axis laser speed measurement probes with dust covers are arranged on the two sides of the conveying belt, so that interference of dust to a light path is eliminated. Laser Doppler frequency shift signals of surface particles and echo intensity data of deep particles are synchronously collected, and a hierarchical control volume model is established; and utilizing the echo intensity to compensate the scattering signal, and generating a flow velocity distribution profile map through self-correlation processing. A particle motion vector field is further constructed by adopting an optical flow method, and a collision energy value is calculated through vector field energy distribution. When the energy value exceeds a preset threshold value, a positioning early warning signal is generated, and real-time monitoring and accurate positioning of particle collision abnormity are achieved. According to the technical scheme, full-dimension monitoring of the particle motion state in the grain conveying process can be achieved in the high-dust environment, collision abnormity is effectively recognized, the fault area is accurately positioned, and the grain conveying quality is guaranteed.

The invention discloses a target detection method, device and equipment based on millimeter wave radar, a storage medium and a program product. Determining a distance-Doppler map based on the echo signal received by the millimeter wave radar; determining the angle of each target based on the phase echo signal of each target; filtering the targets based on a first set threshold value and the echo intensity of each target to obtain candidate targets; determining second detection thresholds corresponding to different angles and / or different speeds; and filtering the candidate targets based on the second detection threshold, the echo intensity of each candidate target and the angle and / or speed of each candidate target to obtain a final detection target. According to the target detection method based on the millimeter wave radar provided by the embodiment of the invention, weak targets, false noise targets and sidelobe false targets caused by strong targets can be effectively filtered out, so that the accuracy of target detection is improved, and calculation resources for performing angle estimation on the targets subsequently are further saved.

The present application provides a method and device for window occlusion detection, which belongs to the field of sensor technology and can be used for assisted driving and autonomous driving. The method includes: obtaining a first window echo intensity and a second window echo intensity, the first window echo intensity represents the reference window echo intensity, and the second window echo intensity represents the window echo intensity at the current moment; obtaining the detection parameters of the target point at the first moment and the detection parameters at the second moment, the detection parameters including the reflectivity and / or position coordinates of the target point; according to the first window echo intensity, the second window echo intensity, the detection parameters at the first moment and the detection parameters at the second moment, obtaining a window occlusion parameter, the window occlusion parameter is used to indicate the window occlusion state. This method improves the accuracy of lidar window occlusion detection, so as to improve the terminal's advanced driving assistance system (ADAS) capabilities in autonomous driving or assisted driving.

The invention relates to the technical field of laser ranging, in particular to a novel railway tunnel deformation real-time surveying and mapping system based on a three-dimensional scanning technology, which comprises a laser sampling module, an echo evaluation module, a space repositioning module, a residual evolution module and a deformation surveying and mapping module. According to the method, after continuous distance information of a target position is obtained, measuring point sequence data is constructed based on a time sequence, a signal abnormal area is recognized through echo intensity fluctuation, the signal abnormal area is further converted into a space coordinate structure, track differences are extracted, vector data are generated, deviation characteristics are analyzed in combination with the tunnel space position, and the deformation amplitude is quantified. Compared with a periodic observation mode depending on manual distribution of measuring points, the method has the advantages that fine coordinate difference data can be continuously output, the deformation monitoring frequency and the space coverage range can be improved, manual interference errors can be reduced, and the dynamic mastering capability of the tunnel structure evolution process can be enhanced.

The invention provides a suspended sediment concentration inversion method capable of resisting particle size interference, which comprises the following steps of: standardizing the original acoustic echo intensity of each observation grid to obtain the standardized volume back scattering intensity; establishing a sonar equation considering the sound wave attenuation of the sediment particles, and performing explicit processing on the sonar equation considering the sound wave attenuation of the sediment particles to obtain an explicit inversion model which resists particle size interference and considers the on-way change of the sediment particle size; and performing model parameter calibration on the explicit inversion model, and performing suspended sediment concentration inversion on the river observation section based on the suspended sediment concentration inversion value of each observation grid. According to the method, the dependence of ADCP inversion of the suspended sediment concentration on suspended sediment particle size distribution is effectively eliminated, and the stability and accuracy of suspended sediment concentration inversion are improved. The particle size interference resistant explicit method can realize continuous and real-time suspended sediment concentration monitoring, and is suitable for various water environments such as rivers, lakes, reservoirs and the like.

