782results about How to "Reduce precision" patented technology

The invention provides a machine room energy consumption optimization method and system based on temperature monitoring, and relates to the technical field of energy consumption optimization, and the method comprises the steps: collecting the temperature data of a machine room in real time, continuously monitoring the temperature gradient of each region, carrying out the fusion processing, and constructing a three-dimensional dynamic temperature distribution model; a hot spot area, an airflow dead angle and a cooling capacity waste area are identified through a deep learning algorithm, a flowing track and a mixing process of cold and hot air in a machine room are predicted through a track regression neural network in combination with machine room layout and equipment distribution, and a machine room temperature control strategy set is generated through adaptive neural fuzzy reasoning, correction and updating of a prediction result; and by taking minimum energy consumption and maximum refrigeration efficiency as optimization objectives and taking a safe operation temperature range of equipment in the machine room as a constraint condition, a plurality of parameters are jointly adjusted through a temperature control optimization algorithm to obtain an optimal temperature control curve, and the optimal temperature control curve is converted into a refrigeration system control instruction, so that collaborative optimization of the temperature and the energy consumption of the machine room is realized.

The invention relates to the technical field of mine potential safety hazard identification, in particular to a mine potential safety hazard identification method and system based on an unmanned aerial vehicle. The method comprises the following steps: acquiring a global image of a mining area by using an unmanned aerial vehicle camera, and constructing a three-dimensional model; thirdly, performing rock-soil landslide probability estimation through weathering erosion mechanism reduction in combination with the three-dimensional model and the global image, and calculating landslide coercing force potential energy increment; then, according to the landslide probability and the coercing force incremental data, carrying out risk grade endowing on the local area of the mining area; and finally, constructing a mine potential safety hazard identification optimization model based on the risk level, and sending the model to a terminal for potential hazard identification. According to the invention, the mine potential safety hazard identification technology is optimized, so that the mine potential safety hazard identification technology is more perfect.

The invention relates to the technical field of ecological data processing, in particular to a plant growth evaluation method based on ecological data analysis, and the method comprises the steps: collecting data; determining a temporary grid; soil type identification; identifying an abnormal grid; adjusting a grid; and evaluating the plant growth degree. According to the method, the accuracy of plant growth monitoring is improved through dynamic monitoring and intelligent adjustment, bad growth conditions and abnormal plants can be recognized in time, then targeted intervention measures are provided, the vulnerability of an ecological system is reduced, and meanwhile, the high efficiency and accuracy of data acquisition are ensured through dynamic adjustment of grid spacing and optimization of a monitoring strategy. The method also provides a scientific basis for soil quality and plant health, is helpful for realizing ecological balance, promoting reasonable utilization of resources, improving the stability of an ecological system, and effectively solves the problems of insufficient evaluation comprehensiveness and reduced data acquisition timeliness caused by dependence on a fixed trigger strategy and single data source.

The invention discloses a receipt identification method and device, equipment and a medium, and relates to the technical field of bill content identification. The method comprises the following steps: acquiring a receipt image through a preset acquisition mode, and identifying the receipt image by using a preset optical character identification model to determine text content and corresponding position information in the receipt image; performing information matching on the receipt image in a preset multi-mode large model prompt word bank to obtain a first prompt word, and inputting the first prompt word, the text content and the position information into a preset multi-mode large model to obtain a key information key value pair; and performing information matching on the receipt image in a preset language large model prompt word library to obtain a second prompt word, and inputting the second prompt word, the text content, the position information and the key information key value pair into a preset language large model to obtain a target key information key value pair. Through the technical scheme of the invention, the accuracy of identifying the key field content of the non-standard receipt can be improved.

