580 results about "Field analysis" patented technology

The invention relates to a rockburst risk monitoring method and system in a tunnel construction period, and relates to the technical field of tunnel construction, and the method comprises the steps: obtaining micro-seismic monitoring data and geological parameters of a tunnel; calculating a rockburst risk index of the tunnel based on the micro-seismic monitoring data and the geological parameters; determining a dynamic stress field analysis result of the tunnel through the dynamic stress field evolution model; based on the rockburst risk index and the dynamic stress field analysis result, dangerous area distribution of the tunnel is obtained; evaluating the rockburst risk grade of the tunnel in the next construction period in combination with the rockburst risk index, the dangerous area distribution and the to-be-performed construction process, and dynamically adjusting the early warning threshold value of the rockburst risk index to obtain a dynamic early warning threshold value; and when the rockburst risk index of the tunnel exceeds a dynamic early warning threshold value, generating a risk assessment result, sending out early warning of a corresponding level, and giving a prevention and control suggestion of construction according to the risk assessment result. The tunnel rockburst risk monitoring accuracy can be improved.

The invention relates to the technical field of heat exchange modules, and discloses a temperature field analysis method of a heat exchange module. The method comprises the following steps: carrying out multi-source data acquisition on a micro-channel double-phase precise phase-change heat exchange module to obtain temperature field acquisition data, pressure data, flow data and phase-change material characteristic data; carrying out dimensionless number analysis calculation to obtain a flow pattern criterion value, and calculating gas-liquid two-phase flow heat exchange coefficient distribution data; performing coupling calculation to obtain heat transfer characteristic data of the phase change area; performing conjugate gradient iterative calculation to obtain temperature field reconstruction data; inputting the temperature field reconstruction data into a temperature field evolution prediction model for temperature field evolution prediction to obtain temperature field prediction data; according to the temperature field prediction data, a dual-objective optimization function containing the heat exchange efficiency and the energy consumption is established, the heat exchanger control parameters are solved, the heat exchange performance prediction accuracy is improved, and meanwhile the optimal control parameters giving consideration to the heat exchange efficiency and the energy consumption are obtained.

The invention relates to the technical field of information management, and comprises a distribution automation operation and maintenance work log intelligent recording platform based on a CS architecture, and the platform comprises a log field analysis module, a task chain construction module, a task logic verification module, and a log storage tracing module. According to the method, missing and abnormal fields are effectively marked and corrected through meticulous analysis and comparison of uploaded log records, the accuracy and integrity of data are improved, task scheduling is optimized and the operation and maintenance management efficiency is improved through association of device numbers and task types and adjustment of execution time in sorting and grouping of task sequences, and the task scheduling efficiency is improved. Task chains are recombined to solve conflicts and adjust priorities, smooth execution of operation and maintenance tasks is guaranteed, delay is reduced, logic verification enhances task reliability through rule verification and error marking, unassociated tasks are deduced, analyzed and corrected, the exception processing capacity is enhanced, the data tracing and storage efficiency is improved, and the tracing capacity of data management is enhanced.

The invention provides an intelligent temperature field analysis-based heat dissipation optimization method for an IGBT (Insulated Gate Bipolar Translator) power module of an offshore flexible direct current converter valve. According to the method, an IGBT module space temperature data matrix and multi-point temperature sensor data are collected, and filtering processing is carried out through a multi-scale sliding window and a self-adaptive threshold value; establishing a multi-layer thermal network parameter model, and analyzing temperature dynamic change characteristics; layering the feature data according to the thermal response speed, and performing adaptive mapping and weight calculation; establishing a reinforcement learning model based on the heat dissipation efficiency index set to optimize a heat dissipation strategy; and predicting the temperature field distribution by using the graph structure neural network model. Accurate sensing, dynamic characteristic analysis, self-adaptive control and predictive maintenance of the temperature field of the IGBT module are realized, the heat dissipation efficiency and the temperature uniformity are improved, and the service life of equipment is prolonged.

