14results about How to "Overcome blindness" patented technology

The application relates to the field of heterogeneous bus communication and discloses a heterogeneous bus fault self-adaptive retransmission decision method and system, which solves the problem that secondary congestion and semantic fault are caused by the incapability of existing static retransmission to perceive cross-domain states. The method comprises the following steps: performing polymorphic fault fusion to output a comprehensive fault judgment signal; realizing standard scalarization and consistency checking of heterogeneous parameters through cross-domain state synchronization and a mapping table; calculating a real-time communication quality index, using clustering decision to determine an adaptive retransmission interval, number and path; performing semantic disassembly on cross-protocol domain data to build a data semantic structure tree, generating a compensation retransmission instruction and interweaving the instruction with a time sequence to issue the instruction. The application realizes a closed loop from perception to semantic compensation, improves communication reliability and can be applied to communication system equipment manufacturing.

This application relates to a feedforward-enhanced robust grid-connected control method for energy storage converters under wide grid impedance conditions, belonging to the field of power electronic control technology. This method transforms the current loop PI parameter design problem into optimizing the feasible stability region of the current loop controller. With the goal of maximizing the common adaptability of the stability region under different grid impedance conditions, it calculates the optimal feedforward coefficients and further calculates a set of current loop PI parameters that can cover wide grid impedance variations and possess high stability. Ultimately, it achieves feedforward-enhanced robust grid-connected control of energy storage converters under wide grid impedance conditions, fundamentally overcoming the blindness and inefficiency of traditional empirical parameter tuning, and significantly improving parameter design efficiency, overall system stability, and grid adaptability.

The application discloses a popcorn raw material screening workshop air filtering system and device, and relates to the technical field of industrial dust removal. The system comprises a micro-mechanical property acquisition module, a flow field fluctuation monitoring module, an environment sensing and adhesion coupling module, a multi-physical field coupling calculation module and a self-adaptive dust cleaning execution module. The anti-breaking strength of raw materials is acquired to construct a crushing particle generation potential factor, and the transient concentration impact load is extracted in combination with the dust concentration time series. Meanwhile, the environmental humidity is introduced to establish a dust capillary adhesion index, so that the dynamic calculation of the dust net deposition mass change rate on the surface of the filter bag is realized. On this basis, the difference relationship between the real-time deposition state and the reference working condition is constructed, and the pulse dust cleaning trigger pressure difference threshold is dynamically adjusted, so that the self-adaptive control of the dust removal system is realized. The application can effectively improve the dust treatment efficiency, reduce the energy consumption, prolong the service life of the filter bag, and is suitable for popcorn raw material screening and other industrial scenes with obvious dust concentration fluctuation.

The application provides a two-dimensional airfoil critical ice shape determination method, device and equipment and a storage medium, relates to the airfoil icing data processing technical field, and the method can more accurately describe the critical influence of the airfoil aerodynamic performance by determining the evaluation parameter corresponding to each icing condition in the current population, performs genetic operation on the current population to obtain a new current population, and determines the evaluation parameter corresponding to each icing condition in the current population again, determines a target icing condition based on the maximum value of the evaluation parameters corresponding to all icing conditions, and determines a two-dimensional airfoil critical ice shape based on the ice shape characteristic parameter corresponding to the target icing condition. By using the evaluation parameter and the genetic algorithm, the global optimal critical ice shape can be automatically found in the entire continuous flow field parameter set space, the locality and blindness of the manual point selection method are overcome, and the efficiency and accuracy of the critical ice shape determination can be improved.

The application discloses a water-rich soft rock foundation pit adjacent tunnel stability control method based on artificial intelligence, which comprises the following steps: prior prediction based on a finite element model, monitoring sensor arrangement, construction and training of a neural network model, scheme safety verification, initial decision based on the neural network model, initial grouting scheme execution, real-time monitoring-based cyclic intelligent decision and online incremental learning; training data is generated by establishing a three-dimensional finite element model containing a water-soil coupling mechanism, a neural network model capable of mapping the complex nonlinear relationship between monitoring parameters and optimal grouting schemes is constructed and trained, dynamic decision is made, and the grouting scheme that has passed safety verification is output and the model is continuously optimized; the method realizes the whole-process closed-loop intelligent control from intelligent prediction, real-time decision, safety control to self-optimization, and significantly improves the guarantee capacity and risk control level of the stability of the adjacent tunnel during foundation pit excavation in the water-rich soft rock complex stratum.

