271 results about "Pid control algorithm" patented technology

The invention relates to the technical field of electrochemical machining, in particular to an electroplate liquid additive automatic supply control method based on conductivity monitoring data. The method comprises the steps that the temperature, the original conductivity and the carbonate concentration of electroplating liquid are obtained, an activation energy coefficient is determined based on the change trend of the original conductivity and the temperature, dynamic thermodynamic decoupling treatment is conducted on the original conductivity, and the net conductivity of the electroplating liquid is generated; according to the cumulative variation of the net conductivity in the historical time period and the total amount of the additive in the historical time period, the transmission inertia factor of the electroplating liquid is calculated in combination with the carbonate concentration, and the retardation risk index is determined based on the evolution trend of the transmission inertia factor, so that a PID control algorithm is reconstructed, and the supply amount of the additive is obtained; and performing automatic replenishment control based on the replenishment amount. According to the method, the accuracy of automatic supply control is improved by evaluating the degradation state of the bath solution components and self-adaptive integral saturation suppression.

The invention provides a glyceryl triacetate production parameter control method and system based on reinforcement learning, and relates to the technical field of optimization control methods, and the method comprises the steps: obtaining the production parameters of glyceryl triacetate; based on the kinetic model, constructing a kinetic equation of the esterification reaction of glycerol and acetic acid; constructing a digital twinborn simulation environment of the glyceryl triacetate production process; defining a reinforcement learning framework by taking a digital twin simulation environment as a scene; according to the reinforcement learning framework, taking the Elman neural network as a state predictor, and predicting the state of the glyceryl triacetate; solving the reinforcement learning framework through an MO-MPO algorithm, and determining an optimal control strategy and an optimal production parameter sequence corresponding to the optimal control strategy; judging whether the process capability index is smaller than a process capability index threshold value or not; if yes, continuing to solve the reinforcement learning framework; otherwise, outputting an optimal production parameter sequence; and controlling the optimal production parameter sequence through a PID (Proportion Integration Differentiation) control algorithm.

The invention provides a centralized dust control method and system for a driving working face, and the method comprises the steps: collecting actual measurement environment parameters of the driving working face in real time through a sensor, and carrying out the preprocessing of the actual measurement environment parameters, and obtaining the preprocessed actual measurement environment parameters; acquiring a target environment parameter of the driving working face, and determining an absolute value of an environment parameter difference value according to the target environment parameter and the preprocessed actually measured environment parameter; according to the absolute value of the environmental parameter difference value, an execution mechanism adjustment instruction value is determined through a PID control algorithm; and controlling the driving working face centralized dust control system based on the execution mechanism adjustment instruction value. Wherein the executing mechanism adjusting instruction value comprises the angle variation of a guide vane in the negative-pressure air duct body, the opening size variation of an air distributor in the negative-pressure air duct body and the rotating speed of a fan. According to the technical scheme provided by the invention, the safety and the environmental protection property of the tunneling operation are improved.

The invention relates to the field of oil field heating furnace control, and discloses an oil field heating furnace intelligent digital implementation method and control method.The control method comprises the following steps that S1, a temperature sensor is used for monitoring the temperature of an oil field heating furnace in real time; s2, calculating a temperature error between the upper limit and the lower limit of the real-time temperature and the set temperature according to the monitoring data of the temperature sensor; s3, a self-adaptive PID control algorithm is applied, and heating power is calculated based on the temperature error; and S4, dynamically adjusting the heating power to control the temperature of the oil field heating furnace. The precision and stability of temperature control can be improved, the oil field heating furnace can control the target temperature more accurately, and the production efficiency is improved. Meanwhile, the self-adaptive PID control algorithm can automatically adjust parameters according to actual working conditions and environment changes, the adaptability and robustness of the system are improved, and the requirements for manual intervention and adjustment are reduced. In addition, the stable and efficient heating process can be achieved by dynamically adjusting the heating power, and energy and cost are saved.

