2512results about How to "Avoid interference" patented technology

The invention relates to the technical field of turning equipment, and discloses turning equipment for a precision bearing assembly, which comprises two symmetrically arranged chucks, a rotation driving assembly for driving the chucks to rotate, a driving base for driving the chucks to translate, and a cutting mechanism for cutting a workpiece, a plurality of first sliding grooves are formed in the chuck in the radial direction, the first sliding grooves are formed in the chuck in a penetrating mode, first sliding bases are slidably installed in the first sliding grooves, and sliding type fixing rods are arranged in the first sliding bases in a penetrating mode; through the arrangement of composite positioning of the axial adjustable sliding type fixing rod and the two-way double chucks, adaptive clamping of long cylindrical blanks with different axial lengths is achieved, and the fixing mode that inner hole multi-point supporting and end face pressing are combined is adopted; the problems of blank local deformation, rotation eccentricity and low coaxiality caused by a traditional clamping mode are effectively solved.

The invention discloses a farmland furrow three-dimensional point cloud data correction method and system based on a laser radar, and relates to the technical field of three-dimensional image processing based on the laser radar, in particular to a three-dimensional image geometric correction technology. The problems that original point cloud data directly obtained under the dynamic operation condition of an existing agricultural machine has geometric distortion, and the shape of a furrow cannot be truly reflected are solved; meanwhile, the problems that furrow quality evaluation seriously depends on low-efficiency manual means, the adaptability of an existing automatic technical scheme to an unstructured field environment is insufficient, and robust, real-time and high-precision perception of a real three-dimensional shape of a furrow cannot be achieved are solved. According to the method, dynamic tilt correction is carried out through real-time acquisition of point cloud and agricultural machine attitude information, boundary feature points are extracted, boundary lines are fitted, and a three-dimensional point cloud set of a single furrow is reconstructed by fusing a self-adaptive clustering algorithm of spatial prior. The method is suitable for the fields of farmland tillage and soil preparation quality detection, precision agricultural management, agricultural machinery intelligent operation and the like under the dynamic operation condition of agricultural machinery.

The invention relates to the technical field of automatic machining equipment, in particular to a bending method and a bending device.The bending method provides bending device.The bending device comprises a first bending unit and a second bending unit, the first bending unit is provided with a first bending part, and the second bending unit is provided with a second bending part; the method comprises the following steps: transferring a flexible structure to a first bending unit; the first bending part is driven to do jacking motion in the first direction to jack the first bending position of the flexible structure, so that the flexible structure forms a first bending structure at the first bending position; the flexible structure bent for the first time is transferred to a second bending unit; and the second bending part is driven to do translational motion in the second direction, so that the flexible structure is pushed to be close to the position of the second bending position, and the flexible structure forms a second bending structure at the second bending position. The invention mainly aims to provide a bending method and aims to realize secondary bending of a flexible structure.

The invention provides a lightweight large model operation method based on end-side deployment. The lightweight large model operation method comprises the following steps: acquiring equipment operation data and storing a model file in a mixed precision format according to quantization precision supported by terminal equipment; determining a mixing precision quantification strategy and carrying out strategy analysis on the equipment operation data; a Key-Value cache file obtained through model reasoning in the historical dialogue is reserved; calculating a semantic embedding vector of the second user request, calculating a cosine similarity between the semantic embedding vector and the first V vector, and judging whether the second user request has a similar intention or not according to a calculation result; and if yes, performing incremental reasoning on the second user request by multiplexing the Key-Value cache file. By monitoring the state of the terminal equipment in real time, dynamically adjusting the quantization level, multiplexing the cache data of the semantic related requests and merging batch request reasoning, the effects of balancing the energy consumption and performance of the terminal equipment, reducing repeated calculation and improving the service time of the equipment and the user experience are achieved.

