162results about How to "Effective correction" patented technology

The embodiment of the invention provides an X-band dual-polarization radar attenuation correction method based on artificial intelligence. The method is applied to the field of X-band dual-polarization radar attenuation correction. The method comprises the steps of performing space-time matching on existing observation data of an X-band dual-polarization radar and existing observation data of an S / C-band radar in each region to generate a space-time matching data set of each region; according to the space-time matching data set of each region, training an attenuation correction model of the corresponding region, and generating an attenuation correction model of each region; and performing quality control on the observation data of the X-band dual-polarization radar to be subjected to attenuation correction, and inputting the observation data into the attenuation correction model of the corresponding region to obtain the horizontal reflectivity and the differential reflectivity of the X-band dual-polarization radar after attenuation correction. Therefore, the signal attenuation of the horizontal reflectivity and the differential reflectivity of the X-band dual-polarization radar can be effectively corrected, the deviation between the X-band dual-polarization radar and the observation value of the adjacent S-band radar can be reduced, the hardware resource overhead can be reduced, and the method can be efficiently applied nationwide.

The invention relates to the technical field of data processing, and discloses a data fusion method and system based on multi-source satellite altimeter data. The method comprises the following steps: performing multi-satellite intersection analysis and orbit error data correction on preprocessed multi-source satellite altimeter data to obtain satellite orbit error correction data; carrying out height subtraction processing on the earth water surface height and the average sea surface height on the sea surface height measured by the correction satellite, obtaining along-orbit sea surface height data, carrying out abnormal height data screening, obtaining coastal height abnormal data, carrying out space-time interpolation processing on the coastal height abnormal data, and obtaining a coastal height data set; the method comprises the steps of obtaining interpolation coastal height abnormal data, performing multi-source fusion to obtain gridded sea surface height abnormal fusion data, and performing abnormal reason analysis on the gridded sea surface height abnormal fusion data to obtain a predicted abnormal reason. According to the invention, the accuracy of data fusion based on the multi-source satellite altimeter data is improved.

The invention belongs to the technical field of transformer manufacturing, and discloses a shearing and stacking integrated lamination method for a large transformer iron core, which comprises the following steps: sequentially shearing and punching a roll material into silicon steel sheets according to the structure and specification of each layer of the iron core, sequentially conveying the silicon steel sheets formed by shearing and punching to a lamination station, and stacking the silicon steel sheets through translation, rotation and positioning operation in sequence. The invention further discloses a large transformer iron core shearing and stacking integrated lamination device which comprises a fixed door frame, at least two conveying assemblies located on the same straight line, a first lamination assembly, a rotation assembly, a second lamination assembly, a material stacking platform, a positioning assembly and a material pressing assembly. The stacking operation steps are simplified, manual operation links are reduced, the production efficiency and quality are improved, positioning of the positioning holes of the silicon steel sheets of different sheet types can be achieved, and the flexibility is good.

The invention provides a data defect detection and correction method for an electric power scene, and the method comprises the steps: collecting the data of a sensor, extracting spatial-temporal features, constructing a global high-dimensional feature representation, and carrying out the dimension reduction, thereby obtaining a feature vector after the dimension reduction; time sequence anomaly detection and space anomaly detection are carried out on the feature vectors after dimension reduction, detection results are synthesized, and a comprehensive anomaly score is calculated; classifying the abnormal data according to the comprehensive abnormal score, and constructing a self-adaptive correction model to preliminarily correct all the abnormal data and iteratively optimize the model; monitoring the corrected data in real time, calculating an anomaly detection error, updating parameters of anomaly detection and correction models, and applying the parameters to the models; the optimal learning rate is dynamically determined to accelerate the convergence of the model, the abnormal detection and correction model parameters are migrated and updated, the model is dynamically updated, and the performance index of the system is monitored in real time, so that the operation safety and stability of the power system are improved.

The invention relates to the technical field of heat preservation plate pressing, and discloses outer wall heat preservation plate processing production pressing equipment and a using method thereof.The outer wall heat preservation plate processing production pressing equipment comprises a workbench, a motor is fixedly connected to the bottom of the workbench, a threaded rod is fixedly connected to the output end of the motor, and a limiting elastic rod is fixedly connected to the bottom of the workbench. By arranging the correcting mechanism, firstly, the heat preservation plate needing to be pressed is placed on the inner wall of a pressing groove, then a motor is started to drive a threaded rod to rotate, when the threaded rod rotates, a threaded ring moves upwards, and when the threaded ring moves, a limiting elastic rod is pushed to contract upwards; and when the limiting elastic rod retracts to a certain position, the threaded ring is limited, the threaded ring is prevented from making contact with the bottom of the workbench, the threaded ring ascends and drives the ascending frame to move upwards at the same time, the ascending frame pushes the ascending rod to move upwards when moving, and the ascending rod drives the pulling rod to move upwards when moving.

