3896results about "Material heat development" patented technology

The invention discloses a directional detection method and system for a power supply shell based on a multi-source heterogeneous sensor, belongs to the field of material characteristic detection, and aims to solve the problems of single dimension, weak anti-interference performance, data isomerism and poor adaptability in traditional industrial detection. Through systematic innovation of multi-source sensor collaboration, dynamic mode control, cross-modal data fusion and self-learning optimization, a high-precision, high-efficiency and high-reliability solution is provided for the precision manufacturing field, and an optical, infrared and ultrasonic multi-modal collaborative detection framework is constructed; the optical unit realizes accurate capture of surface texture and morphology through polarized light imaging and 3D structured light scanning, the infrared thermal imaging unit analyzes the heat conduction characteristic of a material, and the ultrasonic array analyzes internal structure defects to form a surface-material-internal full-dimension detection capability; and nine types of defects such as scratches, pits, weld marks, bubbles, sink marks, material layering, stress cracking, thermal stress abnormity and material pollution are covered.

The invention provides a color steel plate coating thickness dynamic monitoring method and system based on artificial intelligence. According to the method, the temperature distribution data of the surface of the color steel plate coating is obtained, the thermal response map is generated in a pulsed eddy current excitation mode, then the temperature distribution data and the thermal response map are subjected to time sequence correlation processing, the heat conduction characteristics are extracted, and then the heat conduction characteristics are synchronously analyzed; color steel plate coating defect types and thickness abnormal grades are distinguished through a dynamic weight distribution mechanism, a detection result containing defect positions, sizes and thickness deviation values is generated, and finally a coating thickness dynamic compensation instruction is generated according to the detection result; according to the technical scheme provided by the invention, the online control precision and the production efficiency of the coating quality are remarkably improved, and a closed-loop feedback system from detection to control is formed.

The invention discloses a cable insulation aging defect positioning evaluation self-diagnosis method, and belongs to the technical field of power system detection. According to the method, cable multi-dimensional data are obtained through a multi-band broadband dielectric spectrometer, a high-frequency pulse reflection tester and an optical time domain reflectometer, and features are extracted by applying wavelet transform, Fourier transform and a thermal diffusion model after digital processing. A deep convolutional neural network and a long and short term memory network are used for feature fusion and time sequence analysis, and a self-adaptive threshold algorithm and a fuzzy inference system are used for realizing defect accurate positioning and reliability scoring. According to the method, the accuracy and reliability of cable insulation aging defect diagnosis are improved, and intelligent self-diagnosis is realized.

The invention discloses a radiator salt spray corrosion life prediction method based on dynamic time warping, which belongs to the technical field of material corrosion test and life prediction, and comprises the following steps: collecting time sequence data of surface impedance and thermal resistance change of a radiator, constructing a dual-channel corrosion characteristic data set, and recording a salt spray concentration data value. The temperature data value and the humidity data value are combined, and an environment sensitivity weight vector is established. Accelerated corrosion in a salt spray environment is simulated, a laboratory accelerated corrosion test spectrum is generated, meanwhile, an actual environment fluctuation spectrum is monitored, the two spectrums are aligned by using a weight vector, accelerated corrosion data are obtained, and a basic life prediction value is calculated. And calculating an environment-structure coupling factor by combining the interaction between the three-dimensional structure characteristic parameters of the radiator and the temperature and humidity data values, correcting the basic life prediction value, and generating a final life prediction result. According to the method, double-channel feature alignment and coupling factor correction are adopted, and the corrosion life of the radiator of the specific structure under the actual working condition can be predicted.

The invention provides a dissimilar material crystallization welding control method based on microwave energy distribution, which comprises the following steps: acquiring a high-density temperature map of a to-be-welded workpiece through a fiber grating array, and acquiring a real-time temperature value from a dissimilar material interface edge to a central area of the to-be-welded workpiece to obtain initial temperature distribution; calculating a temperature difference value between the edge and the central area, identifying a local overheat point position by comparing a temperature gradient or setting a temperature difference threshold value, and comparing the overheat point temperature with a preset material overheat threshold value to judge whether an overheat area exists or not; if the temperature difference value exceeds a temperature difference threshold value or a local overheating area exists, extracting space coordinates of a low-temperature area and a high-temperature area from the high-density temperature map, and identifying an energy distribution target area needing to be adjusted; and extracting temperature distribution from the updated energy distribution diagram, analyzing a temperature gradient to identify a heating power concentration region, and calculating to obtain a target stress distribution state in combination with the heating power concentration region.