The invention relates to a migratory fly insect intelligent identification method based on trap lamp assisted radar database building. According to the method, insect monitoring data of the moth-killing lamp and the radar in the same night period are fused, the insect data set is established through matching of the two data, and the difficulty of a traditional insect data set database establishment mode in data acquisition is effectively overcome; secondly, a CL-GC-Swin Transform network model is provided, a contrast learning module and a global context block are introduced into the Swin Transform, and training is carried out by using the complete polarization time-frequency characteristic pattern of the insect, so that the characterization capability of the network on the time-frequency characteristic pattern of the insect is significantly enhanced, and the accuracy of insect type identification can be effectively improved. According to the method, the flight characteristics of the insects are directly utilized for identification, complex scattering characteristic calculation and accurate radar calibration are not depended on any more, the requirements for radar system precision and calibration are greatly reduced, and the adaptability and robustness of identification can be improved.

The invention relates to the technical field of fabric performance detection, and mainly describes a fabric performance detection device for shirt fabric. Comprising a base, the base is fixedly connected with a vertically-distributed electric push rod, the telescopic end of the vertically-distributed electric push rod is fixedly connected with a friction disc and a fixing frame, the friction disc and the fixing frame are both in sliding connection with the base, and the fixing frame is fixedly connected with a first elastic push rod; the telescopic end of the first elastic push rod is fixedly connected with a fixing table, the base is fixedly connected with a second elastic push rod, the fixing frame is fixedly connected with an adjusting cylinder, and the base is rotationally connected with a reciprocating lead screw. The reciprocating lead screw drives the telescopic end of the second elastic push rod to do linear reciprocating motion, and then the fitting degree of the friction disc and the fabric is periodically changed, so that friction of different degrees between the fabric and an external article in actual life is simulated, and the accuracy of a fabric pilling test is improved.

The invention relates to the technical field of brain power assessment, in particular to an operator brain power assessment and monitoring system based on manned-unmanned flight cooperative tasks, which comprises the following steps: acquiring brain wave signals, voice fluctuation and finger muscle activity data of an operator, and generating operator brain power load data; setting a personalized load reference value and a threshold range of an operator; based on multi-dimensional regression analysis and a self-adaptive deep learning model, a nonlinear relation model between task characteristics and brain load is constructed, the load state is dynamically evaluated, and a real-time load change prediction value is output; predicting a future high-load risk period according to the fluctuation mode of the mental load fluctuation curve; dynamically adjusting task parameters in a multi-task execution process; according to the invention, the dynamic reference setting of the mental load of the operator is realized, so that the individuation and accuracy of load evaluation are ensured, the influence of key task characteristics on the load can be quickly reduced when the load of the operator is increased, and an efficient and accurate load reduction effect is realized.

The invention relates to the technical field of information processing, in particular to an anomaly detection method and device based on low-rank embedding and multiple scales and electronic equipment. The method comprises the following steps: acquiring a hyperspectral image, and preprocessing the hyperspectral image to obtain an original hyperspectral image; performing feature extraction operation on the original hyperspectral image by using a preset low-rank background feature extraction model to obtain low-rank background features, and extracting global features and local features of the original hyperspectral image by using a pre-constructed multi-scale fusion feature extraction model; and carrying out integration processing on the low-rank background features, the global features and the local features, comparing the obtained target reconstruction background image with the hyperspectral image, and identifying an abnormal region. Therefore, hyperspectral image disaster monitoring is realized by adopting low-rank background feature extraction and multi-scale fusion feature extraction, the problems of long time consumption, low efficiency and low precision in the detection process of the existing detection method are solved, and the method has the advantages of automation, high precision, rapidness, high efficiency and the like.

The invention discloses a high-voltage cable terminal parallel connection lightning arrester total current online monitoring method and system, and relates to the technical field of power grid equipment, and the method comprises the steps: obtaining the cable coupling coefficient of each cable terminal to a current lightning arrester under the single-phase effect at a test stage, and obtaining the cable coupling coefficient of each cable terminal to the current lightning arrester; obtaining an inter-phase coupling coefficient between the current lightning arrester and the remaining lightning arresters under the single-phase action; in actual work, the leakage current detection module is adopted to obtain the leakage current induction value of the current lightning arrester on line; the power frequency calibration coefficient is adopted to calibrate the leakage current induction value, and a leakage current calibration value of the current lightning arrester is obtained; based on the leakage current calibration value, the cable coupling coefficient and the interphase coupling coefficient, obtaining a current leakage current actual value of the lightning arrester; in the scheme of the invention, coupling interference caused by spatial distribution is fully considered, correction is carried out based on the cable coupling coefficient and the interphase coupling coefficient to eliminate interference caused by spatial distribution parameters, and the current leakage amount of the lightning arrester can be accurately monitored.

