113 results about "Nonlinear coupling" patented technology

The application discloses a micro-nano circular plate fracture analysis method considering coupling of surface effect and plastic zone, and firstly establishes a three-dimensional curved surface coordinate system suitable for a surface layer, and then further corrects a Dugdale cohesion force model according to a superposition principle after considering surface correlation of the plate, and then simplifies the Dugdale cohesion force model into a hyper-singular integral equation by using Hankel transformation, and finally obtains influences of the surface effect on the plastic zone size and crack surface displacement by numerically solving the hyper-singular integral differential equation.The method can accurately capture the nonlinear coupling relationship between the crack size, the surface shear modulus, the torsional displacement and the stress intensity factor under the micro-nano scale, effectively corrects calculation deviation generated by traditional classical theory when the surface effect is ignored, ensures the accuracy of the fracture analysis under different scales, and realizes more accurate and more comprehensive theoretical description of the elastic-plastic fracture behavior of the micro-scale material.

This invention discloses a low-cost, low-speed USB circuit control method. It collects bus transmission timing signals, port voltage fluctuation data, and peripheral access status information through an embedded USB fault diagnosis platform to construct a multi-dimensional operational dataset. Based on a differential timing coupling mapping model, it mines the nonlinear coupling relationship of timing signals. A low-speed bus power consumption balancing model regulates power distribution, and a hardware timing error correction algorithm compensates for timing deviations. A low-cost control module converts the corrected parameters into hardware drive signals to achieve data transmission and peripheral control. The fault diagnosis platform monitors operational feedback data in real time and dynamically adjusts model parameters and control strategies. This method eliminates the need for high-cost dedicated chips and solves the problems of accumulated timing deviations and uneven power distribution in traditional methods through multi-model collaboration and closed-loop control. It reduces hardware costs while improving circuit control accuracy, stability, and operational efficiency.

This application relates to a method and apparatus for determining process parameters in metal compound thin film deposition. The method constructs a two-stage cascaded process prediction model. The first stage, a feature extraction model, performs nonlinear transformations and feature extraction on the process parameters, extracting intermediate feature information that comprehensively characterizes the sputtering process state. The second stage, a probabilistic prediction model, establishes a probabilistic mapping relationship between the intermediate feature information and the thin film response information, decoupling the complex nonlinear coupling relationships between multiple parameters in reactive sputtering. It outputs predicted values ​​and corresponding confidence information. Based on the predicted values ​​and confidence information, process parameters are screened, considering both target performance requirements and prediction reliability requirements. This improves the efficiency and reliability of process parameter screening, reduces the number of invalid experiments, and enables the prediction of key response quantities such as thin film deposition rate and chemical composition even with limited experimental data, shortening the process development cycle.

The present application relates to a kind of pre-tensioned steel wire rope lateral impact response calculation method considering geometric and friction nonlinear coupling.First, the linear tensile constitutive model of pre-tensioned steel wire rope is constructed, Von Kármán large deflection theory is introduced, and the geometric hardening relationship of the nonlinear growth of axial tension with lateral deflection is established;Subsequently, a bilinear bending stiffness model is constructed to calculate the critical anti-sliding torque that evolves dynamically with tension;Based on the principle of energy conservation and Rayleigh-Ritz method, the system total potential energy functional of axial tensile potential energy and nonlinear bending potential energy is constructed, and the maximum impact deflection and tension response of the steel wire rope are obtained by solving the energy residual equation, the maximum response is substituted back into the constitutive equation, and the maximum nominal stress of the midspan cross section, the maximum axial tension and the extension length of the internal slip zone are calculated.The present application has very high calculation efficiency compared with full-size finite element simulation, and is suitable for the rapid design and safety evaluation of steel wire rope protection system.