The invention discloses a powder metallurgy gear hardness detection method and system, and belongs to the technical field of metallurgy gears, and the method comprises the steps: obtaining a to-be-detected gear three-dimensional model, and dividing a hardness evaluation region; a thermal response image is collected, a thermal response time gradient parameter TRTG is extracted, and a thermal diffusion characteristic matrix T is formed; establishing a hardness initial model H1 based on the TRTG and compactness; constructing a finite element stress field model, extracting a stress distribution modulation coefficient SDMC, and forming a stress characteristic matrix S; performing weighted correction on H1 based on T and S, and establishing a comprehensive hardness prediction model H2; outputting a hardness prediction result of the whole gear and the key area, and identifying a potential weak area; according to the method, thermal response and stress modulation parameters are fused, non-destructive and high-resolution hardness distribution prediction is achieved, and the method is suitable for quality evaluation and failure early warning of the powder metallurgy gear of a complex structure.

The invention discloses a copper bar connection state detection method and system, particularly relates to the technical field of copper bar state detection, and is used for solving the problem of poor early recognition of copper bar connection deterioration. According to the method, resistance and temperature rise conditions at the joint of the copper bars are measured synchronously in the load change process, signal denoising is realized in combination with finite difference filtering, and characteristic evolution conditions at the joint are captured; the method comprises the steps of determining an analysis window based on a real-time load change event, constructing a thermoelectric track point set and dividing a load rising and falling period, forming a continuous dynamic thermoelectric response curve, dividing a temperature rising track and a temperature falling track through a temperature change trend, extracting a resistance drift amount and a hysteresis loop area, and identifying a connection degradation trend and a structure fatigue characteristic. And connection state information generated by thermal stress action and thermal cycle asymmetry is obtained during load change, and a detection strategy is adjusted according to an analysis result, so that early degradation identification and intelligent risk grading of the copper bar connection state are carried out, and the sensitivity and accuracy of copper bar detection are improved.

The invention provides an on-line monitoring method and system for crack propagation of silicon-based new material equipment in a high-temperature environment, and relates to the technical field of crack detection, and the method comprises the steps: collecting stress distribution data through arranging a stress sensor, and generating a stress field distribution diagram by using an attention mechanism deep neural network model; identifying a stress concentration region based on a region growing algorithm, when a stress value exceeds a preset threshold value, acquiring temperature distribution data, extracting temperature distribution characteristics through a deep mixed probability model, performing multi-modal data fusion in combination with a stress field distribution diagram, and establishing a crack propagation prediction model by using a graph structure neural network. The crack propagation rate and direction are solved through a swarm intelligence optimization algorithm, when the crack propagation rate exceeds a preset threshold value, a control system adjusts equipment operation parameters, the sampling frequency of a sensor is adjusted according to the crack propagation direction, and model parameters are updated through an incremental learning method to achieve real-time monitoring.

The invention relates to the field of water quality monitoring analysis, in particular to a multi-modal water quality monitoring data intelligent processing method and system. The method comprises the following steps: obtaining a water quality monitoring parameter stream and a water quality monitoring image, and carrying out adaptive processing to obtain a filtering optimization parameter stream and an optimization monitoring image; performing water quality state evolution perception according to the adaptive filtering optimization parameter flow, and constructing a water quality state evolution graph; and performing biological index response analysis and water quality ecological influence evaluation based on the water quality state trend evolution graph to obtain a water quality evaluation report. And carrying out pollutant spatial distribution change analysis based on the optimized monitoring image, and executing final water quality monitoring evaluation according to a water quality evaluation report. The invention provides efficient and accurate water quality status analysis.

The invention discloses a real fire test device and test method for a large-diameter cable test model. The device comprises a multi-dimensional adjusting system, a real fire control system, a temperature monitoring system, a calorimetric and flue gas purification system, a high-temperature-resistant video recording device, a thermal imager and the large-diameter cable test model. The multi-dimensional adjusting system comprises a stand column fixed with a guide rail, a cross beam capable of moving along the guide rail, and a height adjusting system and an angle adjusting system capable of adjusting the height and the angle of the large-diameter cable test model; the real fire control system can control the opening degree of a premixing burner and the frequency of a fan so as to control the intensity of a fire source, so that real fire scenes of different types of vehicle fires are provided; before the large-diameter cable test model is tested, a space temperature field needs to be calibrated, and then the space position of the large-diameter cable test model is determined. According to the invention, a scheme can be provided for the fireproof performance test of the large-diameter cable test model of the bridge in a real space state, and technical support is provided for the fireproof design of the large-diameter cable test model of the large-span bridge.

