83 results about "Complex materials" patented technology

The invention provides an intelligent optimization method for inverting new material structure parameters. The method relates to the technical field of material science and engineering structure analysis, and comprises the following steps: S1, acquiring time sequence data and image data of a material under different loading conditions, and preprocessing; s2, constructing a deep diagnosis model: constructing a time sequence feature extractor and an image feature extractor, and respectively extracting time sequence features and image topological structure features; time sequence features and image topological structure features are fused through a stepped mutual attention mechanism; s3, training a neural network based on the fusion feature vector, outputting a final predicted value, and updating network parameters by adopting a residual error-based alternative hyperplane Kaczmarz optimization method and an oblique projection optimization method; and S4, inputting the preprocessed measured data into the trained model, and outputting a material structure parameter inversion result. In this way, rapid inversion of complex material structure parameters is achieved, and the current technical problem is solved.

The invention relates to an intelligent wind power blade defect identification method based on phased array detection, which aims at the anisotropic characteristic of a wind power blade glass fiber reinforced composite material, and can flexibly adjust the sound beam angle, effectively penetrate through the material and inhibit the scattering of an ultrasonic signal through a low-frequency linear array probe with characteristic parameters and an electronic focusing technology. Defects in different directions such as impurities perpendicular to layers, cracks in the fiber direction, wrinkles and the like can be accurately detected, meanwhile, by combining wavelet packet transformation noise reduction and a feature extraction algorithm, the distinguishing capacity of defect echoes and noise in complex materials is remarkably improved, the method is adaptive to complex structures and material characteristics of wind power blades, the application range of the detection technology is expanded, and the detection efficiency is improved. An ultrasonic phased array detection technology and an intelligent algorithm (a K-means clustering algorithm and a YOLOv8 target detection model) are deeply fused, the limitation that traditional detection depends on manual analysis is broken through, and a full-process automatic detection system of data acquisition, feature extraction and intelligent recognition is constructed.

The invention relates to the technical field of data processing, in particular to a BN-based UHPC mix proportion data analysis method and a strength prediction system.The intelligent level of ultra-high performance concrete mix proportion design is improved by introducing a Bayesian network model and a multi-objective optimization algorithm, and the method comprises the steps that firstly, an enhanced feature set is generated through feature engineering; a nonlinear relationship and a cross-level interaction effect among material parameters are fully excavated, and the characterization capability of the model on a complex material system is enhanced; secondly, the Bayesian network model is combined with causal reasoning and a hierarchical regularization strategy, so that the overfitting risk is reduced while the compressive strength prediction precision is ensured; in the multi-objective optimization link, through dynamic weight adjustment and Pareto frontier search, carbon emission and strength requirements are effectively balanced, and candidate schemes with low carbon and excellent mechanical properties are output; and finally, dynamic evaluation and risk analysis are carried out to further screen out a mix proportion with high stability and strong feasibility, and a reliable decision basis is provided for engineering practice.

The invention belongs to the technical field of food processing equipment, and particularly relates to an intelligent optimization device for a food 3D printing material. According to the device, a multi-mode sensing technology is adopted to automatically monitor mechanical properties and form information of a printing base material, high-resolution image data of extrusion deformation and extrusion form of the material are obtained through an image acquisition device, and key mechanical parameters such as hardness and resilience are rapidly predicted in combination with principal component analysis and a machine learning algorithm; and dynamic matching is conducted according to the real-time monitoring data and a preset printing quality threshold value, and when it is detected that the material characteristics or the printing effect deviates from the optimal interval, the particle swarm optimization algorithm is automatically triggered to optimize the printing parameters, and the execution module is driven to execute the adjustment instruction. The online characterization and closed-loop regulation and control functions of the device replace the subjectivity of tedious processes and manual experience parameter adjustment, the 3D printing process is promoted to span from manual trial and error to data-driven intelligentization, and an efficient and reliable technical scheme is provided for precise additive manufacturing of complex materials such as food and composite materials.