The invention discloses an oil and gas reservoir shale content logging curve intelligent prediction method, and belongs to the technical field of rock physics and logging curve processing and interpretation, and the method comprises the steps: in step 101, determining Gardner formula parameters through combining a determination coefficient and a grid optimization method, and determining a Gardner formula parameter; and then generating a virtual density data set capable of covering the actually measured density data set by using a Gardner formula. According to the method, the optimal parameters of the Gardner rock physical formula and the Larionov rock physical formula are determined by using the decision coefficient and the grid optimization method, so that the abnormal value of the actually measured logging data can be effectively corrected, and a fusion data set for training various machine learning models can be generated; a cross validation method, a correlation coefficient, a determination coefficient and a multi-dimensional SHAP method are comprehensively utilized to more comprehensively evaluate and explain a prediction result, compared with a traditional rock physics method, the shale content prediction precision is improved by 12%, a logging curve data set can be effectively corrected and expanded, and the prediction accuracy of the shale content is improved by 12%. And the accuracy and the reliability of predicting the shale content of the oil and gas reservoir can be obviously improved.

The invention discloses a multi-channel illumination adaptive network model with a Laplacian enhanced pyramid and a low-light image enhancement method, and belongs to the technical field of low-light image enhancement processing. Frequency information optimization and brightness adaptation are crucial to low-light image enhancement and exposure correction. According to the network provided by the invention, two modules work cooperatively. The method comprises the following steps: firstly, designing a Laplacian enhanced pyramid (LEP), decomposing an image into components with different frequencies, and optimizing the components to perform preliminary enhancement; and then, a multi-channel illumination adaptive Transform (MIAT) is designed, and the color of the image and a multi-channel gamma correction parameter are inquired, so that further fine adjustment is carried out, and an enhanced image is generated. The MIANet is only about 0.17 M in parameter, the average enhancement processing time is only 0.007 seconds when an image with the resolution of 600 * 400 is processed, and the method is superior to the latest advanced method in LLIE and exposure correction benchmark tests.

The invention discloses a confocal microscopic image distortion correction method based on a two-axis MEMS (Micro Electro Mechanical System) scanning galvanometer. The method comprises the following steps: acquiring an original image by using a confocal microscope of a two-axis MEMS scanning galvanometer; calculating to obtain a galvanometer normal vector; calculating to obtain an incident light unit vector; calculating to obtain a reflected light unit vector; according to the method, distortion introduced by the MEMS galvanometer can be removed, distortion introduced by the MEMS galvanometer can be corrected under the condition that the posture of the scanned end face is unknown, and then a distortionless confocal image is obtained.

The present invention relates to the technical field of gear grinding machines, and discloses a CNC forming gear grinding machine, including a machine base, a fixed frame arranged on the machine base, a control box arranged on the front side of the machine base, and a three-axis control unit arranged on the fixed frame, and also includes a bearing assembly and a gear grinding assembly arranged on the three-axis control unit, a protective frame arranged on the gear grinding assembly, and a protective mechanism arranged on the protective frame. This CNC forming gear grinding machine can quickly and effectively absorb and disperse vibration energy when the grinding wheel first shows signs of shaking through an anti-shake assembly, thereby achieving a preliminary shock absorption effect, thereby reducing fatigue vibration of the grinding wheel when working for a long time, and further absorbs and consumes vibration energy through a damping assembly, thereby achieving deep suppression of grinding wheel shaking, and significantly improves the stability during the grinding process through the dual shock absorption mechanism of the anti-shake assembly and the damping assembly, thereby ensuring the accuracy of gear processing and reducing processing errors caused by shaking.

The invention provides a modeling method for hyperspectral medical component analysis based on a graph convolutional neural network, relates to the technical field of medical component analysis, and realizes effective correction of nonlinear light intensity and temperature and humidity change influence in spectral data through integrated application of illumination and environment correction technologies. By adopting the organic combination of the multiple regression model and the graph convolutional neural network, the robustness and stability of spectral data are ensured, and the accuracy and efficiency of analysis are greatly improved. Therefore, not only is the dependence of experimental conditions on results reduced, but also the application range of the technology is expanded, so that the detection of medicine components is also reliable under variable environmental conditions, and a solid foundation is provided for subsequent component prediction. Through the scheme, a user can obtain a high-consistency detection result in an unfixed external environment, the detection process is simplified, and the overall detection capability is improved.

