149results about How to "Avoid blindness" patented technology

The invention discloses a Fluent-based numerical simulation and experimental design method for shaking of liquid in a tank of a tank truck, and belongs to the technical field of numerical simulation of fluid dynamics (CFD). The method includes the steps that the hole opening position of the wave-proof plate serves as an independent variable, multiple hole opening position schemes are designed, liquid shaking related indexes are determined to serve as dependent variables, a geometric model is established according to the actual structure of a tank truck tank body, a fluid mechanics model and boundary conditions are set, a solver is configured, output parameters and numerical simulation initial values are set, and an experiment is executed. The liquid shaking process of a certain swash plate trepanning scheme is simulated, acting force data, namely shaking index data, between liquid shaking and the inner wall of the tank body is recorded, the advantages and disadvantages of each trepanning position scheme are evaluated based on the shaking index data, and the optimal scheme is determined. According to the method, a real object experiment is replaced by CFD numerical simulation, parameter setting is carried out, the experiment cost and the experiment risk are remarkably reduced, the experiment efficiency is improved, and data support can be provided for industry design.

The invention provides a diabetic patient life management method and system in combination with traditional Chinese medicine knowledge, and relates to the field of medical health data processing, the method comprises the following steps: obtaining multiple groups of sample data, the sample data at least comprising personal information of sample patients and diabetic traditional Chinese medicine syndromes, and the personal information of the sample patients at least comprising diabetes index data; based on the multiple groups of sample data, multiple key traditional Chinese medicine syndrome discrimination units are determined, and a diabetes traditional Chinese medicine syndrome diagnosis scale is generated; based on the multiple groups of sample data, determining music types matched with different diabetes mellitus traditional Chinese medicine syndromes; determining the diabetic traditional Chinese medicine syndrome of the current user based on the personal information of the current user and the filling information of the diabetic traditional Chinese medicine syndrome diagnosis scale; based on the diabetic traditional Chinese medicine syndromes of the current user and the music types matched with different diabetic traditional Chinese medicine syndromes, music, traditional Chinese medicine health maintenance skills and traditional Chinese medicine recipes are recommended, and the method has the advantage of improving the quality of life management of diabetic patients.

The invention provides a cooperative path planning method for searching and tracking an underwater target by a multi-USV unmanned cluster, and the method comprises the steps: introducing a pose-control quantity-time to carry out the three-dimensional double-chain coding of a population in an improved genetic algorithm, enabling a control instruction and an accurate execution timestamp to serve as a genetic gene, and enabling the control instruction and the precise execution timestamp to serve as a genetic gene in the crossover and mutation operation, timestamps, control quantities and poses are transmitted synchronously, and it is ensured that offspring individuals can inherit an excellent cooperation mode of a parent; during population initialization, USV is guided to preferentially cover a high-value region through region division and weighted Gaussian distribution, so that blindness caused by random initialization of a traditional genetic algorithm is overcome, and invalid search is avoided; a target for avoiding secondary search is designed in a fitness function, and repeated access to recently searched areas is quantified by introducing a concept of confidence time intervals, so that an algorithm actively explores unexplored water areas, waste of search resources is avoided, and accuracy and planning efficiency of multi-USV collaborative path planning are improved.

The application discloses a sludge biological drying multi-target proteinase regulation method based on bacterial chemotaxis, relates to the technical field of sludge resource disposal, and comprises the following steps: S1, constructing a microfluidic detection system based on the chemotaxis of thermophilic bacteria, and monitoring and quantifying the metabolic preference degree of the thermophilic bacteria to different amino acids in a sludge biological drying process; S2, selecting and proportioning proteinases with a targeted degradation function according to the metabolic preference degree of the thermophilic bacteria; and S3, decomposing refractory proteins into specific amino acids preferred by the thermophilic bacteria through multi-target regulation of the proteinases. The application optimizes the metabolic environment of the thermophilic bacteria to improve the utilization rate of protein organic matter and accelerate the sludge biological drying process.

The invention relates to the technical field of data processing, and particularly provides a manufacturing industry energy-saving and efficiency-increasing scheme generation method, system and equipment and a storage medium, and the method comprises the steps: collecting the operation state data, energy consumption data and real-time working condition data of industrial equipment in real time through an equipment monitoring module; preprocessing the collected data, establishing an energy efficiency reference, calculating a key energy efficiency index based on the energy efficiency reference to judge the energy efficiency state of the equipment, and executing multi-dimensional root cause analysis when the energy efficiency state is abnormal; according to the energy efficiency state and a root cause analysis result, matching and filtering applicable technical schemes from a technical unit library, and performing quantitative evaluation and comprehensive sorting on the technical schemes to generate a preferential transformation scheme list; and an energy efficiency analysis result is fed back to the equipment monitoring module for state early warning, and a customized proposal is generated based on the transformation scheme. According to the invention, the systematization and automation of industrial energy-saving management are realized by constructing a full-link closed loop generated by data perception, intelligent diagnosis and decision.

