56results about How to "Reliable assessment" patented technology

The invention relates to the technical field of intelligent evaluation and early warning methods, in particular to a nuclear radiation dose space distribution intelligent evaluation and early warning method and system, and the method comprises the following steps: obtaining multi-source monitoring data which comprises gamma radiation dose, alpha radiation dose and beta radiation dose measuring instrument data; performing fusion and enhancement processing on the multi-source monitoring data to obtain an enhanced radiation monitoring signal; based on the enhanced radiation monitoring signal, high-precision prediction of nuclear radiation dose spatial distribution is carried out through a deep probabilistic neural network model; according to the high-precision prediction result, in combination with a nuclear accident severity level standard, a radiation alert evaluation result and early warning information are generated, short-term radiation fluctuation can be captured, a long-term change trend can be identified, and the understanding ability of the system to a complex radiation field is greatly improved.

The invention provides an entropy-based muscle fatigue assessment method and application thereof, and particularly relates to the technical field of signal processing, and the method comprises the steps: firstly collecting a surface electromyogram (sEMG) signal, and carrying out the preprocessing; then, fractional calculus is combined with a fluctuation dispersion entropy (FDE) algorithm, and a multi-scale processing process is introduced, so that an RCMFFDE algorithm is innovatively proposed. Performing multi-scale analysis on the preprocessed sEMG signal by using the algorithm to generate a plurality of entropy curves; the entropy curve meeting the preset condition is selected as the final entropy curve, and the final entropy curve can accurately reflect the muscle fatigue state. According to the method, the muscle fatigue degree can be effectively and reliably evaluated, and the method has important kinematics and medical significance for preventing human body muscle diseases and sports injuries.

The invention discloses a mobile phone data line detection and analysis system, which relates to the technical field of data line detection and is characterized in that a suitable high-speed transmission test environment is created for a data line through a test environment construction module, and signal quality is monitored by equipment such as an oscilloscope and a signal analyzer; the data monitoring module detects a signal transmission bit error rate amplification index and a delay fluctuation index in real time in an environment with or without electromagnetic interference; the data analysis module converts the detection data into a comprehensive feature vector and inputs the comprehensive feature vector into a machine learning model to generate a signal quality index; the comparative analysis module compares the signal quality index with a set threshold value and divides the quality of the data line; and the optimization module predicts the abnormal degree of the low-quality data line, and if the abnormal degree is serious, optimization measures are taken, so that the anti-interference performance of the data line is effectively improved, the error rate and delay fluctuation in the data transmission process are remarkably reduced, and reliable communication and data integrity between equipment are ensured.

The invention discloses a method for evaluating the quality of a metal part, which comprises the following steps of: determining the laser type according to the characteristics of the metal part, obtaining various laser parameters for evaluating the quality of the metal part through an experimental method, and performing laser irradiation by adopting the accurately controlled laser parameters. In combination with real-time monitoring and regulation of instruments such as a power meter, a spectrograph, a roughmeter and an optical microscope, a laser parameter-grain boundary definition data set is formed, and finally a quality evaluation model is established to realize accurate evaluation of the quality of the metal parts. According to the method, the quality of the metal parts can be evaluated quickly and economically.

The invention discloses a model library-based spaceflight radio frequency signal quality multi-domain evaluation and compensation method, and belongs to the technical field of wireless communication. The implementation method comprises the steps of determining signal system parameters based on various CCSDS standards and a spaceflight protocol system, extracting related parameters of spaceflight standards in a time-frequency domain, generating standard time-frequency domain radio frequency signals, converting the standard time-frequency domain radio frequency signals into a related domain, a modulation domain, an energy domain and a polarization domain, and establishing spaceflight radio frequency signal sub-model libraries of the domains; obtaining a time-frequency domain measured signal through a receiver, integrating time domain information and frequency domain information, and constructing a time-frequency domain sub-evaluation model; constructing a multi-domain comprehensive evaluation model by adopting a parallel data transmission mode and a weight data processing method; calculating the weight of the evaluation result of each domain through an entropy weight method, and obtaining a comprehensive quality evaluation result of the spacecraft radio frequency signal; and based on the distortion coefficient, a robust signal equalization algorithm is adopted to process the signal, the influence of the distortion effect on the signal quality is compensated, and the robustness and the anti-interference capability of signal transmission are improved.