The invention discloses a bullfrog biological behavior recognition optimization system based on deep learning, and relates to the technical field of biological recognition. Performing frame decomposition processing on the image data of the bullfrogs to obtain image data frames, extracting first-class feature information and second-class feature information in the image data frames, training an image recognition model to construct moving tracks of different bullfrogs, obtaining theoretical active coefficients and correlation coefficients of the bullfrogs according to the moving tracks, and obtaining the theoretical active coefficients and the correlation coefficients of the bullfrogs according to the theoretical active coefficients and the correlation coefficients; optimizing the theoretical activity coefficient to obtain an actual activity coefficient, inputting the actual activity coefficient into a preset behavior prediction model, obtaining a predicted movement track of the bullfrog, and obtaining predicted bullfrog density of different activity areas according to the predicted movement track; the bullfrog activeness monitoring accuracy can be improved, and the bullfrog density prediction accuracy can be improved.

The invention discloses a multi-source data-based mining equipment positioning system and method. The system is characterized in that a plurality of ultra-wideband base stations are sequentially mounted in a crossheading roadway at intervals; the coding identifiers are mounted on supporting columns of the hydraulic supports in a one-to-one correspondence manner, and are positioned on one side close to the coal mining machine; the inertial sensing unit, the camera, the ultra wide band positioning module and the controller are all mounted on the body of the coal mining machine; the visual angle of the camera faces a supporting column of the hydraulic support. The ultra-wideband positioning module is positioned on one side, close to a crossheading roadway, of a coal mining machine body and is connected with the ultra-wideband base station; the controller is respectively connected with the inertial sensing unit, the camera and the ultra-wideband base station. The method comprises the following steps: carrying out initial position calibration by using the ultra-wideband positioning module; predicting the position of the coal mining machine based on inertial navigation; updating the prediction state of the inertial sensing unit based on the identification of the coding standard by the camera; and the positioning continuity is ensured by fusing the data of the inertial sensing unit and the camera. According to the system and the method, real-time and accurate positioning operation of the coal mining machine in the working process can be realized.

The invention relates to the technical field of optical instruments, and discloses a visible-ultraviolet dual-wavelength projection objective lens and an optical system. Comprising a first lens group with positive focal power, a second lens group with negative focal power, a third lens group with positive focal power and a fourth lens group with positive focal power which are sequentially arranged along the optical axis direction from the object plane to the image plane of the projection objective lens; the projection objective lens further comprises an aperture diaphragm, and the aperture diaphragm is located between two adjacent lenses in the third lens group. Through arrangement of the four lens groups and reasonable matching of positive and negative focal powers, effective correction of chromatic aberration is realized, the imaging quality of the optical system is excellent, and the optical system can be adapted to a high-power large-linewidth deep ultraviolet band light source.

The invention relates to the technical field of communication network session offloading, in particular to a session offloading method and system based on mean shift clustering, and the method comprises the steps: firstly determining the radius of a sliding window of each cluster of a message group through employing an elbow rule; enabling the selected clustering center to continuously drift to a new clustering center until the number of groups in the radius range of the sliding window is not increased any more, and obtaining a candidate clustering center; then calculating the Hamming distance between the candidate clustering center and the clustering center in the existing clustering center set, if the Hamming distance is greater than a set threshold value, adding the candidate clustering center into the existing clustering center set, otherwise, merging the candidate clustering center into the nearest existing clustering center; repeatedly executing the previous steps to obtain a clustering center set; and finally, calculating the Hamming distance between each receiving group and the clustering center in the clustering center set, and completing the estimation of the quintuple according to the minimum Hamming distance criterion to realize the separation of session streams. According to the invention, all data packets can be fully utilized, and the shunting performance is greatly improved.