The application discloses a rotor coupling dynamics calculation method of complex three-dimensional shape layout. A coordinate conversion relationship caused by a front protrusion / after-sweeping / downward-reversing configuration is established; nonlinear elastic deformation of elastic blades waving, oscillating and twisting and nonlinear coupling relationship among them are described; nonlinear motion caused by the complex three-dimensional shape layout is described based on the coordinate conversion relationship and the nonlinear coupling relationship; and the relationship among strain energy, kinetic energy and virtual work of external force of the rotor is established based on the Hamilton principle according to the description of the nonlinear motion, and a finite element method of a 15-degree-of-freedom beam element is used to establish a rotor dynamics equation. The application can effectively reflect the structural coupling characteristics and coupling degree of the waving-torsion direction caused by the front / rear sweep of the blade tip, effectively reflect the structural coupling characteristics and coupling degree of the oscillation-torsion direction caused by the upward / downward reversal of the blade tip, and effectively reflect the rotor dynamics characteristic behaviors caused by the three-dimensional shape of the blade.

This invention discloses a spatial error prediction and compensation method for CNC machine tools based on digital twins and data-driven approaches, belonging to the field of CNC machine tool control technology. This invention addresses the problems of existing CNC machine tool spatial error compensation methods, which generally rely on offline, fixed mechanistic models, making it difficult to accurately describe and adapt to the dynamic, time-varying, and nonlinear coupling characteristics of errors in actual machining, and lacking the ability to predict and actively suppress future errors. This invention constructs a digital twin of the CNC machine tool that integrates a data-driven prediction model, trains the error model based on multi-source industrial big data, and achieves synchronous virtual-real simulation. This enables accurate real-time prediction of complex dynamic errors and converts them into feedforward compensation quantities to proactively correct CNC machine tool motion commands, thereby realizing a shift from passive lag correction to proactive prediction and prevention. This significantly improves the machining accuracy and adaptability of CNC machine tools under high dynamic and multi-condition conditions.

This invention provides a method and system for analyzing database performance indicators based on a large model, relating to the field of data processing technology. The method includes: acquiring performance indicator data of the database during operation, and performing time-series generation and noise removal on the performance indicator data to form standardized indicator sequence data; vectorizing the indicator sequence data and calculating the correlation strength between each performance indicator; performing semantic modeling processing through a large model to extract nonlinear coupling features between multi-dimensional performance indicators, forming bottleneck identification data containing coupling relationship levels; constructing a resource conflict resolution mechanism to determine the scheduling priority between computing resources and storage resources, generating scheduling instruction data containing resource adjustment magnitude and execution order; and updating the multi-dimensional feature representation data based on the performance feedback results after database execution. This invention improves the accuracy of database performance indicator analysis.

The application relates to a multi-curved bending super-large aluminum plate splicing welding residual stress detection system and method, which comprises a control follow-up platform; a cold sound coaxial flexible array probe, which comprises a flexible adhered outer film, a low-freezing-point liquid sound coupling medium layer, an ultrasonic phased array and a pulse cold spray nozzle; and a time-space coordination control system configured to: apply a transient thermal shock to a roughened rough weld surface through the pulse cold spray nozzle; drive the ultrasonic phased array to emit a detection sound wave to the weld in a temperature recovery period after the transient thermal shock, collect a scattered echo signal of the rough surface for time reversal processing and re-emission, so that a dynamic acoustic focus is formed in a target stress area; and simultaneously collect a transient sound velocity change rate in the focused area in real time, and based on a thermal-sound-elastic nonlinear coupling model, calculate and output a real welding residual stress value after eliminating the influence of the bending anisotropy. The application realizes dynamic acoustic focusing in the interior of the ungrounded weld, and improves engineering detection efficiency.