The invention provides a metasurface structure and a metasurface structure preparation method, and relates to the technical field of electromagnetic wave regulation and control. The metasurface structure comprises a frequency selection layer, an isolation layer and a reconfigurable gradient impedance layer, the frequency selection layer is located above the isolation layer; wherein the frequency selection layer is used for receiving a first electromagnetic wave incident at a first angle and inhibiting the echo intensity of scattering of the first electromagnetic wave; the reconfigurable gradient impedance layer is located below the isolation layer; wherein the reconfigurable gradient impedance layer is used for receiving a second electromagnetic wave incident at a second angle and inhibiting the echo intensity of scattering of the second electromagnetic wave; wherein the first angle is smaller than the second angle. According to the application, the echo intensity of mirror scattering is suppressed through the frequency selection layer, and the echo intensity of non-mirror scattering is suppressed through the reconfigurable gradient impedance layer, so that electromagnetic scattering suppression of a wide angular domain is realized.

The embodiment of the invention provides a data processing method and device based on a laser radar. The method comprises the steps that signal characteristic parameters are acquired; and determining an extended echo intensity value of the target echo signal according to the signal characteristic parameters. According to the embodiment of the invention, the method achieves the extension of the echo intensity of the target echo signal through the laser radar, improves the discrimination degree of a close-range target, reduces the crosstalk phenomenon of a sensor in the laser radar, and enables a real target to be effectively distinguished from a false target with the crosstalk phenomenon.

The invention belongs to the technical field of feature recognition of underwater complex targets, and relates to a boundary element-based multi-bright-spot cluster target interference feature estimation method, which comprises the steps of geometric model construction and introduction, numerical calculation based on multi-physics field coupling, echo intensity representation by adopting an angle-frequency spectrum, and analysis of resonance generated by multi-body interference. According to the method, a numerical model for solving a three-dimensional double-gas-cylinder omnidirectional scattering sound field is established based on a boundary element method, and omnidirectional and broadband scattering characteristics of a target in horizontal and vertical attitudes are calculated; a multi-bright-spot dual-target strong scattering coupling mechanism is mainly analyzed, and a multi-body configuration and single target scattering interference fringe generation mechanism is disclosed; according to the method, the inherent attribute characteristics of the single target can still be effectively identified in a cluster target scattering field; the mapping relation among the geometric configuration, the spatial arrangement mode and the frequency response is obtained, and a theoretical formula suitable for double-target sound scattering forecast is deduced.

The invention provides a method and a system for identifying environment abnormity in a direct-current battery swap station. The method comprises the following steps: fusing multi-source images acquired by the direct-current battery swap station; determining at least one suspected abnormal region based on the fused image; constructing a three-dimensional structure model of an object in the suspected abnormal area based on reflection deformation information of structured light projected into the suspected abnormal area for multiple times; determining reflection change information of the object in the suspected abnormal area based on reflection echo intensity and reflection echo time of the obtained ultrasonic wave on the surface of the object in the suspected abnormal area; and performing logic correlation analysis based on the three-dimensional structure model and the reflection change information, and determining a target abnormal region in the to-be-identified direct-current battery swap station. According to the method and the system, the capability of identifying tiny and hidden abnormal objects of the direct-current battery swap station is greatly improved, missed judgment is effectively reduced, the accuracy and the reliability of environment abnormity identification in the direct-current battery swap station are improved, and stable operation of the battery swap station is guaranteed.

The invention provides a ground penetrating radar clutter suppression method and system and a medium, the method highlights a texture change area through first-order difference, can accurately capture change information of echo intensity and suppress background fluctuation and noise, meanwhile, introduces graph regularization to ensure similarity of adjacent pixels, suppresses isolated noise points, and improves noise suppression efficiency. And the stability of the texture structure is enhanced. By means of the combination, clutters can be effectively removed when the method is used for processing complex backgrounds, and meanwhile key structure information is reserved. Complex echo texture data are projected to a singular value feature space through singular value decomposition, singular values with a large change rate are screened out for reconstruction, redundant interference can be effectively removed, and stable echo textures are reserved. According to the mechanism, when the method is used for processing multi-target, dispersed and irregular echo signals, target signals and clutters can be effectively separated, and the detection precision is influenced.