The application relates to the technical field of teaching instruments, and discloses an interactive teaching instrument and a use method thereof, which comprise a supporting assembly, the top of the supporting assembly is provided with a fixing assembly, the top of the fixing assembly is provided with an adjusting assembly, one side of the adjusting assembly is provided with a display assembly, the display assembly is provided with a light-shielding assembly, the supporting assembly comprises a base, pressure sensors are arranged at the lower ends of the four corners of the base, the fixing assembly comprises a fixing plate, the adjusting assembly comprises a rotating motor arranged at the bottom of the fixing plate, the application can flexibly adjust the angle position, effectively reduce the reflection, avoid affecting the teaching effect, actively remove dust from the display component, improve the display definition, timely intervene when the whole is in an unstable state, improve the stability of the whole, effectively protect the display component when the whole is tilted, and prevent the display component from being damaged.

The invention relates to the technical field of unmanned aerial vehicle control, and discloses an unmanned aerial vehicle target classification matching strike control method and system based on deep learning, and the method comprises the following steps: S1, collecting the original environment data of an unmanned aerial vehicle flight region, carrying out the preprocessing of the original environment data, and generating multi-mode perception data; and S2, inputting the multi-modal sensing data into a pre-constructed deep learning classification network, extracting multi-level depth features of the target through the deep learning classification network, carrying out classification identification on the target based on the multi-level depth features, and outputting target category information and target position information of the target. The multi-modal sensing data is input into the deep learning classification network for target recognition, the multi-modal fusion sensing mode can give full play to the complementary advantages of different sensors, high target recognition accuracy can still be kept in complex environments such as night, low illumination and severe weather, and the adaptive capacity of the system to environment changes is remarkably improved.

This invention relates to the field of ultra-high performance concrete (UHVPC) curing technology, and more particularly to an intelligent temperature-controlled curing method for UHVPC. The method includes the following steps: generating preliminary temperature-controlled curing data for concrete based on UHVPC mix proportion parameters and temperature-controlled curing requirements data; analyzing the distributed temperature field characteristics of the pouring nodes using UHVPC pouring node data to generate distributed temperature field characteristic data for the pouring nodes; analyzing the temperature evolution and hydration state of the pouring node temperature field based on the distributed temperature field characteristic data and the preliminary temperature-controlled curing data to generate temperature evolution and hydration regulation state data; and performing dynamic temperature-controlled curing analysis on the preliminary temperature-controlled curing data to generate dynamic temperature-controlled curing data for the concrete. This invention achieves intelligent temperature-controlled curing by combining the application of UHVPC.

This application discloses a method for calculating the vibration isolation of ship vibration isolation devices based on isolator type spectrum data, relating to the field of ship vibration isolation design. The method includes: acquiring the type spectrum data and impedance test data of the target isolator; determining the stiffness and damping parameters of the target isolator based on the type spectrum data and impedance test data; constructing a finite element model of the ship vibration isolation device; inputting the stiffness and damping parameters of the target isolator into the finite element model for calculation, and obtaining the vibration isolation calculation results of the target isolator. This method can efficiently utilize isolator type spectrum data to conduct vibration isolation calculation and evaluation of ship vibration isolation devices during the ship design phase, avoiding resonance between the natural frequency of the vibration isolation device and the excitation frequency of the equipment, and improving the vibration isolation effect.

This invention provides a method for assessing the capacity value of wind farm clusters based on the Johnson distribution system. The method comprises the following steps: Step 1: Establishing a wind farm cluster fluctuation model through power output analysis using a first-order Markov chain algorithm; Step 2: Establishing relevant models for different wind farm clusters through time-series power output analysis using the Johnson distribution system; Step 3: Conducting a reliability assessment of the power system based on the given load level and wind farm capacity, according to the power adequacy index; Step 4: Using a bisection method to adjust the load of the wind farm system to search for the reliable capacity of the wind farm cluster. This invention is designed for large-scale wind turbine integration into the power system and can scientifically and accurately assess its capacity value.