The invention discloses a closed-loop control method for a hydraulic control butterfly valve of a PCCP (prestressed concrete cylinder pipe) long-distance high-pressure water conveying pipeline, and belongs to the technical field of long-distance high-pressure water conveying pipeline control. The problems that in the prior art, due to manual scheduling or single-point PID control, a long-distance PCCP water conveying system has response lag and lacks global cooperation, the water attack risk is difficult to effectively deal with, and the optimal overall energy consumption of the system cannot be considered are solved. According to the invention, by constructing a hierarchical control architecture in which a distributed measurement and control network is coordinated with a central supervision control and data acquisition system platform, a variable-parameter PID control algorithm is built in an equipment PLC, so that millisecond-level identification and active suppression of a sudden water attack working condition are realized; a hydraulic simulation model and a multi-objective optimization algorithm are deployed in a central supervision control and data acquisition system master station, and a whole-line optimal pressure set value is solved through iterative calculation and is issued to each PLC for execution, so that the system energy consumption minimization is realized on the premise of ensuring the pipeline safety.

The invention relates to the technical field of refrigeration equipment control, in particular to a wine cabinet compressor self-adaptive control method and system based on environmental parameters. The method comprises the steps that the external environment temperature, the internal actual temperature and the target storage temperature set by a user of the wine cabinet are collected in real time; an environment thermal potential energy index representing external environment thermal invasion intensity is constructed by calculating static deviation characteristics and dynamic change rate characteristics of the environment temperature; and correcting a proportionality coefficient of a PID control algorithm in real time based on the environmental thermal potential energy index, calculating a compressor control quantity through the PID algorithm in combination with a preset integral coefficient and a differential coefficient, mapping the compressor control quantity into a target operation frequency, driving the wine cabinet compressor to operate, and realizing self-adaptive control of the wine cabinet compressor based on the environmental parameters. According to the method, the environment thermal load change can be actively sensed, the control lag is eliminated, the smoothness of steady-state operation is considered while the thermal shock is inhibited, and the control precision of the wine cabinet compressor is improved.

The invention discloses a building environment real-time regulation and control method, device and equipment based on the Internet of Things and a medium, and relates to the technical field of intelligent building control. Light, temperature and humidity data of a building environment are collected in real time through Internet of Things sensing equipment, frequency domain features of an environment data set are extracted through Fourier transform, classification and recognition are carried out in combination with a preset environment regulation and control model, and a dynamic weight algorithm is adopted to optimize and generate an environment control signal. And through a self-adaptive PID control algorithm of Kalman filtering denoising and reinforcement learning optimization, a deviation integral is calculated in real time to generate a precise regulation and control instruction, and environment regulation and control equipment is synchronously driven. Frequency domain feature analysis, dynamic weight adjustment and adaptive control technologies are fused, multi-parameter coordinated regulation and control of the building environment are realized, and the real-time performance, the stability and the energy efficiency ratio of environment regulation and control are effectively improved.

The invention relates to the technical field of image processing, and discloses an AI-based lithium manganate process parameter regulation and control method and system. The method comprises the following steps: collecting lithium manganate preparation whole-process technological parameters through an infrared temperature measurement array, a pH sensor and an electrochemical workstation to establish a database, training and generating a technological parameter predictor by using an Actor-Critic deep reinforcement learning algorithm, quantifying a deviation degree output early warning level based on a fuzzy comprehensive evaluation algorithm, and determining the lithium manganate preparation whole-process early warning level according to the deviation degree output early warning level. And starting a self-adaptive PID control algorithm to generate a multi-equipment coordination control instruction set, synchronously driving an inclined mixer, a roasting kiln fan and an electrolytic bath temperature control system to adjust, detecting the product quality through an X-ray diffractometer, and feeding back an optimization control instruction. According to the invention, the process parameter control precision and the product quality stability in the lithium manganate preparation process are improved.

