4623 results about "Laser ranging" patented technology

The invention belongs to the technical field of side slope monitoring, and particularly discloses and provides a side slope deformation three-dimensional monitoring system based on fusion laser ranging, which comprises a deformation rule analysis module, a monitoring switching judgment module, an environment monitoring module, a side slope deformation analysis terminal and a deformation risk processing terminal. According to the invention, by identifying abnormal characteristics such as slope change overlimit, automatically capturing potential high-risk areas such as acceleration abrupt change areas and triggering monitoring setting dynamic updating, the problem of coverage blind areas of fixed monitoring areas is effectively solved, adaptive tracking monitoring of slope high-risk points is realized, and the method is suitable for large-scale popularization and application. Meanwhile, a multi-dimensional slope deformation risk assessment mechanism is constructed by performing fusion processing on a past environment tracking log and a three-dimensional coordinate sequence and setting a deformation risk compensation weight, the limitation of traditional single-point monitoring is broken through, and the slope deformation risk assessment mechanism is established by collecting the humidity of a slope area in real time and selecting laser wavelength. And the interference of environmental noise on three-dimensional coordinate data acquisition is reduced.

The invention discloses a multifunctional subway tunnel disease intelligent inspection rail car and a detection method, and belongs to the technical field of rail detection. Aiming at the problems of low manual detection efficiency and single equipment function in the prior art, the invention provides an intelligent inspection vehicle integrating laser scanning, ground penetrating radar and artificial intelligence. The inspection vehicle is provided with a support telescopic system, and camera height self-adaptive adjustment is achieved through a laser distance measuring sensor and an XGBoost algorithm. The disease image acquisition system and the three-dimensional laser scanner cooperate to obtain surface disease data; the internal disease data acquisition system detects internal cracks of the lining through a ground penetrating radar; the disease analysis system deploys an improved YOLOv11 model to realize intelligent identification; and the global control system is integrated with a multi-source data visual interface. The detection method comprises the steps of adaptive adjustment, multi-source data acquisition, preprocessing, intelligent identification and positioning feedback. The system constructs an Internet of Things architecture, significantly improves the detection efficiency and precision, and is suitable for health monitoring of the subway tunnel structure.

The invention relates to the technical field of robot navigation, and discloses a laser vision fused map dynamic construction method and system, and the system comprises a data perception module, a feature analysis module, an information fusion module and a dynamic optimization module. The data sensing module collects an environment point cloud sequence and a scene image sequence through laser ranging equipment and a visual imaging device; the feature analysis module extracts spatial structure features of the point cloud and visual semantic features of the image; the information fusion module adopts a weight distribution strategy to fuse the multi-modal features to generate an initial map; and the dynamic optimization module adjusts the map position and attribute parameters in real time by using the incremental data. Through multi-modal fusion and dynamic optimization, the problems of insufficient precision, semantic deficiency and low dynamic updating efficiency of a traditional single sensor map are solved, and the method is suitable for scenes of robot navigation, automatic driving and the like.

The invention discloses a crane motion track prediction method based on an RGBD image, and belongs to the technical field of crane intelligent control, and the crane motion track prediction method comprises the following steps: S1, synchronously collecting multi-modal data, deploying a binocular RGBD camera array, and obtaining an RGB image and depth point cloud data of a crane operation area in real time; s2, cross-modal feature alignment and fusion are carried out; s3, track prediction and physical constraint correction; and S4, calculating the minimum safety distance between the crane and the dynamic object in real time. According to the method, a cross-modal space-time alignment mechanism is constructed by integrating the binocular RGBD camera array, the millimeter wave radar, the laser range finder and IMU data, the deformable convolutional network is adopted to dynamically compensate sensor data offset, multi-source data conflicts are eliminated, and compared with a traditional single sensor scheme, the method has the advantages that the method is simple in structure and convenient to operate. The multi-mode cooperative mechanism effectively solves the problem of sensing failure in a sensor blind area and a severe environment.