The invention discloses a digital electroencephalograph, and belongs to the technical field of brain-computer interface signal processing. An electroencephalogram signal processor of the digital electroencephalograph acquires digital neural signals of a plurality of channels for a target object, wherein the digital neural signals comprise LFP signals and pulse signals; performing feature extraction on the two signals based on a unified time window and a sliding step length, and integrating a time-aligned feature matrix into a first fusion feature tensor; performing dynamic normalization processing on the first fusion feature tensor, wherein the statistical magnitude is updated along with the change of the input data; and n parallel LSTM networks are used to decode the normalized second fusion feature tensor to obtain n decoding results of different dimensions, the n LSTM networks are mutually independent, and each LSTM network has an independent optimizer and an independent parameter. According to the method, multi-modal features can be aligned in time, signal drift is compensated, decoding robustness is improved, and inter-task optimization decoupling and personalized training are achieved through independent parameters and an optimizer.

The invention discloses a method and a device for determining a maximum submerging range and a nonvolatile storage medium, and relates to the field of remote sensing data processing. The method comprises the following steps: determining first distribution information of normalized difference water body indexes of a target area in a first time period; second distribution information of the normalized difference water body index of the target area in a second time period is determined, and the second time period is a time period after the flood event occurs in the target area; comparing the second distribution information with the first distribution information to obtain difference distribution information of the normalized difference water body index of the target area in the second time period; and determining the maximum submerging range in the target area according to the difference value distribution information. The technical problem that the maximum flood inundation range cannot be accurately determined when the flood inundation range is determined directly based on remote sensing data in related technologies is solved.

The invention discloses an artificial intelligence model training and reasoning management system based on a knowledge graph, and the system comprises the following modules: a data analysis module which is used for collecting multi-source perception data and forming an entity set and an event set; the graph construction module is used for constructing a context knowledge graph based on the entity set and the event set; the context mapping module is used for establishing a reversible mapping relationship between the context knowledge graph and the original multi-source sensing data; the problem analysis module is used for carrying out semantic analysis on a problem input by a user and cutting the problem to obtain a context sub-graph; the reasoning chain generation module is used for generating a reasoning chain meeting time sequence consistency and causal consistency; the graph reasoning module is used for generating graph reasoning embedding based on the improved T-GNN model and outputting a question and answer result in combination with a question and answer generation model; and the feedback updating module is used for updating the context knowledge graph and the model parameters. According to the method, structured modeling and credibility closed-loop management of the question and answer reasoning process are realized.

The invention discloses a pipeline defect positioning method, device and equipment, a medium and a product. An SPPF-LSKA optimization instance segmentation model is combined with an ORB-SLAN3 framework, and dynamic feature points are eliminated by using information of an RGB-D depth map and an instance segmentation mask; secondly, a sliding window confidence evaluation mechanism is introduced, the credibility of feature points can be dynamically evaluated, wrong feature points generated due to instantaneous false detection are removed in time, and high-precision dynamic point removal is achieved; and finally, in a back-end optimization stage, a double-layer map strategy is adopted, a static mapping layer participates in BA optimization to reduce a positioning error, and a dynamic observation layer independently records an optical flow speed and a segmentation result of a dynamic region for dynamic interference analysis and does not participate in global optimization, so that interference of dynamic factors on positioning precision is avoided.

The invention discloses a vehicle target motion state estimation method based on an unmanned aerial vehicle video, and relates to the technical field of computer vision and intelligent monitoring, and the method comprises the steps: receiving a real-time video stream of an unmanned aerial vehicle, decoding the real-time video stream to obtain an original video frame, carrying out the graying, zooming and normalization preprocessing to obtain a processed image, and synchronously adjusting the size of a vehicle bounding box; vehicle targets are detected, a unique ID is allocated for multi-target tracking, and a motion trail is maintained; determining a background feature region, detecting and tracking feature points to estimate an inter-frame transformation matrix, and performing accumulative transformation to obtain a background overall transformation relation and a historical frame-to-current frame mapping mechanism; calculating a displacement residual error based on the trajectory and the mapping, judging direction consistency, estimating a smooth speed, and updating a motion confidence coefficient to judge a vehicle motion or static state and static duration; outputting the ID, the state, the static duration and the average speed of the vehicle; the method effectively eliminates the motion interference of the unmanned aerial vehicle, improves the estimation precision, is suitable for the traffic monitoring of the unmanned aerial vehicle, and is high in real-time performance and reliability.

