247 results about "Matrix model" patented technology

The invention provides an intelligent pressure sensor temperature compensation system, and relates to the technical field of pressure sensors, and the system comprises a hardware sensing module which comprises an elastic sensitive element and is used for reducing the temperature drift magnitude of a pressure sensor; the environment data acquisition module comprises a flexible thermoelectric sensor array and is used for acquiring temperature and humidity data; the humidity correction module is used for integrating a dynamic humidity correction algorithm and establishing a cross-sensitive matrix model to correct the original signal to generate a first pressure correction signal; the temperature compensation module is used for carrying an incremental neural compensation network and constructing a compensation model to perform temperature compensation on the first pressure correction signal to generate a second pressure compensation signal; and the fault compensation module is used for triggering a digital twinborn compensation model to perform fault compensation on the second pressure compensation signal to generate a target pressure output signal when a fault of the single sensor is monitored, so that the pressure measurement error in the whole temperature range can be accurately controlled, and the environmental adaptability and the intelligent level of the system are improved.

The invention provides a real-time dynamic harmonic detection method and system for a traction power supply system, and relates to the technical field of harmonic detection, and the detection method comprises the following steps: collecting a voltage signal of the traction power supply system in real time, and dynamically tracking fundamental frequency fluctuation through a phase-locked loop technology; dynamically adjusting the data window length of FFT analysis; dynamically adjusting a frequency spectrum calculation kernel of the FFT; carrying out linear compensation on the detected harmonic phase; taking the preliminarily detected harmonic parameter as an initial value, and iteratively updating the harmonic parameter until convergence by minimizing a signal reconstruction error; dynamically adjusting a sampling interval according to the fundamental frequency fluctuation, and carrying out anti-aliasing processing by adopting a filter with a variable cut-off frequency; and constructing a matrix model containing a fundamental frequency fluctuation parameter, and calculating a real harmonic parameter through a least square method. According to the method, the detection defect of the fixed window FFT during frequency fluctuation can be systematically solved, and high-reliability real-time data support is provided for harmonic resonance suppression of the electrified railway.

The invention discloses a dynamic optimization setting method and system for process parameters of a biological reaction tank of a sewage treatment plant based on machine learning. The method comprises the following steps: S1, data acquisition; s2, data integration and preprocessing; s3, establishing an effluent quality and concentration simulation prediction matrix; s4, carrying out model fusion; and S5, carrying out dynamic optimization setting on the technological parameters of the biological reaction tank based on the effluent quality simulation prediction model matrix established in the steps S1 to S4. The method comprises the following steps: firstly, establishing an outlet water quality high-precision simulation prediction model matrix, performing setting optimization on process parameters of a green pool and a reverse pool by adopting a particle swarm algorithm according to the model matrix, and finally obtaining process parameter set values of a future operation period; the advanced data analysis technology is fully utilized, the operation efficiency and effect of the sewage treatment plant are improved through the steps of collecting, processing, predicting, optimizing and the like, and energy conservation and consumption reduction are achieved on the premise that it is guaranteed that the effluent of the sewage treatment plant stably reaches the standard.

The invention discloses a host USB structure verification management system based on model fusion, and particularly relates to the field of computer security. The system comprises a data acquisition layer for acquiring a protocol data packet, an electrical signal waveform and equipment logic state information of a USB interface in real time, and generating a standardized multi-modal data stream through time alignment processing; the feature extraction layer is used for extracting modeling features from the standardized multi-modal data stream and encoding the modeling features into a structured matrix; the model fusion layer is used for fusing and outputting joint verification confidence through a protocol rule model, an anomaly detection model and a simulation model; the decision management layer executes a three-level verification strategy in sequence; the user interaction layer provides a visual monitoring and manual feedback interface and supports dynamic model replacement. According to the method, the structural legality of the USB equipment is verified through multi-model cooperation, real-time monitoring and risk level-to-level management of the USB equipment are achieved, the safety and compliance of the host terminal are improved, and the method is suitable for enterprise-level USB equipment protection scenes.

