711 results about "Pid control algorithm" patented technology

The invention relates to the technical field of digital twinning, in particular to a multi-machine running-in test distributed control system and method based on digital twinning. The method comprises the steps that a sensing execution unit collects equipment operation state data based on a multi-source sensor module and carries out preliminary data processing and detection; the digital twinning unit receives multi-dimensional sensing data of the sensing execution unit based on a dynamic twinning modeling module, establishes an equipment state model, and performs simulation verification and parameter optimization on a control strategy through a Q-learning strategy to obtain optimized control parameters; the intelligent control unit constructs an optimal decision-making model of multi-machine cooperative control based on a cooperative decision-making module, adjusts parameters of an execution mechanism in real time through a PID control algorithm and feed-forward compensation, and generates a self-adaptive control instruction; and the fusion analysis unit constructs a multi-dimensional equipment operation knowledge base based on the knowledge graph module, and generates global optimization parameters through a multi-target genetic algorithm.

The invention relates to the technical field of cable production automation control, and provides a crosslinked cable production control method based on an improved PID (Proportion Integration Differentiation) control algorithm, which comprises the step of constructing an optimal reference model by establishing a cooperative control framework of temperature, pressure and traction speed and taking the temperature of a vulcanization pipe as a main control variable and the pressure and the traction speed of an extruder as slave control variables. A main controller tracks a temperature set value in real time, PID parameters are dynamically set according to technological parameters such as the thickness deviation of an insulating layer and the crosslinking degree of a material, and precise control is achieved through a three-ring cooperative coupling improved PID controller. A temperature control ring enables the steady-state error of the actual temperature and the set value to be converged to zero. The pressure and speed control loop converges the fluctuation amplitude to a process allowable range. The temperature stability, the pressure uniformity and the traction synchronism of crosslinked cable production can be improved, the process fluctuation and the defect rate are reduced, and the product quality and the production efficiency are improved.

The invention provides a sewage treatment aeration control system and method based on multi-parameter collaborative optimization. The method comprises the following steps: acquiring multi-sensor data of COD (Chemical Oxygen Demand), BOD5 (Biochemical Oxygen Demand), DO (Dissolved Oxygen Demand), ammonia nitrogen, ORP (Oxidation Reduction Potential), pH (Potential of Hydrogen), water inlet flow and sludge concentration of wastewater in an aeration tank by utilizing a multi-parameter sensor module; according to the dynamic correction oxygen mass transfer coefficient and the feedforward parameter, establishing a relationship between the water inlet load and aeration; calculating the air volume of an air blower and the fine adjustment value of the opening degree of a butterfly valve through a PID control algorithm and feedback parameters, and correcting the aeration quantity to obtain a total air volume target value; and adjusting the opening degree and the rotating speed of a guide vane of the air blower according to the self-adaptive PID control parameters and the corrected total air volume target value by utilizing a self-adaptive PID controller, and adjusting the opening degree of a butterfly valve according to a gradient butterfly valve adjusting strategy. The output of the air blower is optimized by adopting self-adaptive PID, and the opening degree of the butterfly valve of each biological tank is dynamically adjusted through a gradient valve adjusting strategy, so that the accurate control of the aeration rate is realized; the sewage treatment effect is ensured.

The invention relates to the technical field of intelligent equipment monitoring, and discloses a sandstone separator monitoring control method and system based on multi-source data processing. According to the method, equipment operation parameters, real-time image data and vibration sensing data of the sandstone separator are collected in real time, data preprocessing and feature extraction are carried out, a monitoring model based on a multi-modal deep learning framework is constructed, and accurate joint characterization of the equipment state is achieved. The system can dynamically generate a control instruction according to a monitoring result, adjust equipment operation parameters in time, and avoid production interruption and quality problems. Besides, the multi-modal data fusion technology and the self-adaptive PID control algorithm are adopted, so that the operation efficiency and stability of the sandstone separator are further improved, and powerful technical support is provided for the field of intelligent manufacturing.

