186results about How to "Improve limitations" patented technology

The invention discloses an industrial product quality detection method and system based on machine vision, and relates to the technical field of quality detection.During operation of the system, through an industrial camera and an optimized light source layout, high-resolution image acquisition is performed on electronic components in real time by adopting multi-angle shooting, a series of optimization processing is performed on the acquired images, and the quality of the electronic components is detected. The method comprises the following steps: extracting shape, texture and color features according to geometric characteristics of an electronic component to form key parameters for judging defects, identifying potential defects of the electronic component by using a deep learning model algorithm, calculating to obtain a quality evaluation index Q, and calculating the quality evaluation index Q according to calculation results of feature extraction and defect detection. And comprehensively evaluating the quality of each component, comparing the quality evaluation index Q with a first preset threshold value M and a second preset threshold value N to obtain a quality evaluation grade, feeding unqualified detection information back to a production line, and removing unqualified components.

The invention discloses a multi-modal feature joint constraint whole-brain dynamics modeling and parameter optimization method which is applied to the field of computational neuroscience and brain science. Aiming at the defects of a current whole brain dynamic model in the aspect of synchronously fitting multi-modal scalp EEG signals and cortical and subcortical BOLD signals across spatial and temporal scales, the capability of the model for comprehensively and accurately representing real dynamic characteristics of brain activities on different scales is limited; in order to overcome the short plate, the core element of multi-modal feature combined constraint is added on the basis of a whole-brain dynamic model and a parameter space rapid optimization method, and a modeling method and a parameter rapid optimization strategy for the multi-modal feature combined constraint whole-brain dynamic model are designed; by applying a high-dimensional parameter rapid optimization algorithm, the capability of the whole-brain dynamic model in synchronous fitting of brain multi-modal spatial-temporal characteristic signals is further improved; the method has important significance and reference value for developing a whole-brain dynamic model modeling method and a parameter optimization system which are more biological rationality and interpretability.

The invention belongs to the technical field of medical data processing, and discloses an automatic ICD coding method and system based on fusion of various label information, and the method comprises the steps: carrying out the feature extraction of the description of a clinical text and an ICD label, and obtaining the representation of the clinical text and the representation of the label; performing interactive fusion on the ICD tag description and the ICD tag description to obtain tag-related context representation, extracting co-occurrence representation of the tag representation, and fusing the co-occurrence representation with the ICD tag description and the tag-related context representation to obtain enhanced tag representation; performing interactive fusion on the enhanced tag representation and the clinical text representation to obtain a document representation corresponding to each tag, and predicting an ICD code based on the document representation; and defining a loss function, and training the model. According to the method, information from three aspects of context, tag original semantics and tag correlation is fused, richer input features are provided for automatic ICD coding, the comprehensiveness and accuracy of coding are improved, and important support is provided for clinical decision making and medical resource allocation.

The invention provides a tunnel leakage global positioning method and system based on a contour enhanced segmentation network of panorama-infrared double cameras, and the method comprises the steps: capturing a 360-degree panorama image of a tunnel through a double-camera system integrating a double-fisheye camera and a thermal infrared camera, converting the panorama image into a plane image through an equidistant cylinder mapping method, and carrying out the global positioning of the tunnel leakage. The invention provides a tunnel wall segmentation method from a cylinder to a plane image to realize plane display of a tunnel wall surface, and meanwhile, the invention constructs an infrared image leakage segmentation network based on CEIL-Net, the network combines a contour enhancement technology and an attention mechanism, and the precision and robustness of leakage area segmentation are significantly improved. Besides, the leakage area in the infrared image is accurately mapped to the plane image of the tunnel through homography matrix calculation based on the camera attitude, and comprehensive visualization of the leakage position is achieved. The tunnel leakage area can be effectively identified and positioned, and the method is suitable for tunnel health monitoring and maintenance.

The invention discloses an intelligent generation and application method and system for structural data of an engineering drawing, and the method comprises the steps: obtaining the engineering drawing, analyzing the engineering drawing, and determining a data relation, graphic data, text data and image data reflected by the engineering drawing; screening, identifying and combining the data relationship, the graphic data, the text data and the image data to obtain a drawing object, a component object and a space object; and outputting engineering drawing structured data based on the drawing object, the component object and the space object, and applying the engineering drawing structured data. According to the method, the engineering drawing is analyzed and the data of the engineering drawing is structured, so that the processing efficiency and accuracy of the engineering drawing are improved.