This invention discloses an energy-saving control method and system for cold and heat source systems based on particle swarm optimization and nested decoupling, relating to the field of building energy conservation. It solves the problem of solving the coupling parameters of building cold and heat source systems. The key technical points are: establishing an equipment group model of the building cold and heat source system, including chillers, ground source heat pumps, chilled water pumps, ground source circulating pumps, cooling towers, and buried pipes; mapping and matching the associated coupling variables with the same physical meaning among the equipment based on the equipment group model to establish a cold and heat source system group model, including chiller systems and ground source heat pump systems; and using a particle swarm optimization algorithm to optimize and solve the global control parameters of the system based on the cold and heat source system group model, outputting the optimal values ​​of the global control parameters; thus achieving optimal energy-saving control of the building cold and heat source system as well as global collaborative optimization and accurate modeling of the building cold and heat source system.

The invention provides a double-arm robot limited environment flexible cable operation method, device and equipment based on a depth generation model, and the method comprises the steps: determining an initial node and a target node according to an initial configuration and a target configuration, and extracting a feature vector representing a physical characteristic from motion track data; for each extension, sampling through a first generation diffusion model based on the feature vector to generate a legal stable configuration; performing space adjustment on the legal stable configuration through a second generation diffusion model based on the environment information and the task constraint to obtain a sampling guide configuration; generating a plurality of candidate actions based on the target node and the sampling guide configuration, and predicting the next configuration of the flexible cable through a third generation diffusion model based on the current node state and the plurality of candidate actions; expanding the next configuration and the corresponding candidate action as nodes, and constructing a planned path from the starting node to the target node through multiple times of expansion; and controlling the double mechanical arms to operate the flexible cable according to the planned path.

The invention relates to the technical field of air dust removal, and discloses phosphorite mining underground air dust removal equipment which comprises a dust removal box, a top shell, a cloth bag dust removal mechanism, a cleaning mechanism and an ash removal period regulation and control system. The ash removal period regulation and control system is based on the inlet dust mass concentration, the treatment air volume, the pressure difference of the two sides of a filter bag, the gas humidity and dew point margin, the pressure drop recovery rate after last round of ash removal, the initial pressure difference base line after ash removal and the resistance recovery rate. And calculating a dust load impact coefficient, a dynamic resistance coefficient of the filter bag, an environment adaptability degree and a dust cleaning potential coefficient of the filter bag in real time, and dynamically determining a target dust cleaning period according to the parameters. According to the invention, the self-adaptive precise regulation and control of the dust removal period under the instantaneous change of dust load and high-humidity environment is realized, excessive dust removal or insufficient dust removal is effectively avoided, the dust removal efficiency is improved, the energy consumption is reduced, and the service life of the filter bag is prolonged.

The invention discloses a two-stage constraint multi-objective optimization evolution method based on dynamic weight vector selection, and relates to the technical field of multi-objective optimizing.The method comprises the steps that in the first stage, a full-constraint population, a constraint relaxation population and an unconstraint population are maintained in parallel, and the populations are guided to penetrate through an infeasible area through a weak cooperation mechanism; and in the second stage, the unconstrained population is stopped, the distribution information of the constrained relaxation population is utilized, a potential search direction is extracted through a dynamic weight vector selection mechanism, and a search mechanism based on a dynamic vector is adopted to carry out refined environment selection on the main population so as to collaboratively approach a real leading edge. In addition, a high-quality feasible solution is reserved through an external file. The method shows better convergence, diversity and constraint satisfaction capability on a plurality of complex constraint optimization problems, and is suitable for practical engineering optimization scenes such as vehicle path planning and energy scheduling.

The application relates to the technical field of intelligent wearable devices and energy management, and discloses a low-power consumption control method and system for intelligent glasses based on an SD NAND storage chip, which comprises the following steps: synchronously aligning power supply voltage data and instruction frequency data to obtain a matching degree value; if the matching degree value is lower than a preset matching threshold value, using a pre-trained time sequence prediction model to predict a state switching duration and an instruction peak value interval to obtain a load change sequence; combining power supply noise and rhythm stability data to obtain a power supply configuration scheme through weighted calculation; performing sliding window processing on an instantaneous current sequence to obtain an efficiency change sequence; combining a preset efficiency reference sequence to calculate a correlation degree value and performing tolerance operation to obtain a dynamic switching threshold value; and combining a preset scene feature library to distribute weights to obtain a logic execution sequence and adjust the working state of the storage chip. The application realizes fine consumption reduction of the storage chip.

