399 results about "Temperature gradient" patented technology

The invention relates to a concrete temperature-stress two-parameter cooperative monitoring and early warning method and system, and belongs to the technical field of concrete structure health monitoring, and the method comprises the steps: activating a composite sensor network disposed at a preset position of a concrete structure, and executing a sensor self-calibration mode; the method comprises the following steps: synchronously acquiring temperature and stress original monitoring data of each node, processing based on an altitude air pressure compensation algorithm, and outputting a temperature gradient field matrix and a stress tensor sequence with aligned time domains; the method comprises the following steps: separately calculating a thermal stress component and an effective stress component, performing integral calculation on hydration reactivity, generating a multi-dimensional feature vector set, inputting a pre-constructed prediction model, executing time sequence evolution prediction, calculating a crack probability value, performing environment correction in combination with real-time environment parameters, outputting a risk level identifier, and matching a preset regulation and control strategy. And generating an equipment control instruction set and executing corresponding regulation and control actions. According to the invention, the accuracy and timeliness of crack risk prediction can be improved.

The invention provides a tunnel fire behavior inversion method based on multi-modal fusion and physical constraint, and aims to solve the problem that the position and power of a fire source are difficult to invert accurately in real time in traditional fire behavior monitoring. According to the method, data, temperature distribution images and physical parameters of distributed temperature sensors in a tunnel are collected, and a spatial-temporal feature fusion network is constructed; designing an information leakage prevention training mechanism, and adopting a modal random discarding and sensor shielding technology to avoid overfitting of the model to a specific input mode; a physical constraint loss function is introduced, and the temperature gradient, the maximum temperature rise and the longitudinal attenuation law are combined to ensure the physical rationality of an inversion result; a coarse-fine two-stage position prediction framework is adopted, and meter-scale precision positioning of the position of a fire source is achieved. According to the invention, the power and position of the fire source can be inversed accurately in real time, and reliable technical support is provided for intelligent monitoring and emergency rescue of tunnel fire.

The invention relates to the field of mold cooling optimization, and discloses an automobile mold cooling optimization system and method based on reinforcement learning, and the method comprises the steps: collecting the real-time temperature and flow data of each cooling loop, carrying out the preprocessing and abnormity filtering of the data, and constructing a multi-dimensional basic cooling state database through combining historical operation records and environmental parameters; performing spatial mapping and statistical analysis on the temperature and flow data in the basic database, identifying a high-temperature region with heat concentration and a part with remarkable temperature gradient, and forming a local heat feature model; establishing an independent control sub-model, and optimizing cooling water flow and temperature regulation parameters of each loop by adopting a simulation and reinforcement learning combined method; a local adjustment strategy and an overall cooling target are fused, and main loop parameters are optimized through a global control algorithm; in the mold cooling process, temperature and flow fluctuation are continuously monitored, and real-time data are input into an optimization system. The method has the advantage that the cooling precision and efficiency are improved.

The invention discloses a thermal balance control method for a liquid cooling charging module, and relates to the technical field of power electronics, and the method comprises the steps: deploying a multi-dimensional distributed temperature sensing array in a key heating region of the liquid cooling charging module; original data are acquired through the temperature acquisition module and transmitted to the temperature field reconstruction module, a three-dimensional dynamic temperature field model is constructed by using a spatial interpolation algorithm, and temperature values, temperature gradients and temperature difference distribution of all regions are output in real time; the thermal balance control module compares the model output data with a preset temperature threshold value and a temperature difference threshold value, and if the threshold value exceeding condition exists, a regulation and control instruction is sent to a partition cooling execution unit; the subarea cooling execution unit comprises three independent branches (corresponding to key areas), and each branch realizes accurate adjustment through an independent electromagnetic flow valve and a variable frequency water pump; and the steps are circulated until the temperatures of all the key areas reach the standard and the temperature difference of the adjacent areas meets the standard, so that the heat balance precision and the operation safety of the liquid cooling charging module are effectively improved.