According to the integrally-formed composite material structure based on the three-dimensional printing and casting technology and the preparation method of the integrally-formed composite material structure, the preparation method of the integrally-formed composite material structure comprises the three steps that firstly, three-dimensional printing is conducted on a first metal material to obtain a metal insert, and then aftertreatment is conducted; and finally, the second metal material is heated to be in a molten state, and finally the integrally-formed composite material structure is obtained. According to the method, the 3D printing metal insert is precisely designed to be in butt joint with a traditional casting process, an integrated composite metal structure is formed, and the precision and sealing performance of mold assembly are ensured. And moreover, the complex-shaped material is manufactured through 3D printing, complex material forming which is difficult to complete through a traditional manufacturing process can be achieved, the requirements of different fields for manufacturing the complex-shaped metal material are met, and the limitation of a traditional titanium-aluminum compounding process is broken through. The integrally-formed composite material structure is a material with high precision, high strength and good surface smoothness.

This invention relates to the field of renewable resource recycling and processing technology, and in particular to a renewable resource recycling crushing system and method, comprising a multimodal material characteristic sensing module, a pre-cutting dynamic programming module, a three-level closed-loop control module, a harmonic monitoring module, and a digital twin optimization module. Material characteristics are acquired through multimodal sensing technology, and the cutter head motion trajectory is generated by combining model predictive control. Harmonic monitoring, graded response, and digital twin optimization are used to achieve self-evolution of system parameters. This invention solves or at least mitigates the problem of entanglement and jamming of long strip-shaped materials in the crushing chamber, providing a renewable resource recycling crushing system and method. Through multimodal sensing, dynamic programming, harmonic monitoring, and digital twin optimization, this invention achieves accurate identification and efficient processing of complex materials, reduces the risk of entanglement, and improves equipment operational stability.

The utility model relates to the technical field of blind ditches, and provides an assembly type water seepage and drainage blind ditch which comprises a plurality of main bodies which are connected end to end, and each main body comprises a water drainage pipe used for water drainage after being connected; the support is used for supporting the drainage pipe, one side of the support is provided with an installation hole, the other side of the support is provided with a guide column, and the guide column of the adjacent body is used for sliding into the installation hole of the adjacent body. By means of the technical scheme, the problems that in the prior art, blind ditch composition materials are complex, and each material is not a finished product and needs to be automatically machined or remachined after being purchased are solved.

The application belongs to the technical field of additive manufacturing, and particularly relates to an intelligent 3D printing system, which comprises a rack and a controller, the inside of the rack is provided with a laser printing head and a powder laying mechanism, the powder laying mechanism lays powder, and then the laser printing head melts the powder by laser to complete the action of cladding. The intelligent 3D printing system can utilize forward mapping to output the trained network in seconds or even milliseconds, greatly accelerating the real-time simulation effect of design iteration. Meanwhile, the neural network can replace time-consuming finite element calculation in the optimization process of genetic algorithm, and quickly find the optimal design parameters, thereby achieving the effect of optimization design. On the other hand, the backward mapping is used to quickly and accurately identify the complex material model parameters, which is several times faster than the traditional trial-and-error method, and the input or physical characteristics of the system can be back calculated according to the dynamic response of the structure.

The invention discloses a police robot with a door and window quick forcible entry rescue function, and relates to the technical field of police rescue robots, the police robot comprises a rescue robot, an auxiliary mechanism comprises a positive and negative motor, two semi-circular grooves and a clamp, a cable is wound on a winding wheel, one end of the cable is connected with a detonator, and the other end of the cable is connected with a power source. A V-shaped groove is formed in the surface of each first rectangular block in advance, a V-shaped explosive groove cover is arranged in each V-shaped groove, flexible explosive is arranged in each V-shaped explosive groove cover, a communicating hole is formed in the inner wall of each V-shaped groove in advance, and an electric switch is arranged on the periphery of the winding wheel. By means of the technical scheme, the application range of the police rescue robot can be expanded, the function of quickly breaking and dismantling a door and window with the basic thickness and made of simple materials is achieved, a metal door structure with the thick thickness and made of complex materials can be broken and dismantled, and therefore the use efficiency of the police rescue robot is improved.

