1628 results about "Heat distribution" patented technology

The invention belongs to the technical field of welding quality detection, and particularly relates to a visual image-based welding seam defect detection method, which comprises the steps of image acquisition, image preprocessing, data analysis, data output, defect classification and decision making, system closed-loop optimization and the like. According to the method, by synchronously collecting two-dimensional images, three-dimensional shapes and heat distribution data of metal welding seams and adopting a polarization filter and annular LED light source combination scheme, multi-dimensional conjoint analysis of physical defects and thermodynamic characteristics is achieved, basic characteristic data are extracted through primary processing, quantifiable defect coefficient indexes are generated through secondary processing, and the detection accuracy is improved. And finally, generating a comprehensive defect index through a multi-modal fusion algorithm, constructing a well-arranged intelligent analysis decision chain, and establishing a self-evolution mechanism of data acquisition-analysis decision-model iteration through real-time interaction of a detection result and an algorithm model. The system can continuously optimize the detection threshold value and the characteristic weight parameter according to the actual working condition of the production line, and the continuous improvement of the detection sensitivity is kept.

The invention discloses an energy management and safety protection cooperation method for a liquid cooling industrial and commercial energy storage system, and particularly relates to the technical field of energy storage system management. A battery electrochemical model, a heat distribution diagram, temperature gradient data and electrical parameters are used as input, and a battery temperature change trend curve is output; a liquid cooling control strategy is set according to the prediction result; fusing the temperature gradient abnormal parameters, the temperature trend risk and the multi-modal environment data abnormal parameters, starting a fire risk assessment model, predicting the fire probability and position, calculating a fire risk coefficient, generating a fire risk report and setting safety protection measures; a multi-objective optimization mathematical model is constructed based on the energy efficiency ratio, the full life cycle income and the battery health degree, energy storage operation data and power grid requirements are combined, a Pareto optimal solution set is generated by adopting a non-dominated sorting genetic algorithm, and a charging and discharging strategy and liquid cooling parameters are optimized; the liquid cooling pipeline layout is optimized through reinforcement learning, and the problem that the battery temperature cannot be effectively managed is solved.

The invention relates to the field of electromagnetic induction heating, and discloses a global temperature control method for an electromagnetic induction heating system, which comprises the following steps of: acquiring a two-dimensional temperature distribution diagram of a heating area at a plurality of key moments through a multi-point infrared temperature acquisition and induction heating coil synchronous excitation mechanism; performing multi-dimensional region segmentation on the global temperature scene data set, and identifying a temperature abnormal region and a thermal diffusion path feature based on a boundary thermal gradient change rate and an energy transfer path analysis algorithm; a distributed power regulation and control method and a historical thermal field evolution rule are introduced based on the regional thermal response feature map; thermal field feedback information is collected in real time in the temperature control process, and the current global thermal field state is judged in combination with a thermal distribution stability judgment criterion; and based on the updated control parameter configuration table, in combination with the thermal performance parameters of the material and the geometric information of the workpiece, generating an operation instruction set of the heating process, and executing intelligent regulation and control. The induction heating device has the advantage of improving the induction heating quality.

The invention relates to the technical field of safety monitoring, in particular to a smart park safety management method and system based on AI visual identification, and the method comprises the following steps: obtaining a video stream captured by a monitoring camera of a smart park, extracting the movement track data of a person through AI, and carrying out the statistics of the stay duration and access times of a target object in each grid; and constructing retention heat distribution of the grid region to obtain a personnel trajectory retention heat value. According to the invention, through the data processing of the monitoring video stream and the combination of the gridding analysis of the personnel motion trail, the accurate capture of the abnormal cruise behavior is enhanced, and through the calculation of the change rate of the access times between the adjacent grids, the statistics of the round-trip condition of the target among the plurality of areas and the combination of the passing authority data, the abnormal screening is carried out. The method improves the recognition capability of abnormal movement modes, achieves the dynamic adjustment of regional safety risk levels, improves the response capability of park security, enables the recognition capability of abnormal behaviors to be enhanced, and reduces the false alarm rate.

