216 results about "Cross scale" patented technology

The invention discloses a micro-nano scale 3D printer and a method. The 3D printer comprises a spraying head set, a printing tool, a controller and a three-dimensional movement mechanism. The spraying head comprises a plurality of spraying heads, and each spraying head applies a high-voltage pulse power supply between a corresponding electric conductive nozzle and an electric conductive base plate. Fluids are pulled from the nozzles by utilizing strong electric field force formed between the nozzles and the base plate to form Taylor Cones and stable conic jet flows. The controller controls the three-dimensional movement mechanism to drive the spraying head set and the printing tool to move relatively and meanwhile controls the movement of all the spraying heads to conduct micro-droplet spray printing on preset positions of the base material on the printing tool, and a model material, a release material and a supporting material are printed sequentially. Based on electrofluid power spraying printing (namely electric spraying printing), the micro-nano scale 3D printer solves the difficult problems that for micro-nano 3D printing, macro / micro cross-scale manufacturing cannot be achieved, the types of printable materials are few, and support is difficult to remove, and especially overcomes the deficiencies and the limitation, in the aspects of the cost, materials, resolution ratio, macro / micro cross-scale manufacturing, support removing and the like, of the of the current micro-nano scale 3D printing technology.

The invention relates to a system and a method for achieving cross-scale 3D (three dimension) printing by adopting a micro-nano composite periodic structure interference light source generated by a multi-beam laser interference technology, belonging to improvement on the existing 3D printing method. The system comprises an image acquisition data processing module (1), a PC control center (2), a laser (3), a beam splitting system (4), a 3D printing platform (5), a printing material (6) and a CCD microscopic imaging system (7). Original 3D printing speed and resolution are improved, a micro-nano composite structure material of a printed object is directly formed, and the system and the method belong to a high-speed large-area efficient micro-nano composite structure 3D printing technology.

The invention discloses a cross-scale biomimetic micro-nano branch structure array and a preparation method thereof, which relate to the field of micro-nano materials and robots, particularly relate to a biomimetic adhesive material and a preparation method thereof and also relate to an electrochemical anodic oxidation process. The cross-scale biomimetic micro-nano branch structure array consists of a substrate and a micro-nano multilevel branch structure array, wherein the micro-nano multilevel branch structure array at least comprises a primary micron cylindrical structure array and a branch micro-nano cylindrical structure array. The preparation method thereof comprises the following steps of: firstly, etching an aluminum template with an argon ion beam to obtain an aluminum template with a primary micron hole array; secondly, preparing a micro-nano branch structure array in a definite point and direction on the template array by an electrochemical anodic oxidation process; thirdly, performing film extrusion and curing on the template by a polymer replica method; and finally, removing the template for forming to obtain the desired micro-nano structure array to form a biomimetic dry adhesive material. The cross-scale biomimetic micro-nano branch structure array and the preparation method thereof use electric characteristics to effectively solve the control problem of from micron to nanometer cross-scale branch structure arrays and have a great significance for the development of biomimetic adhesive materials and related dry biomimetic robots.

The invention relates to a combination type processing process integrated measurement method based on vision laser, and belongs to the field of geometric quantity measurement. The method adopts left and right cameras to realize online guidance of the pose of a tail end measurement device of a mechanical arm in a vision servo mode, so that local features of a part to be measured are in a measurement range of a laser scanner. The laser scanner is utilized to perform high-precision measurement on the local features, and a laser tracker is utilized to perform tracking positioning on the tail end measurement device; and the pose of the tail end measurement device is adjusted to perform multiple times of measurement on the part to be measured according to regions, and local laser scanning data of the multiple times of measurement are unified to a global coordinate system established based on the laser tracker. The method effectively solves the problem of high-precision processing process integrated measurement in a large space range, has the characteristics of high measurement precision, wide range and high robustness, and realizes large-space, cross-scale and high-precision processing process integrated measurement.

The invention discloses a remote sensing image region of interest detection method based on integer wavelets and visual features, which belongs to the technical field of remote sensing image target identification. The implementing process of the method comprises the following steps: 1, performing color synthesis and filtering and noise reduction preprocessing on a remote sensing image; 2, converting the preprocessed RGB spatial remote sensing image into a CIE Lab color space to obtain a brightness and color feature map, and converting an L component by using integer wavelets to obtain a direction feature map; 3, constructing a Gaussian difference filter for simulating the retina receptive field of a human eye, performing cross-scale combination in combination with a Gaussian pyramid to obtain a brightness and color feature saliency map, and performing wavelet coefficient sieving and cross-scale combination to obtain a direction feature saliency map; 4, synthesizing a main saliency map by using a feature competitive strategy; and 5, partitioning the threshold values of the main saliency map to obtain a region of interest. Due to the adoption of the remote sensing image region of interest detection method, the detection accuracy of a remote sensing image region of interest is increased, and the computation complexity is lowered; and the remote sensing image region of interest detection method can be applied to the fields of environmental monitoring, urban planning, forestry investigation and the like.