The invention discloses a listed company risk assessment method based on cross validation and Bayesian optimization, and the method comprises the following steps: 1, obtaining the comprehensive factor data of a listed company, carrying out the dimension reduction of the factor data through employing a principal component analysis method, obtaining a principal component factor, carrying out the effectiveness verification of the principal component factor through an IC and IR analysis method, and carrying out the calculation of the risk of the listed company; selecting a plurality of principal component factors as input features; 2, on the basis of the multi-factor model, constructing an ensemble learning index enhancement model by taking a decision tree and an AdaBoost algorithm as cores; 3, performing system optimization on parameters of the ensemble learning index enhancement model by adopting cross validation and a Bayesian method, and finally determining an optimal parameter combination to obtain a trained ensemble learning index enhancement model; and 4, evaluating the risk of the listed company by using the trained integrated learning index enhancement model. According to the method, the calculation resource consumption of the model can be reduced, the calculation efficiency is improved, and the over-fitting risk of the model can be reduced.

The invention discloses a brain-computer interface system based on audio-visual matching error monitoring, which is characterized in that: according to EEG data obtained by three feedback paradigms of audio-visual matching errors, important ERP components related to the audio-visual matching errors are extracted by applying ERP analysis, so that neural responses in a specific time window are interpreted; then, on the basis of time-frequency analysis, dynamic changes of the electroencephalogram signals in different wave bands are captured, and the reliability and stability of the electroencephalogram activity in different feedback modes are revealed by combining ITPC of the electroencephalogram activity; and finally, through an improved EEGNet model, automatic feature extraction and efficient classification of the signals are realized, and the robustness and generalization ability of the system are improved. The electroencephalogram signals have high nonlinearity and specificity, by combining ERP analysis, time-frequency analysis and a deep learning model, potential neural mechanisms of audio-visual matching errors can be more effectively understood, the performance of a brain-computer interface system is improved, and the method is applied to clinical research of error processing related obstacles.

The invention discloses a network security situation prediction method and system, and relates to the technical field of network security situation assessment. The network security situation prediction method comprises the following steps: continuously obtaining network equipment operation data of a plurality of network operation time periods when network equipment operates, and carrying out preprocessing analysis to obtain a network internal stability index and a network external threat index of each network operation time period when the network equipment operates; according to the method and the device, the data of the plurality of network operation time periods during the operation of the network equipment is preprocessed and analyzed, the internal stability and external threat factors of the network are comprehensively evaluated, so that the network security index is generated, and the network security index of each network operation time period can accurately reflect the security state of the current network; according to the method, the change rate of the network security index is analyzed, the security index of the next time period is predicted, the monitoring accuracy of the network security situation can be effectively improved, potential network risks are found in time, and corresponding protection measures are taken.

The invention belongs to the technical field of space planning, and particularly relates to a land space planning evaluation method based on deep learning, and the method comprises the steps: constructing a scene graph structure, generating an initial scene graph, updating the scene graph through an iteration planner, recording and feeding back, and enabling the scene graph structure to visually present the relation between planning objects. The complex territorial space layout can be conveniently analyzed; the method comprises the steps of extracting physical characteristics of a current scene graph, deploying a planning evaluation model to generate label distribution, determining evaluation indexes to calculate spatial planning loss, optimizing the planning evaluation model, deeply mining current scene graph information, facilitating accurate grasping of relation characteristics between objects, providing accurate evaluation for spatial planning, comprehensively considering planning constraints, and improving the planning efficiency. Reliable decision support is provided; a dynamic updating mechanism is adopted to discover a space planning problem in time, and rationality and feasibility of space planning are improved.

The invention relates to the technical field of modifiers, in particular to a plant shell powder modifier and a preparation method thereof.The preparation method includes the steps that walnut shell powder, phenolic compounds and amine compounds are added into a stirrer with a temperature control jacket, stirred to be uniform and dried in vacuum, and performance characterization parameters of the plant shell powder modifier are calculated to obtain the plant shell powder modifier. According to the method, the phenolic compound and the amine compound are added into the walnut shell powder to modify the walnut shell powder, the compatibility between the modified plant shell powder modifier and rubber is improved, the dispersing performance is improved, the process is simple, the cost is low, and the method is suitable for industrial production. The performance of the plant shell powder modifier and the performance of a rubber product prepared by adding the plant shell powder modifier are evaluated, and whether the performance of the plant shell powder modifier meets the standard or not can be reliably evaluated.

