127 results about "Temperature mapping" patented technology

The invention discloses a multi-source information collaborative power equipment three-dimensional temperature field construction method. Firstly, an infrared camera, an IMU and a laser radar are utilized to obtain an accurate external parameter relation through joint calibration, point cloud distortion is eliminated, angular points and plane points are extracted, a re-projection residual error, a distance sampling residual error and an IMU pre-integration residual error are constructed, an error state iteration Kalman filter is adopted to optimize a global pose, and positioning is achieved. Providing a self-supervised depth completion network, combining an infrared temperature image and a sparse depth map generated by a laser radar as input, adopting a depth completion strategy guided by an infrared image, estimating relative motion of adjacent frames by using pose information, introducing a feature alignment module to reduce alignment errors, and combining the depth map, the infrared image and IMU data to obtain a self-supervised depth completion algorithm; and efficient construction of the three-dimensional temperature field of the power equipment is realized. According to the invention, the three-dimensional temperature field of the power equipment is constructed more accurately, and the capability of the substation inspection robot for state monitoring and fault diagnosis of the power equipment is improved.

The invention relates to the field of seepage analysis, and particularly discloses a loess slope seepage three-dimensional observation device and method under circulating seepage, and the method comprises the steps: constructing a loess seepage slope physical simulation experiment model, collecting an experiment sample image by using an image collection device, and analyzing the attribute parameters of the device to determine whether to adjust the device; preprocessing, bilateral filtering and temperature difference analysis are carried out on the collected experiment image, preprocessing process parameters are monitored, preprocessing precision factors are evaluated according to the parameters, and whether secondary processing is carried out or not and temperature abnormal areas are separated or not is judged; matching a temperature mapping parameter set based on the precision factor, evaluating the mapping accuracy, and correcting as required; finally, an initial three-dimensional temperature field is generated in combination with sensor data, and a permeation path is generated for three-dimensional rendering; according to the method, through multi-step cooperation, three-dimensional observation and analysis of loess slope seepage are achieved, a systematic technical scheme is provided for research of loess slope seepage characteristics, and improvement of the accuracy and the visualization level of slope seepage research is facilitated.

The invention discloses a temperature self-adaptive adjustment control method and system for an automobile sensor, and relates to the technical field of automobile sensors, and the temperature self-adaptive adjustment control method for the automobile sensor comprises the following steps: S1, obtaining data; s2, performing classification and label addition on the data to form a data set; s3, extracting core temperature characteristic parameters, and constructing a four-dimensional temperature mapping matrix; s4, introducing an ant colony algorithm to iteratively optimize a temperature dynamic weighting rule, and obtaining an adjustment target and a change trend; s5, generating a regulation control strategy, and constructing a temperature fusion regulation feedback model at the same time; s6, performing iterative verification on the model, and generating a sensor three-dimensional verification report; and S7, performing security judgment on the three-dimensional verification report of the sensor. According to the method, through multi-source sensing data acquisition and segmented labeling preprocessing, temperature local mutation features and long-time time sequence dependence features are captured, and temperature data heterogeneity of traditional single-model feature extraction is broken.

The invention relates to a calender roll partition electromagnetic temperature control and infrared thermal imaging feedback system, which belongs to the field of fluoroplastic calendering thickness control equipment and comprises a data preprocessing module, a roll surface temperature zone digital twinborn analysis module, a time sequence temperature and thickness correlation module and a fusion regulation and power correction module. The data preprocessing module establishes a film surface gray scale-temperature mapping relation and outputs effective temperature data; the roller surface temperature zone digital twinborn analysis module constructs a roller surface-film surface coupling thermal field digital twinborn model to generate a temperature thermodynamic diagram, and outputs a temperature deviation value and thermal crosstalk early warning information of an independent temperature zone in combination with a temperature zone thermal crosstalk model; the time sequence temperature and thickness correlation module establishes a temperature deviation-thickness fluctuation basic correlation model and outputs thickness data; the fusion regulation and power correction module corrects the independent temperature zone coil power regulation quantity and outputs a power regulation instruction based on a multi-parameter dynamic weight distribution mechanism; the system solves the problem that traditional temperature control precision is low, and the temperature control precision and product quality of the fluorine plastic film are improved.