The invention belongs to the technical field of cloud computing, and discloses a lightweight multi-domain hyper-fusion platform construction method compatible with heterogeneous hardware resources, which adopts a lightweight hyper-fusion platform architecture compatible with the heterogeneous hardware resources, converts physical resources into virtual resources on a virtual machine based on a KVM (Kernel-based Virtual Machine), shields the difference of underlying hardware, and improves the performance of the platform. According to the method, heterogeneous storage resources are integrated based on Ceph, and storage devices of different manufacturers are integrated into a unified storage pool through a distributed storage technology without being limited by types of bottom hardware devices. Through the SDN technology, the OpenStack network service can decouple a network control plane and hardware, and unified management of different network devices is realized. Through a virtualization technology and an automatic management tool, a simplified elastic expansion solution is provided, and changes of resource demands are easily coped with.

The invention belongs to the technical field of secondary batteries, and mainly relates to a battery aging mechanism identification method, which comprises the following steps of: firstly, judging whether other battery aging mechanisms exist in addition to the growth of a solid electrolyte interfacial film; meanwhile, peak valleys of an I C curve and a DV curve in the battery aging process are analyzed, and whether the aging mechanism of the battery is battery negative electrode active material loss or battery positive electrode active material loss is judged; and further, decomposing the electrochemical impedance spectrums before and after the aging of the battery through a relaxation time distribution technology, and comparing the electrochemical impedance value spectrum before the aging of the battery with the electrochemical impedance spectrum after the aging of the battery to obtain a change result of the electrochemical impedance value spectrum of the battery. Finally, the limitation of a relaxation time distribution technology of a differential voltage analysis method on battery capacity attenuation nondestructive analysis and internal resistance growth quantitative decomposition and quantification is overcome, so that the battery aging mechanism analysis is clearer.

The invention discloses a lithium battery SOC-SOH joint estimation method based on mechanism and data fusion driving, and the method comprises the following steps: firstly, carrying out the training of a prediction model of a least square support vector machine (LSSVM, LSSVM) through a multi-dimensional data set after phase space reconstruction; and then, establishing a state equation based on an ampere-hour integral method and a capacity fading empirical model, establishing an IUPF observation equation through an LSSVM prediction model, and substituting the IUPF observation equation into an improved unscented particle filter algorithm (IUPF, Intermediate UPF) to perform state estimation and parameter updating. And finally, the updated LSSVM model parameters are iterated to a training data set, so that the combined prediction of the SOC (State OfCharge) and the SOH (State OfHealth) of the battery and the online updating of the data driving model are realized. According to the lithium battery SOC-SOH joint estimation method based on mechanism and data fusion driving provided by the invention, joint estimation of the state of charge SOC and the state of health SOH of the lithium battery is realized, and state noise and measurement noise of the system are considered, so that the precision and stability of a battery state estimation result are ensured.

The invention provides a photovoltaic power station short-term output prediction method and system based on a LightGBM-Attention GRU combination model, a storage medium and electronic equipment, and relates to the field of photovoltaic power station short-term output prediction. According to the method, a plurality of features are constructed based on preprocessed multi-source numerical weather forecast data and historical actual output data, and each feature is corrected based on a correlation coefficient between the features and target output; taking the corrected feature data as the input of a LightGBM model to obtain a first prediction result, and taking the corrected feature data and the first prediction result as the input of an Attention GRU model to obtain a second prediction result; and finally, performing weighted summation by adopting an error reciprocal method to obtain a final short-term output prediction result of the photovoltaic power station to be predicted. Based on a combined model of a Light GBM model and an Attention GRU model with different underlying principles, the limitation that scene migration is difficult to carry out by a single model is improved, and the accuracy of photovoltaic power station short-term output prediction is greatly improved.

The invention discloses an Alzheimer's disease auxiliary diagnosis method based on a convolutional neural network, and belongs to the technical field of Alzheimer's disease auxiliary diagnosis. The auxiliary diagnosis method comprises the following steps: acquiring an electroencephalogram to be recognized; obtaining a trained convolutional neural network, and processing the to-be-recognized electroencephalogram according to a basic convolution module to obtain a basic feature map; the residual module takes the basic feature map as input, and the information output end of the residual module is connected with the information output end of the corresponding feature extraction module; processing the basic feature map through a plurality of feature extraction modules and a residual module to obtain an electroencephalogram feature map; and inputting the electroencephalogram feature map into a classification diagnosis module, and then outputting an identification result of the electroencephalogram to be identified by the classification diagnosis module. The electroencephalogram is classified through deep learning, the accuracy of Alzheimer's disease diagnosis is improved while artificial factors are reduced, and the difference caused by manual feature extraction is avoided.