The invention belongs to the technical field of thermal circuit model construction, and particularly relates to a high-voltage power cable intermediate connection thermal circuit fault modeling analysis method and device, and the method comprises the steps: building a high-voltage power cable intermediate connection thermal circuit fault circuit model through analyzing a cable intermediate connection temperature inversion principle; the method comprises the following steps: establishing a geometric model for multi-physics field analysis of the intermediate connection of the high-voltage power cable by utilizing Comsol finite element simulation software, setting material parameters of each component, and setting field domain parameters; an electromagnetic field module is added, boundary conditions of electromagnetic field analysis are set, and a cable intermediate connection electromagnetic field simulation model is obtained; adding a solid heat transfer module to obtain a solid temperature field simulation model; obtaining an electromagnetic-thermal coupling model, and solving to obtain the temperature, current and loss of the cable middle connection wire core and the outer surface in different insulation states. According to the method, the cable intermediate connection fault problem can be found and predicted, and the reliability and the safety of the power cable are improved.

The invention discloses a converter station intelligent gateway image recognition system based on a YOLOv3 target detection algorithm, and the system employs a three-stage cooperative processing architecture design, and builds seamless connection of a multispectral image collection layer, an edge calculation gateway layer, and a cloud operation and maintenance management platform layer. The invention further provides an equipment defect detection method based on the system, bimodal image data are collected through the visible light camera and the thermal infrared imager, preprocessing operation is carried out, equipment positioning and defect classification are synchronously executed by utilizing the improved YOLOv3 network, a structured detection result is output, temperature field analysis is carried out on an infrared thermal image, and the equipment defect detection result is obtained. And an abnormal heating area is identified, when defects are detected, multi-level risk response early warning is generated, and a defect diagnosis report is pushed to the cloud operation and maintenance management platform layer. Real-time image analysis of converter station equipment can be realized, the method is suitable for automatic detection of typical fault defects of the equipment, and the operation and maintenance efficiency of a power grid is improved.

The invention discloses a method and a device for calculating an electromagnetic-heat flow field under a turn-to-turn short circuit fault of a converter transformer. The method comprises the following steps: establishing a converter transformer multi-physical field numerical calculation theoretical model based on circuit-electromagnetic-heat flow coupling; based on the multi-physical field numerical calculation theoretical model, establishing a converter transformer electromagnetic-heat flow field model under the turn-to-turn short circuit fault; setting turn-to-turn short circuit faults at different positions in the electromagnetic-heat flow field model of the converter transformer; and performing winding current waveform, voltage waveform and electromagnetic field analysis and heat flow field analysis of the converter transformer under the set turn-to-turn short circuit fault.

The invention relates to the technical field of boiler heating surface fault diagnosis, in particular to a heating surface fault diagnosis prediction method and system based on boiler flow field analysis. The method comprises the following steps: collecting boiler multi-dimensional data; analyzing a flow field in the boiler; constructing a heating surface fault diagnosis model; coupling the flow field simulation result and the fault diagnosis model to construct a fault prediction model; extracting features and reducing dimensions; performing fault mode identification by using a Gaussian mixture model; and calculating a comprehensive fault score and carrying out risk grading. Through fusion of flow field analysis, deep learning and multi-source data, the accuracy of fault diagnosis is remarkably improved, and the early warning time is remarkably shortened. Experimental results show that compared with a traditional method, the fault detection rate is increased to 96.7%, the false alarm rate is reduced to 3.2%, the early warning time is prolonged to 12.3 hours, and the diagnosis accuracy rate reaches 94.1%. The method provides powerful support for safe and efficient operation of the boiler, and has important engineering application value.

