699986 results about "Control theory" patented technology

The present disclosure provides an underwater detection method for contact leakage of a tunnel joint of a dam culvert, including: obtaining an underwater image sequence of the culvert by an underwater robot; preprocessing and registering the underwater image sequence; extracting particle information appearing in the underwater image sequence based on the registered underwater image sequence; constructing a three-dimensional fluid velocity distribution map based on the particle information, and determining leakage situation according to the three-dimensional fluid velocity distribution map; and superimposing the three-dimensional fluid velocity distribution map on a preconfigured three-dimensional culvert model, and rendering and displaying it. The present disclosure can adapt to the complex and changeable underwater environment inside the culvert, it has a high sensitivity to fine leakage in the deep layer, it can realize the accurate measurement and trend prediction of leakage, and it can automate the detection process to reduce manual dependence.

Disclosed is a microgrid optimal scheduling method taking into consideration a system operation risk and user satisfaction, comprising: generating a power prediction curve of wind power and photovoltaic new energy output in a microgrid, using a Monte Carlo simulation method to obtain a prediction error range to generate a typical scene set, and by means of a data fitting method, acquiring a wind-photovoltaic prediction error probability density distribution function; using value-at-risk and conditional value-at-risk theories to quantify a microgrid operation risk which is increased by slightly high or low output caused by wind power and photovoltaics; obtaining the scheduling cost of an adjustable load in a microgrid system; taking the minimum sum of conditional value-at-risk cost and microgrid system operation cost as an objective function and a user satisfaction level under a demand-side response as a constraint, establishing a microgrid optimal scheduling model taking into consideration the operation risk and the user satisfaction; and using a genetic algorithm to solve the model, and obtaining an optimal result of grid-connected microgrid system optimal scheduling. The safety, economic efficiency, stability and reliability of the microgrid are enhanced.

The invention relates to an intelligent reflux valve adjusting method based on a self-adaptive control algorithm, and aims to improve the accuracy and response efficiency of fluid adjustment. The method comprises the steps that fluid flow, pressure, temperature and flow direction data collected by sensors installed at an inlet and an outlet of the reflux valve are obtained, and the initial target valve opening degree under the current fluid working condition is calculated through a working condition opening degree prediction model in combination with structural parameters of the reflux valve; based on the relation among the flow, the pressure and the valve opening, the initial target valve opening is adjusted through a fuzzy rule base, so that the final target valve opening is obtained, and therefore the dynamic change of the complex fluid working condition is adapted; according to the final target valve opening degree, an execution mechanism is controlled to adjust the operation state of the reflux valve, and precise adjustment is achieved; working condition prediction and fuzzy control are combined, the adjusting precision and stability of the reflux valve are improved, and the method is particularly suitable for fluid conveying systems with large flow and pressure fluctuation and has wide application prospects in the industries of energy, chemical engineering, environmental protection and the like.

Systems and methods described herein include implementation of road surface-based localization techniques for advanced vehicle features and control methods including advanced driver assistance systems (ADAS), lane drift detection, passing guidance, bandwidth conservation and caching based on road data, vehicle speed correction, suspension and vehicle system performance tracking and control, road estimation calibration, and others.

The invention discloses an IMU (Inertial Measurement Unit) dynamic calibration and compensation method and device, vehicle-mounted navigation equipment and a storage medium. The IMU dynamic calibration and compensation method comprises the following steps: acquiring original data of an IMU, sampling and integrating with environmental parameters to obtain an initial measurement sequence; periodically decomposing and calculating the influence of environmental factors on an IMU output value to obtain a measurement supplementary sequence; carrying out segmented calibration and iteration to obtain a calibration reference value; an error change rule is analyzed, and a calibration mapping amount is obtained through feature analysis; performing environmental factor decomposition to obtain compensation factors; each compensation factor is dynamically checked, and a correction coefficient is obtained through threshold comparison; compensating the original data by using the correction coefficient, and reconstructing the data to obtain a correction sequence; carrying out stability analysis on the correction sequence, and obtaining a drift parameter according to a change trend; and carrying out difference analysis on the drift parameter and the calibration reference, and carrying out multi-point correction to obtain a final calibration result. According to the technical scheme, the IMU original data can be accurately obtained, the environmental influence is effectively processed, dynamic compensation is achieved, and long-term stability is guaranteed.