The invention discloses an apple anthracnose leaf blight recognition five-dimensional data fusion method based on a patrol robot, relates to the technical field of anthracnose leaf blight recognition, and solves the problems of limited sensing dimension, large illumination interference and inaccurate spatial positioning in the prior art. Comprising the following steps: S1, acquiring surface curvature characteristics of apple leaves, collecting RGB-D images of the leaves, constructing a three-dimensional topological structure of the leaves, and positioning scab space distribution; s2, acquiring spectral reflection information of apple leaves, quantifying biochemical components of chlorophyll a and carotenoid, and constructing a vegetation index feature set sensitive to diseases; s3, apple tree canopy temperature information is collected, a transpiration anomaly detection model is constructed, and multi-modal fusion of thermal infrared and point cloud data is realized; and S4, integrating spatial distribution, spectral reflection and thermal radiation information, constructing a five-dimensional phenotypic characteristic matrix model, and comprehensively analyzing apple phenotypic characteristics. According to the method, the recognition accuracy under the conditions of blade shielding, uneven illumination, blade posture change and environment interference can be remarkably improved.

The invention provides a grid-connected inverter impedance detection method based on an L-shaped filter, and belongs to the technical field of grid-connected inverter impedance detection. A multi-frequency-point disturbance signal is injected into a preset grid-connected inverter working point, time domain data of inverter side current and common coupling point voltage are collected, fast Fourier transform analysis is carried out on the collected data, amplitude and phase information corresponding to each injection frequency point is extracted, and a frequency domain feature vector matrix is established; and establishing a frequency compensation matrix model to compensate and correct high-frequency band measurement data based on a frequency characteristic attenuation vector, calculating to obtain optimal estimated values of power grid impedance and grid-connected inverter output impedance, performing error analysis and precision verification on an impedance detection result, and outputting a verified impedance parameter value. The technical problem of insufficient power grid impedance detection precision caused by high-frequency band attenuation of the L-shaped filter is solved.

The invention discloses a tunnel stratum recognition method based on shield tunneling machine tunneling parameter machine learning, and relates to the technical field of monitoring analysis, and the method comprises the steps: data collection: constructing a project data set, collecting rock core samples for drilling and coring from the project data set, and determining a learning sample set based on the rock core samples; data feature mining, which is used for obtaining tunneling parameters corresponding to various types of stratums from the learning sample set, mining a statistical feature set responding to stratum changes based on the tunneling parameters corresponding to various types of stratums, and forming a first feature parameter matrix; data feature screening, which is used for carrying out sensitivity analysis on the first feature parameter matrix so as to screen out a second feature parameter matrix; the model construction is used for constructing a stratum recognition model by adopting a K nearest neighbor algorithm based on the learning sample set and the second characteristic parameter matrix; and stratum identification, which is used for identifying the target stratum according to the stratum identification model. The method has the effect of improving the stratum recognition efficiency.

The invention discloses a dynamic coupling modeling method and system for an electric power information physical system, and belongs to the technical field of electric power dispatching automation, and the method comprises the steps: analyzing an AGC control process business data flow, and constructing a workflow engine; performing node classification, generating an information node model and an information branch model of the information system, and constructing a rule engine; constructing an information system network matrix model based on the rule engine, and establishing a preset service strategy based on the information system network matrix model; constructing an information physical coupling model of the AGC control process; and according to the AGC actual service, loading a preset service strategy established by the information system network matrix model based on the synergistic effect of the workflow engine and the rule engine, and updating the information physical coupling model. According to the method, a basic model is provided for cross-level closed-loop simulation verification in the AGC process, the problems of unclear information physical dynamic coupling mechanism, insufficient service logic adaptive mapping and model iteration self-updating are solved, and a guarantee is provided for safe and stable operation of a large power grid.