The invention belongs to the technical field of pipeline welding, and relates to a pipeline welding operation position deviation real-time monitoring and correcting system and method. The method comprises the following steps: fitting a central axis through a pipe end centering module to calculate a residual error and converting the residual error into a welding gun tool coordinate system to obtain a pose compensation amount; constructing a displacement change track, and screening a low-frequency axis offset coordinate sequence based on a pipeline mechanical motion inertia characteristic setting direction and acceleration constraint condition; and after the space offset is superposed with the compensation amount, a correction instruction is generated through a PID control algorithm. The problems of welding gun shaking caused by high-frequency noise interference in suspended pipeline welding, error accumulation and amplification caused by initial fixed deviation and dynamic deviation mixed compensation, and control overshoot or slow convergence caused by large rigid response difference of pipelines of different specifications are solved. Static residual error pre-compensation and dynamic offset decoupling are achieved, synchronous following of the real displacement trend is ensured, misjudgment interference is effectively avoided, and the stability and trajectory tracking precision of the welding process under the complex working condition are improved.

The invention provides a performance simulation test method and system for a pumped storage power station. The method comprises the following steps: acquiring characteristic data of the pumped storage unit, and performing characteristic line method analysis and dynamic impedance modeling to obtain a nonlinear hydraulic system mathematical model; constructing a synchronous generator model and an excitation system model, and constructing an AGC control model and a primary frequency modulation control model; generating a simulation system; generating a coordination control strategy by using a variable gain PID control algorithm based on a fuzzy control theory, and a dynamic weight distribution mechanism and a feed-forward compensation mechanism of an AGC instruction and a primary frequency modulation response; and executing a simulation test of a normal operation condition, a large disturbance condition and a condition switching process, and generating a performance test result. Through accurate modeling and coordinated control strategies, the problem of mutual interference between AGC and primary frequency modulation is solved, the stability and response speed of the pumped storage power station in power grid frequency regulation are improved, and the frequency modulation performance of a unit under different working conditions can be comprehensively evaluated.

The invention relates to the technical field of coating die head control methods, in particular to an ML-based coating die head and slurry pump feedforward prediction control method, which comprises the following steps: collecting coating process parameters in real time to construct an input feature vector; a PID control algorithm is used for calculating the basic adjusting quantity according to the partition surface density deviation and the average surface density deviation; inputting the basic adjustment quantity and the input feature vector into a machine learning prediction model to obtain a surface density change prediction value; calculating a prediction trust coefficient in combination with historical prediction accuracy, and generating a feed-forward correction quantity based on the deviation between a surface density change prediction value and a target value and the prediction trust coefficient; and superposing the basic regulation quantity calculated by the PID control algorithm and the feedforward correction quantity, and then outputting a final control instruction. According to the method, through feedforward fusion of machine learning prediction and PID control, the hysteresis quality of traditional PID control is effectively overcome, waste materials caused by abnormal surface density are reduced, and the stability and consistency (the CPK value is higher and the COV value is lower) of the coating process are remarkably improved.

The invention provides a closed-loop control method for viscosity in a pregelatinized starch production process, and relates to the technical field of intelligent control, which comprises the following steps: acquiring real-time viscosity data and real-time temperature data of pregelatinized starch slurry, calculating a viscosity deviation value, calculating a temperature compensation coefficient by adopting an improved Arrhenius viscosity-temperature equation, and calculating the viscosity deviation value according to the temperature compensation coefficient. A compensated viscosity deviation value is obtained, the compensated viscosity deviation value and the change rate of the compensated viscosity deviation value are input into a double-variable fuzzy controller, and the stirring speed adjusting amount is calculated according to a fuzzy rule; according to the compensated viscosity deviation value and the change rate of the viscosity deviation value, an incremental PID control algorithm is adopted to calculate the adjusting amount of the opening degree of a steam valve, and cooperative control over steam heating and mechanical shearing is formed. According to the method, accurate compensation of the nonlinear relation between the viscosity and the temperature is achieved, by introducing a dynamic correction factor and a multi-protection mechanism, adaptability and stability under complex working conditions are enhanced, and the regulation and control efficiency and the product quality stability in the pregelatinized starch production process are effectively improved.

