118 results about "Temperature response" patented technology

The invention relates to the technical field of industrial control systems, in particular to a PET extruder multi-zone intelligent temperature regulation and control system, which comprises a temperature field parameter acquisition module for acquiring the input power, the real-time temperature value, the temperature change rate value and the temperature difference value between adjacent temperature zones of an extruder to obtain a temperature zone associated state set; and summarizing and mapping the temperature zone association state set, and establishing temperature field response characteristics. According to the method, through correlation analysis of the temperature states of the multiple areas, independent adjustment of a single area is upgraded to dynamic optimization based on the thermodynamic coupling relation, and the coordination of temperature adjustment of the multiple areas is improved. Dynamic parameters required by temperature regulation and control can be calculated in real time in combination with the heat transfer rate, the temperature response delay time and the temperature response gain coefficient of the temperature interval instead of depending on a fixed set value, different operation working conditions are adapted, and the regulation and control flexibility is improved.

The invention relates to the technical field of self-adaptive control, and discloses a self-adaptive temperature control method and system for an automobile heater, and the method comprises the steps: calculating the real-time temperature deviation and temperature change rate of an actuator according to multi-dimensional temperature data; thermal inertia dynamic analysis is carried out on the historical heating power and temperature response relation through a preset thermal inertia compensation function, and a thermal inertia index of the actuator is obtained; the real-time temperature deviation, the temperature change rate and the thermal inertia index are jointly input into a preset fuzzy PID controller, and a preliminary power adjustment instruction of an actuator is output; analyzing the temperature change trend of the actuator in the time period, and performing prospective correction on the initial power adjustment instruction based on the temperature change trend; and controlling an actuator to execute heating operation according to the temperature control instruction, collecting real-time feedback temperature after the heating operation is executed, and performing joint online correction on parameters of the thermal inertia compensation function and a prediction coefficient of the time sequence model according to the real-time feedback temperature. According to the invention, the accuracy of self-adaptive temperature control of the heater can be improved.

The invention relates to an injection mold temperature control method and device and computer equipment. The method comprises the following steps: acquiring temperature data of a plurality of temperature measuring points of the injection mold to obtain a temperature data matrix; establishing a heating and cooling input matrix and a temperature response matrix, and solving to obtain a heat transfer path coefficient matrix; taking the temperature data matrix as state input, constructing a depth deterministic strategy gradient control network comprising a gating circulation unit and a full connection layer, and performing linear mapping to obtain a hybrid action space; inputting the heat transfer path coefficient matrix and the mixed action space into a training environment, performing iterative training on a depth deterministic strategy gradient control network based on an experience playback mechanism, and updating network parameters by calculating a reward function to obtain a temperature control model; and deploying the temperature control model to a target control system, and calculating a real-time control parameter set. According to the invention, coordinated control of the heating stage and the stabilizing stage is realized, the injection molding period is shortened, and the energy consumption is reduced.

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 relates to the technical field of facility management, in particular to a prediction-driven data center thermal resistance control system which comprises an airflow response acquisition module, a thermal hysteresis offset correction module, a heat flux trend extraction module, an air volume priority allocation module and an airflow execution verification module. According to the method, through extraction and sorting of air supply trigger time and thermosensitive node temperature response differences, the temperature control sensing precision is improved, the corrected time sequence is input into the model, the prediction accuracy is enhanced, and dynamic identification of the high-heat-load area and the early warning capability are enhanced in combination with the area temperature change trend and the heat dissipation capability upper limit; the distribution sequence is sorted according to the heat flux trend and the air volume resource relation, the air volume allocation efficiency and the matching degree are improved, the temperature change trend is compared after execution, the adjusting effect reliability is improved, a data closed loop with response recognition, trend extraction, resource sorting and feedback verification as the core is constructed in the whole process, and the initiative and stability of system heat management are enhanced.