This invention relates to the field of membrane production filtration technology, and provides an environmentally friendly high-strength membrane production workshop filtration equipment, comprising: a feed pipeline for conveying the melt or coating liquid of the high-strength membrane production raw material to be filtered; a feed pump, disposed on the feed pipeline, for driving the flow of the raw material; a drive motor, connected to the feed pump, for providing power; a filtration unit, including at least one filter element, the inlet of the filter element being connected to the outlet of the feed pipeline, for filtering impurities in the raw material; and a backwashing unit, connected to the filtration unit, for backwashing the filter element. In this invention, a nonlinear coupled model is constructed using a feed status prediction module, an equipment status assessment module, and a clogging risk assessment module, achieving early warning and accurate quantification of filter element clogging risk, overcoming the lag and inaccuracy of traditional single differential pressure judgment.

The application discloses a method for realizing optical wave and terahertz near-zero refractive index based on a nonlinear mixed waveguide, and steps are as follows: thin film lithium niobate is selected as a nonlinear material to process a mixed waveguide; a one-dimensional corrugated waveguide is used on the mixed waveguide to show a Dirac point-like dispersion characteristic at a Gamma point; an average nonlinear coupling coefficient of the mixed waveguide is calculated, and the quality factor of the zero-refractive-index waveguide is optimized by adjusting the thickness and period of the thin film lithium niobate; hollow rectangular metal waveguides are arranged around the thin film lithium niobate waveguide, and are used for guiding the propagation of terahertz waves and enhancing the nonlinear interaction in the difference frequency process; and the near-zero refractive index of various terahertz frequencies is realized by changing the width of the hollow rectangular metal waveguide. By jointly designing the nonlinear mixed waveguide of the terahertz and optical wave near-zero refractive index, the problems of phase mismatch and weak nonlinear interaction of the conversion of the optical wave to the terahertz wave are solved, so that the efficient conversion of the optical wave to the terahertz wave across the wave band is realized through on-chip optical difference frequency.

The application discloses a high-concentration wastewater dynamic mixing control method based on biochemical treatment redundancy, relates to the technical field of wastewater treatment, and comprises the following steps: constructing a joint probability density function based on heat flow and dielectric spectrum signals; calculating a Riemann scalar curvature representing biochemical treatment redundancy based on the joint probability density function and taking a Fisher information matrix as a measurement; and adjusting a mixing ratio of wastewater and dilution water in real time according to the size of the Riemann scalar curvature. The method can solve the problems that the existing mixing control adopts a simplified adjustment logic, breaks the nonlinear coupling relationship between micro-electric polarization and macro-thermal dissipation, and cannot utilize the singularity divergence characteristics of the Riemann scalar curvature, thereby causing adjustment overshoot and response lag.

This application relates to the technical field of smart blackboards and discloses an interactive resource scheduling and optimization system for a blackboard, comprising a field mapping unit, a field solving unit, a topology unit, a control unit, and an instruction unit connected in sequence. The field mapping unit converts discrete interactive events into a continuous demand density distribution field and a resource capability potential field on the blackboard plane. The field solving unit dynamically obtains the current state of the demand density distribution field and the resource capability potential field by simultaneously solving a system of partial differential equations containing nonlinear coupling terms. The topology unit simultaneously optimizes the resource density distribution and the topology of the resource region by minimizing a preset energy functional. The control unit generates continuous control quantities for resource scheduling accordingly. The instruction unit finally converts these into a real-time sequence of underlying hardware control instructions. By introducing a spatially continuous field description, coupled dynamic system modeling, and topology optimization, the system improves the adaptive capability of resource scheduling, global optimization efficiency, and real-time response performance.

The application provides a battery calendar and cycle aging nonlinear coupling coefficient dynamic identification method and system, which is suitable for energy storage battery system life prediction with 20-year calendar life requirement. The method establishes a nonlinear mapping relationship between the calendar aging acceleration coefficient and the cycle aging intensity index and the cycle history cumulative effect, introduces a damage memory kernel function to quantify the hysteresis effect of cycle history on calendar aging, constructs a double-channel coupled differential equation set containing cross terms, and uses a recursive least squares algorithm with physical constraint projection to identify the coupling sensitive coefficient and memory time constant online, realizes real-time dynamic identification and adaptive correction of the coupling coefficient. The method breaks through the limitation of independent or weak coupling of cycle and calendar aging in traditional technology, reduces the maximum error of 20-year life prediction from 18.7% to 4.2%, and has clear physical meaning of model parameters and easy engineering implementation of system architecture, which meets the actuarial needs of 20-year warranty of energy storage power station.