The invention relates to a power supply switching control optimization method and system, and the method comprises the steps: constructing a multi-dimensional data fusion monitoring system, integrating a real-time voltage ripple coefficient detection module of a main power supply, a load transient response analysis module and an environment temperature and humidity sensor array, and generating a dynamic health degree index; the method comprises the following steps: establishing a fault prediction model based on transfer learning, pre-training through multi-scene failure data in a historical database, receiving a health degree index in real time, outputting a reliability attenuation curve, and activating a dual verification mechanism when the slope of the attenuation curve exceeds a preset threshold; extracting characteristic energy distribution of a frequency band of 0.1-10 kHz; executing a transient load impact test, and measuring dynamic response parameters of voltage recovery time and overshoot amplitude; and generating a switching confidence score based on cross processing of the dual verification result and the attenuation curve, and triggering a hierarchical switching instruction. The accuracy of the switching time of the main power supply and the standby power supply can be improved.

The invention discloses a target recognition and grabbing posture planning system for a collaborative robot, and belongs to the technical field of mechanical arms. According to material posture information provided by a sensing module, the optimal grabbing posture is intelligently matched from a preset grabbing strategy library by fusing mechanical arm movement track parameters and target material physical characteristics; the initial accuracy of the grabbing scheme is ensured, in the grabbing process, the camera continuously collects the material poses in real time, and the offset is accurately calculated by comparing the real-time poses with the expected poses. Once material deviation is detected, a visual and force closed-loop adjusting mechanism is triggered immediately, a force-position hybrid control model is utilized, position deviation is synchronously corrected, and grabbing force parameters are dynamically adjusted, so that the grabbing stability and precision are remarkably improved, the grabbing failure rate is effectively reduced, manual intervention and reset time are greatly shortened, and the grabbing efficiency is improved. Therefore, the production efficiency is comprehensively improved.

An electric motor based system includes an electric motor; an electric motor power controller for controlling the electric motor; a first control unit, adapted to provide first control signals for the electric motor power controller; an electric power storage device adapted to power the electric motor power controller; a first sensor adapted to determine information related to power exchange between the electric power storage device and the electric motor power controller; and a second control unit, wherein the second control unit is adapted to pass the first control signals, received from the first control unit, to the electric motor power controller in a first mode and adapted to provide second control signals for the electric motor power controller in a second mode; and the second control unit inputs and exploits the information.

The invention provides a cold machine and water pump linkage energy-saving control method under a low-load working condition, which relates to the technical field of information and comprises the following steps of: dynamically predicting load requirements under the low-load working condition by analyzing historical operation data of a refrigeration system and combining weather forecast information, equipment operation parameters and data of building personnel activity rules; obtaining a cooling capacity demand curve and a load demand prediction result in future preset time; establishing a system low-load operation mode optimization model, taking the screened control combination meeting the preset energy-saving operation target as model input, and obtaining an optimized system low-load operation mode through the training model; the optimal energy efficiency interval is determined by analyzing the relation between equipment energy consumption and cold storage capacity, and during load demand prediction and control optimization, the interval serves as a target constraint to guide a refrigerator and water pump equipment to operate in a high-energy-efficiency area. And the operation efficiency and the energy-saving effect of the refrigerating system under the low-load working condition are improved.

The invention relates to the technical field of battery management, and discloses a battery energy balanced distribution and optimization method, device and equipment and a storage medium. The method comprises the following steps: performing multi-source parameter acquisition and feature decoupling on each single battery in a target battery pack to obtain a single battery state data set, and performing multi-band excitation scanning and impedance spectrum fitting to obtain internal features of the battery and decompose an attenuation trend to generate equivalent circuit model parameters; performing state mapping and capacity calculation based on the model parameters to obtain a performance evaluation result of the battery pack, and constructing an energy transfer network and identifying unbalanced propagation characteristics through performance difference analysis and consistency calculation; and temperature coupling calculation and compensation matrix reconstruction are carried out based on propagation characteristics, multi-path parallel balance control is realized, and an optimization result of the battery pack is obtained through voltage deviation calculation and polarization compensation. According to the method, the multi-dimensional characteristic parameters and the dynamic change characteristics are combined, and accurate control over battery pack equalization is achieved.