The invention discloses an indoor temperature real-time regulation and control method of a heat distribution pipeline and a control system of the indoor temperature real-time regulation and control method, relates to the technical field of dynamic control of a heat distribution pipe network, and solves the problems of hydraulic oscillation and temperature control hysteresis caused by the fact that local valve regulation neglects whole-network coupling and a first-order linear model is difficult to describe multi-order thermal inertia and large heat capacity in the prior art. According to the scheme, on the basis of pipe network distributed PDE / lumped parameter hybrid modeling and in combination with extended Kalman filtering and unscented Kalman filtering on-line identification, a feedforward decoupling compensation item is generated through spectral decomposition, a self-adaptive multi-model predictive control and iterative learning compensation closed-loop structure is constructed, a control instruction is issued according to a pump-first and valve-second serialization strategy, and a self-adaptive multi-model predictive control and iterative learning compensation closed-loop structure is constructed. Meanwhile, the model weight and the prediction time domain are dynamically adjusted; according to the method, the global balance capability and the temperature tracking precision of heat distribution pipeline regulation and control are remarkably improved.

The invention relates to the technical field of electrical design and intelligent optimization calculation, and discloses a capacitor structure design optimization method and system and a storage medium. The method comprises the following steps: carrying out modeling processing on capacitor structure parameters, and dividing a parameter space to obtain an initial model set; obtaining a multi-physical field simulation model according to the geometric model and the material attributes; obtaining performance indexes such as capacitance value, heat distribution and stress based on the simulation model; setting a target function and constraint conditions, and operating an optimization algorithm to obtain an optimal solution set; performing feedback control processing on an optimization result, and analyzing a convergence path to obtain a structure parameter; according to the invention, the execution efficiency of capacitor structure design optimization is improved, and the consistency and stability of the optimization process and the performance prediction result are improved.

The invention discloses an AR intelligent photovoltaic inspection method and system, and the method comprises the following steps: S1, obtaining a panoramic image and heat distribution data of a photovoltaic module, and generating a data set; s2, multi-modal data preprocessing is carried out, key fault features are extracted, and fault areas are marked; s3, focusing and analyzing the marked area, and identifying a thermal abnormal point; s4, constructing an electrical topological graph, and generating a fault point priority; s5, performing ant colony optimization to adjust the inspection path, and marking the position of a fault point; s6, displaying the path, the fault point and the risk heat map in the AR equipment; and S7, generating an inspection report and performing feedback optimization. According to the invention, through multi-modal data fusion, dynamic path optimization and augmented reality technologies, efficient detection, accurate positioning and visual display of photovoltaic module faults are realized, and the inspection efficiency and the intelligent level are improved.

The invention relates to the technical field of chip heat management, and discloses a chip heat distribution prediction modeling method and device, and the method comprises the steps: obtaining chip design information, carrying out the three-dimensional grid division through a pre-training transfer learning neural network, and constructing an electricity-heat-force multi-physics field coupling model; the method comprises the following steps: monitoring operation load data in real time, carrying out thermal simulation and generating a temperature distribution characteristic matrix, collecting data through a temperature sensor array, simulating thermal diffusion by using particle filtering and Bayesian inference, compressing and reconstructing the temperature distribution characteristic matrix by using a variational auto-encoder, generating a digital twinborn body, and optimizing a heat dissipation strategy by using deep reinforcement learning. The temperature control strategy is generated, the chip heat management precision is improved, the heat dissipation strategy is optimized, the performance and stability are improved, and the problem of insufficient prediction of temperature distribution in a traditional heat management scheme in the prior art is solved.

The invention discloses a temperature monitoring method for a photovoltaic grid-connected cabinet, and particularly relates to the technical field of photovoltaic grid-connected cabinets. The method comprises the following steps: arranging multiple types of temperature sensors in a grid-connected cabinet, collecting real-time temperature data, constructing a heat distribution model, comparing a current heat map with a historical steady-state heat field template, and identifying heat field offset and an atypical temperature rise trend; when the system detects that early warning is not triggered by an existing measuring point in a heat abnormal area, redundancy alarm logic is automatically started, temperature abnormal early warning is generated, and the speculated abnormal heat source position is recorded; according to the method, the sensing capability of the thermal anomaly in the blind area of the sensor is effectively improved, and the safety and the intelligent level of the system are enhanced.