The application provides a fluorite ore wall rock alteration detection system based on pattern recognition, and relates to the technical field of geological exploration data processing. Firstly, hyperspectral, RGB texture and laser radar data are spatially corrected and radiometrically calibrated to obtain an aligned spectral cube. After spectral smoothing and multi-order differential enhancement of weak alteration mineral characteristics, a deep unmixing network is used to decompose mixed pixels into each end-member mineral abundance. In the alteration intensity quantification stage, the mineral interaction and synergy characteristics and phase diversity entropy weight are introduced, and a nonlinear coupling fusion model is established to solve the problem of weak alteration zone recognition accuracy decay caused by the linear cumulative model ignoring the paragenetic relationship of minerals. Finally, the structure tensor is used to perform spatial gradient vectorization analysis on the alteration index, and the adaptive threshold segmentation and gradient flow constraint boundary evolution algorithm are combined to output the alteration detection results with intensity grading and accurate boundary positioning, providing pixel-level precision decision support for deep concealed vein exploration.

This invention relates to the field of non-electric variable regulation technology and discloses a method for regulating reaction parameters in the production of semiconductor-grade electronic hydrofluoric acid. The method includes: acquiring temperature and mass flow rate data of the reaction system; extracting the transient phase difference between the temperature and flow rate differential signals using phase difference tracking logic to characterize the nonlinear physical resistance fluctuations of the fluid; dynamically scheduling the nonlinear coupling coefficient based on the temperature deviation to identify the system error state; correcting the reaction enthalpy change coefficient using the transient phase difference, determining the feedforward compensation control quantity and superimposing it with the feedback control quantity, and outputting control commands for the fluid regulation actuator. This invention achieves compensation for fluid resistance through high-frequency signal phase decoupling, and, combined with an error state-based adaptive switching mechanism, improves the anti-disturbance stability and steady-state convergence accuracy of the purification process.

This invention relates to the technical field of intelligent verification, and in particular to an online self-verification method and system for smart meter operating errors based on edge computing. The system includes: an information acquisition module, a scaling decision module, a dynamic instantiation module, a data acquisition module, a scaling error prediction module, and a prediction result deviation calibration module. It utilizes a performance degradation model to guide the real-time instantiation of a scalable super network, thereby ensuring the energy efficiency ratio of edge resources while accurately capturing smart meter operating errors. Furthermore, to address the non-uniform distribution side effects caused by model pruning, it further calibrates the original prediction error using a scaling factor. By employing dynamic gain and bias correction, it cleverly compensates for the deep nonlinear coupling between the algorithm structure and physical load conditions, significantly improving the adaptive capability of edge nodes to complex electrical environments and effectively avoiding the risk of false alarms or missed alarms caused by model simplification.

The present application belongs to the technical field of machine vision, and discloses a kind of vision measurement error compensation method and system.The method steps include: image acquisition is carried out to target object, and target image is generated;Different material areas in target image are segmented and extracted, and multidimensional gray feature vector reflecting the surface optical response difference of different material areas is generated;Multidimensional gray feature vector is input into a pre-trained error compensation model, and the error compensation coefficient of target image is obtained;Target image is compensated according to error compensation coefficient;Wherein error compensation model is a mapping model, with multidimensional gray feature vector as input, with size measurement error compensation coefficient as output, mapping the nonlinear coupling relationship between light source, material and imaging process.The present application does not need to introduce illumination sensor, and realizes light source error compensation based on only image itself multidimensional information modeling, greatly improves the stability and measurement precision of machine vision size measurement under different materials and complex illumination conditions.

