359 results about "Fuzzy control algorithm" patented technology

The invention discloses a charging chip real-time power scheduling control method, and relates to the technical field of new energy automobile charging pile power scheduling, and the method comprises the following steps: S1, obtaining the operation parameters of charging equipment in real time, including the voltage fluctuation value of an input power grid, the output current of a charging interface, and the temperature of a charging chip; according to the method, the power grid voltage fluctuation, battery SOC / temperature and chip working condition multi-source data are collected in real time, a multi-target optimization model of dynamic weight distribution is combined, the service life loss of the battery is minimized, the charging efficiency and the power grid load are balanced at the same time, the user charging mode and the battery state difference are taken into consideration by adopting a priority scheduling strategy, and the charging efficiency is improved. Millisecond-level power fine control is achieved through cooperative adjustment of the PWM duty ratio and the switching frequency, personalized charging requirements are met, the overall energy efficiency is improved, a dual safety defense line is constructed through a graded load reduction protection mechanism and a fuzzy control algorithm, and a power distribution scheme is intelligently reconstructed when a power grid is abnormal or a battery is overheated.

The invention discloses a metal plate laser cutting control method, and relates to the technical field of laser cutting, material parameters, thickness information and cutting path data are obtained, a mixed enveloping rectangle algorithm is combined with a genetic algorithm to optimize a cutting sequence, and a path sequence containing idle stroke avoidance and nested graph priority is generated; constructing a laser parameter prediction model based on the material, thickness and path characteristics, and dynamically adjusting the power gradient; the slag splashing state is judged through data fusion of a capacitive sensor and an encoder, a quality feedback signal is extracted in combination with machine vision, and laser parameters are dynamically adjusted through a fuzzy control algorithm; wavefront distortion is monitored in real time, the correction frequency is adjusted according to the slag splashing state, and a deformable mirror is used for compensating the phase; when the quality is abnormal, historical parameter combinations are retrieved through a cosine similarity algorithm for joint compensation. According to the method, the path cutting efficiency is improved, and the problems of low efficiency of path planning and parameter adjustment lagging in the prior art are solved.

The invention provides an ecological circulation barrel-in-barrel culture data acquisition method and system, and relates to the technical field of intelligent control, and the method comprises the steps: carrying out the feature extraction of a historical data flow through a multivariable coupling analysis model, carrying out the mode matching through a preset environment threshold interval and a culture environment state matrix, and obtaining a culture environment state matrix; generating a water quality health degree evaluation index and an ecological imbalance early warning signal; and analyzing the water quality health degree evaluation index and the ecological imbalance early warning signal based on a fuzzy control algorithm, dynamically calculating a final feeding amount curve and a water change intensity function, and generating a regulation and control instruction set containing the feeding frequency, the bait particle size and the water pump rotating speed. According to the invention, real-time evaluation and accurate intervention of the water quality health state can be realized.

The invention discloses an automatic batching and stirring control system based on an industrial computer, belongs to the field of new wall material production control systems, and aims to solve the problems that the real-time performance is poor, and the influence of raw material characteristic changes on a fall value cannot be pre-judged. Weighing, humidity, infrared flow velocity, temperature, pressure, torque and airflow sensors are integrated, multi-dimensional parameters such as material weight, flow velocity, humidity and air pressure in a bin are monitored in real time, the influence of environmental interference on the sensors is dynamically compensated through multi-parameter collaborative feedback, the real-time performance and reliability of data acquisition are improved, a fuzzy PID control algorithm and a machine learning model are fused, and the real-time performance of the system is improved. A nonlinear mapping relation is established through a training data set, the initial valve opening degree and the fall value are predicted, errors are corrected in real time, dependence on historical data is reduced, the first-time use error of a new formula is reduced, the response time for coping with sudden environment changes is shortened, a single adjustable-caliber electromagnetic valve is adopted, the inner wall is coated with a nano anti-sticking coating, and the service life of the valve is prolonged. And the opening degree is dynamically adjusted in combination with a PID algorithm.