The invention provides a rotary table bearing-torque motor thermal vibration coupling modeling method, and relates to the technical field of machine tool reliability analysis. Comprising the steps of calculating bearing restoring force, torque and elastic rigidity; giving a dynamic balance equation of the main shaft system; unbalanced magnetic pulling force and unbalanced mass excitation are calculated; a displacement field is solved, and load changes caused by the displacement field are transmitted to the thermal model; the contact force borne by the bearing is updated by considering the load effect related to displacement, and the friction heat generation of the bearing and the heat generation of each part of the motor are calculated; calculating thermal deformation and thermal displacement of the bearing; thermal resistance among nodes is calculated, and a temperature field equilibrium equation is given through a thermal resistance network to achieve rapid thermal-mechanical coupling analysis; the thermal equilibrium equation is solved to calculate temperature response; importing the latest temperature into the kinetic model; lubricating grease viscosity and bearing thermal deformation are updated; and repeating the steps to finally obtain the main shaft displacement field and temperature field response. The method is high in accuracy, high in universality, low in test cost and high in test efficiency.

The invention discloses a host power consumption and temperature balance control method and system, a medium and a program product, and relates to the field of electrical digital data processing.The method comprises the steps that a plurality of heat dissipation air channels are constructed according to air flow data; collecting temperature data in each heat dissipation air duct, and respectively calculating the temperature response rate and the temperature attenuation rate of each heat dissipation air duct; dividing the calculation tasks into a first type of calculation tasks and a second type of calculation tasks based on the temperature response rate; establishing migration rules of the first type of calculation tasks and the second type of calculation tasks according to the temperature attenuation rate; when it is detected that the temperature in any heat dissipation air duct is larger than a temperature upper limit threshold value, migrating a first type of calculation tasks being executed in the heat dissipation air ducts to target heat dissipation air ducts with the temperature lower than a preset temperature threshold value; and migrating the second type of calculation tasks being executed in the target heat dissipation air channel to the heat dissipation air channel. According to the invention, the accuracy of heat transfer and accumulation in the equipment is improved, and the accuracy of temperature control management is further improved.

The invention relates to the technical field of oil and gas well oil testing and production testing, in particular to a method for monitoring the well temperature of a horizontal well after perforation-bridge plug fracturing and evaluating the fracturing effect, and the method comprises the steps that before the horizontal well is fractured, well shaft temperature response data of well shut-in stability before fracturing are measured and collected through a strip-shaped temperature detector, and a well temperature response curve before fracturing is obtained; staged fracturing is carried out in the horizontal well, after staged fracturing of the horizontal well is completed, all bridge plugs in the well are drilled, after the well shut-in temperature is stable, well shaft temperature response data of well shut-in stability after fracturing are measured and collected through a strip-shaped temperature detector, a well shaft temperature response curve after fracturing is obtained, the shapes of the well shaft temperature response curve before fracturing and the well shaft temperature response curve after fracturing are compared, and the well temperature response curve before fracturing and the well shaft temperature response curve after fracturing are obtained. And the fracturing effect is evaluated according to the well section distribution position and amplitude change of the negative temperature anomaly. According to the invention, the ground direct reading of temperature data can be realized, the temperatures of different positions in the whole shaft space can be continuously measured in real time, the temperature monitoring is accurate, and the accurate evaluation of the fracturing effect is facilitated.

The invention discloses a method for identifying micro-leakage of a shaft by using distributed temperature gradient sensing data, which comprises the following steps of: acquiring original temperature data of a continuous time sequence of different depths of the shaft through a distributed temperature sensing device, and transmitting the original temperature data to a Modin distributed sensor data processing platform; the platform divides and distributes the data and screens abnormal data; calling a temperature field dynamic evolution prediction algorithm to calculate a predicted temperature value of each depth at each moment; starting a temperature gradient space-time correlation detection algorithm, comparing the predicted temperature with the actual temperature to obtain a deviation sequence, and analyzing and extracting temperature gradient change characteristics; an ultrasonic excitation thermoelastic effect recognition model is applied, ultrasonic excitation is applied, temperature response data are collected, and whether micro leakage exists in the shaft or not and the specific position are determined through comparison and analysis of the incidence relation between the thermoelastic effect and the temperature gradient change. According to the method, an efficient and reliable solution is provided for shaft micro-leakage identification, safe operation of the shaft is guaranteed, and stratum pollution and resource waste are reduced.