The present application relates to the technical field of gas safety early warning, in particular to a mine gas safety early warning method and system, comprising the following steps: collecting the concentration time series of continuous nodes and real-time roadway wind speed, combining the concentration distribution gradient difference to construct a spatial diffusion attenuation operator, generating a dynamic research limit according to the adaptive adjustment of the operator on the basic fixed alarm limit, and extracting the high-frequency fluctuation variance of the time series to execute secondary feature verification to output an over-limit early warning signal when the current concentration value approaches the limit. In the present application, a nonlinear coupling operator is constructed by using the concentration distribution gradient and fluid motion characteristics to correct the basic limit and generate a dynamic research limit, and then the high-frequency fluctuation variance is extracted to execute secondary determination, a double-layer comprehensive verification mechanism is established to integrate spatial correlation and time series fluctuation, the rigid defect caused by single-point determination deviating from diffusion effect is solved, and the risk of false alarm and missed alarm under pipe network interference is reduced.

This invention relates to the field of port logistics technology, specifically to a parallel collaborative intelligent yard crane scheduling method and system. The method includes the following steps: integrating coordinate parameters to generate a scheduling interference topology graph; constructing a concurrent task queue and establishing operational status data; mapping a three-dimensional envelope surface to calculate the intersection volume difference; mapping the volume difference to a braking level and injecting it into the motor to output an avoidance command; and deriving and superimposing a compensation current based on the sway angle acceleration and the trolley acceleration. In this invention, the three-dimensional anti-collision logic is mapped to a graph structure priority topology stripping to ensure concurrent tasks are immune to spatial deadlock conflicts. The volume derivative is used to dynamically predict the multi-machine displacement overlap rate to achieve flexible trolley coasting and avoid physical collision losses from rigid brakes. The feedforward compensation current is extracted by combining the spatial cross-product nonlinear coupling deviation to compensate for off-center load swaying potential energy from the electrical level and ensure the smoothness of the crane handling process.

The application relates to the technical field of unmanned aerial vehicle evaluation, and discloses an unmanned aerial vehicle FMECA detectability evaluation method based on MBSE-GNN collaborative driving, which comprises the following steps: extracting unmanned aerial vehicle system source data to construct an initial system heterogeneous topology graph; extracting constraint parameters from a node set, collecting time sequence features in a flight process, and extracting real-time control compensation gain; performing cascade fusion of the constraint parameters and the time sequence features to generate an initial node hidden state vector; inputting into a graph attention network, converting the real-time control compensation gain into aggregated attention weights through a conditional edge feature mapping function, and outputting a confidence probability of a compensation failure state; and calculating a detection penalty term and performing nonlinear coupling calculation with the confidence probability. The application unifies static constraints and dynamic features to construct a complete data basis, and the network uses conditional edge mapping to process abnormal gain, so that the fault feature masking problem is overcome.

The application belongs to the technical field of aero-engine manufacturing and intelligent manufacturing, and discloses an aero-engine titanium alloy centrifugal impeller milling vibration and roughness prediction system, which comprises a data acquisition module, a data preprocessing and feature conversion module, an SE-ResNet deep learning prediction model module and an online monitoring and early warning module. The application converts one-dimensional non-stationary vibration signals into two-dimensional image features by a Gram angle field, adopts an SE-ResNet18 model with a fusion channel attention mechanism to learn the nonlinear mapping relationship between vibration and roughness, and solves the problems that traditional methods are difficult to represent the strong nonlinear coupling between the two, have low prediction accuracy and poor generalization ability. The application realizes real-time high-precision prediction and abnormal early warning of the surface roughness in the machining process, and provides technical support for the machining quality control and airworthiness verification of aero-engine life-limited parts.