The invention discloses a cross-scale high-precision dynamic crop growth monitoring and yield assessment method based on high-resolution satellite remote sensing data and a crop model. The method comprises the steps of achieving localization of the model is achieved; performing spatial matching on the remote sensing data and the ground data by using a GEE platform; designing a plurality of simulation scenes; dividing the growth period of the crops into a front time window and a rear time window by taking the green returning period as a node, and calculating various meteorological factors in the whole growth period; constructing a regression equation, and establishing a regression equation of each day in all growth periods; Extracting the maximum values of the satellite remote sensing observation vegetation indexes of two time windows before and after each year and corresponding dates thereof pixel by pixel, and converting the extracted maximum values of the vegetation indexes into independent variables LAI of a regression equation through an empirical formula; And taking the observation dates of the two time windows before and after extraction as references, carrying out pixel-by-pixel calculation by utilizing a regression equation corresponding to the combination date, and obtaining the crop simulation yield after operation on all pixels is completed.

The invention belongs to the technical field of composite material prediction, and discloses a carbon fiber reinforced composite material mechanical performance prediction method based on cross-scalesimulation. The prediction method comprises the following steps: adopting a meso-finite element method, establishing a single cell prediction model of a meso-level carbon fiber composite material andpredicting the mechanical performance of the carbon fiber reinforced composite material; Based on the stiffness homogeneity method, predicting the off-axis angle and multi-angle lamination sequence and verifying the models by experiments. The invention provides a method for predicting the mechanical properties of the composite material, and the experimental results are consistent with the theoretical model.

The present invention discloses a laser processing head and a multi-light source, multi-function and multi-axis processing apparatus comprising the same. The laser processing head includes a shell, an optical path system, a locating conical disk-shaped connecting mechanism, a laser range finder, a motor driving mechanism and a dust collection protection cover. The laser processing head has the advantages of a plurality of processing modes, flexibility in laser selection and easiness in replacement. The multi-light source, multi-function and multi-axis processing apparatus includes an apparatus control and operation system platform, a multi-axis linkage numerically-controlled machine tool and the laser processing head; the laser processing head is fixed on a high-precision multi-axis linkage machine tool through a blade handle type positioning cone device; and large-breadth and cross-scale laser fine processing only requires the switching of a laser light source, a laser optical path and the laser processing head, so that at least three kinds of large complex component fine surface processing application can be realized. The multi-light source, multi-function and multi-axis processing apparatus is especially for the aerospace field. The laser processing head and the multi-light source, multi-function and multi-axis processing apparatus comprising the same of the invention have the advantages of low manufacturing cost, wide application range, convenience in mass production and the like.

The invention relates to an improved robustness in upscaling the resolution of regularly sampled multi-dimensional signals, where a single low-resolution signal is available. These methods are referred to as example-based super-resolution or single-image super-resolution. A method for super-resolving a single image comprises three stages. First, an interpolation-based up-scaling of the input image is performed, followed by a Local De-noising step in contour regions. The second stage comprises extrapolation through cross-scale block matching, wherein an extrapolated high-frequency band is obtained that is de-noised through regularization in the same contour regions. The third stage comprises adding the contributions of the low-frequency band of the high-resolution image and the extrapolated high-frequency band.

The invention provides a crowd counting method based on a generative adversarial network. The method comprises the steps of constructing the generative adversarial network, wherein the generative adversarial network comprises a generator and a discriminator, the generator is used for generating a corresponding crowd density image according to an input crowd image, and the discriminator is used fordiscriminating the authenticity of the crowd density image generated by the generator in a training stage of the generative adversarial network; performing cross-scale consistency training on the generative adversarial network to obtain a trained generative adversarial network; and taking a to-be-counted crowd image as an input of the trained generative adversarial network, obtaining the target crowd density image, and counting the number of people in the target crowd density image. The method is effective for counting the number of people in a monitored scene, and has good robustness for complex and changeable backgrounds and high-density crowds.