The invention discloses a temperature measurement method and a temperature measurement nut, and belongs to the technical field of equipment temperature measurement. According to the method, the dynamic thermal radiation interference coefficient calculation model is constructed through the historical temperature measurement data and the equipment operation parameters, so that the dynamic acquisition of the dynamic thermal radiation interference coefficient can be realized based on the real-time temperature measurement data, and the real-time temperature measurement data is corrected to obtain the corrected temperature measurement data; performing spectral analysis on the real-time temperature measurement data to determine a thermal radiation change frequency correction coefficient, constructing a temperature response function based on the real-time temperature measurement data, and further determining a thermal response time constant based on the temperature response function; and then thermal inertia lag compensation processing is carried out on the corrected temperature measurement data through a thermal radiation change frequency correction coefficient, a thermal response time constant and equipment operation parameters to obtain actual temperature data of the to-be-measured equipment, so that the problem of inaccurate temperature measurement in a high-temperature environment in the prior art can be solved. And the accuracy of temperature measurement in a high-temperature environment is improved.

The invention relates to the technical field of material surface quality nondestructive testing, and discloses a rapid identification method for surface microdefects of a copper alloy strip, which comprises the following steps: firstly, applying a specific time sequence thermal excitation sequence to a surface to be detected, the sequence comprising a state pre-excitation pulse for inducing nonlinear response of thermal physical properties of a material; secondly, synchronously acquiring whole-process dynamic thermal response under the action of thermal excitation, and constructing a thermal response data cube; thirdly, extracting a time-temperature response curve for each pixel point in the data cube, and calculating a multi-dimensional dynamic thermodynamic feature vector; and finally, inputting the feature vector into a pre-trained supervised learning classification model to obtain a pixel-level classification label, and performing post-processing to determine the type, position and size of the defect. According to the method, the nonlinear and spectral response difference of the material is deeply excavated, the feature vector with high discrimination degree is constructed, and the detection sensitivity and classification accuracy of micron-sized physical and chemical defects can be effectively improved.

The invention relates to a fluid temperature and velocity co-measurement method and system based on iterative optimization phosphorescent particle tracking. The method comprises the following steps: dispersing phosphorescent tracer particles in fluid, and carrying out preprocessing operation on an acquired image to obtain a particle phosphorescent signal image; and deeply analyzing the processed image based on a spherical particle light spot integral discretization light intensity function, and determining the position of the tracer particle and phosphorescence intensity information. Meanwhile, the cross-frame matching technology is used for tracking the particles, and a particle motion trail and a phosphorescence intensity attenuation curve are obtained. And calculating the speed of each particle according to the particle motion trail, and processing the phosphorescence intensity attenuation curve according to the temperature response characteristic of the phosphorescence lifetime to obtain the temperature of each particle. And finally, performing post-processing on the speed and temperature data of each particle to realize synchronous measurement of the speed and temperature of the fluid so as to obtain fluid speed-temperature field data. High-precision measurement can be realized in a large-scale unsteady flow field, and a fluid flow and heat transfer coupling mechanism can be deeply explored in an assisted manner.