A portable fan includes an airflow portion and a handheld portion. The airflow portion includes rotation air blades and a drive portion that is driveably connected to the rotation air blades. The drive portion is a three-phase motor that is configured to drive the rotation air blades to rotate to generate an airflow. The handheld portion is connected to the airflow portion. A power supply assembly is arranged inside the handheld portion; and the power supply assembly is electrically connected to and supply power to the three-phase motor.

The invention relates to the field of power equipment control data processing, in particular to a boiler combustion optimization control method based on data driving, which comprises the following steps of: acquiring multi-source data such as temperature field distribution, air and smoke pressure, smoke components and coal quality characteristics, and eliminating noise interference by adopting sliding window mean filtering; generating a standardized feature matrix in combination with principal component analysis and a dynamic time warping algorithm; constructing a dynamic coupling model fusing a gradient boosting decision tree and a long short-term memory network, analyzing a nonlinear relationship between pulverized coal particle size distribution and a wind-coal ratio, and predicting combustion efficiency, pollutant concentration and temperature field uniformity; and model parameter self-correction and weight dynamic adjustment are triggered through actual combustion data feedback, and a closed-loop control link is formed. According to the method, accurate modeling of the multi-physical field coupling characteristic of the combustion system is achieved, the time sequence generalization ability under the dynamic working condition is improved, and the purposes of heat efficiency improvement and pollutant emission reduction are effectively balanced.

The invention relates to the technical field of power systems, provides an association rule analysis-based power load prediction method and system, and aims to solve the problem of hidden fault response lag caused by lack of an equipment health state and load fluctuation dynamic coupling mechanism in the prior art. And the problem of load prediction compensation deviation caused by insufficient weight quantization of the fault propagation path is solved. The method comprises the following steps: generating equipment state data according to a vibration spectrum and an insulation aging index of power equipment; performing fusion analysis, generating an equipment health degree evaluation index, and establishing a dynamic influence model of the equipment abnormal event on the power grid load fluctuation according to the association rule; identifying potential abnormal equipment, performing logic mapping, and generating a fault propagation path weight; and dynamically adjusting according to the weight to obtain an adjusted power load predicted value. According to the technical scheme provided by the invention, equipment vibration and insulation aging data are fused, a health assessment and fault propagation model is constructed, and load prediction is dynamically corrected to prevent and control power grid risks.

According to the server heat dissipation control method, the electronic equipment and the storage medium, heat dissipation control processing is firstly performed on the server according to the operation data of the server and the heat dissipation control algorithm, and then the server subjected to heat dissipation control is evaluated according to the actual heat dissipation requirement of the server, namely the preset heat dissipation condition; and optimizing a heat dissipation control algorithm according to the evaluation result and the operation data of the server after heat dissipation control. Meanwhile, a deep reinforcement learning mechanism is introduced into optimization of a heat dissipation control algorithm, and the balance problems of difficulty in parameter setting and poor system adaptability in traditional heat dissipation control are solved through cooperation of multiple algorithms and combination with edge calculation, namely, preset edge calculation equipment, so that the problem that the system adaptability is poor in the heat dissipation control of the server can be solved. The problems of difficulty in parameter setting and poor system adaptability are solved, and the technical effect of improving the efficiency and the stability of the heat dissipation system is achieved.

An expandable cart with an unfoldable rear frame includes a first column, a second column, a third column, a fourth column, a first folding mechanism, a second folding mechanism, a third folding mechanism, a bottom support mechanism, and a rear frame mechanism. The four columns are arranged at intervals in a rectangular shape, and have lower ends all connected to the bottom support mechanism, and the bottom support mechanism is capable of being folded upward. The first folding mechanism is connected between the first column and the second column, the second folding mechanism is connected between the third column and the fourth column, and the third folding mechanism is connected between the fourth column and the first column. The rear frame mechanism is disposed between the second column and the third column.