The invention relates to a cross-scale micro-nano in-situ three-point bending mechanical performance testing platform which belongs to the field of in-situ mechanical performance testing and structurally comprises a precise drive unit, a transmission and execution unit, a signal control and detection unit and a connection and support unit, wherein a brushless direct-current servo motor is connected with a primary worm, connected with a secondary worm shaft through a primary worm gear drive pair, respectively connected with precise ball screws I and II through a secondary worm gear drive pair,and further connected with a hammer head. The cross-scale micro-nano in-situ three-point bending mechanical performance testing platform has the advantages of small volume, light weight, high rigidity, compact structure and high test precision, can provide plentiful test contents, and can be mutually compatible with carrier platforms of various electronic microscope vacuum cavities.

The invention discloses a method for extracting a remote sensing image interesting area based on multi-scale feature fusion, and belongs to the technical field of remote sensing image processing. The method comprises the following steps: (1) adopting a saliency analysis method based on a multi-scale spectrum residual error to generate a multi-scale low frequency saliency image of the remote sensing image, (2) obtaining multi-scale high frequency saliency images in the horizontal direction, the perpendicular direction and the diagonal direction through integer wavelet transformation, (3) obtaining a luminance saliency image and a direction saliency image through cross-scale weighting and cross-scale fusion, (4) combining the luminance saliency image and the direction saliency image to generate a main saliency image, and (5) carrying out threshold segmentation to extract the interesting area through the OTSU. Compared with a traditional method, the method has the advantages of being low in computing complexity and effectively improving area extraction efficiency and area extraction accuracy. Due to the fact that spectrums and color information of the remote sensing image are not required to be obtained, the method can be directly used for interesting area extraction of a high-resolution full-color remote sensing image. The method has good application value in the fields of land planning, environment monitoring, forestry investigation and the like.

The invention provides a method for reconstructing a micro structure finite element of a multiphase material based on a sequence image, comprising the following steps of: on the basis of collecting, reading and interpolating the sequence image of the material, establishing a finite element topology model forming a mapping relation with the sequence image; using configuration information of the image and a topology structure of the model to determine a node and unit information; and then using a statistical average value of colour information in the image to determine material attributes of each unit of the finite element model. The method disclosed by the invention not only can be used for reconstructing a two-dimensional quadrangular finite element model reflecting a real structure of a material section through a single image, but can also be used for directly reconstructing a three-dimensional hexahedral finite element model reflecting the real structure of the material through the sequence image. By means of the invention, error accumulation in the links of reconstructing, grid dividing and the like in the current geometrical reconfiguration method can be avoided; the reconfiguration time is greatly saved; and the reconfiguration efficiency is improved. The method disclosed by the invention can be widely used in the fields, such as macro-micro cross scale research, optimization design and preparation of the multiphase material.

The invention discloses a stick-slip driving cross-scale precise motion platform which comprises a base, a friction vibrator, a vibrator driving source and a sliding block, wherein the friction vibrator is mounted on the base; the vibrator driving source is mounted between the friction vibrator and the base and provides a driving force for the friction vibrator; the sliding block is connected with the friction vibrator in a sleeving manner, and contacted with the friction vibrator to generate a friction force; a pretightening force adjustment structure for providing a pretightening force is arranged between the side surface of the sliding block and the base, and used for adjusting the magnitude of the friction force; a stick-slip effect is generated between the sliding block and the friction vibrator; and the sliding block makes cross-scale precise motion. According to the stick-slip driving cross-scale precise motion platform, an adjustment mode of the pretightening force of the motion platform is simplified greatly; processing and assembling are facilitated; the output performance of the stick-slip driving cross-scale precise motion platform is further improved effectively; the motion precision and the consistency of the stick-slip driving cross-scale precise motion platform can be guaranteed simply and effectively; and the stick-slip driving cross-scale precise motion platform is suitable for mass production.

The invention relates to an in-situ indentation mechanical testing device based on tensile compression and fatigue combined load mode, and belongs to the field of precise testing instruments. The device is mainly composed of a precise driving unit, a tensile compression and fatigue combined load unit, an indentation load unit, a precise sensing and detecting unit, wherein the precise driving unit can realize quasi-static load; the tensile compression and fatigue combined load unit enables the center of a testing piece to be kept unchanged basically; with combination of a high-resolution imaging system, observation of in-situ mechanical performances of a material can be carried out. A fatigue module is loaded on a tensile compression module, so that fatigue performance of the material can be tested by adopting the precise piezoelectric driving technology. The indentation load unit is arranged right above the testing piece and is pressed in the testing piece vertically, a lead screw stepping motor drives an indentation flexible hinge to feed linearly, and an indentation piezoelectric stack pressed in the testing piece drives precise indentation, so that cross-scale in-situ indentation mechanical test can be carried out. The device has the advantages of compact structure, small size, rapid response, high precision, low cost and the like.