The invention provides a temperature distribution inversion method based on a multi-vertex grid and a high-robustness error functional, and the method comprises the steps: 1, obtaining a temperature gradient change rule of a measured structure under a typical thermal load condition, and determining a three-dimensional multi-vertex grid division scheme and a temperature sensor layout form of the measured structure; step 2, establishing an m vertex grid basis function model, and constructing a conversion matrix between a regular grid and an irregular grid; 3, establishing a high-robustness error functional between the theoretical temperature of the centroid position of each surface of the m-vertex grid and the actually measured temperature of the sensor; 4, a temperature matrix equation containing a temperature coefficient matrix and a temperature amplitude matrix is constructed, temperature vectors of all grid vertexes are solved, the m-vertex grid basis function model is combined, three-dimensional temperature distribution in the structure space is inverted, and according to the method, only few sensors need to be adopted, the global temperature response of the structure can be obtained, and the inversion precision is high; the method is simple, convenient and high in real-time performance.

Systems and methods are disclosed for determining thermal behaviour of a material. A method includes: receiving measured temperatures of the material, times of the measured temperatures, a volumetric heat capacity of the material, and a heat flux, wherein the flux provides a temperature response in the material; and applying a non- linear fitting technique to determine a time-dependent thermal property of the material. Applying the non-linear fitting technique includes: computing estimated temperatures using an initial estimate of the time-dependent thermal property and a temperature function; and iterating values of the time-dependent thermal property to minimize an error between the measured temperatures and estimated temperatures computed using the iterated values of the time-dependent thermal property, wherein the time- dependent thermal property is determined as a value that results in a minimum error measure between the measured temperatures and the estimated temperatures.

The invention provides a heating radiator phase change energy storage real-time control method, which comprises the following steps: according to an obtained energy storage state distribution condition, analyzing a thermal load distribution deviation between each group of heating radiators, calculating a deviation ratio between the actual power and the average power of each group of heating radiators, comparing the deviation ratio value by adopting a preset threshold range, and determining the phase change energy storage of each group of heating radiators. Determining the thermal load distribution deviation ratio of each group of heating radiators; according to the optimized power distribution scheme, an adjustment instruction is sent to a control unit of each group of heating radiators, first-time energy storage state detection is carried out, real-time power execution feedback data and temperature response data of a phase change material are obtained, and whether the adjusted heat supply power reaches a balance state or not is determined; and according to the judged synchronous control deviation degree, the energy storage progress is dynamically corrected, and synchronous operation parameters of each group of heating radiators are obtained by optimizing the latent heat release rate of the phase change material in real time.

The present application relates to the technical field of electric tracing heating systems, and specifically relates to a method, device and system for operating and controlling an electric tracing heating system, which specifically includes: analyzing the severity of the heat compensation imbalance condition of the electric tracing caused by external strong convection and PTC characteristics, and constructing a heat compensation imbalance degree of the electric tracing; analyzing the heat compensation lag condition of the electric tracing for the heated body caused by heat inertia, and constructing a compensation response lag of the electric tracing; combining the two to construct a temperature compensation factor, obtaining the proportional term of the PID control system in the next control interval, and adjusting the power of the electric tracing heating system, reducing the heat compensation lag of the electric tracing heating system under unstable convective heat dissipation conditions, avoiding the drawback that the power output of the electric tracing heating system is frequently adjusted due to the influence of temperature response compensation lag, resulting in local overcooling of the heated body, and improving the temperature stability of the heated body.

The invention provides an illumination radiation heat load dynamic prediction and compensation control method and system based on multispectral perception, and the method comprises the steps: collecting the illumination intensity of each indoor wave band in real time through a multispectral sensor, constructing a spectrum space coupling mapping model through combining the geometric structure, material absorptivity and incident angle information of a heat absorption surface, and carrying out the dynamic prediction and compensation of the illumination radiation heat load. Calculating an equivalent radiation heat disturbance quantity; thermodynamic parameters are fused to establish a thermodynamic prediction model, and the future room temperature change trend is predicted; identifying whether the disturbance type is a stationary type or a mutation type by analyzing the dynamic relationship between the thermal disturbance sequence and the temperature response; and a heat pump compensation control instruction is generated, and advanced adjustment is achieved. The problems that a traditional temperature control system is delayed in response to illumination thermal disturbance and inaccurate in recognition are solved, and the thermal comfort and the energy efficiency level are remarkably improved.