The invention relates to an eye biomechanical characteristic evaluation method based on a dynamic Scheimpflug imaging technology. The method comprises the following steps: capturing a dynamic deformation video of a cornea through a Scheimpflug camera; performing eye biomechanical characteristic evaluation on the dynamic deformation video through the evaluation model; wherein a training sample of the training evaluation model comprises sample cornea data; the sample cornea data comprises sample video data and sample measurement data which are simultaneously measured in the process of pressing the cornea of the user; sample video data are captured through a high-speed Scheimpflug camera, and sample measurement data are obtained through a cornea ultrasonic biomechanical system. The evaluation model adopted in the method is obtained through training based on sample video data captured by a Scheimpflug camera and sample measurement data obtained through a cornea ultrasonic biomechanical system, and the eye biomechanical characteristics can be evaluated more accurately and reliably.

The invention relates to a circuit breaker operation state online monitoring device and method based on distribution automation, the device comprises a sensor and conditioning circuit, an A / D conversion and micro-processing module and a processor, the sensor and conditioning circuit comprises a sensor and a signal conditioning circuit connected with the output end of the sensor; the A / D conversion and micro-processing module comprises an analog-to-digital conversion module and a micro-processing module which are connected with the output end of the signal conditioning circuit; the sensors comprise a displacement sensor, an acceleration sensor, a Hall current sensor and a pressure sensor; the system has the advantages of efficient online monitoring, remote online monitoring, accurate and reliable evaluation and high precision.

The invention provides a chicken behavior statistical method, system and device and a storage medium, and relates to the technical field of chicken breeding, and the method comprises the steps: obtaining to-be-analyzed image data; the to-be-analyzed image data are input into a preset target recognition model, chicken detection data are obtained, and the chicken detection data reflect chickens detected in the images; inputting the chicken detection data into a preset behavior recognition model to obtain chicken behavior data; according to the chicken behavior data, behavior statistical data is generated, and the behavior statistical data reflects the occurrence probability of each behavior type. Chicken recognition and behavior recognition are carried out on the image, manual observation is not needed, the behavior type of the chicken can be automatically obtained, the judgment standard unification of the behavior type is facilitated, the data error is reduced, the data stability is improved, statistics is carried out according to the behavior type of the chicken, the occurrence probability of each behavior type is obtained, and the efficiency is improved. And the comfort of chicken breeding can be evaluated more accurately and reliably.

The invention relates to the technical field of vehicle testing, in particular to a testing method for an automobile accelerator pedal misuse suppression system, which comprises the following steps of: establishing an accelerator pedal misapplication accident data set according to a traffic accident depth survey database; according to the established accelerator pedal misuse accident data set, automatically extracting corresponding test parameters when the accelerator pedal is misused; according to the extracted test parameters, significant correlation analysis is carried out on the test parameters, key parameters corresponding to the severity of the accident affecting the mistaken stepping of the accelerator pedal are matched, and a corresponding test matrix is designed; according to the parameters corresponding to the different test matrixes, on the basis of a preset test strategy of the automobile accelerator pedal misuse suppression system, executing the test strategy on the test vehicle, and outputting a corresponding test result; and according to the output test result, comprehensively analyzing the test result, and outputting a final analysis result.

The invention discloses an anti-demagnetization protection system and method for motor control. The method comprises the following steps: acquiring counter electromotive force of a motor winding and real-time counter electromotive force of each phase of winding of a motor under a fault-free condition; respectively subtracting the counter electromotive force of the motor winding under the fault-free condition from the real-time counter electromotive force of each phase winding of the motor to obtain the maximum difference value of the real-time counter electromotive force of the phase windings of the motor; and comparing the maximum difference value of the real-time counter electromotive force of the motor phase winding with a demagnetization fault threshold value to judge whether the motor is in a demagnetization fault, if the motor is not in the demagnetization fault state, the motor operates normally, and if the motor is in the demagnetization fault state, demagnetization protection is carried out. According to the invention, real-time on-line and high-sensitivity effective evaluation and identification can be carried out on the demagnetization fault degree and the fault mode of the motor.