The invention relates to the technical field of thermal field modeling and control, and particularly provides a molecular beam epitaxy substrate temperature field control method and system based on artificial intelligence, and the method comprises the following steps: obtaining the all-region temperature data of the surface of a substrate, and the heating power and environment parameters of each region of a heating cavity; inputting the heating power and the environmental parameters into the temperature field model, and outputting a temperature distribution matrix and temperature gradient data of the surface of the substrate; predicting temperature prediction data according to the temperature distribution matrix, the heating power and the sequence data of the environmental parameters in the historical time period; and inputting a state vector formed by the temperature distribution matrix, the temperature gradient data, the heating power data and the temperature prediction data into a deep reinforcement learning model, and then outputting the heating power adjusting quantity of each area to control a temperature field. According to the invention, the problems of insufficient prediction precision and real-time performance of the substrate temperature in the prior art are solved, the influence of environmental factors and heating power on the substrate temperature is considered, and the temperature field control capability is improved.

The invention relates to the technical field of intelligent sintering, and discloses a rare earth magnet intelligent sintering production line and a control system, and the system comprises a temperature data collection module, a temperature gradient evaluation module, a temperature change rate fitting module, a heating power adjustment module, a directional heat energy compensation module and an optimized heating instruction generation module. Temperature distribution information in the sintering furnace is obtained; evaluating real-time temperature gradients of different positions in the sintering furnace, and comparing the real-time temperature gradients with a preset gradient threshold value to identify a temperature abnormal region in the sintering furnace; fitting the temperature change rate of the temperature abnormal area; the material phase change critical parameters of the rare earth magnet in the current sintering stage are combined to adjust the heating power of the temperature abnormal area; performing directional heat energy compensation on the temperature abnormal region to obtain a power compensation amount; superposing the power compensation amount and the reference power of the sintering furnace to generate an optimized heating instruction; the intelligent sintering control efficiency of the rare earth magnet can be improved.

The invention relates to the technical field of motor control and sensors, and discloses a displacement error dynamic compensation method, device and equipment and a medium, and the method comprises the steps: obtaining the temperature data and original displacement data of a plurality of temperature measurement points in a moving part and an environment, calling a pre-built nonlinear mapping relation between a temperature gradient and a displacement deviation, and calculating the displacement error of the moving part; based on the nonlinear mapping relation, adaptive filtering is carried out on the temperature data and the original displacement data, a trend component representing temperature drift is separated out, displacement data without the trend component is obtained, and a dynamic compensation instruction is generated based on the trend component and the nonlinear mapping relation; and adjusting the displacement data of which the trend component is removed and outputting compensation displacement data. According to the method, the nonlinear mapping model of the temperature gradient and the displacement deviation is constructed, the drift trend is extracted in combination with multi-point temperature sensing and self-adaptive filtering, the compensation instruction is dynamically generated, accurate real-time correction of the displacement error is achieved, and the responsiveness and accuracy of compensation are improved.

The invention provides an antibacterial ceramic glaze sintering process optimization and intelligent temperature control method and system. According to the method, the molecular vibration characteristics of the antibacterial agent at different temperatures are dynamically obtained, and a thermal decomposition dynamic fingerprint database is constructed according to the attenuation law of the molecular vibration characteristics; meanwhile, a three-dimensional temperature field of the glaze layer is reconstructed based on a coupling relation between sound wave propagation parameters and glaze thermal expansion. And carrying out transfer learning on the fingerprint database and historical process data, predicting a glaze thermal stability attenuation parameter, and calculating a temperature gradient and molecular chain fracture compensation coefficient. And fusing the temperature field and the attenuation parameter, and dynamically regulating and controlling the sintering temperature curve and preserving heat by combining the compensation coefficient. The adjusted parameters generate closed-loop feedback by verifying the matching degree of the glaze microstructure and the antibacterial indexes, the compensation coefficient is corrected, and it is ensured that the antibacterial performance of the glaze is stabilized within the process allowance. The temperature control precision and the antibacterial performance stability of antibacterial ceramic glaze sintering are improved.