The invention belongs to the technical field of physical and chemical analysis, and particularly discloses a high-precision full-automatic titration system and method based on fusion of a spectrum sensor and a PLC, a multi-channel spectrum sensor is adopted to capture fine spectrum characteristics of solution color change in real time, and the flow rate of titration liquid is dynamically adjusted through a PLC embedded PID control algorithm, so that the titration accuracy is improved. The method realizes submilliliter-level precision control, constructs a real-time compensation mechanism in combination with temperature, humidity, pH and other environmental parameters, improves the accuracy and robustness of titration end point judgment, automatically updates an end point judgment threshold and control parameters in combination with an AI self-learning module, realizes self-adaptive adjustment and sustainable evolution of the system, and improves the accuracy and robustness of titration end point judgment. The device has the characteristics of modular structure, high detection precision, high control response and high operation stability.

The invention discloses a UV illumination control method and system for a reel-to-reel exposure machine. The method comprises the following steps: acquiring a real-time moving speed and a tension change value of a coiled material; when the tension change value is greater than the tension threshold value, predicting the deformation trend of the surface of the coiled material based on a nonlinear regression algorithm in combination with the real-time moving speed to obtain a deformation influence value; according to the deformation influence value, a PID control algorithm is adopted to adjust the UV light source, and a light intensity distribution value is obtained; according to the light intensity distribution value, a fuzzy control algorithm is adopted to calculate the output intensity requirement of the UV light source, and speed adjustment is carried out in combination with the real-time moving speed, so that optimized irradiation parameters are obtained; performing area judgment according to the optimized irradiation parameters to obtain an overexposure area and an underexposure area; and adjusting the intensity and distribution of the UV light source in the overexposure area and the underexposure area until the area exposure quality reaches a preset standard range. The method can realize real-time response regulation and control on tension and speed change of the coiled material, and solves the problem of non-uniform exposure dose.

The invention belongs to the field of robot control, and particularly relates to a robot self-adaptive impeller welding control method and system fused with multi-modal data, and the method comprises the steps: obtaining an impeller workpiece image and three-dimensional point cloud data through an industrial vision subsystem, and extracting a three-dimensional welding seam position point set representing a welding seam track; generating a candidate welding path set based on welding seam geometric feature analysis; in combination with welding seam morphology and process requirements, optimal welding process parameters are predicted through a regression model, and a welding gun attitude angle is calculated through quaternion conversion according to a curved surface normal vector; in the welding process, the relative position deviation of a robot and a workpiece and the parameter deviation of welding current / voltage and a planned value are monitored in real time, when the deviation exceeds a preset tolerance interval, a PID control algorithm is adopted to dynamically adjust robot motion parameters or welding process parameters, and closed-loop control over the welding process is achieved; according to the method, precise planning of the welding path and self-adaptive regulation and control of the process are achieved, and the welding quality and the forming consistency are remarkably improved.

The invention relates to the field of navigation signal processing, and discloses a passenger car battery temperature control intelligent regulation and control method and system based on multi-source sensor data, environment data and battery operation state data are acquired by constructing a multi-source sensing array, and fusion processing and feature extraction are performed on the acquired data by using an edge calculation method; analyzing and predicting the charging and discharging behaviors of the battery based on the extracted characteristic parameters, judging the charging and discharging states of the battery, dynamically optimizing the switching threshold value of the refrigerating or heating mode of the battery, switching the mode according to the optimized switching threshold value, and performing matching analysis on the photovoltaic power generation energy and the temperature control energy consumption, so as to determine the temperature control energy consumption of the battery. According to a matching analysis result, an exclusive temperature control matrix is generated through a geographic position and meteorological data, and time-sharing gradient control is performed by using an adaptive PID control algorithm in combination with instantaneous wave cloud characteristics of photovoltaic energy storage, so that customized temperature control strategies can be provided for different environmental conditions, temperature fluctuation is avoided, and the temperature control stability is improved.

The invention discloses a spray drying device for boron carbide production, the spray drying device comprises a spray drying tower, a hot blast stove, a cyclone separator and a system controller, an atomizer and an online detection module are arranged in the spray drying tower, and the online detection module is used for monitoring temperature parameters in the spray drying process; comprising a first temperature sensor, a second temperature sensor and a temperature signal processing unit, the temperature signal processing unit adopts a multi-stage filtering and error compensation technology, noise and interference are effectively suppressed, and the accuracy of detection data is ensured. The air inlet temperature and the air outlet temperature are monitored in real time through the online detection module, the fuzzy-PID control algorithm is combined, the temperature control precision and the response speed are remarkably improved, and temperature fluctuation is reduced. The device dynamically adjusts the heating power of the hot blast stove according to real-time working conditions, the energy utilization efficiency is optimized, and the energy consumption is reduced.