The invention provides a large-aperture medium-format wide-angle automatic focusing lens and an image pickup device. The lens sequentially comprises a first lens group with positive focal power, a second lens group with negative focal power, a third lens group with negative focal power, an aperture diaphragm, a fourth lens group with positive focal power and a fifth lens group with negative focal power from an object side to an image side, in the focusing process, the second lens group moves from the object side to the image side along the optical axis, and the fourth lens group moves from the image side to the object side along the optical axis. The lens satisfies the following conditional expressions: 0.5 < F1 / F < 2.5; f2 / F is greater than-3.5 and less than-2; 0.5 < F4 / F < 1.5; f / H is greater than 1 and less than 2.5. According to the scheme, better imaging quality can be realized under a larger aperture, so that the medium-format lens can adapt to large-aperture photography and video recording.

The invention relates to the technical field of gas sensors, and particularly discloses a sensor drift correction method and system based on transfer learning, and the method comprises the steps: firstly collecting sensor response data of a healthy individual and a lung cancer patient in two different periods, and taking the early-stage data with a label as a source domain data set; the method comprises the following steps of: taking post data without labels as a target domain data set, then preprocessing the data to extract features to obtain a source domain data feature set and a target domain data feature set, and finally performing domain self-adaption on the target domain data feature set based on transfer learning to perform drift correction. According to the method, drift correction is carried out by minimizing the distance between edge distribution and conditional distribution and forcibly maximizing cross-domain category information, and a small number of representative features are extracted to carry out high characterization on original data. Experimental results show that drifting of the sensor can be effectively corrected, and high classification accuracy is obtained on intelligent detection based on the gas sensor, such as lung cancer intelligent detection.

The invention provides an image processing method for correcting metal artifacts in radiotherapy positioning CT (Computed Tomography). According to the method, an attention mechanism module is utilized to enhance the generation capability of a model in a sinogram missing region and improve the correction range of the model in an image domain; in order to protect the relation between the upper layer and the lower layer of the image, the upper layer and the lower layer of the image are additionally added in input, the relevance between adjacent images is enhanced, and the feeling range of the model is widened. Wherein in the sinogram domain, the invention provides a sinogram repairing network, the image area of the metal artifact is accurately learned into the model through an attention mechanism, and the intact sinogram is used for repairing the sinogram influenced by the metal artifact. Meanwhile, in an image domain, 2.5 D image input and an attention mechanism are utilized, information of an upper layer and information of a lower layer are connected in series, and image restoration is completed globally. In addition, an additional discriminator is introduced to form multiple tasks to judge whether the output image meets the requirement or not, so that a better correction result is obtained.

The invention discloses a power pin product electroplated layer appearance defect detection method and device and a related product. The method comprises the steps that a to-be-detected image of an electroplated layer of a to-be-detected power pin is collected in the mode that multispectral imaging equipment and a line scanning technology are combined; preprocessing the to-be-detected image of the electroplated layer by using a deep learning driven denoising algorithm and a physical model-based illumination correction algorithm; a deep convolutional neural network model is used to automatically extract multi-level features in the image; extracting physical characteristics related to the physical characteristics of the electroplated layer in combination with a characteristic engineering method; the multi-level features and the physical features are fused; compressing and screening the fused features by using a feature dimension reduction technology to obtain a fused feature vector; and finally, detecting appearance defects of the electroplated layer by utilizing a defect detection model. According to the invention, high-accuracy, high-precision and high-efficiency detection of the appearance defects of the electroplated layer of the power pin product can be realized.

The invention discloses a correction method especially used for correcting a retroreflection brightness coefficient, and the method comprises the steps: obtaining a to-be-corrected original retroreflection brightness coefficient determined according to marking detection data, at least one part of the marking detection data is obtained under the condition of projection light, and the projection light has a calibrated projection distance; acquiring an actual projection distance of the projection light projected to a detected position when the marking line detection data is acquired; determining a distance correction coefficient according to the calibrated projection distance and the actual projection distance; and correcting the original retroreflection brightness coefficient to be corrected according to the distance correction coefficient so as to obtain the retroreflection brightness coefficient subjected to distance correction. The invention further discloses another correction method based on ambient light correction. In addition, the invention also discloses a related correction device, electronic equipment and a program product.

The invention discloses an error correction method and system for a paper equipment operation record recognition result, and the method comprises the steps: firstly scanning a paper equipment operation record, carrying out the character recognition of the scanned record through an OCR technology, and evaluating the confidence; performing hierarchical error detection on an identification result: identifying characters with low confidence and characters which do not conform to a column mode, and identifying and marking abnormal characters in all columns by adopting an abnormal value detection method; and finally, selecting characters which are most similar to the wrong characters and conform to the column mode from the candidate character set for correction, and generating an accurate equipment operation record table. According to the method disclosed by the invention, errors in the identification result are positioned and corrected by combining the content and the organization mode of the equipment operation record data aiming at a paper equipment operation record document digital scene, so that the correction workload in the equipment operation record sheet digital process is reduced.