The invention relates to the technical field of spraying process control, and discloses a spraying process self-adaptive adjustment method based on temperature measurement. The method comprises the steps that target coating parameters and base material physical property data are obtained, and initial spraying control parameters are generated through a first intelligent calculation model in combination with historical process data and real-time environment monitoring data; when spraying is executed, heat distribution data of a spraying area are collected in real time through a temperature sensing device, and according to the difference between the heat distribution data and a preset target temperature interval, technological parameters are dynamically corrected through a first self-adaptive regulation and control algorithm; meanwhile, a machine vision system is used for capturing actual coating morphological characteristics, and after the actual coating morphological characteristics are compared with target parameters, excitation parameters are adjusted in a partitioned mode through a second self-adaptive regulation and control algorithm so as to optimize uniformity; and collecting whole-process data, comprehensively evaluating the whole-process data through the second intelligent calculation model to generate a process optimization instruction, and updating the first intelligent calculation model and the first self-adaptive regulation and control algorithm parameters according to the process optimization instruction.

The invention relates to the technical field of cloud computing and distributed storage, and discloses a distributed metadata management method and storage system based on cloud computing, and the method comprises the following steps: S1, collecting the access frequency of a plurality of metadata objects in a set time period; s2, performing weighting processing on the access frequency, and constructing access heat distribution under multiple time scales; s3, obtaining the available cache capacity of a plurality of cache nodes, and constructing cache resource weight distribution; s4, assessing the access cost and migration cost between each metadata object and each cache node; and S5, generating a scheduling strategy between the metadata object and the cache node based on a preset optimization target, wherein the optimization target is access cost minimization. According to the method, a heat, resource and cost joint modeling mechanism is constructed, and optimal scheduling and feedback adaptive control are combined, so that accurate decision, dynamic adjustment and migration cost controllability of copy deployment are realized, and the performance and stability of distributed metadata management are effectively improved.

The invention provides a lithium battery equalization thermal management method. Real-time temperature data is obtained by constructing a thermal distribution monitoring network, the temperature difference between a center and an edge area is analyzed, a thermal load distribution coefficient is calculated, and a dynamic heat dissipation intensity adjustment model is established; driving the multi-channel cooling system to operate according to the heat dissipation demand priority, and adjusting the flow distribution proportion of a cooling medium; a dynamic nonlinear feedback correction mechanism is adopted, secondary adjustment is carried out for uneven temperature distribution, and an optimal heat dissipation parameter combination is determined in combination with historical data. Uniformity control over temperature distribution of the battery module is achieved, the problem of heat accumulation in a center area is effectively solved, the heat dissipation efficiency under the rapid charging working condition is improved, and the safety performance and the service life of the battery module are guaranteed.

The invention discloses a dam termite cave positioning method based on transient electromagnetism carried by an unmanned aerial vehicle. The method comprises the following steps: constructing an unmanned aerial vehicle transient electromagnetic detection system; preprocessing the received secondary induction electromagnetic field signal, and obtaining a comprehensive electromagnetic signal according to the response difference of the multi-frequency signal; inputting the integrated electromagnetic signals into a pre-trained deep learning neural network model, identifying characteristic signals related to termite acupoints in the integrated electromagnetic signals, and outputting position coordinates of suspected termite acupoints; a dam surface thermal imaging image obtained by a thermal imaging module is combined for secondary verification, and termite cave position information is transmitted to a ground control terminal in real time through a communication module carried by the unmanned aerial vehicle. According to the invention, efficient, accurate and lossless positioning of the termite cave of the dam is realized, underground electromagnetic signals and surface heat distribution information of the dam are rapidly obtained, and accurate termite cave position coordinates are output.

The invention discloses a public transport passenger flow monitoring method and system based on human body detection, and the method comprises the steps: synchronously collecting skeleton key points, heat distribution and contour features of passengers through a vehicle-mounted multi-view camera and an infrared sensor, and generating a passenger space-time feature matrix; outputting a passenger movement track set based on the passenger space-time characteristic matrix; generating a dynamic congestion degree index according to the staying duration and the spatial distribution density of the passengers in the passenger movement track set; calculating an abnormal behavior probability based on the dynamic congestion degree index, and outputting an abnormal event early warning signal; and fusing the dynamic congestion degree index, the abnormal event early warning signal and the real-time passenger flow data, and generating a bus passenger flow monitoring result through space-time correlation analysis. According to the embodiment of the invention, high-precision, low-delay and intelligent passenger flow state monitoring and abnormity early warning can be realized.