The invention discloses a mixed emulsion explosive one-key production control method and system, and relates to the field of automatic and intelligent control. By means of automatic and intelligent control means, the problems of low efficiency, high cost, quality fluctuation, process uncertainty and the like in traditional mixed emulsion explosive production are solved, accurate feeding of raw materials is achieved through a quality sensor array and a PID control algorithm, and the production efficiency is improved. The stability of production parameters is ensured through multi-sensor data fusion and an advanced control algorithm, so that the consistency of product quality is improved; meanwhile, a feedback control loop and a continuous learning mechanism are established, closed-loop control in the production process is achieved, technological parameters are optimized, the production stability and reliability are ensured, the production efficiency and the product quality are remarkably improved, and the labor cost is reduced.

The invention relates to the technical field of lithium battery manufacturing equipment, and discloses a rolling thickness control method and device, electronic equipment and a storage medium. According to the method, in the working process of the roller press, the real-time thickness of a machined object of the roller press is measured, the real-time thickness is compared with the target thickness, all adjusting parameters in a PID control algorithm are updated according to the comparison result, and the adjustment amount of the rolling parameters of the roller press is calculated through the PID control algorithm with the updated adjusting parameters. And therefore, closed-loop control on the rolling thickness is realized. In the working process of the roller press, the adjusting parameters of the PID control algorithm are updated on line according to the real-time condition, extra manpower and time do not need to be occupied for updating the adjusting parameters of the control algorithm, manpower and time consumption is saved, the adjusted adjusting parameters can better adapt to the real-time working condition of the roller press, and the working efficiency of the roller press is improved. And the accuracy of controlling the rolling thickness is improved.

The invention provides a battery pack temperature equalization control method. According to the method, multi-zone temperature and heat dissipation distribution data acquisition is carried out, a temperature distribution model is established in combination with K-means clustering and a heat conduction equation, heat dissipation parameters are optimized by using a least square method, differential temperature control instructions are generated by using a PID control algorithm, and Q-learning reinforcement learning is introduced to dynamically adjust control parameters. According to the method, accurate monitoring and intelligent regulation and control of the internal temperature of the battery pack are achieved, the problems that a traditional temperature control system is lagged in response and poor in equalization effect are effectively solved, the temperature equalization performance of the battery pack is remarkably improved through multi-level data analysis and a self-adaptive control strategy, the service life of the battery is prolonged, and the service life of the battery pack is prolonged. And reliable guarantee is provided for safe and efficient operation of the new energy automobile power battery.

The invention belongs to the technical field of drilling, and provides an active vibration reduction method and system based on self-adaptive adjustment of a drill rod load in order to effectively reduce vibration of a drill rod. A real-time feeding oil pressure signal is converted into real-time feeding thrust, and a real-time rotating oil pressure signal is converted into real-time rotating torque; filtering the original vibration signal by adopting a singular value subspace decomposition method to obtain a real vibration signal; according to the preset initial value of the feeding thrust and the preset initial value of the rotating torque, a neural network self-adaptive PID control algorithm is used for conducting self-adaptive comparison calculation, the vibration adjustment amount is obtained, and active vibration reduction is conducted according to the vibration adjustment amount; the system comprises six closed-loop control modules including a preset parameter input module, a signal acquisition module, a signal filtering module, a control algorithm module, a control output module and an execution module, accurate vibration reduction control is achieved, the bounce phenomenon of a drill bit is eliminated, the deviation error of a drill hole is reduced, meanwhile, stick-slip vibration is restrained, and the clamping stagnation failure rate of a drill rod is greatly reduced.

The invention provides a greenhouse intelligent temperature control automatic adjustment optimization method based on multi-parameter dynamic coordination, and relates to the technical field of agricultural facility environment control. The method comprises the following steps: acquiring temperature, air humidity, wind speed and airflow distribution environment data inside and outside a greenhouse in real time; the environment state is quantified through a dynamic evaporation efficiency coefficient DEEC and an airflow distribution uniformity index ADUI; the flow of a water pump, the rotating speed of a fan and the opening degree of a ventilation system are dynamically adjusted in combination with an improved PID control algorithm, and the weight of an integral term is dynamically adjusted along with the ADUI to enhance the response efficiency; a time sequence prediction model based on LSTM is adopted to fuse historical and real-time data, a parameter correction amount is predicted, and the adaptation capability of the system to a new environment is improved in combination with a transfer learning algorithm; system hardware comprises a low-power-consumption wireless sensor, a frequency conversion actuator and an embedded control terminal. Through combination of multi-parameter perception and cooperative control, accurate temperature and humidity control and energy efficiency optimization are realized, resource consumption is reduced, and automation and intelligence levels of environment adjustment are improved.