The invention provides a low-energy-consumption three-dimensional point cloud single-target tracking method based on a spiking neural network, and the method comprises the steps: obtaining the three-dimensional point cloud data of a previous frame and a current frame of a target, designing a voxel grid module, and dividing the point cloud into 3D voxels; a feature extraction module is designed, a three-stage pulse convolution block is used as a feature extractor, voxelization point cloud features are extracted, a Transform encoder layer is added, and global context information of the point cloud is captured through a self-attention mechanism; a part-to-part motion modeling module is designed, continuous point cloud features on a time sequence are modeled and coded part by part through a two-dimensional pulse convolution block, and feature information changes of a previous frame and a current frame in corresponding space parts are obtained; and designing a regression prediction module, and inferring the relative motion of the target through a pulse regression prediction module. According to the method, energy consumption is reduced, efficiency is improved, and meanwhile it is guaranteed that the network accurately tracks the target in diversified scenes and motion states.

The invention relates to the technical field of solar cell preparation, and discloses a laser patterned polycrystalline silicon passivation cell, a preparation method and a photovoltaic module. The preparation method comprises the following steps: preparing a passivation contact structure and an oxidation film on the surface of a silicon substrate; laser patterning processing is carried out on the surface of the silicon substrate, the passivation contact structure and the non-metallization area of the oxidation film, so that the processed non-metallization area is not subjected to alkali etching resistance, and doping atoms are pushed into the silicon substrate through laser diffusion to form a doping area; performing alkali wash etching to form an alkali wash etching region etched into the silicon substrate, and leaving a doped region on the silicon substrate exposed in the alkali wash etching region; respectively depositing a passivation antireflection film and an antireflection film on the front surface and the back surface of the silicon substrate; and preparing the metal electrode. According to the preparation method, parasitic absorption loss can be avoided, the transverse transmission capability of internal carriers can be enhanced, the light utilization rate and the photoelectric conversion efficiency of the cell are further improved, the process window is larger, and the process steps are simple.

The invention discloses a fast neutron imaging detector and a detection system, and belongs to the technical field of ray detection, the fast neutron imaging detector comprises a wave-shifting optical fiber array, scintillators and a photoelectric conversion array, the wave-shifting optical fiber array comprises a plurality of crisscrossed wave-shifting optical fibers, and gaps among the wave-shifting optical fibers are filled with the scintillators; and each photoelectric detector in the photoelectric conversion array is correspondingly coupled with the wave-shifting optical fiber. The detection efficiency of fast neutrons is effectively improved by increasing the thickness of the sensitive area of the detector, meanwhile, the collection efficiency of photons generated in the sensitive area of the detector can be remarkably improved through the crisscrossed wave-shifting optical fiber array, and the position information of a detection event can be accurately obtained in combination with a gravity center positioning method. Compared with a traditional fast neutron imaging detector based on combination of a camera and a conversion screen, the imaging detector has the advantages of fast response, large sensitive area, high detection efficiency and the like.

The invention discloses a display screen appearance detection method, device and system and a storage medium, which are used for improving the detection precision of display screen appearance defects. The method comprises the following steps: controlling a light source to emit stripe light of different phases to a display screen to be detected through a time-sharing stroboscopic method, and scanning the display screen to be detected by using a line scanning camera and adopting a multi-frame acquisition mode to generate slice image data; performing dephasing processing on the slice image data to generate wrapped phase image data; performing phase unwrapping processing on the wrapped phase image data to generate absolute phase image data; performing image fusion processing on the absolute phase image data and the slice image data according to a to-be-detected defect type to generate a to-be-detected image set; performing defect detection on the to-be-detected image set to generate a plurality of slice data; and integrating the plurality of slice data to generate target defect data.