The embodiment of the invention provides a fault monitoring method and device for a liquid cooling system and a server system.The method comprises the steps that the liquid inlet temperature, the liquid outlet temperature and the flow of cooling liquid of the liquid cooling system are obtained in real time, the liquid inlet temperature is the temperature when the cooling liquid enters the liquid cooling system, and the liquid outlet temperature is the temperature when the cooling liquid flows out of the liquid cooling system; the current specific heat capacity of cooling liquid in the liquid cooling system is calculated according to the liquid inlet temperature, the liquid outlet temperature and the flow; and when the difference value between the initial specific heat capacity and the current specific heat capacity of the cooling liquid is larger than or equal to the specific heat capacity threshold value, a first alarm is given out to remind that the cooling liquid of the liquid cooling system goes bad.

A gas measuring device (100) and a gas measuring process measure a concentration of a target gas. A detector detection variable sensor (12.1) measures a detection variable (U10) of a detector, which detector detection variable correlates with the concentration of the target gas in a gas sample (Gp). A compensator detection variable sensor (12.2) measures a detection variable (U11) of a compensator, wherein this compensator detection variable correlates less with the target gas concentration. The gas measuring device can be operated in a pressure-compensating mode and / or in a humidity-compensating mode. In pressure-compensating mode, the influence of the ambient pressure on a measurement result is compensated as best as possible under the boundary condition that the influence of the ambient humidity remains sufficiently small. In humidity-compensating mode, the influence of the ambient humidity on a measurement result is compensated as best as possible under a corresponding boundary condition.

The invention discloses a reinforced cable core wire test method and a related device, and the method comprises the steps: carrying out the matching analysis of the material structure parameters of a to-be-tested cable and the phase change characteristic parameters of a critical phase change fluid, and obtaining test parameters; controlling the critical phase change fluid to perform gas-liquid phase change near a critical point according to the test parameters, and applying a phase change stress wave and a circulating temperature load to the to-be-tested cable to obtain stress response characteristics; analyzing phase change stress wave propagation characteristics according to the stress response characteristics to obtain interface micro-motion characteristic parameters; performing quantitative analysis according to the deviation between the interface micro-motion characteristic parameters and the standard reference data to obtain a failure risk level; and determining safe use parameters according to the failure risk level. According to the method, the high sensitivity of the critical phase change fluid to tiny disturbance near the critical point is utilized, and the synergistic effect of the thermal cycle load and the phase change stress wave is combined, so that the high sensitivity detection of the internal interface micro motion of the cable is realized, and a reliable basis is provided for the performance evaluation and the service life prediction of the cable.

The invention relates to the technical field of new energy aluminum alloy precision casting multi-modal quality monitoring, in particular to a new energy aluminum alloy precision casting multi-modal quality monitoring device and method. According to the technical scheme, the new energy aluminum alloy precision casting multi-mode quality monitoring device comprises a quality monitoring device body, an infrared thermal imager probe, a germanium single crystal protection lens, an integrated spectrometer probe debugging port, an acoustic detection microphone array and a honeycomb acoustic shielding cover. An infrared thermal imager probe is arranged on one side of the quality monitoring device main body, and a germanium single crystal protection lens is arranged on the outer side of the infrared thermal imager probe; synchronous acquisition and fusion analysis of multi-physical field data are realized by integrating six modes of spectrum, infrared thermal imaging, vibration, machine vision, acoustics and pressure deformation, and meanwhile, when the shrinkage risk is predicted by the infrared thermal imaging, a die-casting process compensation mechanism is automatically triggered to kill defects in the germination stage, so that the defect rate is greatly reduced.

The invention relates to the technical field of steel rail repair, and provides a steel rail laser additive defect detection method and system.The method comprises the steps that before laser additive repair is conducted on a steel rail damage area, a local area of a steel rail base body is instantly heated, so that an instant hot spot is formed in the corresponding local area; collecting thermal radiation attenuation information of the instantaneous hot spot; according to the thermal radiation attenuation information, the actual heat dissipation rate of the local area corresponding to the instantaneous hot spot is calculated so as to achieve detection of the steel rail damage area; according to the actual heat dissipation rate, repairing process parameters used for laser additive repairing are selected from a pre-stored process parameter combination; and carrying out laser additive repair on the damaged region of the steel rail by adopting the repair process parameters. The method has the effect of improving the quality and reliability of steel rail laser additive repair.