The invention relates to the technical field of thermoelectric Internet of Things security, in particular to a thermoelectric Internet of Things terminal data credible situation awareness and protection platform, which comprises an integrated architecture for constructing a distributed probe acquisition layer, a behavior modeling and knowledge base, a dynamic trust evaluation engine, a situation awareness and decision center and a credible traceability module. Multi-dimensional trust evaluation is realized by fusing terminal behavior consistency analysis, service logic compliance verification and group behavior correlation detection, a self-adaptive weight adjustment mechanism is introduced to adapt to scene change, a hierarchical protection strategy is executed based on a dynamic credibility score, and non-interruption of network disconnection protection is guaranteed by relying on edge calculation. According to the method, the data credible sensing precision is improved, dynamic differential protection is realized, the operation and maintenance cost is reduced, multiple thermoelectric scenes are adapted, and a safety guarantee is provided for stable operation of a thermoelectric Internet of Things system.

The embodiment of the invention provides a three-dimensional model placing method, a three-dimensional model printing method and printing equipment. The three-dimensional model placing method comprises the steps that multiple three-dimensional models are obtained; obtaining at least a first interval needing to be kept in the horizontal direction of the model space and at least a second interval needing to be kept in the printing direction of the multiple three-dimensional models; performing first amplification in the horizontal direction based on the first spacing; performing second magnification in the printing direction and the opposite direction of the printing direction based on the second spacing; and determining the placement positions of the plurality of three-dimensional models in the model space based on the collision relationship of the plurality of amplified three-dimensional models. The model is amplified through the spacing parameter, so that placement and collision detection are performed based on the amplified three-dimensional model, arrangement in a three-dimensional space is realized, and the space utilization rate is improved. And independent interval parameters are set in the horizontal direction and the printing direction correspondingly, multi-dimensional differential interval regulation and control are achieved, and therefore the space utilization rate is increased, and interference of the supporting structure is avoided.

The invention discloses a lithium battery health condition multi-dimensional diagnosis method and system, and relates to the field of lithium battery health diagnos.The lithium battery health condition multi-dimensional diagnosis method comprises the steps that discrete charging data fragments are obtained from a vehicle management system, and intelligent reconstruction of a virtual incremental capacity analysis curve is conducted based on the fragments; a confidence map is synchronously generated to quantify the reliability of the reconstructed data. And then, key health features are extracted from the reconstruction curve, and adaptive weighting is performed on the features by using a confidence map, so that a comprehensive index vector capable of accurately reflecting the real aging state in the battery is generated. And finally, deep diagnosis is carried out based on the index vector, and multi-dimensional accurate diagnosis of the health condition of the battery is realized, so that a multi-dimensional evaluation report of the health condition of the battery is output. Therefore, the interference of poor data quality on the diagnosis precision under the real driving working condition can be effectively overcome, and the practical applicability and reliability of diagnosis are remarkably improved.

The invention discloses an ion trap mass spectrometry device and method capable of switching internal and external ion sources, and the device comprises an ion source cavity, the exterior of the ion source cavity is provided with a heating module, the side wall of the ion source cavity is provided with a sample introduction hole, and the sample introduction hole is internally provided with a chromatographic column I; the electron beam generation system is arranged at the front side position of the ion source cavity; the insulation connecting piece is communicated with the ion source cavity, and a lens I, a lens II and a lens III are sequentially arranged in the insulation connecting piece in the sample injection direction; a signal acquisition system; wherein a chromatographic column II is arranged on the ion trap. The two ionization modes inside and outside the trap are integrated, and different detection requirements can be flexibly met by switching the sample introduction path of the chromatographic column and regulating and controlling the voltage parameters of the lens I, the lens II and the lens III.