The invention provides a high-efficiency control method and system for a central air conditioner refrigeration machine room, and relates to the technical field of automatic control, and the method comprises the steps: 1, obtaining chilled water supply and return water temperature difference and flow data, and calculating the dynamic cold load demand of a building in combination with the personnel distribution thermal imaging data of each floor; and 2, on the basis of the dynamic cooling load requirement, a dynamic adjustment model for the number of running water chilling units is built, matching degree calculation is conducted on the actual cooling load value and the single refrigerating capacity of the water chilling units through a fuzzy PID control algorithm, and a final unit running combination scheme is generated. By calculating the cooling load requirement, dynamically adjusting the operation parameters of the water chilling unit, the chilled water pump and the cooling tower and balancing the equipment operation time, the system energy efficiency is effectively improved, the energy consumption and the operation and maintenance cost are reduced, and stable operation of the refrigerating system is guaranteed.

The invention discloses a target tracking method fusing visual perception and motion control. The method comprises the following steps: improving a YOLOv8 model and pre-training the improved YOLOv8 model; s2, preprocessing an image acquired by a camera, inputting the preprocessed image into the YOLOv8 model trained in the step S1, and outputting a target bounding box and a target center pixel coordinate; target center pixel coordinates are transmitted to a development board of a pre-burning algorithm program through a serial port, the development board is designed according to a stepping motor mathematical model, sine acceleration and deceleration serve as the basis, PID control, sliding mode control and fuzzy control algorithms are fused, and code burning is generated after in-loop simulation optimization; and the development board drives a stepping motor to adjust the posture of the holder according to the target center pixel coordinate control instruction, so that the target stops moving after being kept in the view center. The problems that a traditional YOLOv8 model is large in target recognition error under the complex background, PID control is prone to oscillation under the nonlinear working condition, buffeting exists in sliding mode control, and response lags when fuzzy control is independently used are solved.

The invention relates to a motor power self-adaptive control method and system based on multi-dimensional sensor data, and the method comprises the steps: collecting multi-dimensional signals, such as ground resistance, motor temperature and battery voltage, in real time, carrying out the self-adaptive filtering and noise reduction, analyzing the correlation of all parameters through a multivariable decoupling algorithm, and determining a power demand weight; when it is detected that the ground resistance is a dominant factor, the system generates a load feature vector through weighted fusion, a database is matched to determine an optimal power target value, and PWM output is dynamically adjusted through a fuzzy control algorithm; and a closed-loop feedback mechanism continuously optimizes control parameters to ensure that the system quickly responds to sudden change of ground resistance. According to the method, intelligent adaptation of the motor power is achieved, the problems that adjustment lags behind and multi-parameter coupling processing is insufficient in the traditional technology are effectively solved, the stability of the sweeping robot under the complex ground working condition is remarkably improved, and the service life of the motor and the service life of a battery are remarkably prolonged.

The invention discloses a control system and method for an automatic beer production line, relates to the technical field of automatic control, is used for solving the problems that state judgment is lagged and abnormal trend is difficult to identify in time, identifies electronic tags of key equipment through an RFID reader-writer, imports models and serial numbers into a database, and automatically associates operation parameters. The distributed sensors collect temperature, pressure, flow and vibration data in real time, the analysis unit calculates the operation deviation and the health degree, a multi-condition control strategy is configured through the programmable logic controller based on the health degree, a time window and a task priority algorithm are combined, real-time data and historical data are compared to recognize abnormity, and the real-time data and the historical data are analyzed. And a fuzzy control algorithm is fused to generate an adjustment instruction, the equipment state is automatically adjusted, time sequence modeling is utilized to analyze whole-process data, a start-stop strategy is formulated, energy distribution and process optimization are performed, and intelligent scheduling and self-adaptive optimization of the beer production line are realized.

The invention discloses an intelligent anesthesia depth regulation and control system based on a multi-modal biological signal, which relates to the technical field of anesthesia depth regulation and control and comprises a multi-modal biological signal acquisition module, a signal fusion processing module, an intelligent anesthesia depth analysis module, an intelligent regulation and control decision module and an intelligent control terminal. Multi-modal biological signals of a patient are collected in real time, multi-modal physiological signals such as electroencephalogram, electrocardio and blood oxygen are fused, intelligent analysis is performed in combination with a deep learning model and a fuzzy PID control algorithm, and in combination with a pharmacokinetic model, the individual difference of the patient can be considered, the anesthesia depth of the patient is accurately evaluated, and the accuracy of anesthesia is improved. Individual anesthetic dosage adjustment is completed, a basis is provided for accurate regulation and control of anesthetic, accurate closed-loop regulation and control of anesthesia depth are achieved, physiological changes of a patient can be responded in real time, the anesthetic dosage can be adjusted in time, and compared with a traditional manual regulation and control mode, the risk of knowing and excessive anesthesia in an operation can be reduced.