The invention discloses a laser accurate positioning system and method based on an improved PID control algorithm, and relates to the technical field of laser positioning, a holder laser module is constructed and comprises a laser emission unit and a holder execution unit and is used for executing a control strategy, and a multi-sensor array is constructed to collect parameter data of the holder laser module; a control module is constructed and comprises a dynamic bimodal PID unit, a space-time decoupling learning unit and a frequency domain anti-interference unit and is used for analyzing parameter data to generate a control strategy of a holder execution device, a fault processing module is constructed and is used for detecting whether a fault occurs in the process of a laser precise positioning system, and when the fault occurs, the fault processing module is used for processing the fault. Executing a three-stage shutdown process; according to the invention, by improving the PID control algorithm and the frequency domain anti-interference design, the anti-interference capability and the system stability of the laser positioning system in a complex dynamic environment are significantly improved.

The invention discloses an internet of things-based amusement equipment light dynamic control method and system, and the method comprises the steps: collecting the acceleration, angular velocity and coordinate data of equipment, carrying out the wavelet denoising and Z-score standardization processing, and constructing a dynamic topology model based on a graph attention network and a graph convolution network. A spectral clustering algorithm is utilized to carry out space partitioning on equipment nodes to generate a topological sub-graph, and an LSTM network is combined to predict an equipment motion track and generate a continuous track sequence. Track correlation features are extracted through a graph attention network, a genetic algorithm is fused to optimize and generate a light conversion sequence, dynamic time warping alignment timestamps are synchronously adopted, and phase synchronization of the light sequence and the motion track is ensured. And finally, brightness, color and flicker frequency are adjusted in real time based on a PID control algorithm, and a closed-loop feedback mechanism is formed. According to the method, high-precision dynamic matching of light and equipment movement is realized, and immersive experience and visual interactivity are improved.

The embodiment of the invention provides a hydrochloric acid PH control device in a germanium oxide production process and a control method thereof, and belongs to the field of chemical process automatic control. The device comprises an acid liquor storage tank used for storing raw liquor hydrochloric acid and connected to an acid mixing tank through a raw acid feeding control valve; the acid mixing tank is used for mixing an acid solution with a diluent and is connected to the pH regulation reaction tank through a mixed acid feeding control valve; the alkali liquor storage tank is connected to the pH regulation reaction tank through an alkali liquor adding control valve; the pH regulation reaction tank is used for receiving the mixed acid liquor and the alkali liquor and regulating the pH value of a reaction system, and is provided with a pH sensor for detecting the pH value in real time; and the control unit is used for dynamically adjusting the opening degree of each valve by adopting an improved fuzzy self-adaptive PID control algorithm according to a detection result of the pH sensor so as to control the pH value to be within a target range. According to the scheme, the problems of overshoot and lag caused by traditional fixed parameter PID adjustment are solved, and therefore the stability of the pH value of the solution and the consistency of the technology in the germanium oxide production process are guaranteed.

The invention discloses a sensing optical cable laying robot path planning and obstacle avoidance system and method, and belongs to the technical field of robot path planning. The system comprises an environment sensing module, a data preprocessing module, a path planning module, an obstacle avoidance control module and a post-processing module. According to the method, environment information is acquired and preprocessed through a laser radar and a camera, path planning is performed based on an improved dynamic RRT algorithm, a self-adaptive step length adjustment mechanism is introduced, the step length is dynamically adjusted according to environment complexity, obstacle distance and path curvature, and a smooth path is generated by combining real-time obstacle detection and dynamic re-planning functions. A PID control algorithm is adopted to adjust the speed and the steering angle of the robot to achieve obstacle avoidance, and a post-processing module optimizes an evaluation path. The real-time performance, the path quality and the environment adaptability of the robot in a complex dynamic environment are improved, and efficient, safe and accurate laying of optical cables is ensured.