The invention discloses a chip aging test method based on thermal migration analysis. The method comprises the following steps: acquiring power consumption distribution data, material attribute data and manufacturing process data; discrete mapping and dynamic adjustment are carried out on the power consumption distribution data by adopting finite element network nodes to obtain an initial heat distribution diagram; processing the initial thermal distribution diagram based on a thermal imaging technology to generate a temperature mapping diagram of the surface of the chip; performing network division based on the temperature mapping graph, and generating a heat transfer path graph in combination with a gradient tracking algorithm; based on the heat transfer path diagram, screening a potential area through a preset temperature threshold value, and generating a potential heat distribution diagram through clustering analysis; performing microstructure analysis on the abnormal area according to the potential thermal distribution diagram to generate an abnormal analysis report; and solving high-temperature region distribution according to the manufacturing process data and the anomaly analysis report, and performing region analysis to generate a thermal identification report. According to the method, the problem that the heat transfer path cannot be accurately captured and the hot spot area cannot be identified under the non-destructive test can be solved.

The invention relates to an SSD (Solid State Disk) heat dissipation optimization method and system based on dynamic temperature control. The method comprises the following steps: acquiring a thermal state vector of an SSD through inner and outer ring temperature monitoring; predicting a future 5S temperature track through a long short-term memory network model, and generating a temperature prediction sequence; generating a computing power distribution proportion based on the temperature prediction sequence, and determining a capacity migration proportion at the same time; according to the real-time temperature value of each logic block in the block temperature mapping table and the computing power distribution proportion and capacity migration proportion, heat-sensitive and heat-tolerant classification is carried out on the I / O queue, and an optimized scheduling sequence is generated; calculating a power supply phase parameter according to the access frequency of the heat-sensitive block of the optimized scheduling sequence, and generating a pulse type heat dissipation control signal; the SSD power supply phase is dynamically adjusted according to the pulse type heat dissipation control signal, heat dissipation optimization is conducted through the pulse width modulation technology, updated heat state data is fed back to inner and outer ring temperature monitoring, and therefore the purpose of dynamic intelligent temperature control of the SSD is achieved.

The invention discloses a cold therapy method based on dynamic temperature feedback and intelligent adjustment, and the method comprises the steps: loading a cold therapy preset scheme from a database of a system, and carrying out the self-inspection of equipment of a sensing layer; collecting temperature distribution information of the skin surface of the treated part of the patient to obtain thermal imaging data; acquiring blood perfusion rate information; acquiring tissue moisture content and impedance phase angle information; establishing a temperature mapping relation from the skin surface to the deep tissue; the surface boundary condition is set as the skin surface temperature actually measured by the infrared array, and the deep boundary condition is set as an adiabatic hypothesis; and fusing the acquired multi-source observation data with the numerical solution result. The system has the advantages that accurate control over the cold therapy temperature is achieved, the protection response time is optimized, the safety of a patient in the cold therapy process is guaranteed, the treatment effect is improved, a doctor can conveniently make a personalized treatment scheme, efficient information interaction between the doctor and the patient is achieved, and the treatment experience of the patient is improved.

The invention discloses a heating monitoring method for a stainless steel seamless tube in a heat treatment furnace, which belongs to the technical field of metal heat treatment and specifically comprises the following steps: acquiring an electromagnetic induction signal of a steel tube in rotation advancing in real time and binding spatio-temporal information; kinematics inversion is carried out on the spatio-temporal information based on the movement speed of the steel pipe, and an electromagnetic parameter evolution track of each physical point on the surface is reconstructed; continuously deviated abnormal points are identified based on the evolution trajectory and clustered to extract electromagnetic characteristics of the heating abnormal area, temperature deviation is obtained through a preset electromagnetic-temperature mapping model, and a compensation instruction is generated; and predicting space-time coordinates of the abnormal area reaching the next heating area, and driving the corresponding independent heating unit to execute dynamic energy compensation in the matched time window. Real-time, global and accurate sensing and closed-loop regulation and control of the heating uniformity of the moving workpiece are achieved, the uniformity and stability of heat treatment quality are remarkably improved, and energy consumption is reduced.