A laser distance ranging method includes splitting two combs of dual comb radiation into a signal radiation portion and a local oscillator radiation portion. The signal radiation portions are, after separation, combined into a combined signal radiation and directed onto an object, the distance to which is to be measured. The signal thrown back from the object is split into a first and second signal portions. The first signal portion is superimposed with the second local oscillator radiation portion to generate a first measurement signal, and the second signal portion is superimposed with the first local oscillator radiation portion to generate a second measurement signal. The distance to the object is determined from the first and second measurement signals, and from reference signals obtained by the partial reflection, wherein the Vernier effect can be used to extend ambiguity by comparison of the first and second measurement signals.

The invention discloses an extrusion production process for an aluminum alloy multi-cavity profile. The extrusion production process comprises the following steps that S1, raw materials are prepared; s2, designing and manufacturing a mold; s3, pretreatment before extrusion; s4, extrusion forming; s5, cooling treatment; s6, straightening and finishing; s7, aging treatment; and S8, detecting and packaging. According to the invention, the friction is further reduced by adopting a special high-temperature lubricant and an ultrasonic vibration device in the pre-extrusion pretreatment, the precise control is realized by arranging real-time monitoring and feedback systems such as a laser range finder and an infrared thermometer in the extrusion forming process, and the cooling treatment is realized by automatically adjusting parameters by adding a corrosion inhibitor and arranging a sensor, so that the production efficiency is improved. The cooling quality of the profile is ensured; laser scanning and electrolytic polishing technologies are adopted for straightening and finishing, the straightening precision and the surface quality are improved, a circulating hot air system and a segmented aging mode are adopted for aging treatment, and the aging effect is improved.

The invention relates to the technical field of asphalt pavement paving, and discloses an asphalt pavement 3D intelligent paving cooperative control system and method based on BIM + GIS, and the system comprises a data fusion layer, a real-time control layer, a multi-machine cooperation and task distribution layer, and a quality closed-loop layer. The real-time control layer comprises multi-source data acquisition (positioning / temperature / compaction degree and the like) and three types of core decisions carried out by the cloud center, and the three types of core decisions carried out by the cloud center comprise feeding demand prediction (based on paving speed + thickness) of a dumper, thickness / speed adaptive adjustment of a paver and dynamic planning of a rolling path of a road roller. According to the method, real-time correction of transverse deviation and elevation deviation is achieved through combination of PID control and fuzzy control, the expansion amount of a hydraulic cylinder of the ironing plate is dynamically adjusted by associating the paving speed, the multi-source sensing technology of Beidou, IMU, laser ranging and infrared imaging is adopted, time sequence consistency data synchronization is achieved through 5G communication, and the real-time correction of the transverse deviation and the elevation deviation is achieved. And the precision and the closed-loop optimization effect can be controlled in real time.

The invention provides a full-coverage cleaning modular control method and system for a photovoltaic cleaning robot. According to the method, a photovoltaic panel three-dimensional terrain model is constructed by collecting laser ranging, photovoltaic panel surface temperature distribution, environment airflow and position relation data; and generating an obstacle distribution map based on the model, and dynamically analyzing gap width and attachment height parameters of the cleaning area. Therefore, the bending angle and the telescopic amplitude of a connecting part of the cleaning module are adjusted in real time, and robot pose information is synchronously updated. And in combination with the position data, the obstacle map and the pose of the whole robot, an uncleaned area identifier and a dynamic coverage path are generated, and information is shared through a wireless network. The system dynamically distributes working areas and advancing directions of the multiple robots, and efficient cooperative full-coverage cleaning of the photovoltaic array is achieved. According to the technical scheme provided by the invention, through multi-source environment perception and dynamic pose adjustment, intelligent path cooperation and full-coverage operation of multiple cleaning robots are realized.