The invention provides a shallow coal seam hidden fire source full-field monitoring and early warning method and system, and belongs to the technical field of coal spontaneous combustion fire monitoring and early warning, and the method comprises the steps: S1, obtaining thermal infrared image and visible light image data; s2, eliminating redundant thermal imaging frames and fuzzy thermal imaging frames; s3, obtaining a preliminary surface temperature field distribution map; s4, an open fire source and a suspicious area are distinguished, and positions are marked; s5, acquiring surface temperature gradient distribution and indication gas concentration data of the suspicious area, and acquiring surface temperature data and underground temperature data of the verification point, indication gas data escaping from the detection hole and radioactive radon content data; s6, establishing identification indexes of the dark fire source; s7, establishing a dark fire source grading risk standard; and S8, outputting an early warning result. According to the method, full-time, full-field and three-dimensional monitoring is realized, the accuracy and the reliability are improved, intelligent graded early warning and decision support are realized, and the environmental adaptability and the automation level are enhanced.

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 provides a system and method for inhibiting wafer scratching in double-sided polishing and double-sided polishing equipment. The system comprises: a shunt manifold valve group, which shunts a polishing liquid main flow path into at least three independent branches respectively corresponding to the inner, middle and outer areas of a polishing pad; the at least three online heating units are respectively arranged on each branch to independently heat the polishing solution; the temperature monitoring device comprises at least three temperature sensors which are arranged in different areas and is used for monitoring the temperature of the three areas in real time; and the control system independently regulates and controls the power of each heating unit based on temperature feedback, a preset non-uniform radial temperature gradient is established and maintained on the polishing pad, and the gradient is configured that the temperature of the middle area is not lower than that of the inner area, and the temperature of the inner area is higher than that of the outer area. Thermal deformation of the polishing pad is optimized through partitioned independent temperature control, and wafer scratching is effectively restrained.

The invention relates to the technical field of data processing, and discloses a cable joint arc multi-physical field simulation method and system. The method comprises the following steps: establishing a defect-containing geometric model, judging according to a temperature gradient change rate and a current rising rate to obtain an adaptive time step length, and carrying out bidirectional coupling iteration on an arc temperature field and a material dielectric parameter based on the time step length to obtain an accumulated damage factor; arranging a virtual temperature detection point to convert the simulation temperature field into a virtual monitoring signal, extracting temperature characteristic parameters and ultrasonic spectrum characteristic parameters, and projecting the temperature characteristic parameters and the ultrasonic spectrum characteristic parameters to a two-dimensional characteristic space to obtain a fault mode fingerprint spectrum. According to the method, adaptive adjustment of the time step length is realized by establishing an arc evolution phase discrimination mechanism, and the problems of low calculation efficiency and insufficient transient characteristic capture caused by a fixed time step length are solved.

The invention discloses a convective cloud in-cloud temperature gradient joint inversion method based on a laser radar, and relates to the technical field of meteorological detection, and the method comprises the steps: synchronously collecting multi-modal meteorological remote sensing data through a multi-modal meteorological remote sensing device; constructing an adversarial unsupervised correction network, inputting the multi-modal meteorological remote sensing data into the adversarial unsupervised correction network, and generating corrected multi-source observation data; mapping the corrected multi-source observation data to a uniform space-time grid to form a space-time aligned multi-modal data set; and based on the vertical profile of the temperature gradient, in combination with the radar reflectivity factor and the fusion feature vector, calculating the vertical distribution of the liquid water content, the water vapor density and the particle effective radius in the convective cloud, and generating a quantitative analysis report of the macro and micro characteristics of the convective cloud. According to the invention, by constructing the antagonistic unsupervised correction network, errors in multi-source observation data can be effectively corrected, and a high-quality data basis is provided for fusion and inversion in meteorological service.

The invention relates to the technical field of MEMS sensors, and discloses a temperature drift real-time compensation and correction method and system of an MEMS gyroscope. The method comprises the following steps: acquiring an original output signal and synchronous temperature time sequence data of the MEMS gyroscope under a preset temperature gradient, dividing a dynamic temperature change interval, extracting zero-bias stability and scale factor nonlinearity parameters, and constructing a temperature-error mapping table; checking output signals of multiple gyroscopes through array layout, and screening effective sensor nodes; and a multi-sensor fusion compensation coefficient matrix is generated by combining error calibration test weighted fusion parameters. A corresponding coefficient matrix is loaded according to a real-time temperature query mapping table, and a parameter weight is analyzed and updated by using a sliding time window residual error; when the temperature changes suddenly, an adaptive filtering optimization coefficient matrix is triggered, and finally optimization parameters are written into an embedded storage unit of the PCB integrated chip to complete mass production calibration. The method adapts to a dynamic temperature change scene, enhances the anti-interference capability, and adapts to a mass production process.