The invention discloses a lithology identification method based on a neural network, and the method comprises the steps: obtaining a logging curve, recognizing a missing value in the logging curve, taking the parameter data in the logging curve as sequence data, inputting the sequence data into an established neural network model, carrying out the prediction through the neural network model, obtaining the complementation data corresponding to the missing value, and obtaining the lithology of the logging curve. Filling missing values in the logging curve by using the completion data to obtain a complete logging data set, namely a first data set; based on the first data set, performing equalization processing on lithology classification samples in the first data set to obtain an equalization logging data set, namely a second data set; a whale optimization algorithm is adopted to optimize hyper-parameters of the classification model, target hyper-parameter configuration is obtained, and the classification model is configured; and inputting the second data set into the classification model, and identifying and outputting the lithology category. The method is high in missing value filling precision, excellent in sample equalization effect, remarkable in model performance optimization and high in system practicability.

Aiming at the problems of inaccurate sediment monitoring, extensive sludge discharge control, low dosing accuracy and the like of the traditional sedimentation tank, the invention provides a visual monitoring and model-driven sediment prediction and sludge discharge control method and system for a sedimentation tank. The method comprises the following steps: visual monitoring: collecting images of a sedimentation tank through an underwater camera device, identifying interface characteristics of bottom mud, and constructing a bottom mud thickness distribution thermodynamic diagram in combination with an inverse distance weighted interpolation method; parameter acquisition: acquiring operation parameters such as water inlet flow, raw water turbidity, pH value and the like in real time; model-driven prediction: establishing a BP neural network model coupled with multiple variables, a mud yield model and a multi-dimensional coupled bottom mud distribution prediction model; and intelligent sludge discharge control: generating an optimization instruction of sludge discharge frequency, quantity and area based on a prediction result, and controlling sludge discharge operation. According to the invention, bottom mud monitoring automation and mud discharge control refinement are realized, the precipitation efficiency is improved, and the operation cost is reduced.

The invention discloses a stamping process-oriented defect feedback and digital simulation closed-loop control system and method, and relates to the technical field of closed-loop control. The system comprises a working condition synchronous sensing and feature coding module, a digital simulation prediction module, a defect feedback and decision control module, a process parameter execution module and an online learning and model evolution module. According to the method, multi-source operation data are collected, a working condition feature packet is generated, material parameters are dynamically matched after a formed digital simulation model is input, initial disturbance is injected, and defect prediction parallel to physical stamping is achieved; calculating a prediction confidence coefficient by combining measured data, and generating a precise process adjustment decision by linking defect risk distribution and applying the decision to a next period; and based on actually measured and predicted errors, continuously updating a material parameter library and forming digital simulation model parameters through online learning. According to the method, the problems that traditional stamping simulation and reality are disjointed, and process adjustment is blind are effectively solved, the product defect rate is greatly reduced, and meanwhile the production efficiency and the quality stability are improved.

The invention belongs to the technical field of burn wound analysis. According to the skin burn analysis method and system based on contrast agent blood perfusion, firstly, a fluorescence sequence after a contrast agent is injected is obtained, and a preprocessing sequence is generated through area cutting and down-sampling; a fluorescence intensity time curve of each pixel point is extracted, peak time is determined, and statistics is carried out to construct a peak time histogram; performing smooth denoising, extreme value detection and weak peak removal on the histogram, and adaptively selecting a threshold value for distinguishing normal and burnt tissues; generating an initial mask by using the threshold value, and performing connected domain analysis and morphological post-processing to obtain a target burn area mask; and finally, generating a pseudo-color image in combination with peak time. According to the method, the time dynamic characteristic of blood perfusion is fully utilized, the burn area can be accurately segmented and the microcirculation disturbance degree can be visually presented without depending on skin textures or a large amount of training data, and the objectivity and accuracy of burn depth evaluation are remarkably improved.

The invention belongs to the technical field of satellite communication, and relates to a satellite-ground cooperative beam fault recovery method and system, and the method comprises the steps: carrying out the multi-dimensional monitoring of a downlink signal of a satellite through a ground station, and building a health baseline model for each beam; the satellite-borne equipment executes self-inspection, generates a preliminary alarm data packet when monitoring that the parameter of the key part exceeds a preset threshold value, and reports the preliminary alarm data packet to the ground station through the telemetering link; the ground station performs fusion analysis on the health baseline model, the preliminary alarm data packet, other beam data and space environment data to obtain a fault root cause; the fault root causes comprise temporary attenuation, beam pointing offset and permanent performance recession; the ground station generates a recovery strategy based on the fault root cause; a ground station is taken as a core dominant, and rapid and accurate recovery of on-satellite beam faults is realized through cooperative work with a satellite.