The invention discloses a robot track online compensation and precision control method and system based on multiple sensors, and belongs to the technical field of robot track control. The method comprises the following steps: acquiring target trajectory data and original data of each sensor, and performing time alignment on the original data of each sensor to generate a fusion data set comprising vibration acceleration data and pose data; performing time-frequency feature extraction based on the vibration acceleration data to obtain a dominant vibration frequency spectrum; constructing a mechanical transfer function model of the joint driving torque and the tail end vibration displacement; based on the mechanical transfer function model, constructing an adaptive notch filter to generate a feed-forward compensation sequence; according to the target trajectory data, the pose data and weight parameters, updated in real time, of the sensors, a trajectory fusion deviation value is obtained through calculation; and after the feedforward compensation sequence and the trajectory fusion deviation value are integrated, a joint driving current instruction is generated based on a fuzzy PID control algorithm. The robot trajectory control precision can be improved.

The invention relates to the technical field of laser control, in particular to a light spot consistency control method and system for DFB lasers, and the method comprises the steps: obtaining the current and temperature of each DFB laser at each moment in each control period; calculating the burr saliency, the temperature rise drift coefficient, the temperature drop drift coefficient and the heat source interference value of each DFB laser in each control period; and determining expansion and contraction factors of a positive universe and a negative universe in the fuzzy control algorithm, and controlling the temperature of the DFB laser in real time so as to control the light spot consistency of the DFB laser. According to the method and the device, by selecting the proper telescopic factor and dynamically adjusting the discourse domain range of the fuzzy control algorithm, the response speed of temperature control of the DFB laser is improved, the temperature of the DFB laser is controlled more accurately, and light spot consistency control is realized.

The invention relates to the technical field of electrocatalytic oxidation devices, and discloses an electroplating rinse sewage complex breaking electrocatalytic device based on titanium-based nano conductive ceramics, which comprises an oxidation pond and an acquisition module, the acquisition module acquires catalytic liquid information in real time, and the catalytic liquid information comprises components and state data of a catalytic liquid. And the catalysis module is responsible for treating a catalytic liquid and destroying a complex by utilizing an electro-catalysis reaction. The central control module analyzes complex components of a catalyst through a convolutional neural network (CNN) and a recurrent neural network (RNN), and dynamically adjusts electro-catalysis parameters on the basis of a fuzzy control algorithm in combination with historical data and real-time information so as to optimize the catalytic effect. And the early warning module monitors the changes of the catalytic liquid and the electro-catalysis parameters, judges whether early warning needs to be given out or not by comparing the changes with a preset threshold value, and takes corresponding measures according to the risk level. Through real-time data analysis and intelligent control, the accuracy and efficiency of the catalysis process are improved, and the safety and stability of the treatment process are ensured.

The invention discloses a diamond cutting tooth self-adaptive vibration suppression method based on a fuzzy control algorithm. The diamond cutting tooth self-adaptive vibration suppression method comprises the following steps that S1, a multi-channel signal data set in the diamond cutting tooth machining process is collected in real time; s2, acquiring a preprocessed multi-channel signal data set; s3, carrying out integration to form a feature vector containing multi-dimensional dynamic features; s4, inputting the feature vectors into a fuzzy control module, and performing fuzzy processing on the feature vectors of the channel signals to realize fuzzy quantization of the processing state; s5, generating a control output quantity by using a fuzzy reasoning algorithm according to the fuzzy quantization result, and converting the control output quantity into an executable process control instruction through a defuzzification algorithm; and S6, the process control instruction is fed back to a machining execution mechanism. The method has higher sensitivity and adaptability in unstable machining state recognition, the judgment accuracy of the initial vibration stage can be remarkably improved, and the judgment basis of a control system under complex disturbance is enhanced.