The invention relates to the technical field of resource allocation, in particular to a data preset learning-based dynamic material allocation system for multiple stations, which comprises a topology modeling module, a demand clustering module, a strategy generation module and a decision optimization module. According to the method, laser ranging and dynamic time warping are combined, the work station layout is converted into a moving time consumption parameter, a space correlation coefficient is adjusted according to a difference value proportion, a topological relation matrix is updated in real time, DTW quantifies the mode similarity of a demand interval standard deviation and a usage variable coefficient, a multi-dimensional demand feature vector is constructed, and the prediction and actual consumption matching degree is improved; the method comprises the steps of establishing a response capability curve based on OEE data, dynamically associating residual capacity with demand characteristics through linear programming, realizing strategy pre-generation and capacity early warning, constructing a cooperation unit through a Hungary algorithm, matching material and equipment parameters through cosine similarity, triggering strategy reconstruction, synchronously updating topology, forming a closed-loop optimization system and enhancing the cross-station dynamic response capability.

The invention discloses a wide-range weak feature scene measurement system based on multi-sensor fusion and structured light scanning, and relates to the technical field of wide-range scene scanning, in the system, an extended Kalman filtering algorithm is adopted, fusion is carried out based on positioning data provided by an inertial measurement module and a positioning sensing module, and a wide-range weak feature scene is obtained. And the distance measurement information provided by the laser distance measurement module is combined to correct the fused positioning data, so that the precision and robustness of subsequent point cloud registration are ensured. Then, according to position information and attitude information of the binocular structured light scanning camera during scene scanning, calculating a relative rotation matrix and a relative displacement matrix of each frame of scanning point cloud data relative to the first frame of scanning point cloud data, and performing coarse registration; in the coarse registration process, all frames of point clouds can be converted into a unified coordinate system by directly utilizing global pose information, and the efficiency of coarse registration is greatly improved. And finally, extracting laser marking point clouds projected by the non-contact laser marking device in each frame of scanning point cloud data, and performing iterative precise registration on each frame of scanning point cloud data by using color features and geometric distribution rules of the extracted laser marking point clouds. In conclusion, high-precision, high-efficiency and high-robustness point cloud registration in a large-scale weak feature scene is realized, and the method can be used for realizing high-precision non-contact measurement.

The invention relates to the field of ocean engineering construction monitoring, and discloses a pile body penetration identification method based on multi-modal perception and dynamic coupling modeling, which comprises the following steps: collecting pile body motion data by deploying vision, inertia and laser ranging sensor networks, constructing a pile body-foundation dynamic model in combination with finite element discretization, and constructing a pile body penetration identification model; separating vibration interference and real displacement by using extended Kalman filtering; the YOLOv8 model is improved to realize pile body contour tracking in a low-illumination environment, and multi-source data is fused to predict a pile body motion state; the high-precision penetration is calculated through vibration compensation correction, weighted fusion and dynamic threshold judgment, and grading alarm and construction control instructions are triggered. According to the invention, the problems of low multi-sensor data fusion precision and weak anti-interference capability in a complex marine environment are solved, real-time monitoring and closed-loop feedback of the penetration of the pile body are realized, and reliable technical support is provided for piling construction.

The embodiment of the invention provides a multi-unmanned aerial vehicle cooperative surveying and mapping method and system for areas along a railway, and belongs to the technical field of railway surveying and mapping. The method comprises the steps that the unmanned aerial vehicle collects monitoring data in the flight process; the relative position and posture between the aircrafts are dynamically adjusted, and an observation configuration with variable baseline parameters is constructed; laser ranging modules carried by the unmanned aerial vehicles are controlled to execute synchronous ranging operation, and multiple sets of laser point cloud data covering the railway structure area are generated; performing coordinate registration and fusion on the collected laser point cloud data, and combining position information and attitude information of each unmanned aerial vehicle; and extracting geometric dimension parameters of the railway structure from the compensated three-dimensional model, and outputting the geometric dimension parameters as measurement results. According to the scheme, high-precision non-contact measurement of geometric dimension parameters such as the track gauge, the height difference and the roll angle of a railway track structure is achieved.