The invention discloses an intelligent component three-dimensional position acceptance method based on image and laser data fusion, and the method comprises the steps: (1) providing an oblique photography automatic correction model and employing a step-by-step detection method for solving a problem that the position of a component is difficult to accurately mark and locate by employing a single target detection network, the analysis process of the component image is divided into two independent steps of target detection and positioning. And (2) providing a point cloud segmentation and point cloud and image registration method based on environmental perception for the problem that the pose of the camera and the laser radar is difficult to calibrate in real time. By fusing the above method, the method can be successfully applied to quality detection and evaluation of the embedded plate of a certain nuclear power plant, efficient data acquisition and automatic processing are realized, and the result shows that the method can automatically analyze the three-dimensional position, the rotation angle and the missing of one wall member within 3 min, and visually displays the collision inspection result in combination with the BIM model.

The utility model discloses a coffee bean grinding structure, a grinding machine and a coffee machine. The coffee bean grinding structure comprises a shell, a grinding cavity is formed in the shell, a vertical driving shaft is arranged in the grinding cavity, and a driving device is arranged outside the grinding cavity and is in driving connection with the driving shaft. The bottom of the grinding cavity is provided with a discharge hole, and a powder sweeper and a tool bit which are in direct or indirect driving connection with the driving shaft; the metal grinding head assembly comprises the tool bit, a grinding disc arranged around the periphery of the tool bit and a positioning sleeve arranged around the periphery of the grinding disc, and a conductive terminal is arranged on the positioning sleeve; a shell forming the grinding cavity is made of plastic, and the positioning sleeve and the inner wall of the grinding cavity are installed, fixed and sealed through interference fit; the grinding disc adjusting assembly is made of plastic; the overall cost is reduced by arranging the positioning sleeve, meanwhile, the high precision of ground powder is guaranteed, and the effect of preventing static powder sticking and powder flying can be achieved.

The invention discloses a massage chair real-time control method and system based on electromyographic signals and a computer medium. The method comprises the steps that the electromyographic signals of a current massage user are obtained; extracting time domain features, frequency domain features and geometric features of the electromyographic signals; obtaining a real-time muscle state according to the time domain feature, the frequency domain feature and the geometric feature of the electromyographic signal; and controlling the massage strength and rhythm of the massage chair according to the real-time muscle state and the historical massage data of the current massage user. By analyzing the long-term muscle state and massage record of the user, an instant personalized massage scheme is generated for each user. Therefore, the actual requirements of the user can be better met, the system can provide more accurate and personalized services for the user, and the optimal user experience can be achieved.

The invention discloses a cultivated land parcel extraction method and system based on surface and line fusion and a medium, and the method comprises the steps: carrying out the region surface classification and land parcel extraction of initial land parcel data according to a preset SAM model, and obtaining land parcel-surface data; performing field ridge line extraction and boundary connection on the initial land parcel data according to a preset line model to obtain land parcel-line data; and performing surface-line fusion processing on the land parcel-surface data and the land parcel-line data to obtain a cultivated land parcel extraction result. According to the method, for the land parcels of different regions, the SAM model is used for extracting the region surfaces of the land parcels with different features, the line model is used for extracting the cultivated land boundary line, and then surface-line fusion is carried out to obtain the cultivated land parcel region with higher precision, so that accurate data support is provided for cultivated land protection.