The invention discloses a working area personnel positioning method and system based on a data communication technology, and relates to the technical field of personnel positioning, and the method comprises the steps: estimating the position of a worker in real time through the fusion of an RFID tag and a multi-band signal, and the weighted fusion of a triangulation positioning algorithm and a dynamic signal; according to the method, extended Kalman filtering, multi-target tracking and particle filtering technologies are combined, signal interference is compensated, positioning precision is optimized, a fuzzy control algorithm is adopted for safety early warning, edge calculation and cloud calculation are combined, historical data are analyzed, and the moving trend of workers is predicted. According to the invention, by combining RFID tags, multi-band signals, dynamic signal fusion, multi-target tracking, particle filtering and fuzzy control technologies, high-precision and real-time personnel positioning and safety management are realized, the position of a worker can be accurately estimated, signal interference, attenuation and reflection effects in an environment can be effectively compensated, an early warning strategy is dynamically adjusted, and the working efficiency is improved. And the safety of the working area is improved.

The invention provides a field emission thruster extraction electrode indium deposition cleaning temperature control method and system, and relates to the technical field of space electric propulsion, and the method comprises the steps: obtaining multi-source temperature data and electric field intensity data of a target region, and carrying out the time-space fusion processing of the two data, and generating target feature information reflecting the deposition state of an indium material; based on the feature information, a fuzzy PID control algorithm is adopted to generate a power control signal, and then the embedded heating unit is adjusted; monitoring electrothermal characteristics to obtain thermal impedance parameters, and further generating heat flow distribution data; analyzing heat flow data by using a state observer to predict an indium deposition growth trend to obtain deposition rate information, finally determining a cleaning control strategy according to the growth rate, and controlling temperature change in a non-uniform heating mode to enable the indium material to reach a phase change state. According to the invention, the reliability and maintenance efficiency of on-orbit long-term operation of the field emission propeller are improved.

The invention discloses a heat pump water heater low-temperature freezing oil return control method and system based on dynamic operation parameter adjustment, and the method comprises the following steps: monitoring the evaporator outlet refrigerant temperature, the compressor air return port temperature and the environment temperature in real time through a sensor, and calculating the temperature difference as a core control parameter; the opening degree of an electronic expansion valve and the rotating speed of a fan are dynamically adjusted through a fuzzy control algorithm in combination with the environment temperature and the compressor running frequency, and the low-temperature oil return stability of the system is maintained; when the core temperature difference exceeds a set threshold value, an oil return compensation mode is triggered, and the circulating fluidity of lubricating oil is enhanced by improving the frequency of a compressor and adjusting the opening degree of a bypass valve of a condenser; in the oil return compensation process, closed-loop adjustment is conducted on the exhaust temperature of the compressor through a PID control algorithm, and the operation safety of the system is ensured. The operating parameters are dynamically adjusted, the parameters such as the environment temperature and the system load are monitored in real time, and the control parameters are dynamically adjusted according to the parameters, so that the oil return requirements under different working conditions are met.

The invention relates to the technical field of power grid stability analysis, in particular to a mechanical vibration micro-grid electromechanical coupling system stability analysis method, which comprises the following steps of: detecting a tooth surface contact radius, a relative speed and a Young modulus to generate a contact stiffness initial value, correcting nonlinear stiffness by interval difference, and calculating the stability of a micro-grid electromechanical coupling system. The method comprises the following steps: calculating a coupling response vector by combining rotor displacement and bearing clearance, inputting a Lyapunov exponent method to solve an exponent vector, constructing a model length ratio to detect derivative characteristics, extracting a multidimensional state vector in a positive value period and the coupling response vector to generate a compensation action, and constructing an FPGA simulation path injection disturbance execution error feedback back-transmission fuzzy control algorithm. According to the method, a contact stiffness dynamic correction and nonlinear difference method is introduced, six-degree-of-freedom displacement and bearing clearance parameters are combined, an electromechanical coupling model is established, a stability boundary is recognized through Lyapunov regression, a critical state is detected through derivative features, and multi-dimensional state vector fuzzy control compensation is fused. And the response and the immunity are optimized by combining FPGA simulation and a disturbance mechanism.