The invention relates to the technical field of intermediate frequency furnace sintering temperature control, and discloses a sintering temperature control system of an intermediate frequency furnace. The system comprises a multi-source data acquisition module which is used for acquiring multi-dimensional thermodynamic data, covering temperature distribution, sintering power and heat flow track data in a sintering process in real time; and the temperature field analysis module is used for carrying out dynamic compensation correction processing on the multi-dimensional thermodynamic data, inputting the multi-dimensional thermodynamic data into a sintering analysis processing layer for characteristic modeling, and generating a sintering temperature regulation and control instruction. The sintering analysis processing layer comprises a data preprocessing module and a thermodynamic modeling module, the data preprocessing module performs operation such as temperature interval division and abnormal value elimination on original data, and the thermodynamic modeling module is obtained based on historical data cooperative training. According to the system, through multi-dimensional data acquisition and analysis processing, the sintering temperature can be accurately regulated and controlled, the quality of sintered products and the production efficiency are effectively improved, and the system has good universality and adaptability.

The invention provides a short message issuing processing method and system based on scene self-adaption. The method comprises the steps that a three-dimensional communication characteristic spectrum is constructed through a building information model and infrared thermal imaging data, short message request distribution is analyzed and predicted in combination with a signal attenuation field, cross-operator network quality data is integrated to form a converged communication quality field, and finally short message issuing is intelligently scheduled according to the network state and service requirements. According to the method, accurate short message routing optimization based on real-time communication quality and crowd distribution in a complex building environment is realized. According to the technical scheme provided by the invention, the short message delivery rate and timeliness in a complex building environment can be remarkably improved, and particularly, the communication reliability in a crowded area and a signal blind area is remarkably improved.

The invention discloses a power distribution equipment on-line monitoring system based on multi-modal data fusion, and relates to the field of power distribution equipment management, and the system comprises a sensing module which is used for collecting an electrical signal, a thermal infrared signal, a mechanical vibration signal and an acoustic signal generated in the operation process of power distribution equipment through a multi-type sensing channel, converting the collected various signals into processable equipment state original data to form an equipment operation state original data set; according to the invention, through accurate acquisition of multi-dimensional signals, combination of space mapping and time delay compensation, data quality is optimized, the reliability of original information is ensured, key features are extracted according to working conditions, subtle state changes are captured by means of temperature field analysis and a variable-resolution spectrum technology, the comprehensiveness, accuracy and response timeliness of equipment operation monitoring are effectively improved, and the real-time performance of equipment operation monitoring is improved. Misjudgment and missed judgment are reduced, and fault risks are avoided in advance.

The invention relates to the technical field of data processing, and discloses an employee performance assessment-oriented dynamic data desensitization system, which comprises a field analysis module, a query analysis module, a desensitization strategy module and a desensitization execution module, wherein the field analysis module is used for identifying a risk field combination between fields of object data; the query analysis module is used for calculating the sensitivity of each query party to each field in the risk field combination; a desensitization strategy module synchronously generates a joint desensitization strategy of each query party for the risk field combination based on the sensitivity and desensitization constraint condition of each query party for each field in the risk field combination; and the desensitization execution module is used for executing the joint desensitization strategy and performing joint desensitization of the risk field combination for each query party. According to the method, the desensitization strategy is optimized, and the efficiency and safety of employee performance assessment data management are improved.

The invention provides an XLPE cable aging-based mixed operation system impedance mismatch and imbalance characteristic analysis method, equipment and a medium, and belongs to the technical field of cable aging analysis. Equivalence simplification is performed on a power grid in a simulation system, switching stations and transformer substations are reserved, and a cable structure model is constructed; cable structure parameters are obtained, three-phase unbalanced current-carrying simulation conditions are set, operation parameters are obtained, a cable finite element thermal field analysis model is constructed, cable thermal field analysis data are input, and cable burying depth and surrounding parameters are set; comparing and analyzing the temperature distribution difference, acquiring temperature data of the inner and outer surfaces of the insulating layer, and calculating an average temperature difference value of the insulating layer under the two working conditions; based on the average temperature difference value, the influence degree of the single-phase power-on working condition on the cable insulation life compared with the symmetrical operation working condition is quantified. And according to an evaluation result, a more reasonable cable maintenance plan and replacement period are formulated, faults caused by insulation aging are prevented in advance, and safe and reliable operation of a power system is guaranteed.