The invention relates to a defect detection method based on fast and slow wave chasing, and the method comprises the following steps: 1, calculating a guided wave frequency dispersion curve of a one-dimensional component, and determining the propagation speeds of guided waves under different frequencies, 2, selecting two excitation frequencies, respectively corresponding to different propagation speeds, recording a fast wave with a fast propagation speed as a fast wave, recording a wave speed as V1, recording a slow wave with a slow propagation speed as a slow wave, 3, when the fast waves reach the meeting point, if the point has defects, the defects are fully expanded under the stretching action of the slow waves, so that the reflection of the fast waves is improved, 4, the excitation time interval of the fast waves and the slow waves is delta t, and 5, the emission time interval is continuously changed, so that the fast waves and the slow waves meet at different positions d, and the reflection of the fast waves and the slow waves is improved. And step 6, extracting the intensity of the fast wave echo signals at different d positions as a (x), obtaining a corresponding relation curve of the echo intensity and the length of the component, and if the curve is obviously increased at a certain position, determining that the position has defects.

The invention relates to a radar echo three-dimensional visualization method, device and equipment, a medium and a program product. The method comprises the following steps: acquiring radar scanning data, and constructing a three-dimensional point set based on the radar scanning data; dynamically adjusting the grid resolution in the longitude, latitude and height directions according to the spatial distribution characteristics of the three-dimensional point set to obtain a three-dimensional grid; after an adaptive threshold is determined, segmenting the three-dimensional grid, aligning the dimension of the block with the thread group number of the graphics processor, and synchronously executing table look-up and edge interpolation on each block by adopting a parallelization moving cube operator to generate a three-dimensional contour surface representing specific echo intensity; and carrying out local coordinate centralization and binary block packaging processing on the three-dimensional contour surface, exporting a preset format, and loading to a three-dimensional view to obtain a three-dimensional visual radar echo. Therefore, the million-level voxel processing time can be shortened from the minute level to the second level, the timeliness is greatly improved, and the method has wide application prospects in the fields of meteorological early warning, environment monitoring and the like.

The invention relates to the technical field of computer graphics, sensor simulation and real-time rendering, in particular to a panoramic laser radar simulation method and system based on a single GPU calculation shader, and the method comprises the steps: receiving simulation parameters of a laser radar sensor, assembling the simulation parameters into a constant buffer area object, and carrying out the simulation of the laser radar sensor on the constant buffer area object; the method comprises the following steps: allocating a structured point cloud buffer area and binding shader resources in a rendering dependency graph framework, scheduling and calculating a shader to generate a two-dimensional thread index, calculating a light beam direction vector corresponding to each thread and constructing a ray descriptor based on the two-dimensional thread index, and obtaining hit information; the method comprises the steps of calculating echo intensity based on hit information according to a preset intensity model, simulating noise, writing point cloud attributes into a structured point cloud buffer area, and asynchronously looking back point cloud data for consumption through the structured point cloud buffer area. And the throughput and the data consistency are improved.

The invention relates to an ultrasonic technology, and provides an obstacle recognition method and device, electronic equipment and a computer storage medium, the method comprises the steps that a plurality of spatial points are acquired, and the plurality of spatial points comprise corresponding points of a plurality of ultrasonic points collected by at least one ultrasonic sensor at the same moment in the same preset coordinate system; the plurality of spatial points are clustered to obtain at least one clustering cluster, and the clustering distance between any two spatial points in the clustering process is determined according to the ranging distance and the echo intensity of the ultrasonic wave point corresponding to each spatial point in the any two spatial points; and carrying out obstacle identification on each cluster. According to the invention, the accuracy and robustness of obstacle identification can be improved.