The invention discloses a complex wind field simulation method suitable for a small and medium-sized unmanned aerial vehicle wind resistance test, and relates to the technical field of intelligent wind control, and the method comprises the steps: based on a plasma exciter control instruction set, generating a directional micro vortex group in a wind tunnel through a plasma exciter array, meanwhile, the spatial distribution of the directional micro vortex group is regulated and controlled by adopting an ultrasonic interference method, and a three-dimensional turbulent flow field is generated; an unmanned aerial vehicle anti-risk test is executed, anti-wind performance data is collected and combined with PIV to verify the stability of the nest ring structure, and dynamic adjustment is carried out through a fuzzy PID control algorithm; and constructing a judgment matrix based on the adjusted wind resistance test data, calculating a wind resistance performance index of the unmanned aerial vehicle by adopting a dynamic time warping algorithm, and generating a performance evaluation report. According to the invention, through vortex ring stability feature extraction and fuzzy PID dynamic adjustment based on the deep space-time convolutional network, closed-loop stability control in a complex wind field environment is realized.

The invention discloses a frequency modulation control method and system for a thermal power generating unit, and relates to the technical field of frequency modulation control, and the method comprises the steps: collecting a frequency modulation instruction signal of a power grid, decomposing the frequency modulation instruction signal, and obtaining a plurality of intrinsic mode function components and residual components; performing spectral analysis on each intrinsic mode function component, marking the component of which the main frequency exceeds a high-frequency disturbance frequency threshold as a high-frequency disturbance component, and calculating a fluctuation amplitude and a change rate; a thermal system control instruction is generated through a PID control algorithm, the coal feeding amount and the main steam pressure are adjusted, and an auxiliary compensation control instruction is generated for the high-frequency disturbance component through a fuzzy control algorithm; a thermal system control instruction and an auxiliary compensation control instruction are converted into operation parameters of a thermal power generating unit control mechanism and issued for execution, when the control effect deviation continuously exceeds a deviation threshold value, an optimization process is triggered, and the frequency modulation stability and the equipment safety of a unit in the environment that new energy is accessed to a power grid in a high proportion are remarkably improved.

The invention relates to a method and a system for manufacturing a nano modified polyethylene electronic wire in the field of intelligent manufacturing equipment industry. The method comprises the following steps of: extracting temperature fluctuation characteristics from temperature distribution in a plasticizing process, dynamically adjusting parameters of a cooling system by adopting a fuzzy control algorithm aiming at the fluctuation characteristics, and determining temperature consistency in a forming stage; temperature consistency data in the forming stage are obtained, a preset wire diameter tolerance threshold value is combined, if the temperature consistency is lower than the threshold value, the extrusion speed is adjusted through a servo motor, and the optimized wire diameter precision is obtained; melt rheological parameters are extracted from the wire diameter precision data, melt heat conduction uniformity is calculated by adopting a heat conduction model of a nano-modified polyethylene material, and the formation strength of an interface permeation network is determined; and rheological property data are obtained, a real-time cooperative control algorithm is adopted, coupling parameters of melt pressure and temperature are dynamically adjusted, and optimized extrusion molding process parameters are obtained.

The invention relates to the technical field of transmission shaft machining, and discloses an intelligent clamping method and system for universal joint transmission shaft machining. The method comprises the steps that the geometric dimension, the form and location tolerance number, vibration signal data, unbalance data and pressure distribution data of a transmission shaft are obtained; performing precision correction based on preset machining precision to obtain transmission shaft positioning parameters; adjusting parameters in real time through an adaptive control algorithm to obtain real-time positioning parameters; performing feature extraction to obtain vibration spectrum features; outputting a vector diagram to obtain an unbalanced vector diagram; performing Kalman filtering processing to obtain filtering parameters; calculating by adopting a fuzzy control algorithm to obtain a vibration compensation amount and an unbalance correction amount; performing data processing to obtain a corrected pressure matrix; inputting into a pre-trained neural network model to obtain a predicted risk level; and risk prediction and judgment are carried out, clamping strategy adjustment is carried out, a corrected clamping strategy is obtained, machining of the transmission shaft is carried out, and the machining accuracy is improved.

The invention relates to a ship unloader material transfer process adaptive flexible dust suppression system, which comprises an environment sensing module, an integrated multi-parameter dust concentration sensor array, a temperature and humidity sensor and a material characteristic detection unit, and is used for collecting dust concentration, environment temperature and humidity and material viscosity / granularity data in a transfer area in real time; the data processing module is based on a dynamic model library constructed by an embedded industrial computer, comprises a fuzzy control algorithm and a lightweight neural network, and is used for fusing multi-source sensing data and generating a dust suppression strategy; the flexible dust suppression execution module is composed of a variable-angle high-pressure atomizing nozzle array, a dynamic pressure regulating valve group and a flexible sealing cover body; and the self-adaptive control module is internally provided with a non-linear mapping table based on the material transfer speed and the dust generation amount, and real-time adjustment of the nozzle pressure and the spraying angle is achieved through PID and expert rule mixed control. Accurate dust suppression for different materials is achieved, and the reliability and environmental protection performance of the system are improved.