The invention relates to the technical field of laser temperature control, in particular to a temperature control method and system for a multi-environment VCSEL laser, and the method comprises the steps: collecting the temperature of the VCSEL laser at each moment, and the current of a thermoelectric refrigerating unit used for carrying out the temperature control of the VCSEL laser at each moment; determining the temperature fast adjustment intensity and the temperature oscillation characteristic value of the VCSEL laser at each temperature control moment; obtaining a steady state adjustment value of the VCSEL at each temperature control moment; determining the magnetic field interference suppression intensity of the VCSEL laser at each temperature control moment; and correcting a first threshold value and a second threshold value of the integral separation PID control algorithm, determining a switching coefficient of an integral item in the integral separation PID control algorithm, and performing temperature control on the VCSEL at each temperature control moment. Therefore, the temperature control precision of the VCSEL laser is improved.

The invention discloses an anti-explosion pressure relief ball valve which comprises a pressure monitoring system and a control execution system. The pressure monitoring system is used for forming a pressure distribution model; the control execution system comprises a signal processing module used for calculating the pressure change rate; the abnormal pressure identification module is used for judging whether an abnormal pressure event exists or not according to the judgment condition; the multi-stage pressure relief control module is used for controlling the opening number of the micro-channel systems and controlling the pressure relief amount according to the relation between the current pressure and a preset threshold value; the stepped pressure relief structure comprises multiple stages of pressure relief cavities, so that the pressure relief process conforms to a pressure change formula; and the dynamic feedback control module is used for dynamically adjusting the opening amount of the micro-channel by adopting a PID control algorithm. The system has the following beneficial effects that through pressure monitoring, intelligent judgment and the multi-stage controlled pressure relief module, early recognition, accurate intervention and safe disposal of abnormal pressure events are achieved, and safety accidents such as pipeline burst and flange leakage are effectively prevented.

The invention relates to the technical field of agricultural robot navigation, and discloses an agricultural robot autonomous navigation system based on a three-dimensional point cloud model.The agricultural robot autonomous navigation system comprises a three-dimensional point cloud collection module, a data processing center and a navigation control unit, robot path planning and obstacle avoidance are achieved by collecting environment data in real time and constructing a precise three-dimensional map, and the navigation efficiency is improved. The three-dimensional point cloud acquisition module acquires point cloud data and image information in an environment, and the data processing center adopts a multi-source data fusion algorithm, and performs dynamic environment perception and path optimization, so as to improve the robustness and the real-time performance of the navigation system. The system adopts multi-module cooperative control, realizes dynamic self-adaption of global and local paths, improves the flexibility and reliability of robot operation, combines a PID control algorithm with real-time feedback adjustment, accurately controls the advancing track of the robot, and ensures the operation precision and stability.

The invention relates to the technical field of zirconia ceramic sintering, and discloses a zirconia ceramic microwave single-die-cavity rapid sintering system and an intelligent temperature control method.The system comprises a high-temperature-resistant metal cavity, a microwave generation unit, a temperature detection and control unit, a coil base assembly and an auxiliary structure, and centralized control is achieved through an intelligent touch control computer. A microwave single-mode resonance mode is adopted, a silicon carbide wave absorbing layer is used for enhancing microwave absorption, materials are evenly heated from inside to outside, an intelligent temperature control method is used for monitoring the temperature in real time based on a short-wave infrared thermometer, a PI D control algorithm is combined, the power of a magnetron is dynamically adjusted through an adjustable power source, the temperature control precision reaches + / -2 DEG C, and the temperature control precision reaches + / -2 DEG C; the problems of non-uniform temperature, high energy consumption, high rejection rate, long sintering time and the like in a traditional zirconia ceramic sintering process are effectively solved, the production efficiency can be greatly improved, the cost is reduced, the product quality is improved, the equipment also supports multiple process modes, and diversified production requirements are met.

The invention discloses a real-time monitoring and intelligent deviation rectifying system and method for hoisting of fabricated building components, and the real-time monitoring and intelligent deviation rectifying system comprises a monitoring module, a data preprocessing module, an intelligent decision-making module and a deviation rectifying execution module, the real-time monitoring and intelligent deviation correction method comprises the steps of monitoring data collection, monitoring data preprocessing, intelligent prediction, PID-based real-time balance adjustment and dynamic iteration and optimization. Component postures, stress states, environment wind loads and hoisting equipment operation parameters are monitored in real time through a multi-source sensor, intelligent prediction and decision making are conducted in combination with a deep neural network model, and high-precision tracking of a target tension value is achieved in combination with a PID control algorithm; therefore, intelligent prediction and self-adaptive regulation and control of the hoisting operation of the fabricated building component in the high-altitude complex operation environment are realized.