The utility model discloses an automatic balancing device and an aerial operation robot. The automatic balancing device comprises a connecting seat, a motor and a flying disc, wherein the connecting seat is used for being connected with a foot stool of the aerial operation robot; the motor is fixedly mounted on the connecting seat, the flying disc is fixedly connected with a rotating shaft of the motor, and the flying disc is used for rotating under the driving of the motor so as to provide power for balancing the aerial operation robot. The automatic balancing device is compact in structure and controllable in cost, is mounted on a foot stool of the aerial operation robot, and is used for resisting center-of-gravity shift caused by crosswind or movement on an overhead line, so that interference of the center-of-gravity shift on operation of the aerial operation robot on the overhead line is avoided; the walking stability and safety of the aerial operation robot on the overhead line are remarkably improved.

The application discloses a multi-modal wind turbine electromechanical transient modeling method based on artificial intelligence, relates to the technical field of new energy power generation modeling, and comprises the following steps: using a causal discovery algorithm to perform causal correlation mining and dependent path identification on a standardized space-time data cube, constructing a causal topology graph, and performing cross-modal feature fusion through a space-time graph attention network to generate a high-order feature tensor; dividing the high-order feature tensor into a meta-learning task pool according to different machine types and environmental conditions, and training a cross-machine type parameterization framework by using a double-layer optimization strategy; constructing a composite working condition generator based on the trained cross-machine type parameterization framework, and performing constraint through a causal regularization loss function to form an extended test working condition set; and using a multi-modal deep reinforcement learning algorithm to optimize control parameters of the extended test working condition set to obtain optimized control parameters. The application lays a foundation for realizing electromechanical transient modeling with high robustness and high generalization ability through accurate causal modeling and cross-modal fusion.

An automatic rope binding device comprises an annular rotating disc, a clamping jaw, a rope grabbing mechanism, a knotting mechanism, a rope pulling mechanism and a rope cutting mechanism, the annular rotating disc is installed on a rack, the rope grabbing mechanism is installed on the annular rotating disc, and the clamping jaw, the knotting mechanism and the rope cutting mechanism are all installed on the portion, located on the inner side of the annular rotating disc, of the rack; the rope cutting mechanism comprises a moving cylinder, a rope cutting cylinder and a pair of rope cutting scissors, the moving cylinder is mounted on the portion, located on the inner side of the annular rotary disc, of the rack and used for controlling the rope cutting cylinder to vertically move, and the rope cutting cylinder is used for controlling the rope cutting scissors to be opened and closed to cut the rope. According to the rope tying device, the rope cutting mechanism is arranged on the inner side of the annular rotating disc, interference between the rope grabbing mechanism and the rope cutting mechanism can be avoided, the working reliability of the rope tying device is improved, the rope grabbing reliability of the rope grabbing mechanism can be improved, meanwhile, a long end and a short end of a formed rope knot are easy to distinguish, and later operation is facilitated.

The invention provides an asphalt material softening point prediction modeling method based on an infrared spectrum, and belongs to the technical field of road engineering material performance prediction. The method comprises the following steps: collecting infrared spectrum data of a multi-source asphalt sample and carrying out standardization pretreatment; fusing and extracting functional group quantitative features, wavelet multi-scale features and principal component dimension reduction features; constructing a high-stability feature subset by adopting a progressive feature optimization strategy guided by a physical mechanism; a self-adaptive Stacking fusion model is constructed and trained, the model integrates four base learners including PLSR, SVR, random forest and gradient boosting regression, and Bayesian ridge regression is used as a meta-learner to realize uncertainty quantification of a prediction result. The method can quickly output the predicted value of the softening point without a physical test, solves the technical problems of low efficiency and poor consistency of a traditional method, and is suitable for production quality control, on-site quick detection and formula optimization of asphalt materials.