The invention relates to the technical field of control systems, and discloses a multi-zone cooperative control method and system for a temperature field of a carbon nanotube CVD growth furnace, and the method comprises the steps: obtaining the real-time temperatures of a plurality of temperature zones, and calculating the temperature deviation of each temperature zone; the actual temperature gradient is calculated, if the change rate of the actual temperature gradient exceeds a preset threshold value, the gradient maintaining deviation is calculated, and otherwise, the gradient maintaining deviation is zero; calculating a gain weight; calculating predictive thermal disturbance compensation amount of each temperature zone; calculating a first control item; the predictive thermal disturbance compensation amount forms a second control item; the gradient feed-forward correction value forms a third control item, and the gradient feed-forward correction value is proportional to the gradient maintenance deviation of the temperature zone; and taking the sum of the first control item, the second control item and the third control item as the power control quantity of the temperature zone. Unification and coordination of local temperature control and overall temperature are realized, a stable thermal environment is provided for growth of the carbon nanotubes, and consistency and uniformity of growth of the carbon nanotubes are improved.

The invention provides a boiler heating surface pipe wall leakage detection method, and belongs to the technical field of industrial intelligent detection based on machine learning. According to the method, a heterogeneous sensing architecture combining adaptive signal decomposition optimized by an improved sparrow search algorithm and acoustic array positioning corrected by a physical field is adopted, and complementary features are extracted from time domain statistical features and a frequency domain energy spectrum through a specially designed double-flow space-time attention fusion neural network; therefore, the weak leakage signals in the strong noise environment can be captured and identified. Based on an identification result, a hearth three-dimensional temperature field distribution model is used for carrying out gridding correction on a sound wave propagation path, a nonlinear positioning equation set is constructed, and three-dimensional space sub-m-level accurate positioning of a leakage sound source is realized without manual intervention; the problems of false alarm and missing alarm caused by background noise interference and positioning deviation caused by temperature gradient in traditional acoustic monitoring are thoroughly solved.

The invention relates to an intelligent regulation and control method and system for a pavement asphalt mixture paving temperature field, computer equipment and a computer readable storage medium. The method comprises the steps that an infrared temperature matrix, internal temperature gradient data and environment and equipment operation parameters of a paving area are collected; and based on the temperature gradient data, carrying out compensation correction on the shielding area in the infrared temperature matrix. And fusing the corrected surface temperature matrix with the internal temperature gradient data to form a three-dimensional temperature field tensor. And inputting the tensor into the prediction model, and outputting future temperature field prediction data in combination with environment and equipment parameters. And generating a hierarchical control instruction set according to the local temperature difference, the temperature change slope and the lowest temperature threshold in the prediction data, and distributing the hierarchical control instruction set to a corresponding execution system. And acquiring actual temperature data after instruction execution, calculating errors and dynamically updating prediction model parameters. The paving uniformity, compactness and long-term durability of the asphalt pavement are improved.

The invention provides a mass concrete temperature monitoring method and device for ultra-wide section open cut tunnel construction, and relates to the technical field of constructional engineering.The method includes the steps that geometric parameters of a tunnel are collected, a three-dimensional model is constructed, grid division is conducted in combination with concrete material attributes, and a simulation model is generated; the temperature gradient modulus of a node under each time step is calculated by simulating the whole process of concrete from pouring to cooling; a gradient extraction neighborhood is constructed with the initial temperature monitoring point as the center, the maximum gradient intensity in the neighborhood is extracted, a gradient integral index is calculated, and alternative monitoring points are screened out; and finally, by calculating representative weights between the alternative monitoring points and the nodes, selecting a final monitoring point with the best representativeness to carry out temperature sensor arrangement, so that scientific and dynamic monitoring of the concrete temperature field is realized, and the monitoring precision and efficiency are effectively improved.