The invention discloses a traffic flow prediction method and device based on a space-time diagram convolutional network, and the method comprises the steps: collecting road traffic flow data, and constructing a traffic congestion index matrix model; calculating a road traffic congestion index based on the collected road traffic flow data, and constructing a traffic flow adjacency matrix by using the road traffic congestion index; performing fast time convolution processing on the traffic flow adjacency matrix to generate a traffic flow data sequence containing spatio-temporal information; inputting the traffic flow data sequence into a space-time synchronization graph convolutional network model STSGCN, further learning a spatial topological structure, and deeply extracting space-time features by stacking multiple layers of space-time synchronization graph convolutional layers; and inputting the spatial-temporal characteristics into a wave loss function-based random vector function link network model Wave-RVFL optimized by an index and trigonometric function optimization algorithm, and predicting the traffic flow. The method can improve the precision and efficiency of traffic flow prediction.

The invention discloses a six-degree-of-freedom mechanical arm disturbance compensation control method based on an iterative learning observer, and the method comprises the steps: taking a visual servo system as a research object, enabling the system to comprise a mechanical arm, a sensing part and a target object, and building a state space model based on a depth-independent Jacobian matrix model with joint speed disturbance; constructing an auxiliary state system and an error transfer equation based on joint sensor information, and designing an iterative learning observer to estimate joint speed disturbance; the disturbance estimation value is embedded into a visual model prediction controller, an optimal control signal is generated, joint speed input is corrected through a feed-forward compensation mechanism, and active disturbance suppression is achieved. According to the method, the tracking response speed of sudden disturbance can be improved, the system stability is maintained under the condition that interference exists in the joint speed, and therefore the visual servo task of tracking the expected trajectory is achieved.

The invention provides a power distribution box insulation monitoring method based on dynamic threshold analysis, and relates to the technical field of power distribution box insulation monitoring, and the method comprises the steps: obtaining multi-class parameter data capable of representing a power distribution box in a healthy insulation state, obtaining a multi-dimensional feature vector set of each time window, and constructing a reference matrix model; inputting a current time window multi-dimensional feature vector set of the distribution box needing to be monitored to obtain an estimated multi-dimensional feature vector set, and calculating a deviation index of the current time window multi-dimensional feature vector set; generating a dynamic early warning threshold value; judging whether a preliminary abnormal signal is triggered or not according to a comparison result of the deviation degree index and a dynamic early warning threshold value; if so, continuously acquiring deviation index slopes of a plurality of later time windows, and performing graded early warning on the insulation state of the distribution box to be monitored according to the deviation index slopes. According to the invention, the insulation state of the distribution box is analyzed based on a working condition self-adaptive dynamic threshold value, and the early and accurate hidden danger identification effect is realized.

The invention provides a regulation and control method, system and device for a relay valve overrun test and a medium, and belongs to the technical field of air braking systems. The method comprises the steps that pressure response characteristics of a relay valve pipeline system under different opening degrees of a proportional pressure regulating valve are tested, a finite set representing pipeline dynamic response is constructed based on pressure data in a sampling period, and a dynamic matrix model is generated to describe the relation between future pressure output and control quantity; pipeline pressure output at the future moment is predicted based on the dynamic matrix model, an optimized target function is established in combination with the target boosting rate, and the optimal control quantity is solved to adjust the opening degree of the proportional pressure regulating valve in real time; comparing a predicted pressure value with an actual measurement value to obtain an error, dynamically correcting a predicted model parameter by using a weighted error sequence, and adjusting a subsequent control quantity to compensate system hysteresis and external interference; and circularly executing the processes until the pipeline pressure and the regulation and control time reach corresponding target values, and cutting off the gas source.

The invention discloses a method for determining the position of a box-type transformer of a sand hill photovoltaic power station, and the method comprises the steps: extracting the topographic features of a sand hill through a graph embedding model, converting the topographic features into a high-dimensional vector, and dividing a photovoltaic module layout point matrix in combination with a plane point matrix model layout algorithm. Based on parameters of rated capacity, power supply radius and the like of the box-type transformer, a layout position is determined through the steps of screening effective point locations, dividing power supply partitions, constructing an electrical performance evaluation matrix, optimally screening an optimal candidate point location, performing final verification and the like. According to the method, topographic features and equipment parameters are fused, through multi-step system optimization, the limitation that the prior art depends on experience and single index judgment is overcome, the position determination accuracy and reasonability are improved, the method adapts to the complex sand mountain environment, losses and risks are reduced, and the operation efficiency of a power station is guaranteed.