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 detection, in particular to a thermal insulation performance detection system and method of a thermal insulation gel material.The method comprises the steps that surface temperature data and internal pore distribution data of a thermal insulation gel material sample are obtained and subjected to dynamic heat flow coupling treatment, and a dynamic coupling feature sequence is obtained; constructing a multi-dimensional thermal impedance tensor based on the dynamic coupling feature sequence and carrying out regularization constraint to obtain a thermal impedance time sequence; extracting a nonlinear thermal shielding index in the thermal impedance time sequence, constructing a high-dimensional feature vector, and generating a probability density distribution parameter set; and according to the probability density distribution parameter set, constructing a multi-dimensional input data set and carrying out iterative optimization, calculating a confidence interval of the thermal insulation performance boundary value, evaluating the thermal insulation performance grade of the thermal insulation gel material based on the confidence interval, and generating a performance evaluation parameter report. The comprehensive heat insulation effect of the heat insulation gel material in actual use can be more comprehensively and accurately reflected.

The invention relates to the technical field of hydrogen production, in particular to a quick response system of a double-probe hydrogen leakage explosion detector and a grading early warning method. Comprising a first hydrogen concentration detection probe and a second hydrogen concentration detection probe which are respectively arranged at two different positions of a monitored area to form a space complementation detection network; the signal processing unit is electrically connected with the two probes and is used for receiving and processing the concentration signals output by the probes; the quick response control module is used for calculating the hydrogen concentration change rate in real time based on an output result of the signal processing unit; the grading early warning module is used for generating different grades of early warning signals according to the hydrogen concentration change rate and the absolute concentration value; the communication interface module is used for transmitting the early warning signal to a remote monitoring terminal; the multi-physical-field parameter change of the electrolyte can be sensed in real time, the control instruction is dynamically corrected, and the anti-interference capability is high.

The invention discloses a fault detonation simulation test method and platform for an extra-high voltage converter transformer network side bushing, and the method comprises the steps: providing a critical value calculation method for primary physical explosion and secondary chemical explosion of the extra-high voltage converter transformer network side bushing under different arc fault energy conditions; and the critical conditions of primary physical explosion and secondary chemical explosion can be accurately judged. According to the invention, the whole dynamic evolution process from rapid cracking of transformer oil and sudden pressure increase caused by converter transformer fault arc to superposition of physical explosion and explosion chemistry can be truly simulated, a grid-side bushing fault detonation critical discrimination method is provided, and technical parameters and theoretical support are provided for the explosion-proof and pressure-relief design of the converter transformer.

The invention relates to a roadbed compaction quality detection method and system based on multi-dimensional data, and the method comprises the steps: obtaining sensor data of a roller of a road roller in real time, and obtaining pavement images and positioning data of a plurality of continuous time points; when the road surface is flattened, the roadbed structure is gradually stable, so that the corresponding pressure data and vibration data are gradually stable. By analyzing the stability of the pressure data and the vibration data, the stability of the pressure data and the vibration data is determined. According to the method, vibration data, stable data and temperature data of a road section at a stable time point are extracted, and then a target data reference range corresponding to a corresponding temperature grade and a roadbed material is found from a pre-constructed data model, so that the target data reference range can verify the vibration data and the stable data at the stable time point; therefore, whether the road roller performs the road rolling operation in a reasonable range or not is judged. In addition, the road surface is detected by using the road surface image.

The invention discloses a high-temperature surface contact thermal resistance elimination method based on double thermocouple compensation, and belongs to the technical field of material thermal property characterization and testing. The method comprises the following steps: synchronously acquiring double-thermocouple temperature, and obtaining a temperature difference signal through filtering calibration and environment correction; calculating the real-time heat flux density according to the corrected temperature difference, the Seebeck coefficient and the dynamic correction factor; establishing a nonlinear dynamic coupling model containing contact thermal resistance parameters, and performing temperature interval division; identifying a contact thermal resistance parameter on line by adopting a self-adaptive recursive least square algorithm, and generating a dynamic thermal resistance compensation value; and applying the compensation value to a double-thermocouple signal according to the weight, and outputting accurate high-temperature surface temperature. According to the method, data acquisition and preprocessing, dynamic heat flow correction, nonlinear segmented modeling, self-adaptive online identification and refined compensation output strategies are adopted, the influence of high-temperature surface contact thermal resistance can be effectively eliminated, and the accuracy and reliability of temperature measurement in the high-temperature environment are remarkably improved.