The invention relates to the technical field of CO2 burying and storing amount calculation, in particular to an exhausted condensate gas reservoir CO2 structure burying and storing amount calculation method and device, electronic equipment, a storage medium and a computer product. The method comprises the following steps: constructing a depleted condensate gas reservoir CO2 buried substance balance equation; deducing the depleted condensate gas reservoir CO2 burying material balance equation, and constructing a depleted condensate gas reservoir CO2 structure burying amount calculation model; based on the depleted condensate gas reservoir CO2 structure burying stock calculation model, the depleted condensate gas reservoir CO2 structure burying stock is obtained. According to the method, the change of a mixed gas deviation factor after CO2 injection, the change of the saturation degree of residual stratum condensate oil in the CO2 injection process and the influence of deformation of rocks and bound water are considered. The calculation result of an example shows that the CO2 structure burying amount under different burying pressures in the new method is basically matched with the calculation result of a numerical simulation method, and the error is kept within 6.42%.

The application discloses a kind of beam bridge girder static load deflection prediction methods based on improved AVOA-GRNN network, comprising:1, establish vehicle bridge finite element model and add vehicle bridge uncertainty simulation bridge dynamic static load test, collect dynamic static load test data;2, the above data is selected using the characteristic of pearson linear correlation coefficient;3, using dynamic static load experimental data training GRNN neural network model, and construct the parameter of improved African vulture algorithm optimization GRNN, obtain the corresponding smooth factor when average absolute error is minimum;4, the dynamic load test data of prediction set is substituted into improved AVOA-GRNN network model and carries out static load deflection prediction.The application can use beam bridge girder dynamic load test data to predict corresponding static load deflection, so as to effectively solve the problems, such as high cost of predicting beam bridge static load test, great influence on traffic and easily causing damage to bridge structure.

The invention discloses an integrated sediment methanogenesis anaerobic culture bottle, and relates to the field of microorganism culture and detection.The integrated sediment methanogenesis anaerobic culture bottle comprises a bottle body and an integrated bottle cap assembly, the integrated bottle cap assembly comprises a main cap body, a barometer, an integrated guide pipe and a sampling one-way valve, the main cap body is in sealed connection with a bottle opening of the bottle body, and the integrated guide pipe is connected with the sampling one-way valve; the barometer is installed on the main cover body, a pressure sensing probe of the barometer is communicated with a headspace in a bottle, one end of the integrated guide pipe is communicated with the headspace in the bottle, and the other end of the integrated guide pipe penetrates through the main cover body to be connected with the sampling one-way valve. The integrated sediment methanogenesis anaerobic culture bottle provided by the invention has the functions of air pressure monitoring, lossless gas taking and convenient sampling, and the accuracy, convenience and data output quality of a sediment methanogenesis long-term culture experiment are remarkably improved.

This invention discloses a method and apparatus for accurate bridge damage identification and location based on multi-source data fusion. The method includes: performing spatiotemporal registration and data fusion on the time-series data of the bridge's global planar deformation obtained by ground-based synthetic aperture radar and the time-series data of the bridge's point-like three-dimensional deformation obtained by the BeiDou satellite navigation system to obtain a fused deformation field of the entire bridge area; calculating multiple damage characteristic indicators reflecting different deformation physical mechanisms of the bridge based on the fused deformation field, and determining the corresponding preliminary damage level based on the damage judgment threshold of each damage characteristic indicator; using the preliminary damage levels of each damage characteristic indicator as independent evidence sources, performing evidence fusion to resolve indicator conflicts, and determining the bridge damage location and damage level based on the fusion result. This method can effectively improve the accuracy and reliability of bridge damage identification and location, providing a scientific basis for bridge operation and maintenance decisions.

The invention discloses a power distribution network system bearing capacity evaluation method and device, a medium and equipment, and the method comprises the steps: calculating first index values of a plurality of evaluation indexes at the same sampling moment based on a target access scheme of a to-be-accessed new energy system in a target power distribution network system; based on the first index value of each evaluation index, performing fuzzy judgment on the importance degree of any two evaluation indexes, and determining a target subjective weight of each evaluation index; for the evaluation dimension to which each evaluation index belongs, performing fuzzy judgment on the importance degree of any two evaluation dimensions, and determining a target subjective weight of each evaluation dimension; and determining a score of the target access scheme at least based on the target subjective weight of each evaluation index, the target subjective weight of the evaluation dimension to which each evaluation index belongs and the first index value of each evaluation index, so as to obtain an evaluation result of the bearing capacity of the target power distribution network system. According to the invention, the bearing capacity of the power distribution network system can be accurately evaluated.