The invention relates to the technical field of rail transit, and discloses a rail transit tunnel surface environment vibration assessment method, system and device and a medium. The method comprises the following steps: constructing a vehicle-rail-fastener dynamic model; calculating a fastener acting force frequency spectrum according to the vehicle-track-fastener dynamic model; constructing a 2.5 D finite element-basic solution solving model of tunnel-surrounding rock; solving the tunnel-surrounding rock 2.5 D finite element-basic solution solving model to obtain basic solution equivalent vibration source intensity; and calculating earth surface vibration according to the fastener acting force frequency spectrum, the basic solution equivalent vibration source intensity and the field layered soil body power transfer matrix model. According to the method, track vibration, tunnel vibration and site vibration are decoupled, the calculation method with the highest calculation efficiency is adopted in each subsystem, the advantages of each modeling method are fully combined, the calculation efficiency is extremely high, the obtained result is more accurate, the cost is low, and therefore the track traffic tunnel surface environment vibration condition is rapidly and accurately evaluated.

The invention relates to a cross-domain cooperative scheduling method, device and equipment of a power grid material supply chain, a storage medium and a program product, and relates to the technical field of logistics transportation. The material scheduling efficiency can be improved, and the resource scheduling deviation can be reduced. The method comprises the following steps: according to power grid material supply chain data, constructing a three-dimensional supply and demand state matrix model comprising a supply capability dimension, a transportation timeliness dimension and a demand intensity dimension; generating a supply-demand matching relation table according to the demand prediction data of the power grid enterprise, the productivity data of the supplier and the material allocation instruction of the logistics service provider; according to the supply and demand matching relation table and the parameters of each dimension in the three-dimensional supply and demand state matrix model, a material supply gap type is predicted through a gradient lifting decision tree model, and a cross-domain cooperative scheduling scheme is generated according to the material supply gap type; and feeding back the cross-domain cooperative scheduling scheme to the physical supply chain system, executing the cross-domain cooperative scheduling scheme to obtain a corresponding execution result, and updating the execution result to the three-dimensional supply and demand state matrix model.

The invention discloses a robot intelligent management and control system for energy conservation and efficiency improvement of a cold end of an indirect cooling auxiliary unit, and belongs to the technical field of intelligent management and control, the robot intelligent management and control system comprises an initial evaluation module, a dynamic planning module and a feedback monitoring module, obtaining a scaling thickness distribution diagram and a scaling coverage rate, and generating a fin flow channel matrix model; the dynamic planning module is used for dividing virtual operation blocks, constructing a scaling planning path in combination with a cleaning index, carrying out rapid rough sweeping, carrying out cavitation early warning, and processing cavitation early warning through a hierarchical control architecture; and the feedback monitoring module is used for constructing a quality deviation set, screening out substandard virtual operation blocks, calculating and correcting priorities, sorting and grading, optimizing and correcting parameters by utilizing a genetic algorithm, and performing feedback regulation and control, so that the cold end heat exchange efficiency is improved to achieve an energy-saving target, a fin structure is protected, and the service life of equipment is prolonged.

The invention discloses a concomitant epilepsy depression onset risk prediction system and device, and the method comprises the steps: constructing an array graph model based on multivariable factors, such as marriage conditions, onset age, epileptic seizure frequency, drug treatment types, SEEG epilepsy origin regions, daily life activity ability assessment scale ADL scores, and the like; through the array graph model, the onset risk of concomitant depression of epilepsy patients can be accurately predicted, so that the diagnosis rate of concomitant depression of epilepsy is improved, and a high-risk patient group of depression can be clinically recognized earlier, so that intervention is performed in time, serious consequences caused by depression onset are avoided in time, and the risk of concomitant depression of epilepsy patients is reduced. And a theoretical basis can be provided for clinically and actively intervening the depressive mood of the epilepsy patient.