The application provides an antenna array surface fiber grating layout method based on a genetic algorithm and a neural network, and relates to the technical field of deformation sensing of an antenna array surface structure and optimization of fiber grating layout. The method analyzes strain sensitive positions of the array surface structure through the genetic algorithm and the neural network, arranges fiber grating sensors at optimal layout positions of the array surface structure, and realizes high-precision deformation sensing of the array surface structure under complex service loads. The method solves the problems of node layout redundancy, high data processing cost and insufficient displacement prediction accuracy in traditional antenna monitoring, and provides technical support for efficient sensing of antenna structure deformation and stable guarantee of electromagnetic performance.

The invention discloses a power distribution lightning arrester aging defect identification method and device considering environment confidence, electronic equipment and a storage medium, and belongs to the field of intelligent monitoring of power equipment, and the method comprises the steps: collecting the inspection image data of a power distribution lightning arrester and the time sequence synchronous environment parameters of the power distribution lightning arrester; mapping the environment parameters to defect display conditions, quantifying the adaptation degree of the environment to aging defect display, and generating an environment confidence index; visual features are extracted from the inspection image data, similarity calculation is carried out on the visual features and standard defect features, and an image similarity coefficient is obtained; and weighting the image similarity coefficient based on the environment confidence index to form a fusion defect probability value, and outputting a power distribution lightning arrester aging defect identification result according to the fusion defect probability value. Therefore, by implementing the method and the device, the problems of low identification confidence and missed detection and misjudgment caused by incapability of distinguishing'equipment defect-free 'and'environmental implicit' due to lack of quantitative evaluation on environmental suitability in the prior art can be solved.

The application discloses a preparation process of a high-performance Cu-Ni-Fe alloy based on first-principle calculation design, and relates to the technical field of alloy material preparation. The process constructs a precise Cu-Ni-Fe ternary alloy thermodynamic database by combining a first principle with a CALPHAD method, determines a composition range based on database calculation of a multivariate phase diagram, optimizes the composition by calculating a work function, an elastic constant and a thermal expansion coefficient through a first principle, and obtains a finished product through smelting, heat treatment and forming processing. The final alloy has an atomic percentage composition of Cu 30%-75%, Ni 10%-30% and Fe 10%-30%, a tensile strength of greater than or equal to 816.4 MPa, a total elongation at break of greater than or equal to 34.27%, and a thermal expansion coefficient of less than 20*10 ‑6 / K, and has excellent mechanical properties and thermal stability, thereby solving the problems of blind composition design and large performance fluctuation of a traditional process and being suitable for multiple fields such as ocean engineering and electronic packaging.

The invention relates to a battery fault diagnosis method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a voltage signal of each single battery in a battery pack, and generating an original voltage time sequence according to the voltage signal; adaptively searching an optimal parameter combination of variational mode decomposition based on a triangular topology optimization algorithm; variational mode decomposition is carried out on the original voltage time sequence based on the optimal parameter combination, and an intrinsic mode function component of a voltage signal of each single battery is extracted; selecting a preset time period on the intrinsic mode function component, and calculating a longitudinal outlier average value of each single battery in each time period; and based on the longitudinal outlier average value, judging whether a preset threshold value is exceeded or not, determining whether the single battery has a fault or not, and performing fault early warning under the condition that the single battery has the fault. By adopting the method, the accuracy of battery fault diagnosis can be improved.

The disclosure provides a recruitment post big data mining method and device, the method comprises: semantic normalization step: the original post name is processed by word segmentation, the word segmentation result is matched with the pre-constructed technical noun library and the function verb library, the core word item is extracted, and the normalized post name is generated according to the preset structured template reconstruction; skill extraction step: extracting skill keywords from the original post description corresponding to the normalized post name, generating a skill keyword set of the post category; feature vectorization step: calculating the term frequency-inverse document frequency of the core word item and the skill keyword set of the post category, generating a sparse feature vector of the post category; adaptive clustering step: based on the sparse feature vector of the post category, the clustering result is obtained.