The present invention discloses a representation learning method for mixed distortion of video images in complex environments. Data sets with the same and different types of mixed distortion are established from videos. A method for learning distortion representation by contrastive learning is adopted, thereby realizing automatic modeling of mixed distortion directly from distorted video images. On this basis, an automatic restoration method for mixed distortion of video images in complex environments is constructed to realize automatic restoration of mixed distortion.

The invention discloses a channel time-frequency joint extrapolation method based on a multi-layer perceptron hybrid architecture. Aiming at the problems of high acquisition cost of actual communication scene channel data, high time consumption of model online training and difficulty in covering the actual communication scene by simulation data, the method comprises the following steps of: making a pre-training model by using a large-scale simulation channel data set to extract channel change characteristics; and carrying out online rapid adaptation according to the trace data of the actual measurement scene. Aiming at the characteristics that the time delay spread of an indoor wireless channel is relatively small and the number of antennas is relatively small, a multi-layer perceptron hybrid architecture is applied to the time-frequency domain extrapolation of a single-carrier broadband channel. The model can quickly adapt to an actual communication scene through fine tuning of a small amount of data. The method has the advantages of being high in adaptation speed, small in data dependence, high in scene migration capacity, high in calculation parallelism degree and the like, and is suitable for edge deployment and rapid adaptation to actual scenes.

The invention discloses a blood oxygen signal denoising method and system based on adaptive filtering, and the method comprises the steps: synchronously collecting an original blood oxygen signal and a three-axis acceleration signal through a sensor module, and obtaining an original blood oxygen signal sequence and a three-axis acceleration signal sequence which are aligned in time; the three-axis acceleration signals are fused into one-dimensional motion artifact reference noise signals used for representing the limb motion state of the user; the method comprises the following steps: dynamically calculating an adaptive step length factor sequence through a nonlinear mapping function based on multilevel energy analysis of a motion artifact reference noise signal; constructing a time-varying step size adaptive filter, and calculating noise components in the original blood oxygen signal by using the motion artifact reference noise signal and an adaptive step size factor; and subtracting the calculation noise signal from the original blood oxygen signal, and reconstructing to obtain a pure blood oxygen signal without motion artifacts. According to the method, accurate calculation and efficient suppression of motion artifacts can be achieved, and the purification quality and processing efficiency of blood oxygen signals are remarkably improved.

The utility model relates to textile equipment technical field especially, more camera coordination's fabric weft yarn deformation correction equipment. Its technical scheme includes support foot, the top fixedly connected with crosspiece of multiple support foot, the outer wall of two crosspieces is provided with correction mechanism, the correction mechanism includes the multiple fixed knot of fixed in the crosspiece outer wall, the top fixedly connected with top support column of multiple fixed knot, multiple top support column is provided with transmission, the inner wall of crosspiece is provided with heating conduction mechanism, the transmission includes the outer wall one side fixedly connected with drive motor of multiple top support column fixed in the both sides. The utility model discloses more camera coordination's fabric weft yarn deformation correction equipment, it can realize the efficient correction to different types and degree weft yarn deformation to the advantage that avoids the performance decline caused by the uneven heating of fabric.

The invention belongs to the field of oil and gas exploration and development, and relates to an oil drilling and workover well mouth centering and aligning device and method.The device comprises an upper flange and a lower flange, the upper flange is connected with a rotary control head, the lower flange is connected with an annular blowout preventer, a sealing device is arranged between the upper flange and the lower flange, and the upper flange and the lower flange are each sleeved with a pressing plate; the pressing plate on the upper flange and the pressing plate on the lower flange are detachably connected through a fastening device, and adjusting bolts used for adjusting the upper flange to move in the horizontal direction are arranged on the pressing plate on the upper flange and the pressing plate on the lower flange. A flange position adjusting device is designed, horizontal multi-direction free adjustment can be simply and rapidly achieved, a wellhead can be rapidly, safely and effectively corrected, and vertical centering alignment of the center of wellhead devices such as a rotary control head of the device and a crown block and a traveling block is achieved.