Disclosed in the embodiments are a vehicle risk avoidance method and system, a vehicle, and a storage medium in the technical field of intelligent driving. The method includes the following steps: obtaining first motion state information of a target vehicle and obstacle information of a target obstacle at a plurality of consecutive moments, the obstacle information including two or more of an obstacle type, an obstacle location, obstacle boundary information, and second motion state information; executing a risk assessment strategy corresponding to the obstacle type according to the first motion state information and the obstacle information corresponding to each moment, to determine a risk assessment result of whether the target vehicle collides with the target obstacle; and determining, if a plurality of risk assessment results corresponding to the plurality of moments satisfy a risk condition, a target risk assessment result from the plurality of risk assessment results, and generating a target security protection strategy corresponding to the target risk assessment result to avoid a collision risk.

Disclosed is a clamping device having an automatic direction adjustment function in a vehicle body welding conveying line, including a conveying frame. A driving motor is fixedly connected to a side wall of the conveying frame, and an output shaft end of the driving motor is fixedly connected to a rotating shaft I. The present disclosure facilitates the adjustment of a direction when vehicle bodies to be welded are conveyed on a turning conveying line, and vehicle bodies being conveyed can be corrected to the same horizontal state, to avoid a situation where the clamping device on the conveying line cannot smoothly clamp inclined vehicle bodies for conveying because the vehicle bodies cannot be in the same horizontal plane when being put in.

The invention relates to the technical field of numerical control machine tools, and discloses a self-adaptive error compensation method and system for a high-precision numerical control machine tool, and the method comprises the steps: carrying out the mathematical modeling of a multi-dimensional error of a five-axis numerical control machine tool, and obtaining a thermal deformation displacement vector, a friction force vector and a path deviation vector; inputting into a multi-dimensional expansion state observer for error observation to obtain thermal deformation, a friction force value and a path error value; performing trust domain parameter optimization to obtain a thermal deformation compensation gain matrix, a friction force pre-compensation coefficient matrix and a path error compensation coefficient matrix; performing three-stage series compensation calculation to obtain a compensation position instruction, a compensation speed instruction and a compensation acceleration instruction; and track reconstruction operation is carried out to generate a position instruction sequence, a speed instruction sequence and an acceleration instruction sequence of each axis, so that self-adaptive error compensation of the high-precision numerical control machine tool is realized, and the machining precision of the high-precision numerical control machine tool is improved.

The invention discloses a load flow calculation and simulation control method and system for a digital twin power grid, and relates to the technical field of digital twin simulation control, and the method comprises the following steps: constructing a digital twin power grid model, and carrying out the dynamic topology optimization processing of the digital twin power grid model based on remote signaling credibility weighting; according to the optimized digital twin power grid model, identifying the power grid operation risk based on an integrated learning model; according to the risk identification result, generating a transfer path control strategy based on an analytic hierarchy process and a fuzzy comprehensive evaluation method; mapping the transfer path control strategy into a control action instruction set, and simulating execution and establishing a feedback correction mechanism on the digital twin power grid model; by generating the optimal path control strategy and performing control strategy analog simulation and self-adaptive feedback correction based on the digital twin power grid model, the problem of lack of intelligent path control strategy selection and simulation verification based on state dynamic identification in the prior art is solved.

The invention discloses a full-effect electric energy optimization rapid detection system and method, and particularly relates to the technical field of electric energy detection. The method comprises the following steps: acquiring voltage, current, frequency, harmonic component and three-phase unbalance degree of a power grid in real time, calculating a power grid impedance value and a load dynamic characteristic ratio, drawing an impedance frequency characteristic curve, analyzing a harmonic amplification abnormal degree and a load dynamic response characteristic, and evaluating the accuracy of a detection instruction generated by the full-effect electric energy optimization device. The error correction is carried out on the inaccuracy detection instruction, the duty ratio is dynamically adjusted by utilizing the PWM technology, the accurate matching of the amplitude and the phase of the output current is realized, the error correction effect is evaluated by comparing the real-time detection value with the theoretical calculation value, and the detection model and the compensation strategy are automatically optimized. The problems of detection precision reduction and error compensation caused by complex power grid conditions in the prior art are solved, harmonic amplification, reactive power over-compensation and three-phase balance damage are avoided, and efficient and accurate electric energy optimization and power grid stability improvement are achieved.