The invention discloses a multi-modal fusion material design method and system based on material mechanism constraints, and relates to the technical field of material science and artificial intelligence crossing. According to the system, vertical domain data such as a two-dimensional / three-dimensional structure, a performance index, a cost index, a mass production requirement, an environmental adaptability requirement and a service life requirement of a product are integrated through a multi-modal data input module, and domain rules are converted into quantitative constraints through a material mechanism constraint engine; and then cross-modal feature accurate association is realized through a multi-modal feature fusion module driven by an attention mechanism, and finally, a physical feasible complete design scheme is output by a generative design unit in combination with a multi-objective optimization algorithm. According to the method, the problems of mechanism mismatch and poor process adaptability of a traditional multi-modal model are solved, the development cycle is obviously shortened, the design precision is greatly improved, the development cost and risk of new materials are remarkably reduced in the fields of powder metallurgy and additive manufacturing, and the method is suitable for efficient and innovative design of a complex material system.

The invention discloses an unmanned storage yard intelligent control device for a splitting machine, and relates to the technical field of automatic storage and material carrying, the unmanned storage yard intelligent control device comprises an annular track, and an annular conveyor is arranged on the annular track; under the cooperative arrangement of a plurality of structures such as the adapter A, the adapter B and the plastic column, slitting materials of different specifications, sizes and shapes are conveyed and flexibly adjusted, effective clamping of various materials is achieved, stable clamping is ensured by adjusting the deflection directions of the adapter A, the adapter B and the plastic column and tightly attaching to the contours of the materials, and the clamping efficiency is improved. Compared with the prior art, the method has the advantages that the adaptability to complex materials is improved, the trouble that positioning and stabilizing equipment is frequently replaced due to material specification differences is reduced, production switching is more convenient and rapid under the scene of producing woven bags of various specifications, the overall production efficiency is effectively improved, the large-scale and multi-variety production requirements are met, production interruption caused by equipment adaptation problems is avoided, and the production efficiency is improved. And the continuity of the production process is enhanced.

The present application relates to the technical field of thermal barrier-environment barrier coating materials, and particularly relates to a thermal barrier-environment barrier coating material, a preparation method and application thereof, and a thermal barrier-environment barrier coating and a preparation method thereof.The thermal barrier-environment barrier coating material is a complex material containing rare earth monosilicate and rare earth disilicate; the rare earth monosilicate is monoclinic structure, and the space group is C2 / c; the rare earth disilicate is beta-monoclinic structure and / or gamma-monoclinic structure; the space group of the beta-monoclinic structure is C2 / m; and the space group of the gamma-monoclinic structure is P21 / c.The thermal barrier-environment barrier coating material prepared by the present application is a complex material containing rare earth monosilicate and rare earth disilicate, which has lower thermal conductivity and higher toughness compared with pure-phase double-rare earth silicate, and has higher toughness and lower thermal expansion coefficient compared with pure-phase rare earth monosilicate, and has more excellent performance when applied in the fields of aerospace engines, high-temperature gas turbines and the like.

The invention discloses a deformation failure mode identification method and system for constructing a hybrid rock zone tunnel engineering section. The constructed hybrid rock zone has the characteristics of complex material composition and geological structure and the like, and becomes a complex engineering geological problem and a frequent geological disaster zone faced by tunnel and underground engineering construction. The method comprises the steps that surrounding rock geologic structure types for constructing the hybrid rock zone tunnel are divided; determining five deformation and failure modes of the tunnel section, and establishing a corresponding relationship between each deformation and failure mode and the surrounding rock geological structure type and the auxiliary identification factor; and obtaining tunnel surrounding rock geological information, and according to the established corresponding relation between the deformation and failure mode and the surrounding rock geological structure type as well as the auxiliary identification factor, identifying the deformation and failure mode of the section to be excavated of the tunnel engineering of the constructed hybrid rock zone. According to the method, the geological safety risk in the tunnel construction process of the structural hybrid rock zone can be prevented and solved.