The invention relates to the field of thermal insulation oil pipe detection equipment, in particular to a thermal insulation oil pipe thermal insulation performance detection device and a use method thereof.The thermal insulation oil pipe thermal insulation performance detection device comprises a detection pool with the hollow interior and the open top, and the open end of the detection pool is detachably provided with a pool cover frame with the hollow interior and the two vertical ends open; the heat insulation oil pipe is placed between the detection pool and the pool cover frame, the detection pool and the pool cover frame are jointly provided with clamping grooves used for containing the heat insulation oil pipe, sealing rubber strips are arranged between the detection pool and the pool cover frame, between the detection pool and the heat insulation oil pipe and between the pool cover frame and the heat insulation oil pipe, and end disc covers are detachably arranged at the two ends of the heat insulation oil pipe. The end disc cover is provided with a temperature sensor and an electric heating pipe, the temperature sensor and the electric heating pipe are both electrically connected to the control system, and the detection pool is provided with a liquid level adjusting piece, a liquid constant temperature piece, a gas circulation piece and a detection assembly. The method has the effect of improving the accuracy of the thermal insulation performance detection result of the thermal insulation oil pipe.

The invention relates to the field of construction temperature regulation and control, in particular to an intelligent temperature control method and device for fan foundation construction in an alpine region. The method comprises the following steps: collecting real-time concrete temperature monitoring parameters based on a distributed temperature sensor, carrying out time sequence temperature discrete trend analysis and spatial temperature fluctuation distribution evolution, and constructing a temperature fluctuation distribution evolution diagram; concrete surface environment parameters are extracted, heat exchange simulation processing is carried out on the temperature fluctuation distribution evolution diagram, multivariate coupling correlation analysis is carried out, and a temperature-environment quantitative relation model is constructed; and obtaining historical meteorological logs and meteorological environment data of the construction area, carrying out similar meteorological condition matching calculation, carrying out short-term meteorological trend prediction, and generating short-term meteorological trend prediction features. According to the dynamic temperature regulation and control requirements, safe construction of the fan foundation concrete in the high and cold environment is guaranteed, and the construction quality is improved.

The invention provides an online detection method and system for paper defects, and the method comprises the steps: obtaining an infrared thermal imaging data sequence of to-be-detected paper under the dynamic thermal excitation effect; generating a temperature response characteristic distribution diagram corresponding to the to-be-detected paper according to the temperature gradient change rate of different coating areas of the to-be-detected paper in the infrared thermal imaging data sequence; the temperature response characteristic distribution diagram is input into a pre-trained machine learning model, thickness distribution data of the to-be-tested paper is output, and the machine learning model is constructed based on a random forest algorithm; based on the thickness distribution data, a paper coating thickness detection result synchronous with the speed of the paper production line is generated, and when the paper coating thickness detection result shows that the paper coating thickness is abnormal, the dynamic thermal excitation parameter adjustment action is triggered, so that the thicknesses of all pattern layer areas of other paper in the paper production line are normal. According to the invention, the precision of online detection of the paper coating thickness and the production regulation and control efficiency are improved.

The invention relates to the technical field of fire coal control, and discloses a thermal power plant fly ash floating black online detection control method and system, and the method comprises the steps: 1, employing microwave, infrared and laser sensors for cooperative work, detecting carbon dielectric characteristics through microwave dust interference resistance, identifying thermal radiation difference through infrared, and analyzing particle distribution through laser; 2, on the basis of the detection requirements in the step 1, triple protection of air curtain barrier, ultrasonic cleaning and hydrophobic coating is designed, dust condensation is blocked, and it is ensured that the light transmittance of the sensor is larger than 90%; the invention provides a multi-mode sensing fusion-anti-interference current stabilization-closed loop optimization full-link solution for the industrial problem of signal distortion caused by optical window dew formation and dust deposition, airflow disturbance and environmental interference in fly ash floating black online detection. The light transmittance of the optical window is greater than 93% by combining triple protection of air curtain barrier, ultrasonic cavitation stripping and nano hydrophobic coating.