The invention relates to a thermal management control method and system for an energy storage power supply, and the method comprises the steps: obtaining the real-time temperature data of the energy storage power supply, and carrying out the heat source distribution analysis, and obtaining the corresponding temperature distribution information; heat dissipation operation parameters of the energy storage power supply are obtained, adjustment analysis is carried out in combination with the temperature distribution information, and a corresponding initial heat dissipation control strategy is obtained; acquiring real-time monitoring data of the energy storage power supply, and performing charge and discharge dynamic analysis in combination with the temperature distribution information and the initial heat dissipation control strategy to obtain corresponding charge and discharge adjustment information; based on the real-time temperature data and the thermal management strategy, hot spot identification is carried out, corresponding potential hot spot information is obtained, early warning processing is carried out, and a corresponding hot spot early warning result is obtained; and performing comprehensive control analysis on the thermal management strategy, the initial heat dissipation control strategy and the hot spot early warning result to obtain a corresponding global thermal management control scheme. According to the invention, comprehensive and intelligent control of thermal management of the energy storage power supply can be realized.

A direct current (DC) fast charger for charging a battery of an electric vehicle (EV) includes a primary circuit having seven bidirectional switches electrically linked to a primary wire of a transformer and configured to receive an alternating current (AC) voltage; and a secondary circuit comprising a plurality of diodes arranged to rectify the AC voltage into a DC voltage, electrically linked to the secondary leads of the transformer such that the DC fast charger unidirectionally converts the AC voltage received at the primary circuit into the DC voltage output by the secondary circuit.

The invention relates to an unmanned aerial vehicle intelligent dynamic path guidance method and system based on deep reinforcement learning. The method comprises the steps of obtaining three-dimensional terrain point cloud and obstacle information of a flight area, constructing an environment topological structure diagram, extracting features through a three-layer diagram convolutional network, and generating high-dimensional environment feature representation. And a deep reinforcement learning state space is constructed, and a multi-target reward function is designed. And initializing the deep reinforcement learning network by using [-0.1, 0.1] uniformly distributed random parameters to generate an initial path scheme. Optimizing through a dynamic planning algorithm, adjusting a node sequence according to a path length and a task dynamic threshold value, and calculating a target function value. And judging whether the current path scheme reaches the optimal balance point, if not, adjusting the weight of the reward function by using a gradient descent method, and regenerating the path scheme until the path scheme is optimal. And finally, converting the scheme into a waypoint coordinate and speed instruction, performing real-time monitoring during flight, and triggering re-planning when an obstacle exceeds a safety threshold, so as to achieve the purposes of safe flight of the unmanned aerial vehicle in a complex environment and the like.

The invention discloses a switching loss evaluation method and system based on a semi-soft switching modulation technology, and relates to the technical field of information. According to the method, parasitic inductance parameters and buffer capacitance parameters of a device are obtained, a resonant circuit working model is established, an initial voltage waveform and an initial current waveform are obtained by solving the model, and corresponding voltage stress and current stress are calculated; a parasitic inductance parameter and a buffer capacitance parameter of the device are optimized by using a genetic algorithm; adjusting the design of the buffer circuit according to the optimized device parameters, carrying out the simulation of the resonance process again, carrying out the frequency domain analysis of the optimized resonance voltage waveform and resonance current waveform, and optimizing the device parameters and the design of the buffer circuit. And finally, semi-soft switching modulation simulation is carried out, a temperature coefficient mapping relation between simulation switching loss and actually measured switching loss is constructed, an optimal design scheme of the device is determined, the switching loss of the device is effectively reduced, and it is ensured that the device works in a safe working area.