The present invention relates to the field of data analysis technology, and in particular, to a Taihu Lake cyanobacteria bloom early warning system based on multi-factor analysis and time lag strategy. It includes a data collection and monitoring unit for monitoring and collecting data from various lake areas of Taihu Lake; a data analysis unit determines the key driving factors and time lag response mechanism and lag duration of the cyanobacteria bloom outbreak, and constructs a cyanobacteria bloom outbreak prediction model for different lake areas of Taihu Lake based on the key driving factors and time lag response mechanism of the cyanobacteria bloom outbreak; a risk assessment and early warning unit uses the cyanobacteria bloom characterization parameter results predicted by the cyanobacteria bloom outbreak prediction model to obtain the future cyanobacteria bloom risk. The system can identify the key factors that directly affect the growth of cyanobacteria, and reveal the mechanism of action of those indirect influencing factors. At the same time, it can evaluate the immediate impact of potential variables on the occurrence of cyanobacteria blooms, capture their cumulative effects at different time points, and provide more accurate information for the early warning system.

This invention provides a method and apparatus for evaluating software bill of materials (SBOM) generation tools, relating to the field of computer technology. The method includes: inputting a pre-selected target software project into a SBOM generation tool to be tested, obtaining an original SBOM file output by the tool; performing standardized parsing on the original SBOM file to obtain a corresponding standard SBOM file; performing multi-dimensional evaluation on the standard SBOM file to obtain an evaluation score; the evaluation score includes a field compliance score, a package-level consistency score, and a field-level consistency score; and obtaining an evaluation result for the SBOM generation tool based on the evaluation score. The software bill of materials (SBOM) generation tool evaluation method provided by this invention, by integrating multi-dimensional scores to generate a final evaluation result, achieves an accurate and reliable evaluation of the SBOM generation tool.

The invention relates to the field of paint testing, in particular to a method for testing the cleaning resistance of a marine antifouling coating. According to the test method, experimental equipment is provided, and the experimental equipment comprises a sample plate for coating a coating, a groove body for accommodating the sample plate, a brush disc, a driving device for driving the brush disc to rotate and move up and down, and a control system electrically connected with the driving device. According to the testing method, the cleaning resistance of the antifouling coating is reliably evaluated by matching the steps of artificial seawater soaking experiment, underwater cleaning experiment, coating detection, coating loss grade evaluation and the like. According to the scheme, the cleaning resistance of the anti-fouling coating can be efficiently and reliably evaluated indoors within a short time, scientific data support is provided for research and development of the anti-fouling coating, and the period from laboratory development to practical application of an anti-fouling coating system is shortened.

The utility model discloses an air flotation test device for solid-liquid separation of biogas slurry, which relates to the technical field of anaerobic fermentation product treatment and comprises an air flotation tank, a water collecting tank, a residue collecting tank, a residue scraping mechanism, a reflux pump, a bubble machine and a bubble water releaser, the water collecting tank is communicated with the air flotation tank, and the water collecting tank can receive residue-removed biogas slurry in the air flotation tank; the bubble water releaser is fixedly arranged in the treated biogas slurry in the air flotation tank and can fill bubble water into the treated biogas slurry, a liquid inlet of the reflux pump is communicated with the water collecting tank, a liquid outlet of the reflux pump is communicated with a liquid inlet of the bubble machine, a liquid outlet of the bubble machine is communicated with the bubble water releaser, and the bubble water releaser is communicated with the water collecting tank. The slag collecting tank is fixedly arranged at the top of the inner side wall of the air floatation tank, the slag scraping mechanism is arranged above the air floatation tank, and the slag scraping mechanism can scrape biogas residues on the liquid level of treated biogas slurry in the air floatation tank into the slag collecting tank; according to the utility model, reliable evaluation and pre-estimation can be provided for the actual removal effect of the biogas residue in the biogas slurry doped with the biogas residue by the air flotation equipment.

The invention discloses a power transmission line sag evaluation method and system based on a point cloud data simulation trajectory, and relates to the technical field of conductor sag safety, and the method comprises the steps: S1, obtaining initial point cloud data of a power transmission line region, and carrying out the preprocessing of the initial point cloud data to obtain first point cloud data; s2, establishing an initial meteorological model based on the first point cloud data and an initial meteorological condition, distributing point cloud meteorological attributes, and obtaining second point cloud data; s3, simulating a plurality of meteorological combinations according to a current meteorological condition in combination with historical meteorological data, simulating a spatial form of the power line in the second point cloud data converted from a static point cloud to a dynamic environment, and obtaining third point cloud data; s4, simulating a lead track change state based on the third point cloud data to determine feature changes of the lead under different meteorological conditions, and obtaining fourth point cloud data; and S5, calculating a conductor sag evaluation value based on the fourth point cloud data, and comprehensively evaluating a conductor sag safety state. And the comprehensiveness and the reliability of the safety performance analysis of the conductor sag under the complex environment condition are obviously improved.