This invention relates to the field of force sensor technology, and more particularly to a pressure-balanced underwater six-dimensional force sensor sealing structure and method. It primarily addresses the problems of insufficient sealing pressure resistance and susceptibility to seawater leakage when existing six-dimensional force sensors are applied in underwater scenarios, and the fact that high underwater pressure can cause deformation of the main structure, interfering with strain measurement and leading to force signal deviation. The proposed technical solution includes a force sensor body, with a mounting plate installed at the output end of the force sensor body, and an elastic element disposed at and penetrated by the elastic element at the output end of the force sensor body; a sealing element disposed on the side of the force sensor body away from the elastic element, the sealing element being made of rigid or elastic material. The force sensor body, the elastic element, and the sealing element form a sealing structure that encloses the deformable beam and the PCB board. This invention can improve its underwater sealing pressure resistance and anti-interference capability, ensure force measurement accuracy, and assist underwater robots in precise operation.

The invention relates to the technical field of wearable intelligent equipment, and further relates to a method and device for determining the home position of a user and wearable intelligent equipment. The method comprises the following steps: when the wearable intelligent equipment is in an indoor environment, acquiring wireless signal data and multi-source sensing data; determining wireless signal feature data according to the wireless signal data, and determining a standing proportion, a charging behavior similarity and a position aggregation degree according to the multi-source sensing data; performing weighted summation on the wireless signal feature data, the standing proportion, the position aggregation degree and the charging behavior similarity; and when the weighted summation result is not less than the total threshold, determining that the target coordinate is the user home position. According to the method, the wireless signal data and the multi-source sensing data are effectively fused, the problem that a single judgment condition is prone to interference or misjudgment is avoided, the accuracy and reliability of user home position recognition are remarkably improved, a solid foundation is provided for subsequent intelligent services based on home scenes, and therefore the user experience is optimized.

The invention relates to the technical field of electric power, in particular to a power supply zero-sensing switching method and system based on phase real-time tracking, and the method comprises the following steps: collecting the communication connection state of each inverter node in a micro-grid group, constructing a communication topology model of the micro-grid group, and analyzing a sparse communication connection relationship among the nodes in the communication topology model, and generating a Laplacian matrix reflecting node connectivity according to the sparse communication connection relationship. According to the method, the system state can be comprehensively evaluated from the two dimensions of external alignment precision and internal stability, and misjudgment caused by a single index is avoided. Dual errors are input into a switching stability evaluation model to calculate a stability index, and a switching instruction is generated only when the index exceeds a grid-connected permission threshold value, so that quantitative decision and strict control of a grid-connected opportunity are realized, and the micro-grid and a main grid are highly synchronous in phase and frequency at the moment that a circuit breaker is closed; and transient impact and circulation at the switching-on moment are eliminated.

The application relates to the technical field of unmanned aerial vehicle mounting devices, in particular to a quick switching mounting device for multi-task loads of an unmanned aerial vehicle, which comprises an unmanned aerial vehicle, a connector arranged below the unmanned aerial vehicle, a connecting sleeve fixedly installed at the inner end of the unmanned aerial vehicle, a supporting sleeve slidably installed in the connecting sleeve, a plug box fixedly installed at the upper end of the connector, the plug box being inserted into the supporting sleeve and forming a plug-in cooperation structure with the supporting sleeve, and a locking device arranged between the plug box and the supporting sleeve. The quick switching mounting device for multi-task loads of the unmanned aerial vehicle is characterized in that the connecting sleeve and the supporting sleeve are slidably matched, the plug box and the supporting sleeve are connected in a plug-in mode, the connector can be quickly mounted and dismounted, the mounting device can keep a safe distance from the wing of the unmanned aerial vehicle in the mounting state through the adjusting action of the supporting sleeve on the connecting height, the interference of the mounting structure on the aerodynamic performance of the unmanned aerial vehicle is effectively avoided, and the flight stability is improved.