The embodiment of the invention provides a GaAs-based HBT epitaxial wafer multi-parameter cooperative control growth processing system. The GaAs-based HBT epitaxial wafer multi-parameter cooperative control growth processing system comprises a data acquisition module which is used for monitoring the actual temperature of different positions of a substrate tray and the growth thickness of an epitaxial layer in real time; the temperature regulation and control module is used for independently regulating the temperature of each area according to a preset target temperature range to form temperature gradient distribution; the carrier gas control module is used for dynamically adjusting the carrier gas flow according to the temperature adjustment result to maintain uniform distribution of reaction gas and stable reaction rate; the growth rate monitoring module is used for comparing the actually measured growth thickness with the theoretical design thickness and triggering compensation adjustment when the deviation exceeds a set threshold value; and the model processing module is used for establishing a mathematical model among the temperature, the gas carrying capacity and the growth rate to predict and optimize the growth process. By systematically integrating each functional module, accurate control and intelligent management of the epitaxial growth process are realized, and the product consistency and the production efficiency are remarkably improved.

The invention relates to the technical field of a multi-field coupling simulation shield pump pressure-bearing component service life prediction method, particularly discloses a multi-field coupling simulation shield pump pressure-bearing component service life prediction method, and aims to solve the problem of service life prediction distortion caused by difficult accurate modeling of a nonlinear coupling effect in traditional single field domain analysis. The method comprises the following steps: constructing a three-dimensional self-adaptive grid model covering a pressure-bearing shell, a flange and a bearing seat; defining multi-physical field boundary conditions containing temperature gradient, pressure pulsation, electromagnetic excitation and time-varying creep parameters; and executing thermal electromagnetic full-coupling transient simulation to obtain a stress-strain evolution field. According to the method, through strong coupling modeling, time-varying constitutive embedding and data closed-loop correction, crack dynamic tracking and life rolling prediction under extreme working conditions are realized, and failure early warning perspectiveness and engineering decision reliability are remarkably improved.

The invention provides an injection mold temperature field regulation and control method and device based on multi-sensor fusion, and the method comprises the steps: recognizing a non-uniform region based on a surface radiation temperature distribution image, discrete point temperature data, an instantaneous heat flow direction and heat flow intensity information; based on each non-uniformity area and the heating and cooling unit adjacent to the non-uniformity area, constructing a space mapping relation, and based on the space mapping relation, the instantaneous heat flow direction and the heat flow intensity information, generating a heat flow path guide instruction; triggering a corresponding heating and cooling unit to execute alternate heating and cooling operation according to a preset phase difference based on the heat flow path guide instruction, so that the heat flow directionally migrates in the non-uniform region along a specified path; and monitoring that the temperature gradient change trend of each non-uniform area tends to be uniform based on a dynamic heat balance state formed by the heat flow after directional migration in the mold, and entering a steady-state maintenance mode. According to the invention, high-precision sensing and dynamic cooperative regulation and control of the global temperature field of the injection mold are realized.

The invention discloses a filter element self-adaptive temperature regulation and control method based on a dynamic environment, particularly relates to the field of temperature regulation and control, and aims to solve the problem that an existing filter element is insufficient in deformation compensation under complex working conditions. A time sequence temperature distribution matrix is obtained by constructing a multi-point temperature monitoring network on the surface of the filter element, a heat flow density distribution diagram is generated by combining material heat conduction characteristics, the heat flow convergence acceleration rate is calculated through continuous time sequence heat flow changes, and deformation risk indexes of all areas are obtained by combining material thermal expansion coefficients. And the warping or ripple trend can be identified in advance. And judging a deformation mode according to the time sequence change of the risk index and the temperature gradient, respectively generating a warping compensation temperature instruction or a ripple suppression temperature instruction, and forming closed-loop regulation and control by continuously updating the temperature distribution and the risk index. According to the method, refined temperature regulation and active anti-deformation control of the filter element are achieved, the stability of the filter element is remarkably improved, and the service life of the filter element is remarkably prolonged.