The invention relates to the technical field of semiconductor packaging detection, and provides a self-adaptive semiconductor packaging detection method which comprises the following steps: synchronously acquiring packaging surface heat distribution data, three-dimensional deformation data and pin electric signal data through a multi-source sensor; performing dynamic weighted fusion on the multi-modal data based on the packaging process parameters to generate a defect feature matrix; performing dynamic threshold calibration on the defect feature matrix by adopting an adaptive threshold generation algorithm according to clustering center distribution in the historical defect pattern library; performing matching judgment on the dynamic threshold value and the real-time defect feature matrix through a multi-level logic decision model, and outputting a defect type, a position coordinate and a confidence score; and based on the defect type and the confidence score, triggering adaptive compensation control of the packaging process parameters, generating a feedback control instruction, and adjusting a packaging equipment execution mechanism in real time. The packaging quality and reliability can be improved, and the production cost and the defective rate can be reduced.

The invention discloses an intelligent welding quality evaluation method and system based on vision, and relates to the technical field of welding quality evaluation.The method comprises the steps that the welding process is monitored in real time through multi-mode imaging equipment, weld joint surface texture, molten pool heat distribution and three-dimensional shape information are synchronously obtained, and a three-dimensional voxel model is constructed; establishing a two-stage multi-channel architecture for executing dynamic resource scheduling, and extracting geometric features and deep semantic features in the three-dimensional voxel model; and on the basis of the defect confidence coefficient vector, in combination with the real-time process parameters and the molten pool state, a dynamic evaluation model of the welding quality index is constructed, and time-phased quality scores are calculated and output through stage weighting. According to the method, the welding seam surface texture, molten pool heat distribution and three-dimensional shape information are synchronously collected through multi-mode imaging equipment, a texture-temperature-space coordinate bound three-dimensional voxel model is constructed, and multi-source heterogeneous data fusion analysis of the welding quality is achieved.

The invention relates to the technical field of chip temperature control, and discloses a chip temperature regulation and control system and method, and the method comprises the steps: building a thermal field dynamic model, integrating real-time power consumption data and environment heat dissipation parameters, and generating a thermal resistance adjustment coefficient and a power consumption correction coefficient; establishing a temperature prediction network to perform multi-source temperature field prediction; a dynamic regulation and control strategy is set according to a prediction result, and heat dissipation control parameters are optimized to achieve thermal field balance control; and executing feedback calibration and model iteration. The system comprises a thermal field dynamic modeling module, a multi-source temperature field prediction module, a dynamic regulation and control strategy execution module, a feedback calibration module and an iteration module. The method can accurately predict the heat distribution of the chip, realizes real-time and intelligent temperature regulation and control, improves the performance and reliability of the chip, reduces the energy consumption, and has good adaptability and universality.

The invention relates to the technical field of connector layout optimization, and discloses a high-density four-row connector layout intelligent optimization method. The method comprises the steps that design parameters of four rows of connectors on the high-density circuit board are collected, the design parameters comprise connector position coordinates, the number of pins and electrical impedance values, and related environment data comprise temperature distribution, electromagnetic interference intensity and vibration frequency; performing standardized alignment processing on the design parameters and the environment data to form a layout data set with unified dimensions; the layout optimization model is used for processing the layout data set, an initial layout scheme is generated, and the initial layout scheme comprises connector arrangement sequence and position adjustment suggestions; monitoring change data of the working state of the circuit board in real time, wherein the change data comprise current fluctuation and heat distribution updating; and identifying a layout abnormal condition based on the change data, performing iterative correction on the initial layout scheme according to the layout abnormal condition, and outputting a final optimized layout scheme. The method can dynamically adapt to the working state of the equipment and improve the layout rationality.