A method and apparatus for determining the safety inertia of a power grid system, and a computer device. The method comprises: determining a first safety inertia for ensuring safe operation of a power grid system when a frequency change rate after disturbance occurs in the power grid system exceeds a first threshold (S302); determining a second safety inertia for ensuring the safe operation of the power grid system when the frequency after the disturbance occurs in the power grid system is less than a second threshold (S304); and determining a target safety inertia according to the first safety inertia and the second safety inertia, wherein the target safety inertia is a safety inertia lower limit value for ensuring the safe operation of the power grid system (S306).

The invention relates to a temperature control method, device and equipment of semiconductor equipment and a storage medium. The method comprises the following steps: performing finite element mesh division and modal coordinate transformation on a plurality of temperature control areas of semiconductor equipment to obtain a temperature control area dynamic model; collecting measurement data of a temperature sensor and performing time-frequency domain transformation to generate a temperature prediction data sequence; gaussian mixture modeling is carried out to obtain prior distribution, and temperature parameter probability distribution is obtained; performing sub-domain division on the temperature control range to obtain a temperature inter-domain feature mapping matrix; and a temperature interval thermal coupling coefficient matrix is calculated based on the temperature control area dynamic model, a temperature control objective function is constructed in combination with the temperature prediction data sequence and the temperature inter-domain feature mapping matrix, and a temperature control quantity sequence is solved by adopting a model prediction control algorithm. According to the invention, the accuracy and dynamic response speed of temperature control are improved, and the stability of temperature control and the energy utilization efficiency are ensured.

A method for controlling motions of a quadruped robot based on reinforcement learning and position increment, including: acquiring motion environment information, quadruped robot attitude information, and foot sole position information; based on the acquired information, generating foot sole positions of the quadruped robot during motions within all preset time steps, and calculating a change of the foot sole positions in all the time steps; taking a maximum moving distance within a single time step as a constraint, and accumulating the time steps at the same time to obtain a foot sole position trajectory; and controlling the quadruped robot to perform corresponding actions based on the foot sole position track combined with a preset reward function, so as to keep motion balance of the quadruped robot.

A vehicle-body structure may include a floor panel, a dash panel extending upward from a vehicle front portion of the floor panel and partitioning a vehicle front portion of an occupant space, a cooler disposed on a vehicle front side of the dash panel, a control device disposed in the occupant space, and a supply pipe through which a heat exchange medium subjected to heat exchange at a heat exchanger is supplied to the control device. The heat exchanger may be closer to the control device than a powertrain PT mounted on an automobile.

The invention discloses a high-precision voltage measurement method and system based on multi-parameter adaptive compensation, and relates to the technical field of intelligent voltage measurement. The high-precision voltage measurement method and system based on multi-parameter adaptive compensation comprises the steps that S1, voltage signal data and disturbance source characteristic data are collected, preprocessing is completed, and an analysis basis is constructed; s2, analyzing voltage excursion in combination with disturbance current characteristics, and dynamically adjusting a compensation path; s3, evaluating a compensation correction effect, and driving a compensation output strategy in real time; and S4, comprehensively analyzing the offset characteristics and the correction result, judging an abnormal section and triggering adaptive adjustment. The problems that disturbance components cannot be comprehensively extracted from multiple parameters such as PWM modulation frequency, wire harness impedance and working condition load change and a compensation function cannot be reversely constructed in an existing method, and a measured value does not have stability are solved.

Techniques for controlling an end effector include a computer-assisted device having a drive system configured to actuate a moveable element to a first commanded position and a control unit coupled to the drive system. The control unit is configured to actuate, using the drive system, the moveable element to the first commanded position. The control unit is further configured to monitor a force or torque applied by the drive system to actuate the moveable element to the first commanded position, determine a force or torque limit for the drive system based on the monitored force or torque applied by the drive system in response to determining that the moveable element has reached a first position, and further actuate the moveable element to a second commanded position while limiting a force or torque applied by the drive system based on the determined force or torque limit.