The invention discloses a chirp grating design method and device, equipment and a storage medium, and relates to the technical field of optical fibers, and the disclosed chirp grating design method comprises the steps: analyzing a preset target spectrum function to obtain a target grating structure parameter; layering the initial grating into a plurality of sub-grating regions with uniform periods based on the target grating structure parameters, and establishing a layered transmission matrix model; determining a refractive index modulation depth range of each sub-gate region according to the layered transmission matrix model; and performing iterative optimization on grating structure parameters of the initial grating according to the layered transmission matrix model, the target spectral function, the refractive index modulation depth range and a preset error function to obtain a target grating. The performance of the chirp grating can be optimized.

The invention discloses a hospital scientific research consumable purchase and financial system linkage settlement optimization method, and relates to the technical field of purchase management, and the method comprises the steps: collecting scientific research purchase data, building a scientific research purchase data incidence matrix model, and carrying out the automatic verification based on the submission of a consumable application, and calling the scientific research purchase data incidence matrix model, and completing the purchase. After purchasing is completed, a scientific research fund dynamic balance model is constructed to output fund change information; an account structure is monitored and adjusted by outputting fund change information, and scientific research purchase efficiency and risk assessment model output quantitative indexes are constructed. According to the method, the scientific research purchase data incidence matrix model, the scientific research fund dynamic balance model and the purchase efficiency and risk assessment model are constructed, so that real-time linkage of hospital scientific research consumable purchase and a financial system is innovatively realized. The intelligent verification, fund dynamic monitoring and risk quantitative analysis capabilities of the purchasing process are effectively improved, the reasonable fund structure is ensured, and the intelligent level of scientific research management is promoted to be comprehensively improved.

The invention relates to the field of power equipment monitoring, and discloses a box-type substation internal fault intelligent monitoring method, which comprises the following steps: acquiring high and low voltage side electric signals of a transformer, calculating a 1-10kHz frequency band conductivity difference value, and carrying out temperature-load dynamic compensation; constructing a magnetic flux leakage dynamic matrix model real-time updating coefficient, and outputting a magnetic field change mean value; and fusing conductance and magnetic field characteristics, generating a fault membership degree vector through fuzzy logic, inputting the fault membership degree vector into the deep belief network, outputting a fault probability and triggering hierarchical control. The innovation lies in that the high-frequency conductance difference value improves the fault feature identification capability, millisecond-level magnetic flux leakage update captures early mechanical deformation, fuzzy-deep learning collaboratively enhances the diagnosis robustness, and the problems of misjudgment and missing detection of traditional monitoring are solved. The method significantly improves the timeliness of fault early warning, and is suitable for the real-time monitoring of hidden troubles in the transformer.

The invention discloses an aging furnace aluminum material heating time control method, system and equipment and a storage medium, and relates to the field of hot working technology optimizing.The method comprises the steps of parameter collection and pretreatment, basic heating time calculation, stacking state coupling correction, heat preservation time correlation calculation and dynamic feedback control. The heating time and the heat preservation time are accurately calculated by collecting multiple parameters such as the thickness and the weight of the aluminum material and applying the Fourier heat conduction law and multiple correction coefficients, functions and matrix models, and dynamic adjustment is conducted according to temperature monitoring. An industrial control system anomaly detection system matched with the system comprises a plurality of functional modules which work cooperatively. Compared with the prior art, time can be accurately calculated, high efficiency and energy conservation are achieved, the product quality is improved, the dynamic adjustment function is achieved, query is convenient, the defects of a traditional method are effectively overcome, and the method has important significance on development of the aluminum material machining industry.