The invention relates to the technical field of data processing, in particular to an efficient monitoring and intelligent irrigation management platform for radar rainfall data. Obtaining a first abnormal point location and a non-initial abnormal point location according to a data volume feature in an intensity data cluster of the echo intensity and a data difference feature of the intensity data cluster; obtaining a point location connected domain according to the intensity data cluster of the non-initial abnormal point location; obtaining a spatial noise feature value according to the position distribution feature between the point location connected domains and the data difference feature in the point location connected domains; obtaining a time noise characteristic value according to the historical echo intensity of the non-initial abnormal point location; obtaining a second abnormal point location according to the spatial noise characteristic value and the time noise characteristic value; correcting the corresponding echo intensity according to the position features of the first abnormal point location and the second abnormal point location; and the rainfall is determined according to the corrected echo intensity, and the irrigation rule is adjusted, so that the accuracy of rainfall judgment and irrigation regulation is improved.

The application relates to the technical field of ultrasonic detection, and discloses a welding seam defect detection method and system based on ultrasonic waves, which comprises the following steps: establishing a historical database, and traversing ultrasonic echo signals in the historical database; determining a multiplexing defect strategy or an ultrasonic checking strategy according to a traversal result; when the ultrasonic checking strategy is determined, determining a first ultrasonic result based on echo delay and echo intensity, determining a second ultrasonic result based on ultrasonic echo signals and an ultrasonic characteristic model, determining whether a welding seam to be detected has defects according to the first ultrasonic result and the second ultrasonic result; performing Fourier transform on the ultrasonic echo signals, determining a defect type of the welding seam to be detected based on an ultrasonic characteristic spectrum, determining an attenuation result based on a three-dimensional model and a metal sample, and writing the attenuation result into a simulation database of a simulation environment; and verifying the defect type based on the relationship between an ultrasonic characteristic spectrum and a simulation spectrum curve. The application ensures the reliability and stability of ultrasonic detection.

The invention relates to the technical field of marine geological survey, in particular to a shallow sea sediment classification method and system based on multi-scale and multi-direction feature fusion, and the method comprises the steps: obtaining the multi-source acoustic data of a shallow sea sediment, and carrying out the preprocessing of the obtained multi-source acoustic data, constructing a spatial correlation model based on the preprocessed multi-source acoustic data, performing submarine topographic feature extraction according to a water depth value of MBES data, performing multi-scale and multi-direction texture feature extraction by using an SSS image output by the spatial correlation model, performing feature optimization on the obtained topographic features and texture features, and taking a core feature set as an input to perform feature extraction on the obtained topographic features and texture features; according to the method, the echo intensity image is taken as a core, the problem of poor space consistency in traditional multi-source data registration is solved, classification errors caused by feature space dislocation are avoided, and the accuracy of the multi-source data registration is improved. And classification reliability is improved.

The invention relates to the technical field of mobile robot environment perception and navigation, in particular to a storage environment depth map generation and processing method based on laser vision. Comprising the following steps: an original data acquisition and point cloud construction step: acquiring multi-dimensional original echo data including geometric distance, echo intensity and pulse width, and constructing an initial three-dimensional point cloud; a light-object interaction characteristic decoupling step: analyzing light intensity attenuation and pulse width broadening characteristics, and constructing an intensity distance material mapping model; a material analysis and confidence generation step: analyzing the data to identify high reflection, light absorption deficiency and semitransparent areas, and generating a pixel-level confidence tensor; a semantic enhancement depth map generation step: restoring abnormal pixels based on tensor and endowing physical trafficability semantics to generate a semantic enhancement depth map; according to the invention, the problem of visual deception is effectively solved, and the passing efficiency in a complex storage environment is improved.

The present invention relates to the field of underwater acoustic information processing technology, and provides a method for normalizing active sonar imaging data, comprising: S1, constructing an azimuth-distance matrix: obtaining azimuth-distance data through a sonar system and storing it in a polar coordinate system; S2, smoothing the data: after constructing the azimuth-distance matrix, smoothing each row of data to reduce the impact of noise; S3, calculating expected echo intensity: after completing the smoothing process, calculating the expected echo intensity of each detection point using a data-driven method; normalizing each row of data according to the corresponding expected echo intensity; S4, coordinate system conversion: after the normalization process, converting the processed azimuth-distance matrix data from a polar coordinate system to a rectangular coordinate system. The present invention can reduce the interference of background reverberation and noise on the detection of small targets at long distances.