The invention discloses a cooling module performance testing device and method for an unmanned aerial vehicle motor controller, and the method comprises the steps: determining the position of a to-be-tested cooling module through a sample positioning unit for testing, and collecting the temperature and air cooling environment conditions of the to-be-tested cooling module through a multi-mode sensing test adjustment unit. And the multi-mode sensing test adjusting unit performs multi-physical-quantity coupling control by adopting a PID control algorithm, and performs performance test on the to-be-tested heat dissipation module. The system has the advantages of accurate simulation, multi-mode sensing and self-feedback adjustment, can simulate the working condition of the heat dissipation module for the motor controller of the unmanned aerial vehicle at high altitude, measures the performance of the heat dissipation module for the motor controller of the unmanned aerial vehicle in real time, and automatically adjusts simulation parameters according to the feedback of multiple sensors.

The invention discloses an oil cylinder sealing optimization system based on electromagnetic induction regulation and control, and the system comprises an electromagnetic induction unit, a coil of which generates an alternating magnetic field in a sealing area, and acts on a magnetic sensitive composite material sealing element; the sensor unit monitors the leakage rate, the temperature and the pressure in real time; the control unit executes a self-adaptive PID control algorithm, dynamically adjusts PID parameters according to sensor data, and outputs a PWM signal to control the electromagnetic induction unit so as to optimize the sealing performance in real time; the controllable alternating magnetic field is applied to the magnetic-sensitive sealing element through the electromagnetic induction unit, the elastic modulus and the contact pressure of the magnetic-sensitive sealing element are regulated in real time through the magnetocaloric or magnetostrictive effect, meanwhile, key parameters such as leakage, temperature and pressure are monitored in real time in combination with a sensor, and the sealing state is rapidly responded and dynamically adjusted through a self-adaptive PID algorithm in the control unit. Oil cylinder sealing can be self-optimized according to working condition changes, and the problem that traditional static sealing cannot adapt to dynamic working conditions is solved.

The invention provides an automatic control method and system for cooling water of a photovoltaic glass calender, relates to the field of calender cooling water control, and solves the technical problems of control lag, low precision and poor stability caused by the fact that an existing calender cooling water system mostly depends on manual setting of fixed parameters and lacks dynamic response capability to working condition changes. The method comprises the following steps: acquiring current working condition parameters of a calender, and analyzing the running frequency of a circulating water pump of the calender by adopting a PID control algorithm; calculating the overall comprehensive temperature of the calender based on the surface temperature data of the plurality of areas; the circulating water pressure and flow of the calender are monitored in real time, and when the circulating water pressure or flow exceeds a corresponding preset threshold value, the operation frequency of the calender is recovered to the normal operation frequency through the AI fault-tolerant control model. The cooling water control device is used in the cooling water control process of the photovoltaic glass calender.

This invention relates to the field of semiconductor technology, and more particularly to a method, apparatus, and device for controlling the intrinsic temperature of a wafer. The method involves extracting features from amplitude ratio and phase difference spectra based on a preset time sequence to obtain a corrected growth rate; calculating the process formulation change sequence according to a preset thermal inertia equation and a preset growth kinetic relationship to obtain feedforward compensation power; calculating the corrected growth rate according to a preset multivariable PID control algorithm to obtain feedback regulation power; and solving the feedforward compensation power and feedback regulation power according to a preset decoupling formula to obtain the intrinsic temperature power control command for the wafer. By generating feedback regulation power through the multivariable PID control algorithm, and reducing temperature zone interference through decoupling, the method achieves zoned temperature control, improves the system's anti-interference capability, ensures the stability of epitaxial layer quality, enhances the consistency and reliability of MOCVD processes, and provides support for the large-scale production of semiconductor devices.

The present application belongs to the technical field of rare earth production, and relates to a rare earth production control method and system. The method comprises the following steps: obtaining control parameter data of a rare earth production process and corresponding rare earth product quality data; screening the optimal rare earth product quality data, and obtaining the control parameter data corresponding to the group of rare earth product quality data for preprocessing to obtain first control parameters; taking each control parameter in the first control parameters as a control reference parameter of a current production cycle, and outputting multiple groups of feeding amounts at the next moment through a PID control algorithm; averaging the multiple groups of feeding amounts at the next moment obtained based on different characteristic quantities of the same control parameter to obtain an average feeding amount; and weighting and averaging the average feeding amounts corresponding to different control parameters to obtain a final feeding amount at the next moment. The method obtains feeding amount control parameters, can effectively improve the quality of rare earth production, and reduce the carbon content and iron content in the rare earth product.