The invention discloses a roadbed compactness rapid detection method and system based on a three-dimensional point cloud technology, and relates to the technical field of three-dimensional scanning. The method comprises the following steps: acquiring normalized point cloud of the inner wall of a roadbed compactness test hole, fitting parameters of a matrix cylinder model by combining macroscopic priori knowledge of a test hole drilling tool and adopting a process fusing two algorithms, and calculating an interior point rate; calculating a normal distance from the point cloud to the surface of the model as a geometric residual error, expanding a cylindrical surface to a two-dimensional plane, mapping the residual error, and performing interpolation to generate an initial residual error grid field; obtaining a filler physical and mechanical parameter derivation constraint condition, and optimizing the initial residual error grid field to obtain a physical compliance residual error grid field; and mapping the data back to three dimensions and superposing the data to a matrix model, generating a triangular mesh model, calculating the volume through numerical integration, outputting a result after interior point rate correction, and calculating the compaction degree in combination with filler performance parameters. According to the invention, the accuracy of roadbed compactness detection is effectively improved.

The invention relates to the technical field of geology, in particular to a surface matrix map modification data processing method which comprises the steps of data dynamic acquisition, intelligent preprocessing, three-dimensional modeling, multi-scale nested analysis, decision deduction and dynamic visualization. Compared with the prior art that a regular manual acquisition and static database updating scheme is adopted, the method has the defects that the data updating period is long, and sudden environmental changes are difficult to capture; according to the scheme, a multi-source data real-time access and AI dynamic cleaning scheme is adopted, the method has the advantages of real-time updating capability and automatic abnormal value correction, the surface matrix model can dynamically respond to environmental changes, the timeliness of disaster early warning and emergency decision making is remarkably improved, deep learning is adopted to fuse multi-modal data and a Bayesian uncertainty quantification scheme, and the method has the advantages of being high in practicability and easy to popularize. The method has the advantages of high-resolution three-dimensional modeling and risk area visualization, a complex geological structure can be accurately described, and clear priority guidance is provided for artificial verification.

The invention relates to the field of karst medium modeling and seepage simulation, and provides a three-dimensional reconstruction method and system for a karst coupling medium network. The three-dimensional reconstruction method for the karst coupling medium network comprises the following steps: acquiring corrosion pore characteristics in actual karst geological conditions, and generating an equivalent corrosion pore matrix model; obtaining corrosion hole characteristics in actual karst geological conditions, and generating a three-dimensional corrosion hole equivalent medium model; fracture characteristics in actual karst geological conditions are obtained, an original equivalent three-dimensional fracture network model is generated, fracture parts outside the representation unit body model are cut, and a three-dimensional fracture equivalent medium model is generated; generating a three-dimensional equivalent karst coupling medium network based on the equivalent corrosion pore matrix, the three-dimensional corrosion hole equivalent medium and the three-dimensional fracture equivalent medium model; and performing gridding processing on the three-dimensional equivalent karst coupling medium network to realize fluid mechanics analysis and simulation. The method accurately reflects the equivalent distribution condition and the seepage law of the karst medium.

The invention relates to a digital-intelligent automatic point alignment and full information verification method based on a power distribution terminal tester, which comprises the following steps of: acquiring electrical quantity signals and operating parameters of a terminal through the tester, and establishing communication connection through a digital-intelligent point alignment module; starting a three-remote check matrix model to perform matrix check on telemetering, remote signaling and remote control functions, calling an FFT harmonic synthesis telemetering calibration algorithm to dynamically calibrate a deviation value, introducing an abnormal attribution model based on a Bayesian network to perform probability reasoning on abnormal data, generating a report containing abnormal information and calibration suggestions, and uploading the report. The method improves the verification efficiency and overcomes the problem that the existing mode is tedious; checking accuracy is improved, and the problem that measurement deviation is difficult to correct is solved; abnormality processing capability is enhanced, defects of insufficient attribution capability are made up, stable operation of the power distribution terminal is guaranteed, and support is provided for power grid safety.