The invention discloses a deep tunnel surrounding rock mechanical parameter inversion method based on a three-dimensional brittle failure zone contour and sparrow optimization algorithm-information vector machine (SSA-IVM) combined optimization algorithm. The engineering technical problem that due to the fact that excavation instantaneous displacement is difficult to monitor, deep tunnel surrounding rock mechanical parameters are difficult to reasonably obtain through displacement back analysis is solved. The method comprises the following steps: firstly, constructing a tunnel FLAC3D numerical simulation model with the same ground stress condition at the occurrence position of a three-dimensional brittle failure zone; secondly, taking an absolute error between the total number of computational grid units in the actually measured brittle failure zone and the total number of computational grid units entering a plastic state in the range of the actually measured brittle failure zone after calculation of the FLAC3D numerical model as an optimization objective function; and then, by taking the tunnel surrounding rock mechanical parameters as optimization variables and taking a target function reaching a global minimum value as a target, performing global optimization by combining a tunnel FLAC3D numerical model and adopting an SSA-IVM joint optimization algorithm, thereby obtaining reasonable tunnel surrounding rock mechanical parameters.

The invention discloses a motor stator short circuit ring automatic assembly device, and relates to the technical field of short circuit ring assembly.The motor stator short circuit ring automatic assembly device comprises a control machine table, a controller is installed on the upper surface of the control machine table, a supply conveying belt is installed on the front side face of the controller, and a feeding air cylinder is installed at the conveying end of the supply conveying belt; an assembling assembly is installed on the rear side of the feeding air cylinder, an interval distribution mechanism is arranged on the surface of the supply conveying belt, a damage prevention and centering mechanism is arranged in the assembling assembly, oil liquid is driven to be sprayed out through pressure, then it is ensured that lubricating oil is evenly distributed between a mold and a base by ingeniously using suction force generated by counter-acting force, and a thin oil film is formed; the high-efficiency boundary lubrication effect is achieved, firstly, through continuous and uniform oil film lubrication, direct contact friction between the die and the stator short circuit ring assembly part in the pressing process is effectively reduced, in addition, due to the existence of an oil film, the friction coefficient between contact surfaces is greatly reduced, and material deformation and displacement caused by friction are reduced.

The invention provides an image processing model quantification method, and relates to the technical field of data center server cluster cooperative control, and the method comprises the steps: 1, preparing an image processing model; 2, collecting parameters of the image processing model; 3, quantifying the image processing model; according to the method, the quantized neural network image processing model is subjected to forward propagation to obtain a first performance index, then the first performance index is taken as a target to determine an acceptable range of precision reduction, and then the neural network image processing model is quantized by using a symmetric quantization method, so that the accuracy of the neural network image processing model is improved. Therefore, by taking the precision of the neural network image processing model before quantization as a target, the size of the model is quantized and reduced, and the model is kept within an acceptable range of precision reduction, so that the neural network image processing model can be suitable for being used in an environment with limited hardware resources.

The invention provides a fuzzy uncertainty analysis method for dynamics optimization of a parallel mechanism containing a gap space, and belongs to the technical field of industrial robot modeling and optimization, and the method comprises the following steps: S1, building a spherical pair model containing a dry friction gap; and S2, according to constraint conditions of the spatial parallel mechanism containing the spherical pair dry friction gap, obtaining a dynamic model of the three-degree-of-freedom spatial parallel mechanism containing the spherical pair dry friction gap. S3, performing optimization according to the dynamic model of the spatial parallel mechanism; and S4, agenting the optimized data into the dynamic model of the mechanism, selecting fuzzy parameters, establishing a dynamic model of the spatial parallel mechanism containing the fuzzy parameters, and carrying out solution analysis. According to the method, the adverse effect of the dry friction gap on the dynamic characteristics of the mechanism can be improved, and the method is provided for predicting the influence of the fuzzy parameters of the mechanism on the dynamic characteristics of the mechanism.

The invention discloses a voiceprint-based 10 kV circuit breaker mechanical fault detection method. Comprising the following steps: S1, building a MobileNetYOLOv4 neural network model; s2, acquiring voiceprints through a high-sensitivity sensor; s3, performing convolution operation on a convolution kernel of edge side identification early warning; s4, circuit breaker fault identification; s5, carrying out improved S transformation on the signal; according to the invention, task allocation is dynamically calculated by a resource allocation module embedded in a cloud platform, a lightweight model is constructed, the model operation speed is accelerated, and a real-time target identification and classification system is constructed; the Moblienet neural network structure reduces the running memory of a neural network model and accelerates the running speed of the neural network model, and in order to improve the target recognition speed and solidify the model to an edge device, the MobileNet network structure applies a deep separable convolution technology, so that the target recognition efficiency is improved. The standard convolution of the convolutional neural network is divided into two steps of deep convolution and point-by-point convolution in the calculation process, so that the calculation amount of the network is greatly reduced.