The application relates to the technical field of automation control, and particularly discloses a real-time trajectory generation and tracking control method based on man-machine cooperation, which comprises the following steps: dividing the operation trajectory of a working device of a excavator into a depth section and a trajectory section based on an operator input working mode, a target slope and a target depth; real-time solving of a target joint rotation angle of the trajectory section based on acquired current joint rotation angle information and in combination with a preset constraint condition; mapping the target joint rotation angle to a driving space of a hydraulic cylinder to obtain a target oil cylinder displacement; and calculating and outputting a final control quantity for driving a hydraulic system by using an incremental PID control algorithm based on the deviation between the target oil cylinder displacement and a current oil cylinder displacement. The operator input signal and sensor feedback are introduced into the trajectory generation process, so that the judgment of the operator under complex working conditions can be fully utilized, the trajectory precision and stability can be ensured through the algorithm, and efficient man-machine cooperation is realized.

The invention relates to the field of automobile control, and discloses an intelligent control system for an automobile tail door, which comprises a multi-source input acquisition module; the multi-source input acquisition module is used for synchronously acquiring a voice trigger signal, a touch trigger signal, a vehicle speed signal and a motor current signal; according to the invention, a Kalman filtering algorithm is introduced to carry out real-time fusion and noise suppression on voice, touch, vehicle speed, current, position and other multi-source input signals, noise introduced by sensor errors in the vehicle speed signals is effectively filtered out, and meanwhile, voice intensity, touch pressure and vehicle speed information are uniformly quantized through a weighted fusion mechanism, so that the accuracy of the voice intensity, the touch pressure and the vehicle speed information is improved. A high-reliability fusion signal is generated, and a PID control algorithm is combined to capture current fluctuation characteristics in real time, so that the comprehensive performance of the automobile tail gate electric control system in the aspects of safety, stability, response speed, control precision, environmental adaptability and the like is remarkably improved. The key technical problems of response delay, start-stop impact, anti-pinch misjudgment and the like of a traditional system are effectively solved.

The application provides a kind of based on multi-sensor's air suction disc type seed metering device seed layer thickness detection system and method, comprising the following steps: the distance of acquisition point to vibrating seed tray is obtained by at least one distance sensor;The data collected by at least one distance sensor is filtered;The filtered data are fused to obtain the seed layer thickness;The seed layer thickness is compared with the set seed layer thickness to determine the seed layer difference;According to the seed layer difference, the seed adding amount of the seed adding device is adjusted by RBF-PID control algorithm.The application uses RBF-PID closed-loop control, improves the accuracy of seed layer thickness detection, and optimizes the seed metering effect of seed metering device.

The invention provides a hydrogen fuel cell engine air valve control method and system and an MCU, and the method comprises the steps: obtaining the current position of a valve plate, comparing the current position with an expected target position, and judging the running direction of a motor; the proportional gain and the integral coefficient are adjusted according to the target position, the current position and the motor running direction, the proportional gain is adjusted according to the motor running direction, and the integral coefficient is set in a segmented mode according to the error value of the target position and the current position; based on a PID control algorithm, the duty ratio of the motor is obtained according to the adjusted PID parameters; detecting the motor current in the current limiting window period, and correcting the duty ratio of the motor according to the motor current; and detecting the battery voltage of a power supply of the air valve, and compensating the corrected duty ratio of the motor according to the battery voltage to obtain a target duty ratio for controlling the motor to drive a valve plate of the air valve to rotate to a target position. The overshoot of the valve plate can be effectively improved, and the control precision of the air valve and the running safety of the motor are improved.