The invention discloses a port cargo hazard source real-time monitoring method and system based on the Internet of Things, and is applied to quality safety monitoring of a port cold chain cargo storage area. The method comprises the following steps: configuring a temperature sensor grid, a humidity sensor grid and a thermal imaging device to acquire a temperature distribution matrix, a humidity distribution matrix and a surface temperature image of a cold chain cargo area; extracting temperature and humidity time sequence change features by using a recurrent neural network, extracting space temperature gradient features of a thermal imaging image by using a deep residual network, and performing feature fusion through an adaptive weighting mechanism; the fused features are constructed into a time window sequence, and a gradient boosting tree model is utilized to evaluate the cargo state abnormity risk level and position a hazard source; according to the invention, potential hazard sources can be timely found and accurately positioned, and the intelligent level and early warning capability of port cargo safety management are effectively improved.

The invention provides a training method and device and a control method and device for an air conditioner cluster control model. The training method comprises the steps that historical data of an air conditioner cluster are obtained, feature extraction is conducted on the historical data, and a feature training set is constructed; constructing an initial air conditioner cluster control model; based on the feature training set, utilizing a reward and punishment mechanism to train an initial air conditioner cluster control model to obtain an air conditioner cluster control model; the reward and punishment mechanism is used for optimizing an influence parameter matrix of a prediction temperature mapping relation according to the accuracy degree of the prediction temperature mapping relation from the pre-regulation environment temperature matrix to the target prediction environment temperature matrix; the prediction temperature mapping relation is used for obtaining a target prediction environment temperature matrix according to the influence degree of other devices in the air conditioner cluster on the environment temperature of the installation position of any device and the current environment temperature of the installation position of any device. Multiple influences existing in an industrial production site can be eliminated, automatic multi-dimensional temperature regulation and control are achieved, and the temperature regulation and control precision is improved.

The invention relates to an ultrasonic power control method and system of a suspension chain cleaning machine, and relates to the technical field of suspension chain cleaning machines, and the method comprises the following steps: receiving input material information of a to-be-cleaned workpiece; matching a proper cleaning liquid temperature range of the to-be-cleaned workpiece based on the material information; acquiring a first cleaning liquid temperature sent by a temperature sensor in the cleaning tank; when the obtained temperature of the first cleaning fluid is not within the target temperature range, a heating device is started to adjust the temperature of the cleaning fluid, so that the temperature of the cleaning fluid is within the target temperature range; dividing the target temperature range into n sub-intervals, and obtaining an ultrasonic power and temperature mapping library; acquiring current temperature data sent by the temperature sensor and judging a sub-interval in which the current temperature is located; determining an ultrasonic power value corresponding to the subinterval where the current temperature is located based on an ultrasonic power and temperature mapping library; and controlling the ultrasonic transducer to perform ultrasonic cleaning based on the ultrasonic power value.

The invention discloses a pump body heat treatment uniformity detection method based on infrared imaging. The method comprises the following steps that 1, a pump body three-dimensional structure model is obtained, and detection points are calibrated; 2, applying thermal disturbance to each detection area; 3, carrying out dynamic multi-channel temperature image acquisition to obtain a temperature-time sequence; 4, constructing a non-Fourier thermoelastic inertial response model of each detection point, and extracting thermal response characteristic parameters; 5, constructing a thermal response memory map; step 6, inputting the thermal response memory map into an improved TimeSFormer model, introducing a thermal potential field tensor guide mechanism into the model, and obtaining a thermal treatment uniformity score in combination with the spatial position information of the detection point and the structural topological coding vector; and 7, identifying a heat treatment deviation concentration area and outputting a detection report. The intelligent detection and evaluation method for the heat treatment uniformity of the pump body is realized by combining infrared imaging and the improved TimeSFormer model.