The invention discloses a recycling process of a retired battery. According to the method, through deep fusion of an intelligent dynamic sorting technology, the resource recovery efficiency and the material purity are remarkably improved. The system adopts a multi-source sensing technology to capture physical characteristics and component information of materials in real time, and dynamically optimizes sorting parameters in combination with an adaptive algorithm. For example, for metal particles with different densities, the system automatically adjusts the vibration frequency and the airflow speed, and the problem of metal mixing caused by a fixed sorting mode in a traditional process is effectively solved. And meanwhile, the machine learning model optimizes a sorting strategy library by continuously learning historical sorting data, so that impurity residues in the black powder are greatly reduced, and the production requirements of high-purity regenerated materials can be directly met. The closed-loop regulation and control mechanism breaks through the limitation of static sorting, the efficient and stable sorting performance can still be kept in a complex material scene, and the unit processing energy consumption is remarkably reduced on the premise of guaranteeing the sorting precision by dynamically balancing the relationship between the sorting strength and the energy consumption.

The invention relates to a construction waste resource utilization treatment method which comprises the following steps: performing primary separation on construction waste in a historical remaining stacking point to form garbage with complex material components and garbage with single material components; the garbage with the complex material components is fed into a long-flow process treatment line to be subjected to resourceful treatment; and feeding the garbage with single material component into a short-flow process treatment line for resourceful treatment. According to the arrangement, the material component loaded type garbage and the material component single type garbage can be subjected to a targeted treatment process with high matching performance, and then it is ensured that regenerated products with high purity are sorted out, that is, through scientific classification treatment, on one hand, the sorting precision of the construction garbage is remarkably improved, and the quality of the regenerated products is improved; on the other hand, the two processing lines work synchronously, the processing efficiency is considered and improved, and the comprehensive processing cost is reduced, so that the economical efficiency of project implementation is greatly improved.

This utility model relates to the field of material sorting technology and provides a multi-directional adjustable material sorting device, including a base. The side wall of the base has several first arc-shaped grooves. The base has an internal cavity containing a motor. The motor's output shaft passes through the top surface of the base and is connected to a turntable. One side of the turntable has a second arc-shaped groove. The top surface of the turntable has a material bin, and the bottom surface of the material bin is connected to a discharge pipe that extends into the interior of the second arc-shaped groove. This solution uses a motor to drive the turntable, moving the second arc-shaped groove to different positions of the first arc-shaped grooves, thereby changing the direction of material movement. This meets diverse and complex material sorting needs, avoiding the limitation of existing technologies that only allow for single-direction or fixed-angle material sorting, and greatly improving the flexibility of material sorting.

The invention discloses a hopper loading state monitoring system based on acoustic double-frequency feature extraction and a control method, and the system comprises acoustic double-frequency sensors which are symmetrically arranged at the two sides of the top of a hopper, and the sensors employ a double-frequency alternating excitation mode; the distance between the acoustic double-frequency sensor and the material in the hopper is calculated according to the preprocessed signal, and the filling state is judged according to the distance threshold interval where the calculated distance is located; and the distances from the acoustic double-frequency sensors on the two sides to the materials in the hopper are compared, the weighting index is calculated, and the weighting early warning level of the hopper is determined according to the weighting index threshold interval where the weighting index obtained through calculation is located. The dual-frequency measurement improves the detection reliability of a complex environment and a complex material surface; multiple sensors cooperate to realize synchronous monitoring of the filling degree and the emphasis, so that the accuracy of data monitoring is guaranteed, and accidents are avoided; a grading early warning mechanism for the filling degree and the emphasis level gives consideration to safety and operability, and a manager and a driver can obtain information more visually and judge the severity rapidly.