A weak texture detection-based cross-scale cost aggregation stereo matching method of the present invention belongs to the computer vision field, in particular relates to a stereo matching method of the weak texture images, and comprises the following steps of inputting two color images which are separately a left image and a right image, utilizing the gradient information of the left image to carry out the weak texture detection and segmentation on a picture; calculating the matching cost according to the gradient information and the color information of the left image and the right image; taking the above weak texture detection and segmentation results as the references to carry out the Gaussian filter-based internal scale and cross-scale cost aggregation; adopting a winner taking strategy to calculate the parallax; adopting the left and right consistency detection and an adaptive weight-based method to refine the parallax, and outputting a parallax image. The method of the present invention achieves the technical purposes of improving the weak texture area matching correct rate under the premise of guaranteeing the texture area matching correct rate, and obtaining the better parallax image.

The invention discloses a photoelectric equipment multi-optical-axis parallelism quantitative detection device. The device comprises an off-axis folded aspheric optical system, a CCD image sensor, a two-dimensional translation bench, a double-pentaprism expanding assembly and a control system. The off-axis folded aspheric optical system forms a collimation parallel light tube. The two-dimensional translation bench is installed behind a housing. A cross scale surface of the two-dimensional translation bench is superposed with a focal plane of the parallel light tube. A transition prism group is arranged below an aspheric secondary mirror to realize light parallel inversion. The lens of the CCD image sensor is aligned to the transition prism group. A support group is installed on the housing. Two ends of a beam expanding guide rod of the support group are respectively provided with a pentaprism, and the relative distance between the two pentaprisms is adjustable. The device is capable of realizing quantitative and precise parallelism measurement of every two laser / infrared / white light optical axes of multi-band photoelectric equipment, is advantageous by being wide in spectrum range, high in measurement precision, miniature and portable, and is applicable to optical axis parallelism testing among multi-band photoelectric equipment.

The invention discloses a cross-scale seismic rock physical attenuation model and a method for predicating attenuation and dispersion. The model simulates characteristics of underground oil-gas-bearing double-phase medium, and adopts the construction structure that the influence of a jet flow of a micro-scale fracture in a BISQ elastic wave prorogation theory is introduced under the framework of a macro-scale Biot double-phase medium wave prorogation theory; a periodic stratification White module under mesoscale is introduced, so as to ensure that water-bearing stratums and gas-bearing stratums are alternatively and periodically overlaid; the horizontal direction of each stratum is infinitely extended; each stratum adopts isotropic medium; the thickness of each stratum is far less than seismic wavelength and is greater than the particle size; the control equation of each stratum adopts a BISQ elastic wave prorogation equation, so that the cross-scale seismic rock physical attenuation model is constructed. The model comprises three scale attenuation mechanisms, namely a micro-scale Biot flow, a mesoscale local flow and the micro-scale jet flow. The invention further discloses a method for predicating the longitudinal wave attenuation and dispersion of the model. A predicated attenuation value is very consistent with an attenuation value measured by experiments.

The invention provides a space manipulator trajectory tracking control method based on a cross-scale model. In the case of analyzing the parameter and nonparameter cross-scale characteristics existed during the modeling of a free-floating space manipulator system, the manipulator joint space is subjected to real-time online tracking control. The control method introduces the radial basis neural network to approximate the variation item of the cross-scale characteristic in the dynamic model of the space manipulator and effectively inhibits the influence of the variation item on the system by means of the learning ability of the neural network, and designs the adaptive law to adjust the weight of the neural network in real time and performs the simulation verification by taking the plane two-connecting-rod space manipulator as an example, thereby realizing the fast and accurate tracking of the desired trajectory in the joint space of the space manipulator.

The invention provides an inertia stick-slip cross-scale motion platform capable of achieving unidirectional movement. A balancing weight, a piezoelectric ceramic actuator and a principle mass block are combined, and when forward or backward voltage is applied between the positive electrode and negative electrode of the piezoelectric ceramic actuator, the piezoelectric ceramic actuator stretches or contracts slightly in the length direction and drives the balancing weight and principle mass block to move, so that millimeter-level stroke and nanometer-level positioning precision are realized. Compared with other motion platforms, the inertia stick-slip cross-scale motion platform has the advantages that the structure is simple, quick large-stroke precise positioning can be achieved, multi-freedom-degree driving can be achieved easily, and a special position retaining device is not needed.