The invention provides a bean product fermentation influence factor analysis method and system, and relates to the technical field of food safety detection.The method comprises the steps that multiple sets of key parameters are set within a preset range, physical and chemical index changes under the parameters are monitored in real time, and the physical and chemical index changes comprise the tannin variation, the acid production capacity, the fermentation rate and the active enzyme variation; the method comprises the following steps: establishing a key parameter, constructing a physical and chemical index prediction model, training by taking the key parameter as input, evaluating a fermented bean product, training a sensory evaluation index prediction model by taking the physical and chemical index as input, and finally, determining an optimal combination of the key parameter through a genetic algorithm by taking maximization of the sensory evaluation index as a target, thereby optimizing a fermentation process. By setting and adjusting key fermentation parameters in real time and combining physical and chemical index monitoring and sensory evaluation, the purposes of optimizing the fermentation process and improving the final quality of bean products are achieved.

The invention relates to a multi-modal Chinese interference identification method based on residual fusion language features, which comprises the following steps of: (1) extracting words with anti-interference and non-anti-interference meanings from a self-constructed image-text multi-modal Chinese interference identification data set by utilizing a chi-square statistical method, and constructing a language feature system; (2) extracting language features of words in the language feature system by using a TextCNN model; (3) extracting image features by using a ResNet34 model; (4) introducing a cross attention mechanism, and establishing association between image-text features; and (5) carrying out feature fusion to obtain a classification result. The limitation of the existing method can be improved, and the accuracy of the phage recognition is improved.

The invention discloses a zirconium-nickel dissimilar metal welding method based on active regulation and control of a temperature field. The zirconium-nickel dissimilar metal welding method comprises the following steps that S1, base metal is cleaned; the butt-joint end faces and the welding surfaces of the zirconium and nickel alloy pipes are polished and cleaned, and clean zirconium and nickel base materials are obtained; s2, a to-be-welded part is assembled; the to-be-welded end face of the clean base metal is assembled in a protective gas cavity of the rotary clamping device; s3, welding is conducted; a laser scanner is adopted for welding at a preset welding position, heat source gradient distribution of base metal at the two ends of a welding seam is controlled by regulating and controlling laser power, welding seam temperature field feedback is established through an infrared temperature sensor, and real-time monitoring and laser power regulating and controlling are conducted; s4, postweld heat treatment; and the laser power is adjusted in real time according to welding seam temperature field feedback so as to adjust and control the welding seam cooling process. According to the method, effective connection of zirconium-nickel indissolvable metal is achieved by controlling the regional welding temperature field, the temperature range for forming brittle compounds is avoided, the uniformity of a molten pool between Zr and Ni materials is ensured, and welding defects such as hot cracks and air holes are reduced.

The invention belongs to the technical field of laser welding, and particularly relates to laser welding equipment and a welding method thereof. Comprising a body, a connecting pipe and a laser welding gun, a winding disc is arranged at the top of the body and used for winding the connecting pipe, one end of the connecting pipe is wound on the winding disc, and the other end of the connecting pipe is connected to the side, away from the output end of the laser welding gun, of the laser welding gun; the laser welding gun is provided with a rotating and sucking assembly, and the rotating and sucking assembly is used for sucking splashing particles generated in the workpiece welding process of the laser welding gun. A cooler is arranged at the top of the laser welding gun through a bolt, and a multidirectional temperature control mechanism is arranged on the cooler; according to the device, splashing particles are sucked into the containing square box along with flowing of air by rotating the sucking assembly, it is avoided that time and energy need to be spent on cleaning bonded impurities afterwards, the working intensity of workers is reduced, the using and welding effects of the device are improved, and the limitation of the device in the using process is further reduced.

The present invention discloses a defect detection method based on deep contrast learning, which relates to the field of computer vision technology, including obtaining the original image data of industrial workpieces, and performing normalization, denoising, cropping and resizing to form standardized image data; inputting the standardized image data into a deep contrast learning model based on Transformer, and outputting the global feature vector of the workpiece image; inputting the optimized positive and negative sample pairs into a meta-learning unit, and performing rapid adaptive training on the deep contrast learning model through a meta-learning mechanism; applying the trained contrast learning model to real-time defect detection, performing defect judgment on the newly input workpiece image, and outputting the defect detection result of the workpiece. The present invention improves the accuracy of defect detection, while greatly reducing the training time and data requirements, and significantly improves the limitations of the prior art in a small sample environment.