The invention relates to the technical field of underground coal gasification, in particular to a coal underground gasification process stability monitoring and evaluating method which comprises the following steps: determining a space mapping relation between a gasifier temperature field and an acoustic emission event according to the temperature gradient and the acoustic emission event of a gasifier; carrying out three-dimensional inversion on a combustion cavity of the gasification furnace, and determining attenuation trends of the coal seam under different temperature gradients; according to the attenuation trend of the coal seam under different temperature gradients, the propelling direction of the boundary of the combustion cavity is determined by utilizing the spatial distribution density and the relative position of each acoustic emission event; according to the propelling direction of the fuel cavity boundary, boundary moving paths are formed, and the propelling area proportion of each position in the propelling direction is calculated according to the distance difference of the boundary moving paths; and according to the propulsion area proportion of each position in the propulsion direction and the expansion rate of the combustion cavity, determining the space stability classification of each part of the combustion cavity. The accuracy and the efficiency of monitoring underground gasification of the coal seam are realized.

The invention discloses a thermal insulation performance detection method and system for a composite wallboard, and relates to the technical field of building material detection, and the method comprises the steps: dividing a composite wallboard sample into a plurality of grids, setting an inversion starting point for each grid according to initial data, starting an inversion algorithm to gradually adjust the heat conductivity coefficient of each grid, and generating a heat conductivity coefficient distribution diagram, calculating the average heat conductivity coefficient and the overall thermal resistance value of the sample; the test platform applies full-automatic thermal excitation and sound wave excitation to a sample, collects sound signals and thermal imaging data related to internal defects of the composite wallboard, calculates the optimal matching time point of the sound signals and the thermal imaging data, and extracts defect related characteristics in the sound signals and temperature anomaly characteristics in thermal imaging in a double-flow processing mode. Generating a comprehensive defect distribution diagram, and comparing the comprehensive defect distribution diagram with the heat conductivity coefficient distribution diagram and the average heat conductivity coefficient to obtain preliminary judgment; through acoustic-thermal multi-mode cooperative detection, the spatial distribution of tiny defects in a sample is accurately positioned, and the influence of the tiny defects on the heat-conducting property is judged.

The invention discloses a damping thermal insulation material performance evaluation method and system for a battery pack, and relates to the technical field of battery pack thermal management, and the method comprises the steps: extracting a calibration sample set, applying transient thermal excitation, and collecting an infrared thermal image sequence to extract thermal response features; performing industrial CT scanning to obtain defect quantitative indexes, and forming a calibration data set with the thermal response characteristics; establishing a quantitative correlation model based on the calibration data set, and determining a batch quality threshold according to model output distribution; executing the same excitation and collection on an online sample to be detected to extract the characteristics of the sample, inputting the model to obtain a defect quantitative prediction value, comparing the defect quantitative prediction value with a batch quality threshold, and outputting an evaluation result; when a preset period or a trigger condition is met, a new sample is supplemented and extracted, and newly added calibration data is obtained to update the model and the threshold value. According to the method, accurate material performance evaluation is provided by establishing a quantitative model of thermal response characteristics and defect quantitative indexes, and evaluation consistency and stability are enhanced through a dynamic updating mechanism.

The invention belongs to the technical field of sensor error correction, and discloses a data synchronization and error correction method based on multi-source gas detection, and the method comprises the steps: firstly achieving the time-space synchronization of a multi-source sensor through the combination of GPS / Beidou hardware time service and a gas diffusion transmission model; non-negative matrix factorization (NMF) is adopted to decouple sensor cross interference, and an LSTM neural network is utilized to predict a sensor drift amount caused by environmental temperature and humidity changes; and finally, carrying out dynamic weight fusion based on the real-time confidence of each sensor, and outputting a high-precision gas concentration value. The problem of data distortion caused by time sequence dislocation, cross sensitivity and environment drift in a multi-sensor system is effectively solved, the accuracy of detection data and the reliability of the system are remarkably improved, and the method is particularly suitable for multi-component gas detection scenes in the fields of chemical engineering, environment monitoring and the like.

The invention discloses a rapid drug quality detection system, and relates to the technical field of drug quality detection. The system integrates a multi-modal fusion detection front end, comprises an image acquisition assembly, a spectral analysis component, a thermal imaging auxiliary module and an image recognition module, and realizes comprehensive detection of appearance, components and thermal state characteristics of drugs. Through microscopic imaging, light source accurate regulation and control and imaging task scheduling, the detection precision and efficiency are improved. The intelligent self-adaptive detection middle end is combined with a physical and chemical detection platform, and deep analysis is carried out on suspected problem drugs. And the cloud data processing and remote monitoring rear end ensures real-time uploading, intelligent analysis and remote operation and maintenance of data, and constructs a drug full-life-cycle traceability system.