The invention discloses an intelligent control method and system suitable for a child thermometer, and relates to the technical field of control supervision, and the method comprises the steps: collecting multi-modal data, carrying out the enhancement processing of image data, and generating an enhanced image; performing image registration and temperature mapping based on the enhanced image to generate a child real-time body temperature mapping image; local temperature hot spot detection is carried out based on the child real-time body temperature mapping image, candidate abnormal areas are marked, abnormal area features are extracted for abnormal analysis, and a preliminary abnormal detection label is generated; using a Haar cascade algorithm to extract a child face region, using a neural convolutional network to extract emotional features, and analyzing a child emotional state; and based on the preliminary anomaly detection tag, the abnormal region features, the child emotional state and the environmental data, performing comprehensive analysis on the child health state, generating a health report, sending a temperature control instruction, and feeding back to parents. A closed-loop system is formed, and the intelligent level of the child thermometer is improved.

The invention discloses a bridge section temperature field calculation method fusing infrared imaging and finite element analysis, and belongs to the technical field of bridge temperature measurement. According to the method, unmanned aerial vehicle acquisition equipment with an infrared lens is used for performing surface infrared temperature image acquisition on upper, lower, left and right sections of a to-be-measured cross section of a bridge at multiple moments; spatial mapping of temperature information is realized through format conversion and temperature information extraction of the infrared image; on the basis of a finite element analysis platform, the extracted surface temperature data are imported into a bridge cross section numerical model, temperature field distribution solving is carried out through a solid heat transfer and stress analysis function, and accurate reconstruction and temperature effect analysis of a bridge cross section temperature field are achieved. According to the invention, non-contact rapid monitoring and accurate calculation of the bridge temperature field are realized, and reliable technical support is provided for health assessment of a bridge structure.

The invention discloses a thermal management method and system for immersed user side energy storage equipment, and relates to the technical field of thermal management of energy storage equipment, and the thermal management method comprises the steps: S1, carrying out the electrochemical impedance spectroscopy test of a battery module of the energy storage equipment under different internal temperatures, charge states and health states, and building an impedance spectroscopy-temperature mapping model; s2, according to a sampling interval, collecting impedance spectrum data of a current energy storage equipment battery module under the characteristic frequency point, and calculating the internal temperature of the battery module by using a mapping model; s3, collecting the surface temperature of the battery module in the time interval through a temperature sensor according to the sampling interval; s4, calculating the temperature difference between the internal temperature and the surface temperature of the battery module at the same time, and drawing a temperature difference curve according to the time sequence; and S5, identifying whether a thermal imbalance or thermal runaway event occurs or not according to the temperature difference curve, performing thermal management based on the thermal imbalance or thermal runaway event, and adopting a thermal management system of the immersed user side energy storage equipment of the thermal management method.

The invention provides a fault positioning method for a temperature-sensitive color-changing cable, and the method comprises the steps: obtaining thermochromic image data of a cable coating, segmenting a fault color development region through multi-channel significance transformation, and generating a region segmentation image; converting the image from RGB to HSV space to extract H, S and V parameters, and calculating color-temperature correlation features; processing through a feature weight dimension reduction module to generate a principal component feature vector, and training a temperature response neural network to obtain a fault temperature mapping curve; and outputting a fault physical coordinate in combination with the color-temperature characteristics and the mapping curve. Wherein the multi-channel saliency transformation comprises generation of an RGB channel saliency map, histogram transformation, fusion screening and binarization processing; according to feature dimension reduction, low-weight features are gradually removed through weight calculation; the neural network adopts an 8-16-layer convolution structure; and finally, fault coordinates are positioned according to the temperature threshold and the chromaticity parameters and graded identification is performed. According to the invention, the fault detection efficiency and the temperature anomaly identification accuracy can be improved.