The invention relates to the technical field of smart bracelets, and discloses a swimming stroke-based bracelet track positioning method and device and computer equipment, wrist nodes are obtained based on a human body model, and a swing area of a radar sensing assembly is obtained according to the wrist nodes, so that the motion range of a bracelet can be known through the swing area; swimming stroke information of a user in a preset time period is obtained based on the swing area of the user, the distance between each part and the radar sensing assembly and the time from sending to receiving are used for comprehensively representing the swimming stroke, and the adaptation degree of the user in water can be known through the underwater sensing coefficient. According to the technical scheme, the radar echo intensity can be calculated through the swimming stroke information and the underwater induction coefficient, whether the current swimming stroke is accurate or not can be known by judging the radar echo intensity, and when the current swimming stroke does not meet the preset condition, prompt information can be generated to remind a user, so that the bracelet effectively recognizes whether the swimming stroke is correct or not.

The present application relates to the technical field of concrete height measurement, and provides a concrete pouring height self-adaptive monitoring method and system, which controls a motor drive cloud platform to drive a laser ranging module to automatically scan a monitoring area and determine an effective monitoring point through an edge computing terminal, and sequentially performs automatic measurement, thereby improving monitoring real-time performance and reducing labor costs. During the monitoring process, when the ranging value suddenly changes and the echo intensity meets a preset condition, the cloud platform is controlled to swing and the maximum ranging value in the swinging process is taken as an effective value to actively avoid shielding and obtain a real concrete liquid surface distance. The number of consecutive invalid points is accumulated to automatically eliminate the invalid points, and new points are obtained by supplementally scanning near the eliminated points when the points are insufficient, thereby realizing automatic updating of the monitoring point set. The inclination of the device is obtained in real time through an inclination sensor, and the ranging value is accurately converted into pouring height in combination with the absolute installation height, thereby eliminating the device inclination error. The present application has low implementation cost and is convenient to deploy.

The application provides a kind of based on multimodal sensing of bad grain conveying state monitoring method and system. Wherein, by arranging the multi-axis laser speed probe with dust cover on both sides of the conveying belt, eliminate the interference of dust on light path. Synchronous acquisition of surface layer particle laser doppler frequency shift signal and deep layer particle echo intensity data, establish layered control body model. Use echo intensity to compensate scattering signal, generate flow velocity distribution profile by autocorrelation processing. Further adopt optical flow method to construct particle motion vector field, calculate collision energy value through vector field energy distribution. When the energy value exceeds the preset threshold, generate positioning early warning signal, realize real-time monitoring and accurate positioning of particle collision anomaly. The technical scheme provided by the application can realize full-dimensional monitoring of particle motion state in the process of bad grain conveying in high dust environment, effectively identify collision anomaly and accurately locate the fault area, and ensure the quality of bad grain conveying.

The invention discloses a visualization method for marine survey shallow stratum profile data, which is applied to the field of marine survey, and comprises the following steps: extracting acoustic echo samples, navigation data and attitude data from JSF format data collected by a shallow stratum profiler, analyzing the JSF format data into a JSON format containing the original echo intensity, geographic position and attitude information of each Ping, and analyzing the JSON format data to obtain the marine survey shallow stratum profile data. The method comprises the following steps of: firstly, dividing a local sub-block, mapping the local sub-block into an initial gray level image matrix, then enhancing the initial gray level image matrix by adopting CLAHE, and generating a high-contrast profile image capable of clearly identifying the characteristics of the seabed shallow layer structure by dividing local sub-blocks, calculating a local histogram cumulative distribution function and redistributing pixel values. According to the method, the data accuracy is ensured, the accuracy and the efficiency of interpreting the submarine pipeline burial depth and the stratum structure by interior interpretation personnel are improved, the data processing cost is reduced, the readability, the transportability and the compatibility of the data are improved, and a standardized interface can be provided for long-term management of ocean survey data and application of different platforms.