The application provides a traffic classification method and system based on federal semi-supervised learning. The method comprises the following steps: constructing an unlabeled traffic dataset and a labeled traffic dataset; a center server decomposes a global model into supervised learning parameters and unsupervised learning parameters and initializes the parameters; the parameters and an auxiliary agent are sent to each client; each client performs unsupervised training based on the supervised learning parameters, the unsupervised learning parameters and the auxiliary agent by using a local unlabeled traffic dataset, uploads the difference between the unsupervised learning parameters to the center server; the center server aggregates and updates each unsupervised learning parameter; supervised training is performed by using a local labeled traffic dataset, and the difference between the supervised learning parameters and the difference between the unsupervised learning parameters are sent to each client; a new auxiliary agent is obtained based on nearest neighbor search, and the new auxiliary agent is sent to each client when a set sending condition is met; the two steps are iteratively executed until a stop condition is met.

The utility model provides a kind of composite pipeline support structure, including support piece, support piece can be deformed along the length direction parallel to it, support piece includes support outer plate, connecting plate and support inner plate, the number of support inner plate is multiple, and it is interval setting along the length direction of support outer plate, and form the accommodation space for installing cladding between support outer plate, avoid the interference with clamp, so that cladding can realize larger area cladding on pipeline;Connecting plate is located the part between two support inner plates and is provided with notch;Support piece has first state and second state, in first state, support piece is flat type;In second state, the head of support outer plate is connected, to make support piece form closed structure compatible with different pipe diameter, shape pipeline;Limitation groove is set on support outer plate, for installing clamp, to realize the conversion of support piece from first state to second state and fixed closed structure, improve adaptability, flexibility and universality.

The application relates to the technical field of sports training and discloses an intelligent sensing and feedback personalized sports training guidance system, which comprises a dynamic interactive field sensing module, a data processing and analysis module, an immersive feedback module and a personalized model evolution module; the sensing module collects real-time interactive data through an intelligent training pad integrated with pressure and vibration sensors; the data processing and analysis module is internally provided with a predictive intention engine, which can evaluate a posture before a user action and trigger a feedforward early warning, and calculate an actual motion track of the user after the action, namely a fact path; the personalized model evolution module maintains a baseline model based on historical best performance of the user, and the data processing module calls the model to generate an idealized counterfactual path; the immersive feedback module presents an early warning signal on the training pad and synchronously visualizes playback of the fact path and the counterfactual path. The application realizes high self-adaptation and personalization of training guidance and significantly improves training efficiency.

The utility model discloses a kind of efficient paint mixing and stirring device, comprising: bearing frame, the surface of the bearing frame is fixedly connected with pull ring;Stirring assembly, one side of the stirring assembly is fixedly connected with bearing frame surface side, the stirring assembly is for the sufficient stirring mixing of paint;Vacuum component, one side of the vacuum component is communicated with the surface of stirring assembly, the utility model relates to stirring device technical field.The efficient paint mixing and stirring device, by the setting of vacuum component, by the setting of vacuum pump, the mixed bubble inside load barrel is directly vacuumized, effectively removes internal air, and the paint splashed in the process of vacuumizing is blocked and filtered using filter core, to avoid its random into suction duct, filter core bottom inverted cone, avoid paint adhering on filter core surface, spring can complete its push compact, pull handle rod can be pulled apart, convenient operation.