The invention provides a micro-flow field measurement method of a mechanical biological net port flowmeter, and belongs to the technical field of micro-flow field measurement, and the micro-flow field measurement method comprises the following steps: firstly, constructing a net port cavity digital model, and realizing micro-flow field high-resolution characterization by using fluorescent particle tracing liquid and a laser confocal system; and recording a fluid movement track and processing original data by applying a track optimization function under the condition that the microfluidic driving system generates a constant pressure gradient. And solving fluid pressure distribution by adopting an orthogonal grid system and a Navier-Stokes equation, and processing speed field and pressure distribution data by utilizing a pre-trained micro-flow field analysis neural network model. Finally, the flow and pressure relation curve is obtained by calculating the flow flux of the cross section of the network port, a micro-flow field measurement correction coefficient table is generated, and the technical problems that in the prior art, the accurate measurement difficulty of the biological network port micro-flow field is large, and multi-scale flow characteristic representation is insufficient are solved.

A multi-physics computation method and system for digital twin online simulation, relating to the technical field of physics simulation. A multi-physics coupling simulation computation model of a simulated object is established, and the multi-physics coupling simulation computation model is simplified, and the order of a temperature field simulation model is reduced, thereby greatly reducing the amount of computation, and improving computational efficiency; a low-precision dataset is obtained by means of temperature field analysis, so that the data size required for a model is reduced by means of low-precision data, thus reducing modeling costs; and a basic data-driven model is constructed by means of the low-precision dataset and a sample space corresponding to the low-precision dataset, so that a temperature field distribution result can be rapidly outputted, further improving computational efficiency and reducing computational errors.

The invention discloses a thermal management control method and device for a new energy automobile battery, and relates to the field of battery thermal management control, the device comprises an entropy change module, a fault module, a decision module, a phase change module and a scheduling module, entropy change intensity and nuclear heat flow field analysis is carried out on collected current and voltage signals to obtain an aging thermal topology, and the aging thermal topology is subjected to thermal management control. The method comprises the following steps: constructing an anisotropic diffusion equation based on aging thermal topology in combination with a fault diffusion tensor, discretizing a sub-strategy set for a safety margin field, constructing a cooling Nash game, analyzing through a payment matrix and a replicated dynamic equation, screening a stable strategy, mapping, and constructing an implicit phase change criterion model for the surface temperature of a battery to obtain a phase change cumulant; the phase change cumulant latent heat is analyzed and then cooperatively arbitrated with the cooling membership degree to obtain arbitration cooling capacity, the water pump flow is obtained through limiting operation based on the arbitration cooling capacity and the temperature deviation, then cubic root mapping is conducted on the water pump flow and the arbitration cooling capacity to obtain the fan rotating speed, and accurate control over battery thermal management is achieved.

The invention discloses a laser cladding temperature field analysis method based on a finite element simulation method. A metal flat plate is used as a research object. ANSYS software is adopted for simulation. A laser cladding process is simulated by constructing a finite element model and a refined mesh in combination with a moving Gaussian heat source and birth-death unit technology, and simulated laser heating is applied to the surface of a part as a thermal load. The ANSYS processing unit calculates a simulation result, and the postprocessor displays temperature field distribution. Simulated and actual coating cross section molten pool shapes are compared, it is found that the size of a simulation model is highly consistent with the size of an actual molten pool, the maximum error is only 9%, and the reliability of numerical simulation is verified. According to the method, a solid theoretical basis and an effective simulation means are provided for the metal laser cladding process, the process research level is improved, and the development cost is reduced. The method has an important value for practical engineering application, and provides a scientific basis for optimizing the laser cladding technology.