A multi-user detection and distance measurement method based on a thermal array sensor, called TADAR for short, comprises the following steps: collecting environmental thermal radiation data by using the thermal array sensor, and generating a 2D temperature map; preprocessing the 2D temperature map, and pooling the human body region to form a temperature feature vector; and estimating the distance between the user and the sensor by using the feature vector and a regression model. In addition, individual users are distinguished and confirmed by spatio-temporal tracking techniques, and TADAR supports multi-user detection and separation. The TADAR has the advantages that the temperature reading of each part of the body is fully utilized, so that the distance measurement accuracy is improved; moreover, training is not needed, texture-free, low-resolution and high-noise thermal array data can be processed, and a plurality of users can be effectively detected and separated. Besides, the TADAR utilizes space and time sequence information, so that accuracy and robustness in different environments are ensured, and a solution which gives consideration to imaging resolution and privacy protection is provided for ubiquitous human body perception.

This invention discloses a method for generating building energy-saving optimization strategies based on UAV infrared imaging, specifically relating to the field of building energy-saving management technology. The method includes acquiring infrared images, timestamps, location coordinates, and air conditioning records collected by a UAV during target building inspections; stitching the infrared images together according to the location coordinates; extracting the room activation status and set temperature from the air conditioning records according to the timestamps; and outputting a temperature map and operation table. By collaboratively organizing the infrared inspection results, room air conditioning operation information, and control area constraints at the edge into an action list, room execution sequence, and area execution sequence, energy-saving recommendations can be transformed from static recommendations into strategy results with constraint resolution, prioritization, and batch execution capabilities, relatively improving the problems of recommendation conflicts and implementation difficulties.

A method for detecting a defect in a bonded wafer includes receiving the bonded wafer on a wafer holder, the bonded wafer including a first structure bonded to a second structure, the first structure including first contacts, the second structure including second contacts, and the first structure bonded to the second structure forming a bonding layer including metal contacts between the first contacts and the second contacts. The method further includes illuminating a portion of the first structure for a first time duration to heat the portion of the first structure to a starting temperature, and detecting, using a light detector, a temperature map of the bonded wafer, the temperature map being detected after a second time duration. And the method further includes determining, based on the temperature map, the defect in the bonding layer of the bonded wafer.

The present invention discloses a temperature - adaptive infrared image colorization method, belonging to the field of image processing. The method includes: capturing infrared images and visible - light images at different ambient temperatures; establishing a temperature mapping relationship; constructing paired temperature - mapped image - infrared normalized image - visible - light normalized image data pairs, and dividing the image data pairs into an image training set and an image test set; constructing a temperature - adaptive network, including a temperature module and an infrared colorization module, and completing the training process of the temperature - adaptive network; inputting the image test set into the trained temperature - adaptive network to generate infrared colorized images. The purpose of the present invention is to enhance the robustness of the network affected by the ambient temperature. By inputting infrared images and temperature - mapped images into the network, high - quality color images can be accurately reconstructed.

The present invention discloses an infrared temperature measurement method for selecting an optimal regression model, which includes the following specific steps: collecting thermal imager images and focal plane temperature data; establishing a set of polynomial F(TP) functions to be fitted according to the focal plane temperature TP; establishing a set of polynomial F(T, TP) functions according to the target temperature T and the focal plane temperature TP; respectively processing the F(TP) function set and the F(T, TP) function set to obtain the parameter sets and R values of each function; setting a threshold thr_R1 and a threshold thr_R2; by comparing the R values of the F(TP) function set and the F(T, TP) function set with the set thresholds, determining the optimal function model and the optimal function parameters; downloading the obtained optimal function model and the optimal function parameters into the thermal imager, obtaining the current focal plane temperature TP of the thermal imager and the current target temperature image value Y, and calculating the target temperature T to complete the mapping from the image value to the temperature value. The algorithm of the present invention automatically selects the optimal model for calculation, reducing the algorithm configuration parameters.