The invention relates to the technical field of on-line aging, in particular to an on-line aging method and system for a projector, and the method comprises the following steps: dividing temperature sections through an aging chamber, carrying out the aging of the projector, collecting temperature change data, calculating the temperature change rate, response delay and phase difference fluctuation, and generating a thermal response data set; temperature response delay and phase difference abrupt change are identified, a thermal response index is calculated, aging is suspended and temperature control is adjusted when a threshold value is not reached, temperature zone aging is switched, aging is terminated when response is weak, a temperature zone record set is generated, and a change interval is counted to generate an aging result. According to the method, the adaptability is dynamically judged by continuously collecting temperature data, calculating thermal response parameters and generating response indexes through normalization, aging is suspended and temperature adjustment intervention is carried out when the indexes are low and continuous, and when the indexes are met, temperature zones are switched, response trends and aging tracks are archived and converted into thermal response for aging, so that the sensing and intervention precision is improved.

The invention discloses a cutting machine motor intelligent temperature management method and system based on load prediction, relates to the technical field of cutting machine motor temperature management, and is used for solving the problems of temperature response lag and local overheating under the conditions of complex tracks and load fluctuation. In the operation process of the cutting machine, three-phase stator side current signals of the motor are continuously captured, a current vector input quantity is obtained through coordinate transformation and input into the sliding mode observer to estimate the rotor position and the motor rotating speed, a load trend quantity is generated, combined compensation modulation is carried out, and a compensation value is output to a power output link to dynamically adjust the duty ratio. According to path analysis, marking a hot stacking sensitive path section, calculating a power output change rate and shielding wind flow disturbance intensity, screening out a thermal response to-be-detected section, collecting data through a thermosensitive channel to construct a regional thermal risk index, executing differential air cooling adjustment and power modulation path adjustment, and recording state data in real time; and fine management of the full-working-condition temperature of the motor of the cutting machine is realized.

The embodiment of the invention provides an intelligent heating method and device based on machine learning and electronic equipment, and the method comprises the steps that preset temperature adjustment operation on indoor temperature is controlled, the temperature change condition of the indoor temperature is obtained, and the temperature response performance of a room is determined; acquiring a preset target temperature, determining a regulation and control temperature and a time pre-threshold thereof according to the target temperature and the temperature response performance, and determining a target control strategy according to the temperature response performance and the regulation and control temperature; acquiring an environment state in real time, identifying the environment state through a pre-trained environment identification model, updating the temperature response performance, and adjusting the target control strategy through the updated temperature response performance; according to the method provided by the embodiment of the invention, through accurate thermal energy compensation, the indoor temperature can be always kept within a set numerical value or range, and discomfort caused by large-range fluctuation of the temperature is reduced.

The application discloses a driving motor temperature estimation method based on machine learning and double Kalman filtering and relates to the technical field of motor temperature monitoring and control. The application comprises the following steps: constructing a finite element simulation model, collecting motor loss data and temperature response data under multiple working conditions through finite element simulation, and constructing an offline parameter database through a physical information machine learning method; based on the offline parameter database, a second-order lumped parameter thermal network model is constructed, and the second-order lumped parameter thermal network model is converted into a linear parameter variation state space model. The application switches parameters in real time through an LPV model, dynamically corrects model errors in combination with a double Kalman filter, overcomes parameter drift caused by temperature and rotating speed, and solves the problem that the precision of an offline modeling open-loop estimator is insufficient and accurate real-time estimation under all working conditions cannot be realized due to modeling errors, time-varying thermal parameters and other reasons in the traditional rotor temperature estimation method under wide-range complex operating conditions of an electric vehicle.