The present invention relates to a curcumin 2-chloroadenine derivative compound or a stereoisomer, a deuterated substance, a solvate, a prodrug, a metabolite, a pharmaceutically acceptable salt or a cocrystal thereof.

The invention discloses a decimal multi-modulus frequency divider circuit based on space-time averaging and phase interpolation technologies. The decimal multi-modulus frequency divider circuit comprises a third-order noise shaping modulation module, a dynamic element matching and phase selection module, a phase switching frequency divider module and a pipelined phase interpolation module. The third-order noise shaping modulation module is used for performing time averaging on the input frequency dividing ratio to generate an instantaneous frequency dividing ratio; the dynamic element matching and phase selection module is used for spatially averaging the instantaneous frequency dividing ratio and generating a frequency divider control word and a phase interpolator control word; the phase switching frequency divider module is used for generating a clock signal corresponding to a frequency dividing ratio according to the frequency divider control word; and the pipelined phase interpolation module is used for performing phase interpolation according to the clock signal to generate a final clock signal with an accurate phase. According to the embodiment of the invention, the mutual cooperation of the modules is utilized, the fusion of the space-time averaging technology and the phase interpolation technology is realized, and the limitation of the space-time averaging technology is improved.

The invention relates to the technical field of precision hardware machining, in particular to milling equipment for precision hardware production and a control method of the milling equipment. A first concave base pier is arranged on the left side of the platform base, a first stand column is arranged at the top of the first concave base pier, a first sliding table module is installed on the front face of the first stand column, a vertical shifting head is fixed to the first sliding table module, and a first Y-direction lead screw module is connected to the bottom of the vertical shifting head. The first Y-direction lead screw module is arranged in a power groove in the front face of the first stand column, one end of the first Y-direction lead screw module is connected with a first stepping motor through a coupler, and the first stepping motor is fixed to the top of the first stand column. According to the multifunctional milling machine, the functions of vertical milling, horizontal milling, special-shaped clamping, structure scanning and the like can be integrated, the singleness and limitation of functions and modes of traditional milling equipment are improved, manual labor force is replaced, and the qualified quality of milled products can be effectively improved.

The invention discloses a shock wave CT inversion method and a rock burst early warning method based on active and passive double-source combination. The method comprises the following steps: 1, constructing a probability non-uniform initial velocity distribution model and a working face initial grid model of shock wave longitudinal waves and / or transverse waves; 2, travel time tomography forward modeling is carried out, and theoretical travel time and residual errors of theoretical longitudinal waves and / or transverse waves are calculated; 3, solving the gradient of the target function of the travel time residual; 4, carrying out seismic wave travel time tomography inversion, enabling the residual error and the RMS residual error to reach a stable state through the iterative adjustment of the seismic source and the velocity parameters of the longitudinal wave and / or transverse wave of the seismic wave, and outputting the final seismic source parameter and wave velocity; and 5, verifying the feasibility and accuracy of the inversion model through active CT numerical simulation, passive CT numerical simulation and active and passive double-source combined CT numerical simulation experiments. Working face wave velocity distribution obtained through inversion is more accurate, and the efficiency and accuracy of the shock wave CT technology are improved.

The present invention discloses a DC charging gun quick cleaning device and cleaning method, which relates to the field of DC charging gun cleaning technology, including a fixed frame, a docking frame head is installed at the bottom of the fixed frame, a telescopic cleaning mechanism, the telescopic cleaning mechanism includes a cleaning sleeve, a cleaning tube, a fixed plate and a movable top rod, the fixed plate is installed at the top of the docking frame head, a plurality of movable mounting holes are equidistantly opened in the middle of the fixed plate, a plurality of cleaning tubes are arranged at the bottom of the fixed plate, the tops of the cleaning tubes are all located inside the movable mounting holes, and the cleaning sleeve is sleeved and installed outside the cleaning tube. The present invention can effectively and quickly clean the inside of the charging gun head and also clean the pins synchronously. Since the charging gun is used frequently, the pins are conductive components. During long-term use, the column head will be contaminated and oxidized, resulting in increased contact resistance, heat generation during charging, and in severe cases, the gun head or vehicle will burn.