The present invention discloses a three-temperature testing method and device for a semiconductor chip, relating to the technical field of semiconductor chip testing. The method comprises the following steps: inputting an initialization parameter set into an impedance-temperature mapping model, performing phase angle analysis and multi-band feature fusion through a broadband impedance spectrum analysis method, obtaining the instantaneous value of the chip junction temperature, dynamically compensating the instantaneous value of the chip junction temperature using a PID controller, mapping the result into an execution instruction set through a fuzzy rule base inference engine, converting the execution instruction set into a bidirectional voltage signal through pulse width modulation, driving a semiconductor refrigeration plate to perform bidirectional temperature rise and fall control in a three-temperature environment, and synchronously collecting real-time temperature change test data. The present invention adopts broadband impedance spectrum analysis combined with multi-band feature fusion technology to more accurately obtain the instantaneous value of the chip junction temperature. At the same time, the combination of the PID controller and the fuzzy rule base inference engine can quickly respond to rapid temperature changes, greatly improving the response capability.

The invention discloses a multi-field coupling underactuated quartz lamp electric heating system temperature mapping control method, system, equipment and medium, and the method comprises the steps: obtaining a quartz lamp and a test piece, building a nonlinear thermodynamic model of a multi-field coupling underactuated quartz lamp electric heating system, carrying out the online estimation of the state and total disturbance of the quartz lamp electric heating system, and calculating the temperature mapping of the quartz lamp electric heating system. Introducing a barrier function method, mapping each temperature variable to an unconstrained space, obtaining a test piece temperature mapping variable, taking the test piece temperature mapping variable as a control object to design a first control law, generating a control demand of a test piece temperature change rate, and mapping the control demand of the test piece temperature change rate into a quartz lamp temperature change rate instruction; and a second control law is designed and a quartz lamp input power control quantity is calculated by combining a quartz lamp layer thermodynamic model and a disturbance estimation result, so that the temperature of the test piece is converged to a target position in a preset safety interval within a fixed time, and the method has rapidness, robustness and safety.

The invention relates to the technical field of electrical equipment diagnosis, and discloses a temperature measurement diagnosis method and system based on a box-type substation, and the method comprises the following steps: S1, obtaining the partial discharge data, current data and temperature data of the box-type substation; s2, establishing a partial discharge and temperature correlation model according to the partial discharge data and the temperature data; establishing a current and temperature mapping relation according to the current heat effect of the current data; and S3, establishing a processing model according to the partial discharge and temperature correlation model, the current and temperature mapping relation and the temperature data, inputting the partial discharge data, the current data and the temperature data into the processing model, and outputting a diagnosis result and a linkage control signal by the processing model. The problem of low accuracy of temperature measurement diagnosis in the prior art is solved.

The invention discloses a thermal infrared imager based on multi-level thermal image analysis and an intelligent fault diagnosis method, and relates to the technical field of thermal infrared imagers, and the thermal infrared imager comprises a multi-level temperature data acquisition module, an intelligent temperature data processing module and an intelligent fault diagnosis and early warning module. According to the invention, the surface layer, deep layer and transient temperature data of the monitored object are collected at the same time, so that more comprehensive and accurate temperature information can be obtained, and the monitoring accuracy is improved. The intelligent temperature data processing module effectively fuses the temperature data of different levels, generates a more accurate comprehensive temperature map, and provides a reliable data basis for subsequent analysis. The intelligent fault diagnosis and early warning module automatically identifies and matches fault features by establishing a fault mode model, thereby reducing the dependence on artificial experience and improving the efficiency and accuracy of fault diagnosis. The temperature change can be monitored in real time, potential faults can be early warned, a more effective maintenance plan can be formulated by accurately diagnosing the faults, and unnecessary downtime and maintenance cost are reduced.