This invention relates to the field of motor dynamic performance technology, specifically disclosing a method for optimizing excitation control parameters based on a high-voltage direct-connected synchronous condenser, comprising: Step S1, defining the excitation control parameters of the high-voltage direct-connected synchronous condenser excitation system; the excitation control parameters include: the gain of the thyristor, the time constant of the integral element of the excitation regulator, the time constant of the differential element of the excitation system, and the coefficient of the thyristor regulation element; Step S2, performing sensitivity analysis based on simulation examples to obtain the influence law of each excitation control parameter on the overvoltage value; Step S3, based on the influence law, constructing a nonlinear coupled mapping model with the excitation control parameters as input and the overvoltage value as output using a neural network; Step S4, using the LMSSA sparrow search algorithm with a leader mechanism, with the minimum overvoltage value output by the mapping model as the optimization objective function, searching and optimizing the combination of excitation control parameters, and outputting the optimized combination of excitation control parameters.

The application discloses a kind of plunger spherical profile degree error compensation processing methods, belong to precision ultra-precision machining technical field.First, facing the ultra-precision grinding processing of hydraulic pump plunger part spherical surface, based on process experiment and device error measurement result establishes the processing device error mapping model and grinding cross-scale simulation model of profile error.Then, construct process parameter-device error two-dimensional multivariate nonlinear coupling mathematical model, the contribution of each error influencing factor and its coupling is quantified and screened core item, complete profile error traceability decomposition.Finally, establish the two-dimensional profile error control mode of device error compensation and process parameter optimization coordination, realize the ultra-precision machining of plunger spherical profile.The application cooperates and controls spherical profile degree error by process parameter and device error two dimensions, significantly improves machining precision and precision stability, is applicable to the high efficiency, high stability ultra-precision machining of precision plunger spherical surface in the field such as hydraulic pump.

The present application provides a kind of coastal water level prediction method based on multi-modal observation data, belong to coastal water level prediction technical field, the present application is by collecting the multi-modal marine observation data of different sensors, the spatial and temporal alignment of heterogeneous data is realized by establishing multi-scale space-time registration matrix, constructs marine dynamic process feature extractor to identify astronomical tide storm surge and wave characteristics and calculate nonlinear coupling parameters, using adaptive space-time fusion algorithm according to the weight of data quality dynamic adjustment generation space-time consistency dataset, establishes marine dynamic coupling strength discrimination model to determine modeling strategy, finally generates the coastal water level prediction product containing prediction value confidence interval and risk warning, solves the technical problem that multi-modal marine observation data is difficult to effectively fuse under the condition of space-time scale mismatch, resulting in insufficient coastal water level prediction accuracy.

The application relates to a bearing radial clearance state monitoring method and device in a gear-shaft-bearing system. The method comprises the following steps: arranging an acceleration sensor at a position close to the bearing of a gear box of a gear-shaft-bearing-box fourteen-degree-of-freedom nonlinear coupling vibration system, continuously collecting vibration time domain signals of the system at different running moments, carrying out detrending and filtering processing on the vibration time domain signals, and obtaining pretreated signals; carrying out discrete Fourier transform on the pretreated signals, obtaining modulation signal bispectrum based on traditional bispectrum expansion; carrying out carrier frequency normalization processing on the modulation signal bispectrum, obtaining nine groups of MSB-SE amplitudes, superimposing the nine groups of MSB-SE amplitudes on (1, 2, 3) x GMF on (1, 2, 3) x BPFO, obtaining MSB-SE comprehensive indexes of each moment for monitoring the bearing radial clearance, drawing a curve of the indexes changing with running time, and determining a bearing radial clearance monitoring result. The accurate and online monitoring of the bearing radial clearance is realized.