The invention relates to an asphalt mixture gradation identification method and system based on Vision Transform, and the method comprises the steps: shooting a slice map of an asphalt mixture test piece, and recording the gradation of the test piece; an OpenCV library is used, automatic cutting is carried out according to the aspect ratio of the slice map, and a data set is constructed in combination with grading of test pieces; preprocessing the data set sample, wherein the preprocessing comprises size adjustment, brightness matching, image enhancement and data amplification; and a Vision Transform classification network is used, training and testing are completed on the established data set, and asphalt mixture gradation identification is realized. Compared with the prior art, the method has the advantages that the accuracy rate is guaranteed, the cost of grading identification of the asphalt mixture can be remarkably reduced, and the tediousness caused by tests in the identification process is reduced.

The invention discloses pipeline laying equipment for construction in a narrow space, and relates to the technical field of pipeline laying, the pipeline laying equipment comprises a fixed frame, movable frames are arranged on the front side and the rear side of the bottom end of the fixed frame, moving wheels are mounted in the middles of the bottom ends of the movable frames, and brake universal wheels and laying mechanisms are mounted on the two sides of the bottom ends of the movable frames; the laying mechanism further comprises a fixing plate, a fixing frame and a winding and unwinding roller, the fixing plate is installed in the middle of the top end of the fixing frame, the fixing frame is installed at the top end of the fixing plate, a movable through groove is formed in the middle of the fixing plate, and the winding and unwinding roller is installed on the rear side of an inner cavity of the fixing frame. When the pipeline is laid, the laying mechanism and the stabilizing auxiliary mechanism are started, and when the pipeline is moved, placed and constructed in a narrow space, through double placing and lifting, the stability and safety of construction operation can be improved, the device can further adapt to the narrow construction environment, and the efficiency of the construction operation is improved.

The present application relates to the field of pharmaceutical preparations, in particular to a long-acting eye composite preparation for improving the symptoms of blepharitis. The preparation comprises a combination of two active ingredients in a therapeutically effective amount, and one or more ion-sensitive polymers or their complex systems, which are used to treat the symptoms of blepharitis caused by Demodex through a special double-cavity drug delivery bottle. By using a specific ion gel matrix concentration and regulating the viscosity of the drug solution before it reaches the eye, the limitations of traditional eye preparations are overcome, the retention time of the drug in the eye is prolonged, the bioavailability is improved, the probability of adverse events is reduced, and the medication compliance is increased.

The invention relates to the technical field of hydraulic engineering, in particular to a backflow surface velocity field algorithm. Through a particle image velocity measurement technology and in combination with an advanced image processing algorithm, automatic identification and tracking of a complex flow state of a Three Gorges change backwater area are realized. Through key technologies of image preprocessing, feature point matching, flow field interpolation and the like, visual display of a flow velocity vector diagram, the flow velocity and the flow velocity direction can be provided, so that powerful technical support is provided for reservoir operation management, ship navigation safety guidance, environment monitoring and scientific research; besides, the provided backflow surface velocity field algorithm not only can improve the flow state identification capability of the Three Gorges Reservoir, but also is expected to be popularized to other large-scale water conservancy projects and applied to ship navigation safety guidance, and has wide application prospects and commercial values.

The utility model discloses a feeding support assembly of a hydraulic plate shearing machine, relates to the technical field of hydraulic plate shearing machines, does not need to manually support a metal plate to move, is low in manual labor intensity and effectively solves potential safety hazards, and comprises two sets of main frames and secondary frames, and one sides of the main frames and one sides of the secondary frames are movably connected with adjusting assemblies; a reinforcing assembly is welded between the main frame and the secondary frames, an attaching seat is welded between the two secondary frames, a supporting frame is welded to the lower portion of the main frame, and an inclined frame is welded to one side of the supporting frame; the first strip-shaped frame and the second strip-shaped frame are movably connected to the interiors of the main frame and the secondary frame correspondingly, according to the size of a metal plate, after a handle is held to pull outwards or push inwards, the distance is adjusted, two sets of inserting rods are inserted into inserting grooves in the first strip-shaped frame for limiting, corresponding adjustment can be conducted according to the size of the metal plate, and the overall limitation is high; the use is convenient.