The application provides a multifunctional testing device for simulating a real use scene of a paper diaper, and relates to the technical field of paper diaper performance detection. The multifunctional testing device comprises a base, a large arm connected to the base, a first rotating component arranged on the large arm, a small arm rotatably connected to the large arm through the first rotating component, a turning flange connected to the small arm, a second rotating component arranged on the turning flange, a baby posture simulation model connected to the output end of the second rotating component, a liquid simulation unit in communication with the baby posture simulation model through a liquid pipeline, a temperature control unit connected to the liquid simulation unit, a gas simulation unit arranged in the baby posture simulation model and used for outputting gas, a sensing unit arranged on the surface and / or inside of the baby posture simulation model, and a control unit electrically connected to the first rotating component, the second rotating component, the liquid simulation unit, the temperature control unit, the gas simulation unit and the sensing unit respectively.

The invention relates to a method for operating a brake system (1) of a motor vehicle, comprising a service brake device (2) having at least one wheel brake (3), which brake system adjusts a brake pressure applied to the wheel brake (3) at least in short time as a function of the setting of an operating element, the brake pressure is used to generate a brake force acting on a brake disc (4) of the wheel brake (3). According to the invention, the state of the coating (6) of the brake disc (4) of the wheel brake (3) is determined on the basis of the brake pressure present on the wheel brake (3) and the deceleration of the motor vehicle caused by said brake pressure. The invention also relates to a brake system (1) for a motor vehicle and to a computer program product.

The invention provides an aircraft performance evaluation model construction and evaluation method based on arm angle influence, and the method comprises the steps: building a traditional flight mechanical model based on a power unit model, a control efficiency model, a rigid body dynamic model and a rigid body kinematic model, and obtaining various aerodynamic parameters of an aircraft arm at different angles through CFD simulation; the method comprises the following steps: constructing aerodynamic relation models at different angles, embedding the aerodynamic relation models into a traditional flight mechanical model to obtain a flight mechanical model based on arm angle influence, and constructing a flight performance simulation evaluation model based on a power unit model, a control efficiency model and the aerodynamic relation models. According to the method, more reliable aircraft scheme evaluation and higher-precision flight performance calculation are realized. The construction of a flight performance model fusing the influence of the external parameters of the aircraft also has expansibility, and the flight performance model can be embedded into an influence model of other appearance parameters and is used for evaluating the flight performance of multi-rotor aircrafts of different configurations.

This invention relates to the field of power equipment technology, and more particularly to an intelligent monitoring method for the operating status of charging cables. The method includes: conducting a torsion test on a sample of the charging cable to obtain its structural stability; determining the distribution of monitoring points to implement a monitoring strategy for the operating parameters of the charging cable; acquiring fluctuations in current, voltage, and resistance at several monitoring points during operation to determine if the fluctuations are abnormal; determining an anomaly index based on the average of several historical fluctuation data that could cause abnormal charging temperatures; determining a temperature monitoring mode for the charging cable based on the anomaly index and establishing a correlation prediction model for the charging cable temperature; adjusting the distribution of monitoring points based on the historical accuracy of the temperature prediction model; and determining an optimization strategy for the temperature monitoring mode based on the changes in the adjusted accuracy. This invention solves the problem of inaccurate temperature monitoring of charging cables.

The present invention belongs to the technical field of forest point cloud segmentation, and discloses a method and system for three-dimensional point cloud tree structure segmentation based on deep learning, obtains a data set of forest point cloud data, and divides it into a training set, a validation set, and a test set according to a certain ratio; uses a multi-scale sampling method to sample the data set and establish a projection, and the sampled data constitutes a new data set; configures a network operating environment, and uses the training set and validation set in the new data set to train the network; the test set uses the trained network for prediction, and uses the projection information to project the label of the data set into the original point cloud, visualizes the results, and realizes the tree structure segmentation of the entire point cloud. The present invention can realize the seamless integration of data collection and point cloud segmentation; has an excellent recognition effect on tree branch points, and the recognition coverage is far ahead; can not only recognize the primary branches, but also the secondary branches.