This invention discloses a continuous terahertz wave radiation source based on optical parametric oscillation in a waveguide cavity, its usage method, and its fabrication method, belonging to the field of optical communication technology. The continuous terahertz parametric oscillation radiation source includes a nonlinear dielectric waveguide layer and a substrate waveguide layer disposed on the upper and lower surfaces of the nonlinear dielectric waveguide layer. Reflective films are disposed on two opposite sides of the nonlinear dielectric waveguide layer to form a waveguide cavity within the nonlinear dielectric waveguide layer. The thickness and width of the nonlinear dielectric waveguide layer both satisfy the wave vector matching condition, and the thickness of the nonlinear dielectric waveguide layer is 5~50 μm. By obtaining a large nonlinear coupling coefficient, a small terahertz propagation loss, and achieving wave vector matching, the continuous terahertz wave radiation source provided by this invention can achieve high terahertz conversion efficiency, the waveguide cavity has a high quality factor, enhances the effective field strength within the nonlinear dielectric waveguide layer, and significantly reduces the terahertz parametric oscillation threshold.

This invention discloses a multi-axis random load fatigue damage prediction method incorporating a cross-attention mechanism. The method includes a data processing stage: acquiring multi-axis random load signals and preprocessing them; aligning load signals from different axes according to time steps to obtain multi-axis time-series data segments; converting the preprocessed multi-axis time-series data segments into a high-dimensional feature representation that can be processed by the model; inputting the high-dimensional features into a Transformer encoder and introducing a cross-attention mechanism; the Transformer encoder ultimately outputs multi-axis fused time-series features; and inputting the S3 multi-axis fused time-series features into a fully connected layer to obtain fatigue damage. By introducing a cross-attention mechanism to dynamically model the coupling relationship between multi-axis loads, the method can automatically learn the contribution weights of different load components to fatigue damage, achieving high-precision prediction of fatigue damage under multi-axis random load conditions. This avoids information loss and can characterize the temporal nonlinear coupling effect, thereby significantly improving prediction accuracy and generalization ability.

The application discloses a high-precision torsion rope driving mechanism based on segmented retainer, which comprises a driving connecting frame and a free end joint, the inner side of the driving connecting frame is fixedly connected with a driving motor, elastic reset members are arranged in an array between the driving motor and the free end joint, retainers are arranged between every two elastic reset members, and a plurality of torsion ropes are further arranged between the driving motor and the free end joint, and the plurality of torsion ropes are radially isolated from each other through the retainers. The high-precision torsion rope driving mechanism based on segmented retainer radially isolates the plurality of torsion ropes through segmented retainers, avoids deformation of the torsion ropes caused by mutual extrusion, determines system transmission relationship by geometric structure, and improves the precision and stability problems caused by nonlinear coupling. Meanwhile, direct friction between the torsion ropes is changed into contact between the torsion ropes and the retainers, friction loss is reduced, and operation stability and service life of the mechanism are improved.

This invention proposes a target detection and tracking method and system based on AI image recognition, comprising: pre-acquiring a complete three-dimensional image of the part to be tracked, and extracting edge curvature abrupt change features and residual stress distribution features of the part based on the complete three-dimensional image; performing nonlinear coupling processing on the edge curvature abrupt change features and residual stress distribution features of the part to generate a holographic feature value set of the part to be tracked, and obtaining a joint abrupt change threshold, so as to solve the problem that existing target detection and tracking methods are difficult to accurately identify parts with smooth surfaces under occlusion and whose visible areas exhibit low texture features, which easily leads to part positioning deviation, affects subsequent tracking and production processes, and leads to a reduction in production efficiency and quality.

The present application belongs to the field of boiler control, and particularly relates to an automatic baling biomass boiler fuel gasification coupling control method. The method comprises: extracting raw material activity index and dynamically adjusting baling machine parameters to produce customized fuel; collecting multi-modal data of a gasification furnace and a boiler in real time and constructing a data vector; using a gasification combustion digital twin to calculate the nonlinear coupling relationship between fuel properties and the data vector to generate an optimal operating parameter combination; and using a model predictive control algorithm to issue coordinated control instructions to the fuel forming, gasification, distribution and heat exchange whole chain. The present application realizes source compensation for raw material fluctuations and accurate mapping of dynamic characteristics through whole-process closed-loop control, improves the system comprehensive energy efficiency and load tracking rate, optimizes the safety and environmental performance, and improves the intelligent level of the biomass boiler system.