The utility model belongs to the field of monitoring devices, and particularly relates to a water quality real-time dynamic monitoring device which comprises a base and a monitoring and adjusting device, the monitoring and adjusting device is provided with a mounting plate, the bottom of the mounting plate is fixedly provided with a guide rail, one side of the guide rail is movably provided with an electric sliding block, the bottom of the electric sliding block is fixedly provided with a movable plate, the bottom of the movable plate is fixedly provided with a servo motor, and the bottom of the movable plate is fixedly provided with a plurality of supporting plates. A guide roller is movably mounted on one side of the plurality of supporting plates in a penetrating manner; through cooperation of a guide rail and an electric sliding block, the electric sliding block generates electromagnetism on the guide rail through alternating current to achieve horizontal sliding, the bottom of the electric sliding block drives a movable plate to perform corresponding displacement, the movable plate moves to move the lifting position of the water quality monitor, and the function of monitoring position adjustment is achieved; the problem that water quality detection at different water levels cannot be stably carried out when obstacles such as garbage exist underwater is solved, and the overall working adaptability is improved.

The invention discloses an iron tower piece continuous machining punching device, and relates to the technical field of metal machining punching, the iron tower piece continuous machining punching device comprises a machining platen, a working frame head and a fixing mechanism are installed at the top end of the machining platen, the fixing mechanism comprises a placing notch and a movable clamping plate, and the placing notch is formed in the middle of the top end of the machining platen. When punching operation is carried out, the fixing mechanism is started to trigger the discharging auxiliary mechanism and the punching mechanism, during punching operation, to-be-machined parts of different sizes can be fixed, metal waste clamped at the bottom end of the punching end can be discharged after punching, the efficiency when the punching end is reused in the later period is improved, and the punching efficiency is improved. The problems that during punching operation, metal waste is clamped at the bottom of the punching end after punching is completed, normal punching cannot be conducted and punching operation cannot be completed due to the fact that resistance is too large during punching operation in the later period, the bottom of the punching end needs to be manually treated, and the working efficiency is reduced are solved.

The utility model relates to the technical field of chemical fiber yarn disc defect detection equipment, in particular to a chemical fiber yarn disc inner supporting type clamp which comprises a grabbing part, a telescopic part and a rotating part, and the grabbing part, the telescopic part and the rotating part are used in cooperation to achieve the grabbing telescopic and rotating functions. According to the utility model, an internal supporting type clamping mode is adopted, so that extra damage to the chemical fiber scroll is effectively avoided; the supporting claw structure with the protruding points can be in multi-point contact with the inner wall of the paper tube after being opened, clamping friction force is improved, clamping stability is guaranteed, the paper tube deformation risk is reduced, meanwhile, the control capacity of the clamp for a scroll in the rotating process is improved, and the clamping device is particularly suitable for occasions needing high-precision image collecting and positioning. Through cooperation of the grabbing part, the telescopic part and the rotating part, the rotating part drives the whole to rotate, the telescopic part controls stretching, and the grabbing part is responsible for grabbing a scroll and is used for stably clamping the scroll during detection.

The utility model provides a placing device for automobile door processing, and belongs to the technical field of automobile door placing. The placing device for automobile door machining comprises an installing frame and a fixing frame, a placing mechanism comprises an assembling rod and an installing rod, and the assembling rod and the installing rod are both fixed between the installing frame and the fixing frame. Therefore, when automobile doors of different sizes need to be placed, the automobile doors of different sizes can be placed on the top of a placing table in the placing mechanism, then threaded rods on a limiting frame and a fixing frame are taken out, and then the position of a connecting rod can be adjusted by moving a fixing rod; the automobile doors with different sizes can be limited by rotating the limiting frame and the threaded rod on the fixing frame, and then the position can be fixed by rotating the limiting frame and the threaded rod on the fixing frame, so that the automobile doors with different sizes can be clamped, and the use limitation is improved.

The invention discloses a kiwi fruit container seedling raising early-maturing-promoting cultivation method, and relates to the technical field of kiwi fruit cultivation, and the technical scheme is characterized in that Jiangxi red soil, an organic fertilizer, peat, chaff, perlite and vermiculite are mixed according to a specific proportion to form a substrate suitable for kiwi fruit growth; the scions of the grafted kiwi fruit seedlings are soaked in a 1.2% cyanamide solution, and the scions are taken out after being treated for a certain time; putting the treated grafted seedlings into a nutrition bowl, placing the nutrition bowl in a heat preservation shed, controlling the temperature in the shed, and promoting the scions to germinate in advance; after the scions germinate, conventional seedling culture management is carried out until the kiwi fruit seedlings reach the standard of high-quality seedlings. According to the method, the formula matrix based on specific red soil in Jiangxi is used, greenhouse covering heat preservation and 1.2% cyanamide agent treatment are combined, early germination of kiwi fruit scions can be effectively promoted, and the high-quality seedling rate of half-year seedlings and one-year seedlings of kiwi fruits is remarkably increased.