This invention belongs to the field of triple mode redundancy (TMR) technology, and particularly relates to a selective TMR conversion method and system based on two-stage decoupling. The method includes acquiring the Verilog design code to be converted and parsing the circuit signals; calculating the dynamic activity of each circuit signal, dividing the circuit signals into critical and non-critical circuit signals, and forming a list of critical circuit signals; reading the list of critical circuit signals, traversing each assignment statement in the Verilog design code to be converted, and identifying whether the current circuit signal is a critical circuit signal; performing TMR operation on the identified critical circuit signals, and using logical assignment to make the replica signals track the original signals in real time for the identified non-critical circuit signals, thus completing the selective TMR conversion. This invention completely decouples the two stages of dynamic activity analysis of circuit signals and selective conversion of source code, and performs true / pseudo-TMR splitting processing.

The application discloses a kind of based on semantic guide's video frame processing method, system and storage medium, comprising: obtaining original video, obtains semantic guide text;The time position information of each frame is encoded after fusion with the visual features of this frame, form time sequence enhancement features, according to time sequence enhancement features to video frame grouping, select multiple representative and diversity key frames from pre-sampling frame;Multiple candidate local cropping regions are generated for selected key frame, the semantic similarity between each candidate region and semantic guide text is calculated respectively, and the candidate region with the highest similarity to semantic guide text is cropped out. Through the semantic perception of key frame selection in time dimension, and adaptive frame cropping in spatial dimension, the fine-grained refinement and alignment of video content are realized, thereby the performance of cross-modal text-video retrieval is significantly improved.

The invention discloses a full-process simulation and blasting pressure prediction method for a weak-rigidity core mold composite material shell, and belongs to the technical field of solid rocket engine integrated explosive forming shell design. The method comprises the following steps: designing an equal residual stress tension system based on a fiber winding layer stress theory; constructing a finite element model in the shell winding process, iteratively optimizing a tension system and determining a stress field and a strain field after winding; taking the stress field and the strain field as predefined fields, constructing a finite element model in the curing process, and calculating the stress field and the strain field after curing; and based on the stress field and the strain field after curing, progressive damage analysis is realized through a three-dimensional Hashin criterion, and the maximum blasting pressure of the shell with the powder is predicted. The problems that in the prior art, a tension system lacks collaborative optimization, simulation cannot cover the whole process, and blasting prediction deviation is large are solved, precise coupling prediction of the process and performance is achieved, and theoretical support is provided for optimization of the integrated forming process.

The present application belongs to the technical field of agaric cultivation, and particularly relates to an intelligent irrigation device for agaric cultivation, which comprises a water storage tank, an electric control pressurizing mechanism, a water distribution pipeline, a clogging-proof spray head and a humidity sensor. The water distribution pipeline is connected with the water storage tank through the electric control pressurizing mechanism. The clogging-proof spray head is arranged in the middle aisle of the area where the agaric sticks are stacked through a plug rod. The clogging-proof spray head is in communication with the water distribution pipeline. The clogging-proof spray head is of a split structure. A filter cavity for collecting impurities is arranged in the clogging-proof spray head. The humidity sensor is distributed in the soil where the agaric sticks are stacked. The humidity sensor is electrically connected with the electric control pressurizing mechanism. The water storage tank is provided with a filter mechanism. The filter mechanism is a laminated filter. The present application can adjust the spraying irrigation amount of agaric according to the humidity of the soil, improve the growth quality of agaric, and effectively avoid the clogging of the spray head.

The invention discloses an earth pressure balance shield construction method integrating freezing reinforcement, which comprises the following steps of: carrying out geological and hydrological investigation to obtain stratum engineering parameters; construction process parameters are determined; according to the construction process parameters, freezing pipelines and auxiliary measures are laid, and freezing pipe laying parameters are obtained; performing a pre-freezing test, and correcting construction process parameters; establishing a state space model, and performing online correction and multi-step prediction on the state space model; based on the state space model, system operation parameters are dynamically adjusted, so that tunneling and the frozen front are synchronously propelled, and the working state of the frozen front is obtained; and unfreezing and forming permanent support according to the working state of the freezing front and a design program. The problems that when an earth pressure balance shield is constructed in a complex soft stratum with high water content, high permeability and uneven hardness, an excavation face is prone to instability, the deslagging efficiency is low due to underground water invasion, and equipment damage, axis deviation and the like are caused by uneven stress of a shield tunneling machine are solved.