The application discloses a kind of sensing optical cable laying robot path planning and obstacle avoidance system and method thereof, belong to robot path planning technical field.The system includes environment perception, data preprocessing, path planning, obstacle avoidance control and post-processing module.Method is obtained environment information by laser radar and camera and pre-processing, based on improved dynamic RRT algorithm carries out path planning, introduces adaptive step adjustment mechanism, according to environment complexity, obstacle distance and path curvature Dynamic adjustment step, combine real-time obstacle detection and dynamic replanning function Generation smooth path;PID control algorithm is used to adjust the speed and steering angle of robot to realize obstacle avoidance, and the post-processing module optimizes the evaluation path.The application improves the real-time performance, path quality and environmental adaptability of the robot in complex dynamic environment, ensures efficient, safe and accurate laying of optical cable.

The invention discloses an anti-fogging endoscope lens temperature control method and system, and relates to the technical field of temperature control, and the method comprises the steps: arranging a temperature and humidity sensor on an endoscope, collecting temperature and humidity data, carrying out the noise suppression, and calculating the temperature and humidity of an endoscope lens according to the temperature and humidity data; performing stable clamping on the humidity, calculating a normal pressure correction coefficient, calculating saturation water vapor pressure of an endoscope lens so as to obtain actual water vapor pressure, performing inverse solution through the normal pressure correction coefficient so as to obtain an instantaneous dew point, and smoothly outputting a final dew point by using a first-order index; calculating an instant dew point margin according to the lens temperature and the final dew point, calculating a negative margin correction item, predicting a future margin, calculating a logistic risk index, and finally comprehensively obtaining a lens adaptive margin; and calculating the total error of PID control, outputting a control command by adopting a PID control algorithm, and executing the control command. According to the invention, the fogging probability and the definition fluctuation are obviously reduced, and the temperature overshoot and fluctuation are reduced.

The invention provides a hydrostatic driving method and device for a snow pressing vehicle and a hydraulic system, and relates to the technical field of snow pressing vehicles. The method comprises the steps that the actual rotating speed of an engine is detected and compared with a preset optimal rotating speed range, and a rotating speed deviation signal is generated; based on the rotating speed deviation signal, the displacement adjusting amount of a variable pump and the displacement adjusting amount of a variable motor are calculated through an incremental PID control algorithm; dynamically adjusting the displacement of a variable pump and a variable motor according to the displacement adjusting quantity so as to realize stable control on the rotating speed of the engine; wherein when the load is increased, the variable displacement motor is adjusted to increase the displacement, and if the displacement of the motor reaches the maximum, the variable displacement pump is adjusted to reduce the displacement; when the load is reduced, the variable displacement pump is adjusted to increase the displacement, and if the pump displacement reaches the maximum, the variable displacement motor is adjusted to reduce the displacement. According to the method, the pump and the motor are cooperatively controlled through the incremental PID, the rotating speed of the engine is stabilized, efficient operation of the engine is maintained, and therefore the power utilization rate and the fuel economy are improved.

The invention discloses a variable pesticide application system based on a K-means clustering optimization algorithm and a control method, and relates to the technical field of variable pesticide application, and the variable pesticide application system comprises a rotating cage nozzle, a direct current brushless motor, a brushless water pump, a positioning module, a flow sensor, a core controller, a wireless transmission module and a cloud platform. The control method comprises the steps that farmland geographical position data are collected in real time through a positioning module and uploaded to a cloud platform, the cloud platform conducts clustering analysis on the geographical position data through a K-means clustering algorithm, a farmland is divided into multiple areas, and pesticide applying parameters of all the areas are generated; after the core controller receives the parameters, real-time positioning and flow feedback are combined, the PWM duty ratio is dynamically adjusted through a PID control algorithm, the rotating speed of a motor and the flow of a water pump are controlled, and precise variable pesticide application is achieved. Intelligent zoning and closed-loop control based on data driving are achieved, the pesticide utilization rate is effectively increased, pesticide liquid waste and environmental pollution are reduced, and the system is suitable for large-scale precise pesticide applying operation of field crops.