The invention relates to the technical field of space measurement and calibration, and discloses a laser ranging-fused vision measurement system calibration method, which comprises the following steps of: S1, establishing a system coordinate model of a vision measurement system and a laser range finder, and defining a laser ranging coordinate system, a camera coordinate system and a world coordinate system; s2, calibrating a camera, and obtaining an internal parameter matrix and an external parameter matrix of the camera; s3, acquiring image pixel coordinates of the laser points on the calibration plate; s4, converting the pixel coordinates of the laser points into three-dimensional coordinates under a camera coordinate system based on the internal reference matrix and the external reference matrix of the camera; s5, fitting a direction vector of a laser beam through the three-dimensional space distribution data of the laser points; and S6, based on the laser beam direction vector and the laser ranging value. A direction vector of a laser beam is extracted through principal component analysis, abnormal points are eliminated in combination with a random sampling consistency algorithm, a fitting result is optimized, and the calibration robustness and precision are remarkably improved.

The invention discloses a laser radar test method based on a long-distance target distance measurement result, and the method comprises the following steps: obtaining a laser radar echo signal, and extracting the frequency spectrum information of the echo signal; doppler frequency shift characteristic parameters are extracted according to the frequency spectrum information, and the relative speed of the target is calculated based on a preset frequency shift calculation model; acquiring multi-source sensor data associated with the laser radar test platform, and fusing to construct a dynamic ranging reference coordinate system; performing dynamic motion compensation on a laser ranging result according to the relative speed of the target to obtain a target initial measurement distance after Doppler correction; mapping the target initial measurement distance after Doppler correction to the dynamic distance measurement reference coordinate system to obtain a remote target final distance measurement result aligned with a test platform coordinate system; and outputting the accurate position and moving state information of the target in the three-dimensional space according to the final distance measurement result. According to the invention, the ranging precision and stability can be improved.

The invention provides a double-robot collaborative welding dynamic compensation system which is characterized by comprising two welding robots slidably mounted on two ground rails, a six-axis laser welding seam locating device is mounted on each welding robot, and a machine vision assembly is arranged in each laser welding seam locating device. A stand column cantilever used for driving the welding robot to move is installed on the ground rails in a sliding mode, a rotary table position changing machine is arranged between the two ground rails, a powder concentrator rotor is placed on the rotary table position changing machine, and a control system is electrically arranged beside the welding robot. The double robots cooperatively work through the laser distance measuring sensor and the visual assembly, rapid concentric alignment of a rotor, blade angle calibration and real-time tracking of a welding seam are achieved, high-precision positioning of the laser distance measuring instrument is combined with intelligent image processing of the visual module, the accuracy of welding path planning is remarkably improved, deviation caused by manual intervention is avoided, and the working efficiency is improved. The two robots cooperate with each other, so that the welding efficiency is improved by more than 40% compared with a single-machine system.

The invention discloses a vehicle-mounted ground penetrating radar attitude compensation device and a control method, and belongs to the technical field of ground penetrating radar detection. The attitude compensation device comprises a control mechanism and a monitoring system, the control mechanism comprises a radar supporting part and a vehicle-mounted supporting part, the radar supporting part is connected with the vehicle-mounted supporting part through a buffer compensation part, the buffer compensation part comprises a mechanical telescopic structure, and the two ends of the mechanical telescopic structure are connected with the radar supporting part and the vehicle-mounted supporting part respectively; the monitoring system is arranged on the radar supporting part and comprises an IMU sensor, a laser range finder and a data processor. The IMU sensor, the laser range finder, the data processor and the like of the monitoring system are utilized, pose information is fed back in time through information monitoring, and the compensation device is controlled to carry out pose compensation by analyzing motion data, so that the platform is always located at a horizontal position with a certain distance from the ground; the detection precision and the anti-interference capability of the ground penetrating radar system are obviously improved, and different road conditions are flexibly coped with.

The invention relates to the technical field of laser processing, and discloses a sports kettle trepanning method and system based on a laser cutting technology. The method comprises the steps that through three-dimensional point cloud scanning and local curvature calculation, reinforcement learning dynamic path planning, transient thermodynamic coupling parameter optimization, deformable mirror-mechanical arm cooperative control and infrared temperature field feedback closed loop, high-precision cutting and thermal damage suppression of the complex curved surface are achieved, and path re-planning is triggered when deviation exceeds the limit. The system comprises a laser ranging sensor array module, a reinforcement learning decision module, a thermodynamic coupling solver module, a deformable mirror and six-axis mechanical arm cooperative control module and a multi-sensor feedback module. Through curvature self-adaptive laser processing, multi-physical field thermal damage cooperative control, optical-mechanical dynamic focusing and intelligent closed-loop optimization, high-precision cutting of the complex curved surface is achieved, the calculation efficiency and the system stability are both considered, and the processing quality and adaptability are effectively improved.