The utility model relates to the technical field of sheet metal part correction, and discloses a sheet metal part correction device which comprises a base, a mounting plate is fixedly arranged on one side of the top of the base, an air cylinder is fixedly arranged on the top of the mounting plate, and a correction plate is fixedly arranged at the tail end of a piston rod of the air cylinder. A mounting plate is arranged on the top of the base, a supporting rod is vertically arranged on the top of the base and located on one side of the mounting plate, a transverse moving mechanism is arranged between the lower end of the supporting rod and the base, a U-shaped supporting plate is fixedly arranged at the upper end of the supporting rod, a metal plate is placed in the U-shaped supporting plate, and a metal plate clamping mechanism is arranged in the U-shaped supporting plate. The structure for correcting one end of the sheet metal part is adopted, the two ends of the sheet metal part do not need to be fixed, space is provided for length change of the sheet metal part in the correcting process, and therefore the sheet metal part cannot be damaged.

The application provides a scene understanding-oriented open-vocabulary three-dimensional scene graph generation system and method, and a computer storage medium, and relates to the technical field of three-dimensional scene graph generation.The method comprises the following steps: acquiring an RGB image;reconstructing a three-dimensional Gaussian representation scene based on multi-view RGB images with camera poses;constructing a plurality of view selectors based on the three-dimensional Gaussian representation scene;acquiring a SAM mask based on a SAM model and the RGB image, and performing clustering;independently constructing a local K-neighbor graph for each cluster based on the clustering result and the three-dimensional Gaussian representation scene;performing smoothing processing on the K-neighbor graph;performing Gaussian codebook encoding based on the image subjected to the smoothing processing to obtain a root cluster node and a leaf cluster node;and generating a three-dimensional scene graph based on the root cluster node and the leaf cluster node.The application can alleviate the boundary feature pollution caused by alpha blending in the three-dimensional Gaussian representation, and retain semantic distribution information under different views.

The invention discloses a toughened PPR pipe production equipment and a production method, comprising a machine body, a transmission platform is arranged on one side of the machine body, a laser cutter is arranged on one side of the machine body, a correction device is arranged on the surface of the transmission platform, the correction device comprises a slider, the slider is slidably connected to the transmission platform, a first cylinder is fixedly connected to one side of the transmission platform, a telescopic rod is fixedly connected to one side of the first cylinder, a side of the telescopic rod away from the first cylinder is fixedly connected to the slider, a hole one is opened on the surface of the slider, a connecting rod is slidably connected to the inner wall of the hole one on the surface of the slider, there are two connecting rods, the two connecting rods are arranged in a mirror symmetric manner, a ferrule is fixedly connected to the side of the connecting rod away from the slider, a first motor is fixedly connected to one side of the slider, and the position of the pipe is effectively corrected by arranging the correction device, the stability of the equipment is increased, the difficulty of operating the equipment is reduced, the safety of the equipment is improved, and it is convenient for users to cut.

The invention relates to the field of spine correction, in particular to a multi-body-position continuous correction device based on scoliosis treatment, which comprises a seat, a backrest capable of turning backwards is hinged to the rear side of the seat, a liftable control panel is arranged in the middle of the backrest, a protective module is detachably arranged on the control panel, and the protective module is connected with the seat. The front portion of the protection module can be attached to the spine position of a patient, and a limiting module for fixing the spine of the patient is arranged on the front portion of the control panel. According to the multi-body-position continuous correction equipment based on scoliosis treatment, a patient can conveniently go out to move in the rehabilitation stage after correction, the sitting posture and the lying posture can be switched, the situation that the patient is switched back and forth on a bed and a wheelchair, and consequently muscles around the spine are pulled and painful is avoided, and when the posture of the patient is switched, the posture of the patient can be adjusted, so that the posture of the patient can be adjusted. The fixing device can be used for fixing and protecting the muscles of the patient conveniently, so that pulling of the muscles is reduced, comfort of the patient is guaranteed, and normal activity of the patient is guaranteed.

The present application relates to a kind of unmanned aerial vehicle image radiation consistency correction method under varying illumination conditions, comprising: obtaining the orthographic image of target farmland area;Orthographic image of target farmland area is positioned and corrected in space, and the spatial position of each farmland plot or test plot in orthographic image in target farmland area is obtained;According to the spatial position of each farmland plot or test plot in orthographic image, orthographic image is cut, and the radiation information affected by illumination change in cut image is corrected in radiation consistency;Based on the image data after radiation consistency correction, crop growth monitoring, farmland condition evaluation, variety comparison analysis or yield prediction are carried out.The present application can be widely applied to the field of remote sensing image processing and spectral correction.