The application relates to a parameter optimization method and system based on a variational quantum enhanced Bayesian network, and relates to the field of quantum computing. The method comprises the following steps: obtaining an initial meteorological parameter value combination with the maximum lightning occurrence probability based on Bayesian network model traversal of historical meteorological parameter value combination data sets; mapping the initial meteorological parameter value combination into an initial bit string corresponding to an initial quantum state of a variational quantum circuit, running and measuring the variational quantum circuit to obtain a plurality of bit strings; parsing the bit strings into corresponding meteorological parameter value combinations; obtaining corresponding lightning occurrence probabilities based on the Bayesian network model; calculating a target function value based on the lightning occurrence probabilities, and adjusting the parameters of the variational quantum circuit until a convergence condition is met; and obtaining an optimal meteorological parameter value combination based on the converged variational quantum circuit. The application realizes optimization of meteorological parameter combinations with the maximum lightning occurrence probability as a constraint condition.

The invention provides a material growth simulation method, device and equipment and a storage medium, and relates to the technical field of simulation, and the method comprises the steps: calling material growth simulation software to execute simulation based on initial simulation parameters; calling material growth simulation software to execute simulation based on the initial simulation parameters; the initial simulation parameter is obtained by screening from a first simulation parameter interval input by a user according to a first model obtained by supervised learning, or is obtained by optimizing the first simulation parameter input by the user according to a second model obtained by reinforcement learning; when it is determined that simulation fails, the initial simulation parameters are optimized according to a second model, and target simulation parameters are obtained; and taking the target simulation parameter as an initial simulation parameter, and continuing to call the material growth simulation software to execute simulation based on the initial simulation parameter until it is determined that simulation succeeds. According to the method, automatic closed loop of simulation, verification and optimization is realized, so that the optimization efficiency of simulation parameters is improved.

This invention belongs to the field of industrial automated assembly technology. It provides an automated control system for valve assembly based on intelligent vision. During the intelligent vision-assisted assembly of valves, the system detects whether there is an angle between the valve stem axis and the valve body flow channel axis, and determines whether the actuator is perpendicular to the valve body mounting surface. If not perpendicular, it analyzes the uniformity of the bolts distributed on the actuator flange to assess the uniformity of the force. From the perspective of installation accuracy, combined with real-time monitoring and feedback of the installation angle using intelligent vision technology, the bolt tightening force can be adjusted in a timely manner to ensure that the actuator flange is perpendicular to the valve body mounting surface. This ensures that the valve stem axis coincides with the valve body flow channel axis. Furthermore, uniform force distribution reduces the superposition effect caused by uneven force distribution, prevents an angle between the valve stem axis and the valve body flow channel axis, ensures the consistency of the valve stem and valve body flow channel axes, and makes the internal mechanical structure of the valve meet design requirements, thereby improving the assembly quality of the valve.

The embodiment of the invention provides a vehicle control method and system, a vehicle and a computer readable storage medium, and relates to the technical field of vehicle steering control. The method comprises the following steps: acquiring a vehicle state data set of a target vehicle; based on a first sub-data set in the vehicle state data set, determining a road adhesion coefficient of the target vehicle, the road adhesion coefficient being used for representing friction coefficients between a plurality of wheels of the target vehicle and the road; according to the road adhesion coefficient, a target rear wheel steering mode of the target vehicle is determined, and the target rear wheel steering mode is used for representing a vehicle driving mode matched with the road adhesion coefficient; determining a target rear wheel steering angle corresponding to the target rear wheel steering mode based on a second sub-data set in the vehicle state data set; and controlling the target vehicle to steer according to the target rear wheel steering angle. The technical problem of how to adaptively adjust the steering angle of the rear wheel of the vehicle so as to ensure the control stability and the driving safety of the vehicle is solved.

The invention relates to an electromechanical pipeline collaborative arrangement method and system. The method comprises the following steps: extracting a central axis vector and a minimum external cylinder of each pipeline; in the same leaf node or adjacent leaf nodes of the octree, calculating the closest common vertical line segment distance between the central axis vectors of any two pipelines, and when the distance is smaller than or equal to the sum of the radiuses of the minimum external cylinders of the two pipelines, judging that hard collision exists; the method comprises the following steps: generating a discretized directed distance field covering a pipeline safety distance for a pipeline with high priority or gravity gradient constraint, and judging whether soft collision exists or not by querying a field value of the directed distance field at key points on the surfaces of other to-be-arranged pipelines; when the hard collision or the soft collision is identified, constructing an arrangement cost function based on the collision type, the professional attribute of the pipeline and the pipe section and pipe fitting increment estimated for eliminating the collision; and taking the arrangement cost function as an optimization target, iteratively updating the position of the arrangement cost function until all collisions are eliminated, and outputting a pipeline three-dimensional model after collaborative arrangement.