The invention relates to a PLC data acquisition control method and device for an AI exhibition hall, equipment and a medium, and the method comprises the steps: executing an acquisition control code, carrying out the statistics of a data volume index of PLC data at a current moment based on a preset first acquisition frequency, and constructing an observation data volume at the current moment according to the data volume index; according to the observation data volume at the current moment, the historical smooth data volume at the previous moment, the maximum response coefficient and the minimum smooth coefficient, calculating and determining a dynamic smooth coefficient of the data volume index; calculating and determining the smooth data volume at the current moment, calculating and determining the collection frequency adjustment amount of the first collection frequency by adopting a preset PID control algorithm, updating the first collection frequency to determine a second collection frequency, and continuing to collect the PLC data of the target interaction object by the central control system of the AI exhibition hall according to the second collection frequency; and repeating the steps until the PLC data of each target interaction object in the AI exhibition hall is acquired. According to the invention, the problems of blocking and poor real-time performance of a traditional PLC data acquisition system can be solved.

The application discloses an intelligent pipe cooling circulation control system and method based on ship lock construction, which comprises the following steps: dividing a ship lock construction structure into A pipe cooling circulation control subareas; covering the A pipe cooling circulation control subareas by B cooling circulation pipelines; receiving multi-dimensional data of each pipe cooling circulation control subarea by each edge key control node, and transmitting the data to a cloud cooling control service; after receiving the data, the cloud cooling control service generates A cooling circulation load demand risk coefficients based on a first deep learning algorithm; if it is judged that at least one of the A cooling circulation load demand risk coefficients is at risk, then the B cooling circulation pipelines are subjected to pipe cooling circulation control based on a second algorithm, and a PID control algorithm is used to adjust the cooling water flow and the cooling water temperature of the pipelines; the application realizes precise pipe cooling circulation control adjustment, improves the ship lock construction quality and reduces the risk of concrete hardening cracking through deep learning algorithm prediction and monitoring and the introduction of an unmanned aerial vehicle for the inspection of the outer surface of the cooling pipe.

The invention provides a battery intelligent regulation and control method and system based on charge and discharge terminal SOC dynamic calibration, and the method comprises the steps: collecting battery operation data in real time through a sensor, and carrying out the preprocessing of the battery operation data; constructing an SOC estimation model based on the preprocessed battery operation data to obtain an SOC estimation value; updating the SOC estimated value through an error compensation mechanism according to the SOC estimated value, and introducing a temperature compensation factor to optimize the updated SOC estimated value to obtain an optimized SOC estimated value; and based on the optimized SOC estimation value, dynamically adjusting the charging and discharging power through a PID control algorithm. According to the technical scheme provided by the invention, through dual mechanisms of error compensation and temperature compensation, the precision and environmental adaptability of SOC estimation are remarkably improved, intelligent, stable and safe regulation and control of the charging and discharging process of the battery are realized in combination with adaptive PID control and nonlinear power mapping, the service life of the battery is effectively prolonged, and the energy management efficiency is improved.

The application discloses a kind of manufacturing devices of multilayer co-extrusion film, comprising: blowing machine is used to extrude molten plastic material;Multilayer co-extrusion die is used to melt different materials and is co-extruded into multilayer structure;Sensing detection module is used to monitor film bubble diameter change and film bubble surface cooling state in real time;Control module is used to receive sensor signal, using PID control algorithm, output fan frequency, air valve opening degree instruction matrix;Wind power control module is used to adjust wind power according to fan frequency, air valve opening degree instruction matrix, and then control film bubble diameter;Film bubble forming module is used to form final film.The application also discloses a kind of using method of manufacturing devices of multilayer co-extrusion film.The application solves the problem that multilayer co-extrusion film is easily separated between film layers during manufacturing process, and film is broken or poorly bonded due to inaccurate film bubble diameter control.

The utility model discloses a sampling device with pressure control, and aims to solve the problem of pressure unbalance of a freeze dryer in multiple sampling processes. The sampling device comprises a mounting connection assembly, a pressure control assembly and a sampling platform which are connected in sequence. The mounting and connecting assembly comprises a flange plate and a sampling channel and is used for communicating the sampling device with the freeze dryer; the pressure control assembly comprises a vacuum isolation valve and a U-shaped air entrainment valve and is used for controlling the pressure balance of the sampling device and the freeze dryer. The sampling device adjusts the opening degree of the air entrainment valve through a PID control algorithm, the accuracy and reliability of pressure control are ensured, and the operation efficiency is improved.