The invention provides a gradable video coding system based on multi-scale online dictionary learning. A multi-scale training set establishing module based on layered sparsity is used for obtaining layered sparsity structures, in different scales, of an image through wavelet transformation. By means of a Gaussian differential filter set, direction energy is extracted so that primitive areas in the image can be obtained, and a multi-scale training set is generated by cutting out image blocks of the primitive areas. By means of an online dictionary learning module, it is ensured that dictionary atoms are iterated and optimized under low complexity according to the stochastic gradient descent method so that a sub-dictionary base corresponding to the multi-scale training set can be generated. For low-frequency video frames, a cross-scale video frame reconstruction module learns lost high-frequency information on different levels through the constructed sub-dictionary base; the aim of grading video quality is achieved through different-grade wavelet inverse transformation reconstruction. By means of the gradable video coding system, complexity of a super-resolution algorithm based on learning is lowered, the reconstruction quality gain is obtained at different transmission rates compared with H.264, and high expandability is achieved.

Aspect of the disclosure relate to methods of assessing a bioreactor culture that involve determining a culture parameter of the manufacturing-scale bioreactor culture using a model that relates a Raman spectrum to the culture parameter. Related bioreactor system are also provided.

The invention provides an optical micro-structure and a manufacturing method of an optical micro-structure layer, a light guide assembly and a display device. The manufacturing method comprises the steps of forming a photopolymer film layer, and performing holographic exposure on the photopolymer film layer to form a phase-type micro-structure with planar refractive index modulation. According to the manufacturing method of the optical micro-structure, a large-size product can be prepared; a cross-scale light ray micro-structure can be separated by sections; besides, the change of phase distribution in a hololens, caused by clinging or filling of film layers, can be avoided; and in addition, the mass producibility and the product reliability are high.

The invention relates to a cross-scale two-dimensional large-stroke high-speed and high-precision motion platform. The cross-scale two-dimensional large-stroke high-speed and high-precision motion platform is of an H-shaped structure and is composed of a Y-direction working platform on the upper layer, an X-direction dual-edge driving working platform on the lower layer, a marble platform and a support. The Y-direction working platform on the upper layer is connected with the X-direction dual-edge driving working platform on the lower layer in series, a high-speed rolling linear guideway is used for guiding, and a grating ruler is adopted for position feedback. The Y-direction working platform on the upper layer is driven by a linear motor and is fixed to a movable platform of the X-direction dual-edge driving working platform on the lower layer through an adapter plate; the X-direction dual-edge driving working platform on the lower layer is driven by two linear motors at the same time and is fixed to the marble platform through screws; the marble platform is placed on the support. By means of the cross-scale two-dimensional large-stroke high-speed and high-precision motion platform, a two-dimensional motion platform driven by the linear motors, fed back by the grating ruler and guided by the rolling guideway is adopted, the structure is high, the rigidity is high, the bearing capacity is large, the positioning accuracy is high, and the two-dimensional large-stroke high-speed and high-precision motion can be achieved.

The invention discloses a method of manufacturing a surface cross-scale functional micro-nano structure; the method comprises the steps of first, scanning the surface of a base by millisecond pulsed laser to obtain a micro structural graph; scanning the manufactured micro structural graph by femtosecond pulsed laser to obtain manufacture a nano structural graph on the surface of the micro structural graph by induction. By using the method of manufacturing surface micro-nano functional structure combining millisecond pulsed laser etching and femtosecond laser induction, the cross-scale high-performance low-cost manufacture of the micro and nano functional microstructure can be achieved, the manufacturing efficiency is far higher than that of semiconductor process, and the method has a better application prospect.

The precision and the timeliness of a training sample are two challenges in current image super-resolution field. The invention provides a super-resolution processing method for a single image with respect to the problem. The method comprises a fuzzy kernel function estimation stage and a super-resolution reconstruction stage. The fuzzy kernel function estimation is realized by minimizing image cross-scale diversity, to improve the precision of the training sample; and the super-resolution reconstruction is realized by anchoring space mapping on the basis of a feature extraction strategy of reverse projection residuals and dual dictionary learning, to enhance the expression capability of an algorithm on the bottom feature of the image and accurately reflect the mapping relationship between low-resolution and high-resolution feature spaces. To improve the efficiency of the algorithm, the high-resolution feature reconstruction is completed by adopting anchoring space mapping, and both the fuzzy kernel function estimation stage and the super-resolution reconstruction stage adopt a block processing manner. The method provides a powerful competitive advantage for improving the performance of imaging equipment, and provides necessary theoretical and technical supports for further improving the super-resolution processing effect.