The invention discloses an underground anti-seepage structure leakage monitoring method and system based on discrete time, and relates to leakage detection. The method comprises the following steps: collecting transient electromagnetic response data generated by an excitation signal; according to the initial conductivity parameter and the electrode position parameter of the monitoring area, establishing a three-dimensional geophysical model of the monitoring area through a full waveform inversion algorithm; obtaining electromagnetic abnormal data by using a finite element forward modeling algorithm; according to the temperature data, a distributed temperature field analysis method is adopted to calculate the space gradient and the time change rate of the temperature, and temperature abnormal data are obtained; according to the pressure data and time sequence change characteristics of the pressure data, determining pressure abnormal data; fusing the electromagnetic abnormal data, the temperature abnormal data and the pressure abnormal data by using a Bayesian algorithm to obtain fused data; and inputting the fusion data into a pre-trained machine learning model to obtain a leakage detection result. Aiming at the low dynamic leakage monitoring precision of the underground anti-seepage structure, the dynamic monitoring precision is improved.

The invention relates to the technical field of data processing, and discloses a high-temperature early warning method and system for a welding device. The method comprises the following steps: carrying out multi-point temperature measurement by using a K-type thermocouple and an infrared thermal imager; fourier heat conduction calculation is conducted on the welding heat field; extracting temperature anomaly region features through thermal gradient analysis; carrying out multi-parameter risk assessment by combining material melting point parameters; a multi-channel alarm instruction is output through the industrial control bus; and current-voltage curve real-time adjustment is conducted on the welding power source, and closed-loop self-adaptive control is achieved. According to the method, a complete closed-loop system from multi-sensor temperature collection, thermal field analysis, abnormal feature extraction and risk assessment to multi-stage alarm and self-adaptive control is established, so that early recognition and accurate control of thermal abnormality in the welding process are realized, and the welding quality and the production safety are remarkably improved.

The invention provides a grain pile form dynamic monitoring method based on an intelligent visual system, and the method comprises the steps: extracting a speed field and a direction field of grain flow motion from video data in a grain flow falling process through employing an optical flow field analysis method, and obtaining the initial information of a grain flow track; according to the track change information, the initial diffusion range of the grain flow at the bin bottom is analyzed, whether the diffusion mode is uniform or not is judged, and if diffusion is not uniform, the corresponding area is marked as an irregular diffusion area; a dynamic diffusion model is established based on the track change information, the dynamic diffusion model is adopted to process an irregular diffusion area, and the accumulation speed and the form change trend of the grain pile are predicted in combination with the speed field and the direction field of grain flow movement; and according to the predicted grain pile stacking speed and form change trend, operation parameters of the conveying equipment are adjusted, and the operation parameters comprise the speed and angle of a conveying belt.

The invention relates to the technical field of automatic focusing, and discloses a narrow space imaging automatic focusing method and system based on depth-of-field analysis, and the method comprises the steps: obtaining original image data, and carrying out the refraction correction according to the original image data, and obtaining an initial depth-of-field distribution diagram; carrying out scattering interference analysis according to the initial depth-of-field distribution diagram to obtain interference intensity distribution; performing focus analysis according to the interference intensity distribution to obtain a candidate focus set; performing exposure optimization according to the candidate focus set to obtain an optimized focus set; performing locking threshold calculation according to the optimized focus set to obtain a locking threshold of the optimal imaging position; and when the distance between the target position and the optimal imaging position is smaller than the locking threshold value, triggering focus locking, performing scattering compensation, and outputting a high-precision imaging result. The method has the following effect that the accuracy of automatic focusing of imaging in a narrow space can be improved.

The invention discloses a power transformation equipment infrared image analysis and diagnosis method and related equipment, and the method achieves the precise analysis and intelligent diagnosis of the operation state of power transformation equipment through the steps of multi-modal data collection, data preprocessing, equipment target recognition, temperature anomaly detection, intelligent fault diagnosis and equipment health trend prediction. And by adopting the improved target detection network, the identification precision of the equipment target is improved, the segmentation effect of key parts of the equipment is optimized in combination with multi-modal data, and the false detection rate in a complex environment is reduced. Based on a dynamic hot area enhancement algorithm and a temperature gradient field analysis method, an abnormal temperature area is effectively extracted, and the accuracy of abnormal temperature detection is improved in combination with an environment compensation mechanism. The equipment state is intelligently analyzed through a deep learning model, fault types such as poor contact, insulation aging, overload heating and cooling abnormity are accurately classified, dependence on a fixed temperature threshold value is reduced, and diagnosis adaptability is enhanced.