The invention discloses a college subject layout planning method based on regional economic development, and the method comprises the steps: obtaining the industrial structure, employment market, scientific and technological innovation and policy oriented data of a target region in real time through constructing a multi-dimensional regional economic development data collection system, and building a regional economic factor correlation analysis model through employing a big data mining technology, and key industrial fields and technical bottlenecks are identified. An industrial talent demand prediction map in the next 5-10 years is generated through a grey prediction model and a machine learning algorithm, a college subject evaluation index system is established, a matching degree index of a subject and a regional economic demand is calculated by using an entropy evaluation method, and a subject dynamic adjustment matrix model is designed to generate an optimization scheme. And meanwhile, a government-industry-university-research collaborative verification platform is constructed, a closed-loop correction mechanism including market demand feedback, education quality evaluation and economic contribution degree measurement and calculation is formed, and finally a visual decision support system, a subject layout optimization route map and a dynamic monitoring and early warning platform are output.

The application discloses a two-dimensional woven composite material geometry modeling method, device, equipment and medium, relates to the technical field of composite material structure design and modeling, and is used for solving the technical problems that the simulation model precision and reliability are low in the prior art. The method comprises the following steps: an initial matrix model is created by using a random distribution algorithm and a Boolean subtraction operation; a two-dimensional woven unit cell model is created according to a preset yarn space trajectory formula; a multi-layer two-dimensional woven fiber bundle model is created according to a plurality of two-dimensional woven unit cell models; a reserved fiber bundle matrix model is created by performing a difference set on the initial matrix model and the multi-layer two-dimensional woven fiber bundle model; and a two-dimensional woven three-dimensional model containing random pores is created by in-situ assembly of the reserved multi-layer fiber bundle matrix model and the multi-layer two-dimensional woven fiber bundle model. Therefore, the simulation model precision and reliability can be improved by using the technologies of "random distribution algorithm, Boolean subtraction operation, reserved position and in-situ assembly".

The invention discloses an assembly precision analysis method for a rotary shaft system of a mechanical structure based on a laser tracking measurement system, and in the laser tracking measurement system, the high precision guarantee of an assembled mechanical system is the premise of realizing accurate measurement. In order to obtain the assembly precision of a laser tracking measurement system, the invention provides an assembly precision analysis method based on Jacobi-spinor for a rotary shaft mechanical structure of the laser tracking measurement system. A Jacobian matrix model in the deviation transfer process and a spinor model comprising plane features, cylinder features and plane and cylinder parallel features are combined, a laser tracking measurement system rotating shaft assembly precision analysis model is established, and Monte Carlo simulation is adopted for calculation results to simulate actual assembly errors. A result shows that a difference value between a theoretical assembling condition and an analogue simulation actual assembling condition is 6.79 microns. The result shows that the provided method can qualitatively analyze the assembly precision of the rotating shaft of the laser tracking measurement system.

A weather prediction method includes generating radiance differences as a difference between measured radiances from satellites and forecast satellite radiances generated by a radiative transfer model and forecasted state profiles output by a numerical weather prediction (NWP) model. When the radiance differences exceed a noise threshold, the method includes generating updated state profiles by generating radiance-sensitivities using a Jacobian model and the forecasted state profiles; constructing a Kalman-gain matrix from background error covariance (BEC) matrices and the radiance-sensitivities; generating filtered state-profile changes from the Kalman-gain matrix and the radiance differences; updating the state profiles by adding the filtered state-profile changes to the forecasted state profiles to yield updated state profiles.

The invention discloses a resolution-oriented 4D millimeter wave radar antenna array and physical layout collaborative optimization method, a program, equipment and a storage medium, which are suitable for a radar system with a limited space and a multi-chip structure. The method comprises the steps of firstly collecting system input parameters; then, an antenna design constraint model is constructed, spatial discretization is carried out, and an optimizable matrix model is formed; transmitting and receiving array structures in the azimuth angle direction and the pitch angle direction are jointly designed through a virtual array mapping strategy, so that the requirements of MIMO mapping efficiency maximization and target angle resolution are met. After an antenna structure is determined, an optimization objective function is further constructed based on strong constraint and soft constraint, and an antenna layout scheme which meets the manufacturing requirements and has optimal performance is obtained through a traversal and search method. According to the method, the virtual aperture can be effectively improved, the antenna number redundancy is reduced, the wiring accessibility is optimized, and the resolution and engineering realizability of a 4D radar system are enhanced.