The invention discloses a vertical pre-tightening type stick-slip drive cross-scale precise motion platform which comprises a base plate, a base, a friction oscillator, an oscillator drive source and a sliding block. A pre-tightening force adjusting structure for providing pre-tightening force is arranged between the sliding block and the base plate and comprises adjusting screws used for providing the pre-tightening force, the adjusting screws penetrate through the sliding block and the base and then are connected with the base plate, and the pre-tightening force can be adjusted by adjusting the threaded connection length of the adjusting screws and the base plate. The pre-tightening force adjusting method of the motion platform is greatly simplified, machining and assembling are facilitated, the output performance of the stick-slip drive cross-scale precise motion platform is effectively improved, motion precision and consistency of the stick-slip drive cross-scale precise motion platform are simply and effectively ensured, and volume production is facilitated.

The invention discloses a drop seepage characteristic monitoring method and device for cross-scale movement slits. No monitoring devices are available for monitoring flowing behaviors of drops to cross millimeter-micron-nano scale slits. A horizontal positioning block and a vertical positioning block are horizontally and vertically positioned by a tested sample separately; a slit shape and gap between the tested sample and a standard glass brick are set by means of an adjusting bolt on the standard glass brick; an injector is adjusted to a preset height by means of a lifting table to obtain the initial speed of the drops into the slit; and the relative movement speed of the tested sample and the standard glass brick in the vertical direction is set by setting the movement speed of the vertical positioning block. By adding a preset liquid into an injection syringe, a feeding mechanism enables the injector to fall drops in preset volumes, and after the drops enter the slit, the seepage characteristic is photographed and recorded through a high-speed camera. The distance between the silts is precisely controlled by means of an optical detection and joggling control method. The flowing state of the drops in the relative movement silt is monitored by means of a high precision slide rail and the high-speed camera.

The invention relates to a cross-scale complicated geologic body ground stress field identification method, and belongs to the technical field of geological engineering, rock mass engineering and numerical analysis. The cross-scale complicated geologic body ground stress field identification method comprises the following steps: an optimization model capable of identifying ground stress is established; a genetic algorithm is adopted for solving the optimization model so as to obtain protolith parameters and side pressure coefficients of a geologic body; the protolith parameters of the geologic body are substituted into a three-dimensional numerical model to obtain a stress field. A device used for implementing the method comprises an optimization model establishing module, a genetic algorithm calculation module and a ground stress field obtaining module, wherein the optimization model establishing module is used for establishing the optimization model capable of identifying the ground stress; the genetic algorithm is used for solving the optimization model to obtain the protolith parameters and the side pressure coefficients of the geologic body; the ground stress field obtaining module is used for substituting the protolith parameters of the geologic body into the three-dimensional numerical model so as to obtain the ground stress field. According to the cross-scale complicated geologic body ground stress field identification method and device, the initial ground stress field in the geologic body can be obtained, so that the problem that existing ground stress inversion theories and methods are limited by ground stress inversion of a cross-scale complicated geologic body.

The invention discloses a method for solving insufficient failure data in service life analysis and prediction of a high-speed rail gearbox body. The method comprises the following steps: firstly, carrying out finite element analysis on the high-speed rail gear box body by utilizing a finite element simulation technology; secondly, analyzing the distribution law of the fatigue life of the gear boxbody material by utilizing the result of the rotary bending fatigue test of the gear box body material, carrying out parameter estimation, and establishing an SN curve model of the gear box body material; and finally, analyzing and predicting the service life of the gearbox body by combining the finite element simulation data of the gearbox body and the fatigue test data of the material. According to the invention, the high-speed rail gear box body is large; Load complexity, a structure with a long service period is an object; Aiming at the problem of insufficient failure data of the high-speed rail gear box body, the invention provides a method for solving the problem of insufficient failure data in the life analysis and prediction of the high-speed rail gear box body from the perspective of cross-scale, thereby laying a foundation for further predicting the fatigue life of the gear box body and providing a new research method for the fatigue life analysis of such structural parts.