The invention discloses an intelligent collaborative operation large-weight test piece dynamic self-adaptive connecting device which comprises a mechanical structure and a control system, the mechanical structure comprises a connecting clamp, an adjusting mechanism and a driving device, and the control system comprises a sensor, a controller and an actuator. An intelligent control algorithm adopts a mode of combining a fuzzy control algorithm and a neural network algorithm, and a plurality of connecting devices communicate through a wireless network to realize collaborative operation. Automatic connection is adopted, large-weight test pieces are rapidly and accurately connected, the connection efficiency is improved, manual operation is reduced, and potential safety hazards are reduced. The position and the posture of the heavy-weight test piece are monitored in real time through the sensor, the connecting device is controlled to automatically adjust the position and the posture, accurate connection is achieved, and the connecting precision is improved. The connecting device can automatically adjust the position and the posture so as to adapt to the dynamic change of the large-weight test piece, and the connecting reliability is improved.

Disclosed in the present application are a method and apparatus for regulating the power of an offshore wind farm energy storage system on the basis of the state of charge. The method in the present application comprises: acquiring a power grid frequency and the state of charge of an offshore wind farm energy storage system, and on the basis of the power grid frequency and the state of charge, acquiring a power grid frequency deviation and a state-of-charge recovery demand, respectively; determining whether the power grid frequency deviation is within a preset power grid frequency dead band, if the power grid frequency deviation is within the power grid frequency dead band, in view of the power grid frequency deviation and the state-of-charge recovery demand, acquiring an inertia power regulation and control amount of the energy storage system by means of a fuzzy control algorithm combined with a preset adaptive inertia frequency control model, otherwise, in view of the power grid frequency deviation and the state-of-charge recovery demand, acquiring the inertia power regulation and control amount by means of the adaptive inertia frequency control model; and on the basis of the inertia power regulation and control amount, regulating and controlling the inertia power of the offshore wind farm energy storage system. By means of the present application, the level of refinement and accuracy of a regulation and control process for an energy storage system can be improved.

The invention relates to the technical field of water conservancy projects, in particular to a side-hung gate water distribution method and system based on multi-parameter adjusting.The method comprises the steps that multi-parameter data in side-hung gate water distribution is obtained, and a temperature compensation coefficient is introduced to preliminarily adjust the obtained multi-parameter data; carrying out preliminary flow distribution adjustment based on the adjusted multi-parameter data, carrying out fuzzy control adjustment by utilizing a flow distribution proportion, carrying out flow distribution according to a preliminary flow distribution result, carrying out dynamic optimization adjustment on the flow distribution result, and outputting an optimized control signal to an execution mechanism to complete flow distribution adjustment. According to the method, the opening height of the downward opening type gate is adjusted through the fuzzy control algorithm introducing the dynamic weight factor, the factors such as the liquid level change trend, the deviation between the current liquid level and the target liquid level and the weir water head height change rate are comprehensively considered, flow distribution and adjustment are more flexible and intelligent, and the problem of uneven flow distribution caused by the liquid level difference is effectively solved.

The invention relates to the technical field of ultrasonic riveting, in particular to a 224G high-speed wire harness assembling method and system based on ultrasonic riveting, and the method comprises the steps: carrying out the pretreatment of a high-speed wire harness raw material, and obtaining a pre-riveted wire harness; aligning the pre-riveted wire harness with a pre-constructed target connector to obtain a to-be-riveted wire harness; riveting the to-be-riveted wire harness by using the ultrasonic parameter value, the environment temperature value and the riveting time, and monitoring the to-be-riveted wire harness during riveting in real time based on the riveting monitoring instruction to obtain a compression deviation value and an energy absorption value; based on the compression deviation value and the energy absorption value, acquiring an updated ultrasonic frequency value by using a fuzzy control algorithm, and acquiring a pre-confirmed high-speed wire harness by using the updated ultrasonic frequency value; and performing quality detection on the pre-confirmed high-speed wire harness to obtain a target high-speed wire harness, and realizing the assembly of the high-speed wire harness based on the target high-speed wire harness. According to the invention, high-precision assembly of the high-speed wire harness can be realized by utilizing ultrasonic riveting.