The present application relates to the field of monitoring equipment, specifically relates to the slope deformation monitoring equipment based on GNSS and use method, including main rod, the outside of the top of main rod is provided with support, the both sides of support are respectively fixed with solar panel and system box through bolt, the top of main rod is provided with GNSS equipment, GNSS equipment is electrically connected with support, solar panel is electrically connected with system box, the bottom of main rod is installed with lower buried fixed rod group, the inside of lower buried fixed rod group is installed with auxiliary fixing assembly, the outside of lower buried fixed rod group is provided with lower buried auxiliary sleeve rod group fixed by auxiliary lower buried fixed rod group, and the main body of buried fixed rod is directly inserted into hole and is quickly docked with main rod through connecting thread sleeve, so that complex material transportation and long-term maintenance are not needed, meanwhile, auxiliary fixing assembly only needs to rotate screw rod through external wrench, so that lateral insertion rod can be driven to complete lateral fixation, installation process does not need professional pouring equipment, and single-point deployment period is shortened.

The application discloses a multi-category material sorting method and device based on AI machine vision and hyperspectrum, relates to the field of renewable resource recycling, and aims to solve the problem of low accuracy in complex working conditions such as same color and different materials when only visible light images are used for sorting materials in related technologies. The method comprises the following steps: obtaining visible light image data and hyperspectrum image data of the material to be sorted; identifying the material according to the visible light image data to obtain a first material category and a category confidence; when the category confidence is low or the first material category belongs to a preset easily confused category set, hyperspectrum analysis is enabled, and a second material category of the material is determined according to corresponding spectral feature data of the material as a final identification result; otherwise, the first material category is directly taken as an identification result, and finally, a sorting instruction is generated. Through intelligent cooperation of AI machine vision and hyperspectrum technology, simple materials can be quickly identified, and complex materials can be accurately distinguished, so that high-precision and high-throughput material sorting are realized.

The utility model relates to the related technical field of silicon material processing, in particular to an efficient silicon material soaking device which comprises a frame body, a material soaking box is arranged at the bottom of the frame body, a lifting mechanism is arranged in the frame body, and an auxiliary material soaking mechanism is arranged in the material soaking box. Through the arrangement of the lifting mechanism, the inclined material pouring function of the material soaking basket is achieved through the cooperative movement of the first electric telescopic rod and the second electric telescopic rod, manual carrying or other complex material pouring equipment is not needed, after soaking is completed, only the movement of the electric telescopic rods needs to be controlled, and material pouring is completed. The material soaking basket is driven to incline through sliding of a second connecting bolt in a sliding groove and the rotation relation between connecting pieces, operation is easy and convenient, an auxiliary material soaking mechanism makes full contact with silicon materials in the material soaking basket through fine round holes in the surface of a leakage pipe, the leakage pipe can further form different flowing paths, the silicon materials can be evenly scoured and soaked by a solution conveniently, and the service life of the silicon materials is prolonged. And the soaking uniformity is greatly improved.

The present invention discloses a method and apparatus for optimizing dock folding structures based on nonlocal homogenization modeling. The method comprises: establishing a nonlocal heat conduction model based on a three-dimensional homogenization problem with a temperature gradient only in the x-direction; defining a nonlocal homogenization term and using the integration by parts method to convert the nonlocal homogenization term of the x-direction temperature gradient into the form of a temperature difference between two surfaces obtained using a finite element tool, thereby obtaining a simplified model under uniform temperature field conditions; obtaining a heat conduction model that takes into account the effects of width and height; and obtaining an effective thermal conductivity formula based on a metamaterial structure with infinite dimensions in three directions using a multiscale method and periodic boundary conditions, calculating the temperature distribution of the metamaterial structure, and optimizing the metamaterial structure. The method can more accurately simulate and predict the thermal performance of complex materials at the microstructural scale, particularly when considering nonlocal effects, thereby improving the accuracy and practicality of the heat transfer model.