The invention provides a blade winglet control method and system for three-dimensional flow field analysis of a wind turbine blade, and relates to the technical field of intelligent control, and the method comprises the steps: solving a hydrodynamic equation through a numerical solution to generate three-dimensional speed, pressure and temperature distribution data of a blade surface; according to the speed, pressure and temperature data, the aerodynamic performance and the flow failure mode of the blade tip are recognized, so that the flow state of the blade area is obtained; the flow state of the blade area is analyzed to obtain geometric parameters of the winglet, and the geometric parameters comprise the length, the width, the installation angle and the shape; according to the geometric parameters of the winglets, the installation positions of the winglets are obtained, and the winglets comprise the pressure surface winglet and the suction surface winglet. According to the invention, the instability of airflow can be reduced, vortex and noise are reduced, noise emission during operation of the wind turbine is effectively reduced, and the environmental adaptability of the wind turbine is improved.

The invention discloses a bridge vortex vibration early warning method and system based on vortex field monitoring. The system comprises a wind field acquisition subsystem, a vorticity calculation and prediction subsystem and a vortex field analysis and early warning subsystem. The wind field acquisition subsystem is used for monitoring wind speeds and wind directions of different space points around the main beam in real time. And the vorticity calculation and prediction subsystem calculates the wind speed and wind direction space point data acquired by the wind field acquisition subsystem in real time to obtain the vorticity value around the main beam, and predicts the vorticity value at the future moment. And the vortex field analysis and early warning subsystem performs frequency domain analysis on a vorticity time history, monitors and predicts vortex intensity and vortex shedding frequency in real time, and gives an early warning before vortex vibration possibly occurs. The system can give an alarm in real time according to a vortex vibration mechanism and can play a role in early warning in advance.

The invention belongs to the technical field of multimedia, and particularly relates to a short drama translation and explanation method based on a multi-mode neural network, which realizes full-process automatic processing from subtitle extraction to culture adaptation translation by integrating advanced technical means such as an OCR (optical character recognition) model, optical flow field analysis, an LSTM (long short term memory) network and a graph neural network. Particularly, the subtitles in a complex background can be accurately recognized and processed, subtitle traces are effectively removed, plot conflicts are understood through a deep learning algorithm, and then translation content conforming to target culture is generated. The method not only improves the accuracy of subtitle extraction, but also enhances the cultural adaptability of the translated content, so that the multimedia content can be more naturally and smoothly understood and accepted under different cultural backgrounds, and the watching experience of global users is greatly improved.

The invention provides a jelly foreign matter deep learning detection method based on multi-mode intelligent sensing data driving, and the method comprises the steps: obtaining an original image of jelly, and generating a cross-view light field matrix through a polarized light compensation algorithm and synchronous triggering time sequence control; a cross-view light field matrix is obtained, the attenuation path of each light ray is reversely tracked in the jelly volume direction, and the foreign matter shielding probability is calculated in combination with a sugar degree-absorbance curve in a material library; foreign matter existence probability thermodynamic diagrams are generated in the three physical levels respectively, and a three-dimensional centroid probability field is obtained; and dynamically compressing a three-dimensional centroid probability field analysis time window according to the passing speed of the current production line jelly, comparing misjudgment cases of the same kind of jelly in a historical library, and adjusting a judgment threshold value of a corresponding space level to obtain a real-time judgment instruction set with production line parameter adaptability. Through deep cooperation of multi-mode light field perception and cross-level probability modeling, the technical breakthrough of full-dimensional foreign matter detection of jelly products is realized.