The invention discloses a multi-group film winding tension cooperative control system, which belongs to the technical field of plastic film production control, and comprises a plurality of groups of parallel winding devices, each winding device is provided with a motor, a winding wheel group, a belt, a speed sensor, a laser range finder, a data acquisition module, a tension calculation module, a speed adjustment module and a control execution module, the tension calculation module is used for acquiring corrected winding tension characteristics according to the film winding tension information, and the speed adjustment module is used for adjusting the winding speed according to the tension information and the historical tension information and outputting the corrected winding speed; through comprehensive consideration of multiple factors, the tension calculation accuracy is improved, cooperative control over the tension of multiple sets of films is achieved, and the purposes of dynamically adjusting the winding speed and then improving the system stability are achieved.

The invention relates to a related light measuring device based on a bevel mirror and a control method, and solves the problem that the existing three-dimensional detection technology is insufficient in comprehensive adaptability and cannot meet the requirements of precision detection for stability, precision and data collaboration, and the related light measuring device comprises a laser emission head, a double-bevel mirror, a light path receiving module, a zoom camera and a circuit processing unit. The first bevel mirror is provided with a through hole for laser to directly irradiate a target; the light path receiving module receives and reflects the laser-to-electric signal; the second bevel mirror reflects the target and the light spot light to the camera to obtain visual information; and the circuit processing unit controls all the components, integrates laser and visual information, and realizes three-dimensional detection of the target. The method has the following effects: through the light path collaborative design of the double-bevel mirror, precise and synchronous acquisition of laser ranging signals and visual contour / light spot information is realized, so that high-precision three-dimensional detection of the distance, the flatness and the segment difference of a target object is efficiently completed.

The invention belongs to the technical field of coal mine underground positioning, and discloses an underground personnel positioning and tracking method based on laser ranging, which comprises the following steps: calculating the distance between nodes through ranging signals between UWB mobile nodes, and establishing a relative positioning model of the UWB mobile nodes in combination with preset fixed base station coordinates; performing registration alignment on the first local octree map of the collapse area and the relative positioning model, fusing heterogeneous data of the laser radar and the UWB sensor in time and space dimensions, and forming an initial positioning result of the trapped person; acquiring real-time data of the second local octree map and the UWB relative positioning model under the extreme condition of communication blocking or signal interruption, and predicting the position of the trapped person; and according to a path planning result after local obstacle avoidance adjustment, position coordinates of rescue worker mobile nodes are updated in real time, and positioning data of trapped persons are corrected through a graph optimization algorithm. According to the invention, the positioning problem of a mine collapse disaster site in a complex environment is solved.

The invention provides a welding path planning method based on multi-modal fusion and deep learning, and relates to the technical field of welding automation, the method comprises the following steps: synchronously acquiring three-dimensional coordinate information of a welding workpiece through a laser ranging module and a CCD visual sensor, and fusing laser height parameters and visual plane feature points; an initial path is generated based on the dynamic welding adaptation coefficient and the welding environment complexity, and laser errors, visual matching deviation and environment interference intensity are quantified; laser and visual data are dynamically weighted by using multi-modal feature fusion weights, spatial-temporal features are extracted through a deep learning model, and a welding track is optimized; and the six-axis mechanical arm is controlled to execute welding operation, weld quality is monitored in real time, and path parameters are adjusted in a closed-loop mode. According to the method, the problem of insufficient precision of a single sensor is solved through a multi-modal data complementation mechanism, sudden obstacles and temperature fluctuation are dealt with in combination with dynamic parameter calculation and real-time path correction, and the local path optimization capability is improved by using the convolutional neural network and a self-attention mechanism.