This invention discloses a method for detecting the uniformity of heat treatment in a pump body based on infrared imaging, comprising the following steps: Step 1: Obtaining a three-dimensional structural model of the pump body and calibrating the detection points; Step 2: Applying thermal perturbation to each detection area; Step 3: Acquiring dynamic multi-channel temperature images to obtain a temperature-time series; Step 4: Constructing a non-Fourier thermoelastic inertial response model for each detection point and extracting thermal response feature parameters; Step 5: Constructing a thermal response memory map; Step 6: Inputting the thermal response memory map into an improved TimeSFormer model, which incorporates a thermal potential field tensor guidance mechanism, and combining the spatial location information of the detection points with the structural topology encoding vector to obtain a heat treatment uniformity score; Step 7: Identifying concentrated areas of heat treatment deviation and outputting a detection report. This invention combines infrared imaging with an improved TimeSFormer model to realize an intelligent detection and evaluation method for the uniformity of heat treatment in a pump body.

Systems and methods for estimating battery surface temperatures comprise generating a core temperature estimate for the battery based on a battery model. A set of lumped temperature states may be generated based on the core temperature, the set of lumped temperature states comprising temperature estimates for different regions of the battery. Additional condensed information may be retrieved relating to the battery. A surface temperature map may be generated for the battery based on the set of lumped temperature states and the additional condensed information using a mapping function.

The invention relates to the technical field of paper-plastic molding equipment temperature control, and discloses an AI-driven paper-plastic mold self-adaptive temperature control device which comprises a mold body, a multi-dimensional sensing module, an AI calculation main control module, a power driving module, a self-adaptive temperature control execution module and a state feedback module. Each independent temperature control area has a clear area, and the AI calculation master control module comprises an improved GRU neural network pre-judgment module, a dynamic PID parameter self-tuning module and a product type-thickness-temperature mapping database. A laser thickness sensor and a mold wear monitoring unit of the multi-dimensional sensing module respectively establish one-way data transmission with the mapping database and the GRU module, and each module establishes two-way communication connection; the device solves the problems of poor pertinence and response lag of the existing integral temperature control, realizes self-adaption and precision of mold temperature control, and adapts to the production requirements of paper-plastic molding.

The invention relates to a data processing device or control unit (123) for operating a forklift truck (120a) for transporting a plurality of goods (140) in a warehouse. The data processing device (123) comprises an interface (123b) configured to receive a plurality of sensor data from the forklift truck (120a) during its movement in the warehouse, wherein the plurality of sensor data includes a plurality of thermal imaging data of the forklift truck's (120a) surroundings. Furthermore, the data processing device (123) comprises a processor (123a) configured to create or update a temperature map of the warehouse based on the plurality of thermal imaging data, wherein the temperature map indicates a respective temperature value for a plurality of points in the warehouse. The data processing device or control unit (123)The control unit (123) can be part of the industrial truck (120a) or a stand-alone server.

The present invention discloses a method for quickly detecting the fault risk of a solar heat collection field, which includes the following steps; Step 1: By setting an infrared thermal imaging camera for real-time monitoring, an overall temperature distribution thermal map of the solar heat collection field is obtained through shooting; Step 2: Establish communication between the infrared thermal imaging camera and the computer to collect temperature images of the temperature state of the heat collection field; Step 3: Preprocess and regionally divide the overall temperature distribution thermal map of the heat collection field, and perform feature extraction to obtain a scatter plot of the fault temperature field of the collectors in each region; Step 4: Import the extracted feature information of the temperature field distribution and related characteristic parameters in each region into the feature library of the solar collector fault model, and perform two matching analyses of the feature library of the fault model in sequence, so as to improve the fault detection efficiency of the heat collection field, reduce the false alarm rate and the missed alarm rate, and ensure the safe operation of the solar heat collection system. The present invention has the characteristics of simple operation and no need to upgrade the system and add new sensors.