The invention discloses a holder control method and device, a storage medium and electronic equipment. The method comprises the following steps: in response to a cradle head control start instruction, controlling a cradle head to execute a target action corresponding to the cradle head control start instruction, and obtaining a time delay and a frame rate corresponding to the cradle head, the cradle head control start instruction is sent by a target terminal, and the time delay represents a transmission time delay between the target terminal and the cradle head; the frame rate represents the frame rate used by the holder to transmit data; and determining the number of target frames based on the number of frames which are sent to the target terminal by the cradle head and are not determined to be received by the target terminal, the time delay and the frame rate, clearing non-key frame data corresponding to the number of the target frames in the first cache data, and controlling the cradle head to stop executing a target action in response to a cradle head control ending instruction. The technical problems that a holder and a video picture are not synchronous enough and the video picture is delayed in the prior art are solved.

The invention relates to a wind-resistant cable structure convenient to install on a pedestrian suspension bridge and a construction method of the wind-resistant cable structure. The method is suitable for the field of pedestrian suspension bridge design and construction. According to the technical scheme, the wind-resistant cable structure convenient to install on the pedestrian suspension bridge is characterized by being provided with a main beam, the main beam is hung on a main cable through slings, wind-resistant main cables arranged in the length direction of the main beam are arranged on the two sides of the main beam, the two ends of each wind-resistant main cable are anchored to the ground through wind-resistant anchors, and the wind-resistant main cables are connected with the main cable through the wind-resistant anchors. First connecting pieces are sequentially arranged on the wind-resistant main cable in the length direction of the wind-resistant main cable, second connecting pieces are sequentially arranged on the main beam in the length direction of the main beam, at least one inhaul cable structure is arranged between the main beam and the wind-resistant main cable in the length direction of the main beam, and each inhaul cable structure is provided with an inhaul cable. The inhaul cable shuttles between the first connecting piece on the wind-resistant main cable and the second connecting piece on the main beam.

The invention relates to the technical field of wastewater treatment, and discloses a multi-point fixed-depth putting wastewater pool detector, which comprises a detector protective cover, the detector protective cover is of a cylindrical frame body structure, a wastewater data detector is arranged in the detector protective cover, and the detection end of the wastewater data detector penetrates through the side wall surface of the detector protective cover. According to the multi-point fixed-depth putting wastewater pool detector, the wastewater data detector in the device is used for detecting multiple depth points of a wastewater pool and comprehensively reflecting the water quality condition, and the protection assembly is located at the bottom end of the wastewater data detector and pushes away floccules and solids in wastewater; according to the waste water data detector, the detection position of the waste water data detector is prevented from being influenced by the existence of solids, and the cable guide assembly is arranged, so that the situation that the waste water data detector excessively deviates from the detection point position in the descending process, data accuracy is influenced, adjacent waste water data detectors collide with each other, and the number of damaged waste water data detectors is increased is avoided.

The invention provides a non-contact distance measuring system and method. The non-contact distance measuring system comprises a first sensor, a second sensor and a converter, the converter comprises a sensor excitation unit, a sensor signal acquisition unit and a control unit; according to the environment temperature, the temperature compensation coefficient corresponding to the environment temperature is determined; compensating a voltage signal acquired by a sensor signal acquisition unit according to the temperature compensation coefficient; and obtaining the distance between the first sensor coil and the surface of the measured target object according to the compensated voltage signal. According to the invention, the environment temperature is measured through the second sensor, and the influence of the temperature on the measurement precision is reduced according to the voltage signal acquired by the temperature compensation sensor signal acquisition unit. According to the invention, the conversion of the eddy current signal can be realized, and the separation state of the detected target object is judged.