This application relates to the field of vehicle technology, disclosing a wiring harness fixing bracket, a B-pillar assembly, and a vehicle. The wiring harness fixing bracket includes a support plate and a mounting plate. The support plate supports the wiring harness and includes a first support plate and a second support plate connected together, forming an angle between them. The mounting plate is connected to one side of the second support plate in the width direction and extends along the width direction of the second support plate, also forming an angle with the second support plate. The wiring harness fixing bracket is connected to the vehicle body through the mounting plate. The wiring harness fixing bracket provided in this application includes a support plate and a mounting plate. The support plate includes a first support plate and a second support plate arranged at an angle. The support plate can guide the wiring harness to bend, thereby changing the direction of the wiring harness and allowing the wiring harness to be arranged in a narrow space. The mounting plate is connected to one side of the second support plate in the width direction, which facilitates the installation of the wiring harness fixing bracket and avoids interference with other components.

The utility model discloses an electromagnetic damping vibration isolation device belongs to vibration control technical field. The utility model solves the technical problem of the magnetic field intensity fixed of electromagnetic damping vibration isolation device and coil heating easily leads to performance attenuation. The utility model discloses an electromagnetic damping vibration isolation device, including coil subassembly and conductor block. Coil subassembly includes coil and coil clamp. Coil clamp is held in the outer periphery of coil. Coil clamp includes clamp body and water cooling pipeline. The heat dissipation block is equipped on the clamp body, and the heat dissipation block extends along the radial direction of coil, and multiple heat dissipation blocks are evenly arranged around coil. The water cooling pipeline is surrounded in the clamp body. The conductor block is located between at least two groups of coil subassembly, and the magnetic pole of every two groups of coil subassembly is opposite, thereby making the conductor block can be subjected to electromagnetic damping force when producing vibration. The utility model discloses a vibration isolation device can cover the vibration control demand of multiple frequency bands, avoids coil overheat aging, improves the life of vibration isolation device.

The utility model discloses a modularized pelvis fixator, relates to the technical field of medical instruments, and solves the problem that secondary injury is caused to a patient due to the fact that a connecting rod and a bone traction needle possibly interfere with each other when the number of operation parts is too large in the prior art. The main mounting seat is arranged on the outer trapezoidal supporting frame and used for mounting and locking the connecting rod, more straight line sections can be conveniently connected with the locking block through the outer trapezoidal supporting frame, meanwhile, the trapezoidal structure avoids shielding of an operation space in an operation, and better applicability is achieved; the outer trapezoid supporting frame has the advantages that the fixing rod scheme combination is more visual and convenient, meanwhile, the straight line section and the locking block can be connected more stably, the problem of unstable connection of the arc section is avoided, the inner rectangular supporting frame is adopted on the inner side, the inner operable space is larger, and operation in the operation is facilitated.

The invention provides a molecular probe targeting EDB-FN as well as a preparation method and application of the molecular probe. The structural formula of the molecular probe targeting EDB-FN is shown in the specification, according to the molecular probe targeting EDB-FN, the probe is based on a cyclic peptide probe with Lys-Glu side chain lactam bridge conformation fixed, the connection mode of a DOTA chelating agent is optimized, and the clinical transformation bottlenecks that an existing probe is poor in stability, low in affinity, insufficient in targeting specificity, poor in diagnosis and treatment integration compatibility and the like are solved. The probe can be used for early diagnosis and molecular imaging research of tumors, and provides a reliable basis for tumor malignancy degree evaluation and treatment effect monitoring.

The invention provides a laser radar three-dimensional target detection method based on a coarse-to-mental network, and the method comprises the steps: firstly constructing a coarse positioning network based on a Transform network structure, and enabling the coarse positioning network to be used for positioning an interval to which an effective echo pulse signal belongs in one-dimensional time; and a fine positioning network based on a coding-decoding structure is further designed, and pulse peak positioning with higher time resolution is carried out on a high signal-to-noise ratio signal interval extracted by the coarse positioning network. The coarse positioning network of the method can eliminate noise signal segments irrelevant to effective echo pulses to the maximum extent, so that the influence of noise on the fine positioning network is reduced, and the signal-to-noise ratio of echo data and the three-dimensional target detection precision of the system are improved.