The invention relates to the technical field of motor shaft size detection, in particular to motor shaft size detection equipment which comprises a detection table, a fixing mechanism, a length detection mechanism, a diameter detection mechanism and a cleaning mechanism. The length detection mechanism comprises a top plate, a detection plate, a first laser distance measuring sensor and a moving assembly, the cleaning mechanism comprises a transverse plate, an electromagnet, a sponge eraser, a telescopic assembly, a rotating assembly and a transmission assembly, and the diameter detection mechanism comprises a sliding frame, a sliding assembly and two second laser sensors. The length of the motor shaft can be detected, the diameter of the motor shaft can be obtained by arranging the two second laser sensors, the length and the diameter of the motor shaft can be synchronously detected by using one detection device, and the size detection efficiency of the motor shaft can be improved.

The invention relates to a buoyancy tank wharf real-time assembly quality control method, and belongs to the technical field of port engineering automatic construction. According to the method, aiming at the problems of large geometric positioning deviation, uneven contact surface stress and difficulty in real-time control of attitude instability in buoyancy tank assembly, laser range finders are mounted at four corners of a buoyancy tank through a geometric positioning layer to monitor horizontal deviation, and pressure sensors are arranged on a butt joint surface through a mechanical sensing layer to generate a pre-tightening force curve; the attitude monitoring layer adopts a bottom inclination angle sensor to detect inclination; according to the horizontal deviation, the curve similarity deviation and the inclination angle deviation, the real-time management and control platform triggers a hydraulic adjusting mechanism, a torque wrench and a balance weight drive to conduct adjustment; meanwhile, data are stored through a buoyancy tank number, a timestamp and a sensor type three-dimensional index, and a rechecking instruction is generated based on the difference between the current adjusting quantity and the first three mean values. According to the invention, real-time control and dynamic adjustment of the assembly process are realized, and the modular assembly precision and safety of the floating wharf are improved.

The invention relates to the technical field of target identification, in particular to an aerial target identification tracking method and system based on a multi-band electromagnetic fusion sensing technology. According to the invention, through the cooperative work of the infrared high-definition camera, the event type camera and the multispectral camera, the advantages of each sensor are fully played, and the recognition blind spots of a single sensor in a complex environment are effectively overcome, so that the accuracy and reliability of target recognition are greatly improved, and meanwhile, the accuracy and reliability of target recognition are greatly improved by introducing a laser ranging technology. The distance information between the target and the pod can be acquired in real time, so that the system accurately tracks the motion state of the target and timely adjusts the tracking strategy, and the real identity of the target can be deeply discriminated and recognized through the multiband data acquired by the multispectral camera in combination with the spectral characteristics of the known target in the data storage module. In addition, the method has the capability of coping with various environments such as low-illumination and high-dynamic scenes, and is suitable for wide application fields.

The invention discloses a millimeter wave radar and range finder golf sports monitoring system and method and a medium, and relates to the field of sports monitoring, the system comprises a handheld integrated terminal, a laser ranging module, a millimeter wave radar module, a processing unit and a display unit are integrated in the handheld integrated terminal, and a first communication module is connected with the processing unit; the data interaction module is used for performing data interaction with an external mobile terminal; the mobile terminal comprises a second communication module, a trajectory prediction module and a recommendation decision module, and is used for comparing the predicted flight trajectory with a target trajectory preset by a user and generating a swing suggestion in a training mode; and in the motion mode, the central processing unit is used for planning and recommending a ball hitting strategy based on the expected drop point distance input by the user and the real-time environment data measured by the handheld integrated terminal in combination with historical training data of the user. According to the invention, accurate monitoring and dynamic analysis of the golf ball flight path are realized.