The invention discloses an underground water-surface water lateral exchange flux fine inversion method and system, and belongs to the technical field of hydrogeological monitoring. The method comprises the following steps: acquiring actually measured temperature response data of an active heating optical fiber arranged along a riparian zone in an active heating process; constructing an underground water-thermal coupling numerical model for representing the site; an ensemble data assimilation algorithm is adopted, stratum prior information obtained by analyzing an optical fiber drilling rock core is combined, actually measured temperature data and simulated temperature data are compared through iteration, and non-homogeneous-mass hydrogeological parameters are obtained through inversion; and finally, carrying out numerical simulation based on the high-precision parameters, and calculating to obtain the lateral exchange flux. According to the method, the active heating optical fiber test and the improved integrated smooth multi-data assimilation algorithm are fused, so that the lateral exchange flux can be described with decimeter-scale resolution and high precision, and key technical support is provided for water resource management and environmental protection.

The invention discloses an Ebnite rubber roller production method based on temperature and pressure intelligent regulation and control, and relates to the technical field of rubber roller production, and the method comprises the following steps: constructing a temperature collection credibility function according to a local temperature abnormal distribution matrix, carrying out fitting comparison on the temperature response of each collection point and a target temperature rise curve, and obtaining a target temperature rise curve; and generating a credibility index for judging the credibility of the temperature data, and correcting the judgment logic of temperature acquisition according to the abnormal change of the local temperature under the condition of abnormal heat conduction caused by air resistance in the vulcanization heating process. The problem of temperature control misjudgment caused by abnormal local heat conduction due to formation of air resistance in the vulcanizing and heating process of the Ebnite rubber roller is solved, dynamic identification and self-adaptive regulation and control on abnormal temperature and pressure are realized, sufficient vulcanization, uniform structure and stable performance of each area of the rubber roller are ensured, and the product quality and the service reliability are improved.

The invention provides an intelligent monitoring method and system for an electronic detonator continuous production line. The method comprises the following steps: performing continuous temperature field scanning on the surface of the injection mold to obtain gradient change data; driving a temperature response unit array configured by the mold to execute subarea phase change triggering, absorbing heat of a local overheating area and generating a phase change completion degree quantization parameter; analyzing and positioning a heat-flow density abnormal region by using a thermal resistance network, and performing spatial topological correlation processing to generate a heat-flow density deviation distribution diagram; executing multi-objective optimization on a cooling channel airflow controller to generate a self-adaptive airflow distribution instruction set; and path planning is conducted on the air cooling execution mechanism, and a mold temperature production line regulation and control parameter set is generated. According to the technical scheme provided by the invention, through three-stage cooperation of zoning phase change temperature control, explosive chamber safety association and multi-target airflow optimization, the mold temperature balance control is realized while the thermal shock risk of the detonator charging area is avoided.

The invention provides a power load monitoring data fusion method, device and equipment and a storage medium, and the method comprises the steps: firstly obtaining power load multi-source data containing meteorological elements, and constructing a power physical constraint branch according to the data; a differential equation module is used for modeling a temperature response curve, a delay integral module is used for simulating a rainfall penetration process, and physical rule dynamic weights are generated and set as gating signals. And the gating fusion unit is controlled to output the weight through the signal, so that load monitoring physical rule embedding is realized. According to the method, a power physical constraint branch is constructed, a temperature-power relation and a precipitation hysteresis effect are modeled by a specific module, a dynamic weight driving gating signal is generated, a physical rule is embedded into a fusion model, and the accuracy and generalization of load monitoring are improved.

The invention discloses a CO2 phase conversion dynamic monitoring system and method suitable for a CO2 conveying pipeline, and belongs to the technical field of CO2 capture, utilization and storage. The system comprises a gas supply system, a pressure control system, a phase change controller, a high-pressure loop system, a measuring device and a data processing device. According to the system, gas is supplied to two pieces of equipment in the phase change generation system through one gas supply system, transformation observation between different phase states is very comprehensive, and the research cost is saved. The pressure and temperature response conditions of CO2 phase change can be accurately and efficiently reflected by adjusting parameters such as pressure and temperature of the system.