The invention provides a cooling adjusting method and system for an injection mold, and relates to the technical field of injection molds. The method comprises the following steps: acquiring real-time temperature data in the injection molding process of the mold by utilizing temperature sensors arranged at a plurality of preset measuring points of a mold cavity of the injection mold; based on the real-time temperature data, a mold cavity heat distribution model representing mold cavity temperature distribution information is generated; according to the mold cavity heat distribution model, the mold cavity is divided into a plurality of sub-cooling areas, and each sub-cooling area corresponds to at least one cooling loop; determining the temperature state of each sub-cooling area based on the mold cavity heat distribution model, and generating a flow regulation instruction of the corresponding cooling loop according to the temperature state; and controlling an electric control valve and a variable frequency water pump of each cooling loop according to the flow regulation instruction so as to regulate the flow of the cooling fluid flowing through each sub-cooling area. According to the technical scheme, partition precise adjustment of the cooling process of the injection mold can be achieved.

The invention relates to the technical field of wind power operation and maintenance technologies, and discloses a combined heat dissipation system of a fan, the system comprises a multi-source sensing module, a decision control module, a heat dissipation execution module and a safety early warning module, and by setting multi-mode cooperative control, when fan heat dissipation regulation and control are carried out, the heat dissipation of the fan can be controlled in a multi-mode cooperative mode; a dynamic matching mechanism of temperature field characteristics and heat dissipation modes is established, and air cooling, liquid cooling and phase change strengthening modes are automatically switched in real time according to the temperature rise rate and the heat distribution gradient, so that the system can accurately adapt to heat dissipation requirements under different working conditions, timely heat dissipation of a high-temperature core area is guaranteed, the heat dissipation response accuracy is improved, and the service life of the system is prolonged. By arranging the three-dimensional thermal field balancing system, the hot area distribution difference of the bearing, the winding and the power module is recognized in real time, the cooling liquid flow and the airflow guide angle are dynamically adjusted, the three-dimensional thermal unbalance phenomenon in a traditional heat dissipation mode is eliminated, and it is guaranteed that the temperature gradient of all areas in the motor is always kept within a safety threshold value.

The invention discloses a waste heat recovery scheduling method and system for a two-phase cold plate of a data center, and relates to the technical field of refrigeration and heat management. The waste heat recovery scheduling method and system for the two-phase cold plate of the data center comprises the following steps that S1, key thermal parameters and tail end state variables are collected through multiple types of thermal monitoring devices, and thermal state monitoring data are obtained and preprocessed; s2, on the basis of the thermal state monitoring data and in combination with an SLA configuration file, performing priority division on the heat utilization terminals, and constructing a scheduling deviation judgment mechanism to identify thermal state changes; s3, under driving of the regulation and control instruction, accessing multi-source waste heat and distributing the multi-source waste heat to each terminal scene, and evaluating a matching condition of the waste heat and a terminal demand; and S4, based on the change of the heat distribution state and the thermal state monitoring data, identifying an overload risk in combination with a multi-parameter linkage mechanism. The problems that waste heat recovery is insufficient and the energy utilization rate is limited under the light-load and multi-heat-source cooperative working condition are solved.

The invention discloses a high-voltage integration and cooperative control method and system for an energy storage system, and the method comprises the steps: carrying out the three-dimensional space coupling design of a high-voltage box and a power conversion system PCS through a topological optimization algorithm according to the power level and heat distribution demands of the energy storage system, and generating a physical layer architecture scheme of a high-voltage all-in-one machine; based on a physical layer architecture scheme of the high-voltage all-in-one machine, constructing a collaborative optimization data set by using a timestamp alignment technology; inputting the collaborative optimization data set into a model predictive control framework to generate dynamically adjusted PCS working parameters; and according to the PCS working parameters, the internal temperature distribution of the high-voltage all-in-one machine is calculated in real time through the three-dimensional thermal field reconstruction model, the rotating speed of a cooling fan and the switching frequency of a power device are dynamically adjusted, and a cooperative control instruction is generated. According to the embodiment of the invention, the integration level and the cooperative control capability of the high-voltage energy storage system can be improved, and the efficient and stable operation of the energy storage system is realized.