The invention relates to the technical field of digital health, in particular to a personalized rehabilitation exercise method for rheumatoid arthritis patients based on a BCW theory, which comprises the following steps: acquiring joint angle change and calculating a pain delay response coefficient, detecting fluctuation of supporting force and stabilizing force to obtain a joint load tolerance value, analyzing respiratory coordination to generate a respiratory coordination index, and performing rehabilitation training on the respiratory coordination index. The method comprises the steps that a joint angle sensor and pain intensity data are analyzed, a BCW capacity factor weight value is generated in a weighted mode, a fuzzy control algorithm is input to conduct hierarchical mapping adjustment on action amplitude frequency and rest intervals, and exercise adaptability feedback data are generated through monitoring completion degree and pain feedback. The exercise intensity is dynamically adjusted in real time through a data model, a personalized rehabilitation scheme is automatically optimized, the problems that subjective feedback is relied on, and physiological changes cannot be responded in time are solved, more accurate exercise amount adjustment is provided, the situation that the joint burden is increased due to improper exercise intensity is avoided, and the rehabilitation process is effectively promoted.

The invention relates to the technical field of automobile manufacturing, in particular to a multi-focus dynamic regulation and control method for laser welding of a truck frame, which comprises the following steps of: S1, carrying out panoramic digitalization on a to-be-welded part of the truck frame through a three-dimensional laser scanner, and constructing a three-dimensional digital model; millisecond-level dynamic adjustment of the laser multi-focus number, spatial distribution and energy ratio is achieved through a programmable optical system and a fuzzy control algorithm, welding deviation is corrected in real time according to a multi-source sensor and a closed-loop feedback mechanism, and therefore it is guaranteed that the laser focus is accurately matched with the geometric characteristics of a welding seam and the real-time welding state; and the quality problems of abnormal temperature of a molten pool, geometric deviation of welding seams and the like are effectively avoided, the precision, stability and complex working condition adaptability of laser welding of the truck frame are remarkably improved, and meanwhile the manual intervention cost is reduced.

The invention discloses a decision control system and method based on temperature field and atmosphere analysis, and relates to the technical field of intelligent control. A monitoring module in the system obtains a temperature set and a gas concentration set; the trend analysis module constructs a three-dimensional model and establishes a coordinate system, a variation function is combined with a Kriging equation to supplement a temperature set to generate an expanded temperature set, the three-dimensional model is discretized into a plurality of nodes and is matched with points in the expanded temperature set through nearest neighbor search, a heat conduction equation and a convection boundary are set, and a finite element matrix equation set is constructed; solving to obtain a temperature field model and carrying out statistics to generate a temperature trend curve; a decision module compares the temperature trend curve, the gas concentration set and a process standard to obtain an abnormal section number, and analyzes a section temperature difference and a concentration error vector of the abnormal section number by adopting a fuzzy PID control algorithm to generate an adjustment vector; and the execution module performs automatic adjustment based on the adjustment vector, so that intelligent decision adjustment based on temperature field and atmosphere conjoint analysis is realized.

The invention discloses a motor temperature control method and system based on hydraulic transmission and fuzzy control. The method comprises the steps that current temperature data are collected in real time through temperature sensors arranged in a plurality of key temperature areas in a driving motor and preprocessed; predicting the temperature change trend of the key temperature zone by adopting a self-learning fuzzy control algorithm, and generating a hydraulic coarse tuning signal and an electromagnetic fine tuning signal; controlling a hydraulic actuating mechanism to adjust the flow of a cooling medium to realize preliminary cooling, and controlling an electromagnetic fine adjustment mechanism to adjust the flow of the cooling medium corresponding to a local area in the key temperature area to perform temperature compensation; and uploading the regulated current temperature data to a cloud platform in real time, updating control parameters, and feeding back the control parameters to a self-learning fuzzy control algorithm to form closed-loop control. According to the invention, real-time dynamic balance regulation and control of the temperature of each key temperature zone in the driving motor can be effectively realized, and local thermal load changes are quickly responded, so that the overall temperature of the driving motor stably reaches a preset standard.