The invention provides a lightning fall area identification method based on a wind cloud satellite temperature profile and an atmospheric instability index, and relates to the technical field of weather forecast, and the method comprises the steps: obtaining vertical layering temperature profile data, atmospheric instability index data and satellite lightning positioning data of a wind cloud satellite; the vertical stratification temperature profile data, the atmospheric instability index data and the satellite lightning positioning data are preprocessed, and the preprocessed vertical stratification temperature profile data, the preprocessed atmospheric instability index data and the preprocessed satellite lightning positioning data are obtained; and on the basis of the preprocessed vertical stratification temperature profile data, atmospheric vertical temperature gradient derivative elements are obtained by calculating atmospheric vertical temperature gradients between different air pressure layers. According to the method, intelligent identification and auxiliary decision-making of the lightning falling area can be realized, and meanwhile, technical support is provided for satellite-to-ground lightning observation data quality evaluation and control.

The invention relates to the technical field of microfluidics, in particular to a carbon quantum dot hydrothermal synthesis system and method based on microfluidics thermal field equilibrium, which comprises a thermal field sensing module, an equilibrium analysis module, a thermal field coupling module, an equilibrium regulation and control module and a closed loop execution module, the thermal field sensing module is used for collecting array temperature on the surface of the micro-fluidic chip and fluid pressure data in a flow channel, and reconstructing three-dimensional temperature distribution in the micro-channel through a multi-physics field coupling algorithm to obtain a real-time thermal field state matrix. According to the invention, by constructing a multi-physical field coupling algorithm of a thermocouple array-flow resistance model-conjugate heat transfer equation, the three-dimensional temperature distribution of the fluid in the micro-channel can be inverted and reconstructed by using surface temperature and pressure data, so that a control system can pass through a chip matrix, and the temperature of the fluid in the micro-channel can be controlled. The radial temperature gradient and the axial thermal distortion in the fluid are directly sensed, the hysteresis and the error of sensor measurement are eliminated, and a real physical basis is provided for accurate temperature control.

The invention provides a power grid equipment monitoring method and system based on multi-source satellite power grid image data processing, and the method comprises the steps: firstly obtaining heat radiation temperature data and contour data of equipment from an infrared satellite and a visible light satellite, and carrying out the time-space synchronization processing; secondly, extracting temperature gradient distribution information from the heat radiation temperature data, and identifying and sequencing local overheating areas in combination with radiation intensity difference; enhancing equipment contour edge identification according to the sequence to obtain an enhanced contour image; superposing the data with thermal radiation temperature data, and extracting comprehensive distribution characteristics to determine an initial fusion weight; identifying a temperature distribution imbalance region, evaluating the reliability of the two types of data sources, and adjusting the weight in combination with the operation state of the equipment to obtain a final ratio; the two types of data are weighted and fused according to the proportion, and a final temperature distribution image is obtained through temperature field distortion correction; and extracting the geographic position of the overheat area and mapping the geographic position to the equipment layout diagram to complete power grid equipment thermal anomaly monitoring. Through the scheme of the invention, the thermal anomaly of the power grid equipment can be monitored.

The invention relates to the technical field of radiator design and thermal management, in particular to a radiator cooling channel design method based on three-dimensional topological optimization. The method comprises the following steps: carrying out thermal imaging scanning on the electronic equipment, obtaining temperature distribution data, and generating a hotspot map; calculating a temperature gradient according to the hot spot map, determining a temperature gradient threshold value, dividing a main circulation area and a secondary circulation area, performing circulation area boundary smooth optimization, and generating a circulation partition map; based on the cyclic partition map, determining an inlet position and a heat flow demand, and identifying a thermal anchor point set; determining a hierarchical branch structure of a primary loop and a cellular network structure of a secondary loop; generating a channel skeleton graph based on the hierarchical branch structure and the cellular network structure; and a basic isolation wall is determined, a reinforcing structure is added, and thickness optimization is conducted according to the local temperature difference to form a heat conduction valve structure. According to the invention, the problem of low efficiency of the radiator under a complex thermal load is solved through radiator design and a thermal management technology.