The invention provides a frying and baking equipment heat preservation automatic control method and system, and relates to the technical field of food processing equipment control, and the method comprises the steps: collecting temperature signals of different positions through a plurality of groups of thermocouples and infrared thermal imaging sensors which are arranged in a frying and baking area, constructing a dynamic three-dimensional temperature field model, and obtaining a dynamic three-dimensional temperature field model; calculating a temperature standard deviation and a maximum temperature gradient in real time according to the dynamic three-dimensional temperature field model; and when the temperature standard deviation is larger than or equal to a preset threshold value, according to the heat distribution difference of the three-dimensional temperature field model, a multi-region differential compensation strategy is generated, the power distribution proportion of each heating unit is dynamically adjusted, and the duty ratio parameter of pulse width modulation is optimized in real time. Through multi-sensor accurate monitoring, dynamic regulation and control and intelligent stop judgment, uniform and stable temperature control, energy conservation and consumption reduction are achieved, the service life of equipment is prolonged, meanwhile, the use safety of a user is guaranteed, and the cooking experience is improved.

The invention relates to the technical field of wire performance detection, and discloses a wire high temperature resistance detection method, device and equipment and a storage medium. The method comprises the following steps: arranging micro thermocouple array sensors on the surface, the bending part and the connecting point of an outer insulating layer of a to-be-measured wire rod to obtain a wire rod temperature monitoring network; placing the to-be-tested wire rod in a constant-temperature box to execute a high-temperature cyclic loading test, and collecting real-time temperature response data of the to-be-tested wire rod; carrying out temperature gradient analysis and heat distribution characteristic calculation to obtain a temperature change characteristic parameter set; executing temperature fluctuation compensation and thermal stress accumulation calculation to obtain thermal stress characteristic parameters; and carrying out aging characteristic analysis on the wire insulating material through the thermal stress attenuation network model to obtain wire predicted life and failure probability distribution of the to-be-tested wire in a high-temperature environment. The method can comprehensively capture the temperature change characteristics of each part of the wire rod, and achieves the precise prediction of the failure probability of the wire rod under different temperature conditions.

The invention discloses a rubber product quality detection method and system, and relates to the related technical field of rubber quality detection.The method comprises the steps that rubber products are conveyed to a target detection table, and data acquisition of the rubber products is executed; inputting the wave impedance distribution data and the surface heat distribution gradient field into a defect causal atlas channel to execute phase inversion fusion processing, establishing a cross-modal coupling phase tensor, and identifying deep defect response characteristics by solving a phase difference matrix; activating a pressure spectrum sensing unit to apply control pressure, reading a local mechanical response spectrum, sending the local mechanical response spectrum to a cross-modal calibration layer, and executing joint error authentication; and performing quality detection report according to a self-calibration defect mapping result. The technical problems that in the prior art, multi-modal sensing data fusion efficiency is low, deep defects are difficult to comprehensively recognize, and consequently the quality detection precision and reliability of rubber products are insufficient are solved, and the technical effects that cross-modal cooperative detection is achieved, and the precision and reliability of defect recognition results are improved are achieved.

The invention discloses a water-cooling energy consumption adaptive regulation and control method suitable for a data center, and the method comprises the following steps: obtaining a multi-dimensional operation parameter set of the data center in real time, and generating a real-time thermal load density distribution diagram reflecting the heat distribution condition in a machine room; calculating the overall thermal deviation degree and the local hot spot intensity, and solving through a dynamic energy efficiency optimization function to obtain a target system supply and return water temperature difference and a target cooling liquid flow; inputting into a hydraulic and thermodynamic simulation model, and generating an optimal multi-device coordinated regulation instruction set; and executing the multi-device coordinated regulation instruction set, and then performing parameter calibration on the hydraulic and thermodynamic simulation model. The method has the following advantages and effects that the thermal environment of the machine room can be sensed in real time, the energy consumption and heat dissipation requirements can be intelligently balanced, and multiple devices in the cooling system can be cooperatively regulated and controlled, so that the overall energy consumption of the cooling system is optimized while the local overheating risk of the machine room is thoroughly eliminated.