The invention relates to the technical field of general control or regulation systems, in particular to a sushi type S-shaped layered horizontal self-driven transmission mushroom and vegetable shelter planting system. The system comprises a data acquisition module, a path planning and scheduling module, a motor driving control module, an environment regulation and control module and a central controller. The system collects environment parameters, carrier states and crop growth information in real time through a sensor network, and constructs system state vectors. The central controller combines a heuristic path planning algorithm, an adaptive PID control algorithm, a model prediction control algorithm and a DQN optimization strategy based on deep reinforcement learning to realize carrier path optimization, motor driving precision control, cabin environment prediction regulation and control and system closed loop feedback optimization. The system has the advantages of flexible orbit scheduling, efficient operation response, fine environment control, high intelligent level and the like, and can realize subarea fine management and continuous optimization evolution of the system in a multi-category crop co-cabin planting scene.

The invention relates to an artificial intelligence-based agricultural management platform control method and platform for teaching, and the method comprises the steps: collecting the seedling environment data and controller parameters of the platform, combining with a deep learning model to precisely predict the germination rate and the seedling growth state, generating recommended target environment parameters, and according to the target environment parameters, carrying out the calculation of the germination rate and the seedling growth state. The operation information of the controller and the attributes of the static controller are combined, the operation parameters of the controller are optimized through a PID control algorithm, and the seedling raising environment is adjusted to be optimized in real time; students control the controller through manual programming, the platform records control parameters of the students and operation results of the controller, control results of the students are compared with parameters recommended by the deep learning model, difference indexes are evaluated, and the students adjust control logic and improve equipment operation strategies by checking comparison results and system suggestions. Students not only can manually control equipment through programming, but also can intuitively understand the optimization ability and principle of deep learning through comparison with a recommendation result of the deep learning model, so that the ability of the students to solve complex agricultural problems is improved, and the cultivation of intelligent agricultural talents is promoted.

The invention relates to the technical field of air compressor optimization, and discloses an intelligent air compressor optimization control method and system based on an IOE control system.The intelligent air compressor optimization control system comprises a collection unit, a preprocessing unit, an analysis unit and an optimization unit, rich operation data such as air inlet pressure, flow, exhaust pressure and temperature are comprehensively collected in real time, denoising is conducted through a moving average method, and data accuracy is ensured; normal, overload and abnormal fluctuation modes are clearly divided, accurate judgment is performed by means of a preset interval and reasonable calculation, and powerful support is provided for control decision making; in a normal mode, intelligent regulation is performed according to a parameter average value, and operation efficiency and stability are improved; the valve opening degree is adjusted according to the deviation degree in the overload mode, the load is effectively reduced, and equipment is protected; in the abnormal fluctuation mode, a PID control algorithm is used, the opening degree, the cooling amount and the like of the valve are flexibly adjusted according to deviation and the change rate, and parameters are rapidly recovered to be stable. The fault rate and the maintenance cost can be greatly reduced, and the working efficiency is remarkably improved.

The invention relates to the technical field of pH value adjustment, and discloses a pH value adjustment method and system, a storage medium and equipment. The method comprises the following steps: denoising time sequence data of a pH sensor to obtain a smooth pH value sequence, and calculating a first-order difference of the smooth pH value sequence to obtain a pH value rate change sequence and rate characteristics; when any value in the sequence exceeds a preset threshold value, extracting feature distribution data, and inputting the feature distribution data and real-time state data of the solution into a solution state evaluation model to obtain an estimated value of the buffer capacity and reaction rate change of the solution; based on the estimated value, the pH value rate change sequence and the rate characteristics, calculating a preliminary control sequence of the acid-base addition amount, adopting a self-adaptive PID control algorithm to adjust parameters, generating an optimal control sequence, controlling the acid-base addition equipment to adjust the addition amount, obtaining new pH value data, and performing fast Fourier transform to obtain a stable pH value sequence. The stability of pH value control of the solution is improved.

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 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 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.