The invention discloses an industrial and commercial user load data cleaning method and device for energy storage safety, and belongs to the technical field of electric power data cleaning. The method comprises the following steps: acquiring original load data, and preprocessing an original load sequence to obtain a preprocessed load sequence; performing time domain decomposition on the preprocessed load sequence to obtain a trend component, a periodic component and a remainder component; performing frequency domain decomposition on the remainder component to obtain intrinsic mode components of different frequencies; wherein the intrinsic mode component comprises a low-frequency component and a high-frequency component; performing abnormal date confirmation based on the high-frequency component, and correcting a remainder component of the abnormal date based on a preset PSO-BP prediction model; and superposing the trend component, the periodic component and the corrected remainder component to obtain corrected load data. According to the method, the accuracy and reliability of user power data cleaning of the industrial and commercial energy storage system can be remarkably improved.

This invention relates to the field of permanent magnet motor design and optimization technology, specifically a high-efficiency integrated permanent magnet rotor magnetic circuit optimization design system, comprising: a configuration module, a topology generation module, an analytical calculation module, an index evaluation module, a parameter analysis module, and a scheme output module. The system generates multiple candidate magnetic circuit schemes based on initial parameters and performs rapid magnetic field analysis and comprehensive performance scoring using the equivalent magnetic circuit method. The parameter analysis module performs parameter perturbation analysis on the preferred schemes, accurately identifying the key design variables that have the most significant impact on performance; the scheme output module then iteratively optimizes these sensitive variables as the main optimization objects. This technical solution transforms traditional high-dimensional global optimization into low-dimensional directional search targeting key variables, reducing computational complexity and optimization time, effectively improving the efficiency and accuracy of permanent magnet motor rotor magnetic circuit design, and ultimately outputting optimal configuration parameters and a complete magnetic circuit design model.

This invention discloses a method and system for calculating the strength of surrounding rock based on the equivalent support reaction force of prestressed anchor bolts, relating to the field of surrounding rock data processing technology. The method includes: acquiring the initial mechanical parameters of the surrounding rock, tunnel excavation parameters, and anchor bolt support design parameters; calculating the cohesion increment, the elastic modulus of the anchor bolt-surround rock composite structure, and the equivalent support reaction force based on the design parameters; superimposing the cohesion increment with the initial cohesion of the surrounding rock to obtain the total cohesion; applying the equivalent support reaction force as a boundary condition to the bearing arch model; calculating the rock mass strength safety factor, the anchoring system efficiency coefficient, and the comprehensive deformation stability coefficient in parallel; and synthesizing the rock mass strength safety factor, the anchoring system efficiency coefficient, and the comprehensive deformation stability coefficient to obtain the final surrounding rock strength safety factor. This invention, through quantitative analysis, reduces the possibility of engineering risks and provides technical support for the special and complex engineering type of large-span tunnels.

The invention provides a water conservancy project maintenance quota material unit price calculation method, and relates to the technical field of water conservancy maintenance cost calculation, engineering function attributes and market maturity of materials are quantified into comprehensive field regulatory factors, contribution degree thresholds are dynamically set for different material types according to the comprehensive field regulatory factors, key features are screened out, and the value of the key features is calculated. The method comprises the following steps: constructing an optimization model taking minimization of prediction errors and maximization of time sequence extrapolation stability as double objectives, performing automatic optimization on random forest hyper-parameters by using a particle swarm algorithm to obtain a combined prediction model, training and evaluating the model through forward chain type time sequence cross validation to ensure that the model meets stability and precision requirements, and performing prediction on the random forest hyper-parameters. And finally, predicting unit prices in multiple periods in the future and prediction intervals thereof by adopting a rolling window mechanism based on the model, and performing dynamic weighted synthesis by applying dual weights fusing time decay and interval width inverse ratio to generate an optimal quota unit price fitting a high-confidence market trend.