The invention relates to the technical field of intelligent temperature control, in particular to an industrial mainboard computer heat dissipation optimization method and system based on AI intelligent regulation and control, and the method comprises the steps: obtaining mainboard real-time temperature data, carrying out time sequence preprocessing, and generating distributed time sequence data; extracting thermal features and classifying and identifying the thermal features to obtain coordinate distribution of the high-energy-consumption area; inputting a classification model to output a classification result, and screening areas exceeding a preset threshold to determine a priority regulation label; performing spatial interpolation based on the label to generate a heat map, and extracting heat distribution boundary data; analyzing thermal resistance according to the boundary data and identifying a bottleneck region to obtain thermal resistance distribution; performing fan parameter optimization based on the thermal resistance to obtain an optimized heat dissipation strategy; inputting a load model, and outputting dynamic load adaptation regulation and control parameters; and real-time regulation and control and energy efficiency evaluation are executed according to the regulation and control parameters, and final heat dissipation operation parameters are screened and solidified. The method can solve the problem of heat dissipation control lag.

The invention discloses a secondary network heat supply temperature control method and device based on a negative pressure water mixing technology, and relates to the technical field of secondary network heat supply control. The secondary network heat supply temperature control method and device based on the negative pressure water mixing technology comprises the steps that S1, operation data, structure steady state data and thermal environment data in a current heat supply task are collected, and a standardized heat supply working condition data set is constructed after preprocessing; s2, local hydraulic fluctuation characteristics are evaluated, and the water mixing proportion, the water supplementing flow and bypass path configuration are dynamically adjusted; s3, jointly analyzing the temperature difference of supply water and return water, the heat deviation and the valve state, and driving water mixing adjustment and path optimization; s4, evaluating adjustment intensity and heat response deviation, and realizing abnormal disturbance response and adjustment strategy correction; and S5, recording negative pressure, uneven heat and cold and response data for subsequent diagnosis and steady state identification. The problems that a traditional water mixing control means is difficult to effectively inhibit pressure fluctuation of the water return end, local negative pressure is easily formed, and local energy waste and uneven heat distribution are caused are solved.

The invention discloses a liquid cooling heat dissipation control method and device for a high-power charging pile, and the method comprises the steps: obtaining the temperature data of a heating element in the charging pile and external environment parameters, building a dynamic heat load distribution model through a pre-built heat conduction algorithm according to the incidence relation between the temperature data and the charging power, and achieving the heat dissipation of the charging pile. Obtaining heat distribution characteristics; according to the heat distribution characteristics, in combination with a preset heat dissipation efficiency threshold value and a power density requirement in the liquid cooling heat dissipation control system, the cooling liquid flow and the cooling liquid circulation rate under the current working condition are calculated, and a cooling liquid distribution scheme containing a flow distribution proportion and a circulation path is determined; and if it is detected that the external environment temperature in the external environment parameters exceeds a preset threshold range, corresponding environment challenge data are matched from a working condition database, the cooling liquid circulation rate is adjusted, an auxiliary heat dissipation mechanism is activated, and an environment adaptation type heat dissipation mode is generated. The heat dissipation efficiency of the charging pile is improved, precise temperature control is achieved, and therefore safe and stable operation of the charging pile is guaranteed.

The invention relates to the technical field of thermal equipment operation state dynamic test and compensation control, in particular to an AI-based boiler air pre-heater temperature uniformity regulation and control system, which comprises a collaborative closed-loop control network of a data acquisition module, an AI prediction module, a heat storage system control module, a temperature compensation control module and a thermal stress analysis module. The data acquisition module acquires flue gas temperature, coal quality parameters and load instructions in real time, the flue gas temperature, the coal quality parameters and the load instructions are transmitted to the AI prediction module through an industrial bus, XGBoost, LightGBM and a deep neural network model are used for carrying out spatial-temporal feature extraction on the evolution trend of a temperature field, and the heat storage system control module dynamically switches heat storage and release modes according to the load state. The heat distribution proportion among the multiple units is adjusted by combining the three-dimensional stress field distribution data of the thermal stress analysis module; the bottleneck of lack of thermal inertia regulation of an existing system is broken through, dynamic balance of a temperature field under the condition that thermal stress of a heat transfer element is controllable is achieved, and the heat exchange efficiency and operation stability of the air pre-heater are improved.