The invention relates to the technical field of welding, and discloses a latticed column and tubular pile welding method which comprises the following steps: judging whether welding conditions are met or not according to an environmental particle concentration value, and determining initial welding power according to a welding contact length; acquiring a temperature index value corresponding to each temperature analysis point, comparing the environment temperature value with historical data, determining a temperature similarity according to the environment temperature value and the historical data, determining a power adjustment coefficient according to the historical data when the temperature similarity is greater than or equal to a similarity threshold value, and determining a power adjustment coefficient according to the historical data when the temperature similarity is less than the similarity threshold value. Generating temperature response marks for the corresponding temperature analysis points according to the temperature index values, extracting feature points from the processed multidirectional images, combining the processed multidirectional images to obtain a welding image, judging whether repair welding is carried out or not according to the welding image, and adjusting target welding power according to the welding length and the welding contact length. The method has the characteristics of good dynamic adjustment and accurate welding.

The invention relates to a photovoltaic energy storage power station intelligent operation and maintenance method and system based on multi-modal data fusion. The method comprises the steps of obtaining current change data corresponding to a current change event; based on the current change data and the thermal characteristic parameters of the photovoltaic module, determining the thermal response characteristics of the photovoltaic module; determining cloud shadow moving characteristics according to the meteorological radar data; based on the cloud shadow movement characteristics and the thermal response characteristics, calculating thermal inertia compensation parameters triggered by the energy storage system in response; according to the thermal inertia compensation parameters and the current change data, generating a theoretical temperature response curve containing response characteristics of the energy storage system; obtaining infrared thermal imaging data considering the photovoltaic module, comparing the time sequence relation of the infrared thermal imaging data with the time sequence relation of the theoretical temperature response curve, and detecting a temperature anomaly event; and carrying out feature analysis on the detected temperature anomaly event, and distinguishing whether the temperature anomaly event is a real hot spot fault or temperature anomaly caused by thermal inertia in combination with a current recovery feature in the current change data.

A method, system, medium and program product for balanced control of host power consumption and temperature, relating to the field of electrical digital data processing, in which a plurality of heat dissipation ducts are constructed according to air flow data; temperature data in each heat dissipation duct is collected, and the temperature response rate and temperature decay rate of each heat dissipation duct are calculated respectively; computing tasks are divided into first-class computing tasks and second-class computing tasks based on the temperature response rate; migration rules for the first-class computing tasks and the second-class computing tasks are established according to the temperature decay rate; when it is detected that the temperature in any heat dissipation duct is greater than the upper temperature threshold, the first-class computing tasks being executed in the heat dissipation duct are migrated to the target heat dissipation duct whose temperature is lower than the preset temperature threshold; the second-class computing tasks being executed in the target heat dissipation duct are migrated to the heat dissipation duct. This application improves the accuracy of controlling the transfer and accumulation of heat inside the device, thereby improving the accuracy of temperature control management.

This application provides an integrated temperature-sensitive thermal barrier protection A2B2O7 ceramic material, its preparation method, and its application, which possesses A... 2‑ a The B2O7:aX material has a general structural formula and a crystal structure that is defective fluorite, pyrochlore, or a mixed two-phase structure. Doping with two or more types of luminescent ions allows for temperature measurement based on the fluorescence intensity ratio of non-thermally coupled energy levels, overcoming the limitations of relative sensitivity in traditional thermally coupled energy level temperature measurement. It utilizes the anti-thermal quenching or low-thermal quenching effects of the luminescent ions to extend the upper limit of temperature measurement, and the different temperature response characteristics of different luminescent ions enhance relative sensitivity. This material can be directly used to prepare a dual-function integrated coating for temperature sensing and thermal barrier protection, eliminating the difficulties of externally mounted sensors, avoiding damage to the coating integrity, and simplifying the complex layout of functional layers. It achieves the integration of thermal barrier protection and high-temperature sensing functions, providing a forward-looking solution for the safety assurance and condition monitoring of components operating in extreme high-temperature environments such as aero-engines and gas turbines.