The invention discloses an unmanned aerial vehicle inspection device and method, the unmanned aerial vehicle inspection device comprises an unmanned aerial vehicle, a laser ranging camera, a holder, a telescopic device and an ultrasonic detection device, the telescopic device is installed on the unmanned aerial vehicle, and the ultrasonic detection device is connected with the telescopic device through the holder. The laser ranging camera is connected with the first end of the unmanned aerial vehicle through the holder, and the laser ranging camera and the ultrasonic detection device are both located below the unmanned aerial vehicle. The invention belongs to the technical field of unmanned aerial vehicles, and aims to solve the problem that in the prior art, iron tower inspection cannot inspect the nut loosening condition. The technical effects are that the anti-loosening condition of the nut can be reliably and accurately detected, the loosening condition of the nut can be timely detected, and the stability of an iron tower can be guaranteed.

The invention provides a method for automatically centering and assembling a bearing on a long-axis part, and belongs to the technical field of bearing assembly.The method comprises the steps that position information of the long-axis part and the bearing is collected in real time through a binocular camera and a laser distance measuring sensor, a central line equation is calculated through the least square method, and position deviation is determined; a centering adjustment vector is generated to control a multi-degree-of-freedom precise attitude adjustment platform to perform preliminary adjustment, a mechanical arm is matched with high-precision laser ranging to perform precise centering, the centering process is modeled into a weighted undirected graph, an optimal adjustment path is solved, optimal press fitting parameters are calculated based on a bearing press fitting physical mechanics equation, and press fitting is performed. Meanwhile, the assembling process is monitored through a force sensor and a displacement sensor, an assembling quality evaluation matrix is constructed, finally, the assembling result is detected and evaluated, and high-precision automatic assembling of the long-axis part and the bearing is achieved.

The invention provides a sandy stratum tunnel water burst risk prediction method. The method comprises the steps that a radar instantaneous energy spectrum in front of tunneling is obtained through a geological radar, a micro-seismic spectrum is obtained through a micro-seismic array, and a residual distance is obtained through laser ranging; aligning and coupling the two spectrums to obtain a water inrush risk index, inputting the water inrush risk index and the residual distance into a self-adaptive threshold comparator, and if the water inrush risk index and the residual distance exceed the limit, dynamically adjusting the rotating speed of a cutter head, propulsive force, the rotating speed of a screw conveyor and grouting pressure, and generating a risk avoidance path; and calling a water inrush risk model library constructed by LSTM-Attention, inputting a risk index sequence, a residual distance, cutterhead torque, a soil pressure gradient, a current change rate and other auxiliary variables, and outputting a future multi-step risk level. According to the method, accurate prediction and real-time avoidance of the water gushing risk of the sandy stratum tunnel can be realized, and the safety and efficiency of tunnel construction are improved.

The invention provides a marine target real-time positioning and tracking system and method based on multi-source data fusion, and belongs to the field of target positioning and tracking. The sensor portion collects raw data. The data acquisition and time synchronization module is responsible for receiving and aligning data of each sensor; the multi-stage coordinate system registration and transformation module unifies all observation data to a world coordinate system by using IMU data and preset calibration parameters; the AI visual target detection module processes the video stream to identify a target; the adaptive federated Kalman filtering fusion module receives each path of processed data and outputs optimal target state estimation; and the dynamic task and resource scheduling module performs optimal allocation on system resources according to the current tracking state to form closed-loop control. Through deep fusion of high-precision RTK positioning data, laser ranging data, photoelectric pod attitude information and an AI vision algorithm, the positioning precision, tracking robustness and system real-time performance of a sea target under a complex dynamic sea condition are improved.

The invention discloses a cable eccentricity online monitoring method based on multi-point laser ranging, and relates to the technical field of cable manufacturing and detection, and the method comprises the following steps: twelve laser displacement sensors are uniformly arranged at the periphery of a cable core to be detected, the sensors are arranged at fixed intervals of 30 degrees, and a closed annular monitoring array is formed; the method is used for synchronously acquiring radial distance data from the surface of the cable core to the inner wall of the insulating layer at each measuring point. Full-circumferential real-time monitoring is achieved through the high-density laser sensor array, the measurement precision is guaranteed through multi-algorithm fusion and temperature compensation, a closed-loop feedback control mechanism is formed in combination with production equipment, the problems of eccentricity detection blind areas, error interference and manual lag are effectively solved, and the quality consistency and production efficiency of cable manufacturing are improved.