The invention provides a direct-drive type full-rotation device and system and a using method. The direct-drive type full-rotation device comprises a servo motor, a motor shaft, an aluminum alloy diaphragm coupling, an intermediate transmission shaft and a rotating shaft. The angle of the servo motor is accurately controlled in real time according to a set route and information fed back by a GPS and an attitude sensor, and stable heading control of the ship body is achieved; the servo motor transmits torque with the middle transmission shaft through the aluminum alloy diaphragm coupling, the motor rotates to directly drive the rotating shaft to rotate so as to change the direction of the tail end propeller, and the tail end propeller is directly driven to steer while overload of the motor is protected. Generation and transmission of large torque and high-precision angle control can be achieved, the heading angle of the ship body is accurately controlled according to feedback, and the device has the advantages of being simple in structure and convenient to maintain, integrally has the characteristic of small modular design and is convenient and fast to replace.

The invention relates to the field of spindle boxes, and discloses a shockproof high-precision spindle box structure which comprises a spindle box body. A buffering assembly is arranged at the bottom end of the main spindle box body, first buffering springs are evenly installed at the bottom end of the main spindle box body, spring seats are installed at the bottom ends of the first buffering springs, auxiliary assemblies are arranged at the top ends of the spring seats, and connecting round rods are fixedly installed between the spring seats. Sliding seats are slidably mounted on one sides of the spring seats, the sliding seats are connected through second buffer springs, and connecting rods are rotatably mounted at the top ends of the sliding seats; by arranging the auxiliary assembly, the damping protection effect of the device on the main spindle box body is enhanced, the springback speed of a first buffer spring is reduced, resetting of the main spindle box body is smoother and more stable, then the working precision of the main spindle box body is improved, and the quality of machined products is improved.

The invention discloses a time-varying gravity field model establishment method of a new generation of low-low satellite tracking satellite scheme based on China region enhancement, and belongs to the field of satellite gravitational mechanics. The method refers to a selection index of a global optimal double-track four-satellite formation scheme, determines a plurality of double-track four-satellite formation schemes in a China region, selects an optimal scheme from the double-track four-satellite formation schemes, and establishes a time-varying gravity field model of the new generation of low-low satellite tracking satellite scheme. Different data in the optimal scheme are adopted to independently solve low-order and high-order gravitational potential spherical harmonic coefficients, the negative influence of the time domain aliasing effect on the precision of the time-varying gravity field model is weakened, the error of the high-order gravitational potential spherical harmonic coefficients can be reduced to a certain degree, and finally the Chinese region gravity field model with higher precision is obtained. A final result shows that compared with an independent polar orbit formation, the method not only greatly weakens south-north stripe errors caused by a south-north tracking mode in a Chinese region, but also avoids the problems of gravity signal leakage and the like caused by a post-processing process, and finally obtains a Chinese region gravity field model with smaller errors and larger signal-to-noise ratio.

The invention discloses an intermediate double-gear axial correction value measuring device, a measuring method and a grouping matching method, and the measuring device comprises a bottom plate, and a first support device, a second support device, a helical gear positioning tooth, a straight gear positioning tooth, a gauge stand device and a contact indicating device which are disposed on the bottom plate. The first support device, the second support device, the bevel gear positioning tooth and the straight gear positioning tooth are respectively provided with a contact indicating device, and the first support device, the second support device, the bevel gear positioning tooth and the straight gear positioning tooth are completely attached to the matching face of the measured middle double gear to form a circuit loop. According to the invention, the measurement efficiency can be ensured, the measurement stability can be enhanced, the measurement difficulty is reduced, the measurement efficiency is improved, the measurement repeatability and consistency are improved, and the condition that the vibration value of the whole machine exceeds the standard or the meshing part is abnormally damaged or even scrapped due to poor meshing of gears caused by inaccurate measurement is effectively avoided.