A micron-sized speckle preparation method for quasi-in-situ OIM-DIC mesoscopic strain field analysis comprises the following steps: (1) polishing the surface of a sample to be detected to obtain a bright and scratch-free mirror surface; (2) preparing Si powder turbid liquid; (3) dipping speckles of a sample to be detected in the Si powder turbid liquid to obtain micron-sized speckles; and (4) observing and shooting speckle morphology, and if Si particles are uniformly distributed and dispersed, applying the Si particles to quasi-in-situ OIM-DIC mesoscopic strain field analysis. The method is simple, convenient and rapid, low in operation and construction cost, high in practicability, good in particle dispersity, high in precision, more suitable for calculation of a quasi-in-situ OIM-DIC mesoscopic strain field, controllable in preparation process, low in cost and free of damage to the surface of a sample, the definition and stability of speckle characteristics are remarkably improved, DIC mesoscopic micron-scale operation under a quasi-in-situ OIM mechanical test can be effectively achieved, and the method is suitable for large-scale industrial production. And the grain and mesoscopic strain field information is successfully coupled.

The invention provides an automatic equipment anomaly monitoring method and system based on image processing, and relates to the technical field of automatic equipment anomaly monitoring, and the method comprises the steps: converting an equipment operation video into a multi-dimensional physical field feature: in a motion field dimension, based on optical flow field analysis, extracting a full-period displacement statistical histogram and a space thermodynamic diagram, the motion instability characteristic of the mechanical transmission system is accurately quantified; in a vibration field dimension, an energy spectrum and a vibration thermodynamic diagram are generated innovatively through time-frequency transformation of a displacement signal of a frequency spectrum monitoring point, and frequency domain feature visualization of a hidden vibration fault is achieved; in the dimension of a structure field, edge gradient analysis and texture feature extraction technologies are fused, a time sequence structure thermodynamic diagram sequence is constructed to capture a progressive damage evolution rule, a three-field abnormal index dynamic weighting fusion mechanism overcomes the limitation of traditional single-point monitoring, connected domain analysis of a fused thermodynamic diagram is combined with an LBP texture and morphological feature decision tree, and the defect of the prior art is overcome. Automatic equipment abnormity monitoring based on image processing is realized.

The invention relates to the technical field of graphene electric heating floor heating, and discloses a graphene electric heating floor heating intelligent temperature control system and method.The system comprises an area temperature recognition module, an instruction analysis module, an energy consumption division module and the like; the thermal field monitoring module collects basic temperature data, a real-time power curve and thermal imaging data, the energy consumption division module judges the temperature and energy consumption grade, the temperature control strategy module generates a dynamic adjustment strategy according to the grade, and the temperature difference judgment module and the path correction module achieve power correction and path optimization. And the thermal field analysis module is combined with the user terminal to early warn abnormity and visualize thermal imaging data. According to the scheme, regional refined temperature control, dynamic energy consumption management and intelligent path planning are achieved, the heating comfort level and the energy utilization rate are improved, and the method is suitable for intelligent temperature control scenes of graphene electric floor heating.

The invention belongs to the technical field of flow field visualization, discloses a quick flow field visualization data loading method, and provides a quick flow field visualization data loading method for effectively utilizing processor resources through a multi-thread method in order to solve the problems that the flow field loading speed is low and grid and flow field rendering efficiency is low. Comprising the following steps: importing and initializing flow field grid data, and normalizing the flow field grid data; flow field features are extracted, physical features of the flow fields are extracted through a multi-thread programming technology according to the properties of all the flow fields, and the extracted physical features are stored; decoupling the graphical user interface and flow field loading, and carrying out data loading and separation of the graphical user interface GUI through a multi-thread programming technology; grid and flow field drawing and visualization are carried out, and grid data are visually displayed through a VTK system; interaction between a user and a 3D visual scene is realized through a VTK system; and performing flow field analysis according to a visualization result.