The invention relates to the technical field of double-component pouring sealant testing, and discloses a thermal conductivity testing method and system based on a double-component heat-conducting pouring sealant. The method comprises the following steps: classifying base material component proportions and curing conditions of the two-component heat-conducting pouring sealant, and determining a material curing state classification label; loading a corresponding heat conduction reference model, judging the thermal response coverage of the model, and generating correction parameters and updating the model by thermodynamic simulation when the thermal response coverage is insufficient; based on the updated model, applying heat source excitation to the sample under a preset temperature change gradient, and collecting surface dynamic temperature field distribution data; extracting a heat conduction offset position and an abnormal temperature rise node, and generating an abnormal thermal behavior identification group; obtaining temperature change correlation time of the offset position in the identification group, and calculating a thermal response delay interval and a conduction path offset; therefore, the temperature lag time length and the heat flux attenuation ratio of each layered interface of the sample in the continuous thermal cycle period are extracted, a layered thermal resistance response characteristic value is generated, and a reliable basis is provided for evaluating the heat-conducting property of the two-component heat-conducting pouring sealant.

The invention provides a strength data processing method and system for concrete performance, and relates to the technical field of data processing.The method comprises the steps that hydration heat temperature strain data of a concrete structure of a super high-rise building foundation is obtained to generate a temperature strain data set with spatial distribution characteristics, and the strength data of the concrete performance is obtained by combining material characteristic parameters of the concrete structure; constructing a concrete three-dimensional entity by using the pre-constructed digital twin model so as to simulate a temperature gradient field, a thermal stress field and a time-space evolution rule of strength development of a concrete structure; based on the space-time evolution rule and different maintenance condition parameters, predicting a strength increase curve of the concrete structure under different maintenance conditions; according to the strength increasing curve, the strength standard probability and the risk threshold value of different curing stages are calculated, strength development simulation and risk early warning of the concrete structure are carried out based on the strength standard probability and the risk threshold value, and the intelligent monitoring and early cracking risk early warning capacity of the concrete strength development process is improved.

The invention discloses a fire-fighting detection early warning system, and relates to the technical field of fire-fighting early warning, and the system comprises a multi-source data obtaining module which comprises a gas monitoring unit, a smoke monitoring unit and a temperature obtaining unit, obtains the concentration of combustible gas, the granularity of smoke and the temperature data, carries out the preprocessing of the data, and integrates the data into a data set; the analysis and early warning module analyzes the data based on the data set, introduces a gradient compensation algorithm into the temperature acquisition unit, synchronously records the ambient temperatures of three different distances around, calculates a temperature gradient value, judges whether the temperature data exceeds the standard or not based on the gradient value, preliminarily obtains a judgment result from the temperature direction, and sends the judgment result to the early warning unit; and performing trend prediction on the multi-source data based on a time sequence analysis method. According to the method, the gradient compensation algorithm is introduced, the gradient value is calculated by using the three temperature monitoring points at different distances, local temperature anomaly can be accurately captured, the danger diffusion trend can be recognized earlier, local fluctuation and system risks can be distinguished, and time is won for early intervention.

The invention relates to the technical field of fire disaster simulation, and discloses a fire disaster emergency simulation method and system based on scene digital twinning. The method comprises the following steps: acquiring spatial topological data of a target building through a three-dimensional laser scanning technology, and constructing a geometric model and a thermodynamic attribute model of the digital twin of the building in combination with temperature gradient distribution data acquired by a thermal imaging sensor; according to fire source diffusion mode data in a historical fire case library, pyrolysis kinetic parameters of different materials are extracted, and a fire spread probability matrix is established; inputting real-time meteorological monitoring data into the thermodynamic attribute model, and calculating a dynamic coupling relationship between a temperature field and a smoke concentration field in the building; and generating a fire scene evolution path set based on the fire spreading probability matrix and the dynamic coupling relationship, and outputting a traffic capacity attenuation curve of the key escape node. According to the method, accurate simulation and dynamic evolution prediction of a fire scene are realized, and scientific support is provided for fire emergency decision and personnel evacuation planning.