The utility model discloses an automatic magnetizer which comprises a workbench, and a magnetizing assembly and a discharging assembly are arranged on the workbench. The magnetizing assembly comprises a feeding port and a discharging port, and the horizontal plane where the feeding port is located is higher than the horizontal plane where the discharging port is located. The discharging assembly comprises a rolling wheel which is located at the discharging port, and the rolling wheel rotates to drive materials at the discharging port to be discharged. Compared with the prior art, through mutual cooperation of the feeding port, the discharging port and the rolling wheels, magnetizing and discharging of materials are completed, intermittent feeding of a material conveying mechanism is avoided, the moving speed of the materials on the magnetizing machine is increased, then the production efficiency is improved, complex material transferring and discharging mechanisms are omitted, and the production cost is reduced. And the investment cost is reduced.

The invention discloses an atomic feature updating method based on a graph convolutional layer general inter-atomic potential energy model, and belongs to the technical field of chemical and material science combined with a neural network. According to the method, the model can automatically distinguish contribution weights of different atom types to interaction information, the problem of feature confusion in a traditional splicing method is avoided, and therefore the multi-body action law in a complex material system and a distance attenuation weight mechanism designed based on the physical law are more accurately captured, and the attenuation characteristics of inter-atom influences are considered in the Message convergence stage. The injection of the priori knowledge guides the model to learn the physical law, the dependence of the model on the training data volume is reduced, and the generalization ability and stability of the model under the limited data condition are remarkably improved especially in the modeling of a rare material system.

The utility model discloses a kind of ladder type cutters, it is related to gantry shearing technical field.The utility model includes fixed cutter seat and the dynamic cutter seat of slidingly being arranged on gantry, linearly several step parts are equipped in the rear side of dynamic cutter seat, the cross section of step part is right triangle structure, the height of dynamic cutter seat bottom surface is sequentially increased from left to right, sliding edge is equipped in the both sides of dynamic cutter seat, both sides in gantry are equipped with slide rail, two slide rails are staggered distribution in front and back on gantry, dynamic cutter seat is slid up and down in gantry by sliding edge and slide rail, one side surface of step part is parallel with the width direction of gantry.The utility model is presented ladder type structure after being assembled to gantry shear, realizes the partition of cutting point, can reduce the load of hydraulic system, improve service life, simultaneously realized segmented shearing can improve shearing efficiency and effect, and it is suitable for the shearing of complex material and large quantities of material.

The invention relates to a display rack for exhibition arrangement and an assembling method, which can be applied to the exhibition field and other fields. The display rack mainly comprises a display rack body A and a display rack body B which are the same in structure, the display rack body A and the display rack body B are both formed by combining main body frames and suspension systems, and the main body frames are composed of transverse square timbers and vertical square timbers; the display rack A and the display rack B are connected in a penetrating mode, and the two display racks can be combined based on actual requirements through different penetrating modes. The display rack can be extended or combined according to requirements, materials used by the whole structure are environment-friendly, and the product can be mounted without various complex materials and special tools, so that the display rack is convenient to process, simple to assemble, attractive in appearance, multifunctional and diversified, and the purpose of quickly and conveniently arranging an exhibition can be achieved.

The invention discloses a multi-category material sorting method and equipment based on AI machine vision and hyperspectrum, relates to the field of renewable resource recovery, and aims to solve the problem of low accuracy under complex working conditions such as same color and different materials when a related technology only depends on a visible light image to sort materials. The method comprises the following steps: acquiring visible light image data and hyperspectral image data of a to-be-sorted material; identifying a material according to the visible light image data to obtain a first material category and category confidence; when the category confidence coefficient is low or the first material category belongs to a preset easy-to-confuse category set, hyperspectral analysis is started, and a second material category is determined as a final recognition result according to spectral feature data corresponding to the material; and otherwise, directly taking the first material category as an identification result, and finally generating a sorting instruction. Through intelligent cooperation of AI machine vision and the hyperspectral technology, simple materials are rapidly recognized, complex materials are accurately judged, and high-precision and high-throughput material sorting is achieved.

The invention relates to the related technical field of material production, in particular to a premixing device for preparing high-temperature-resistant castable, the premixing device comprises a mixing barrel and a motor, and the outer side surface of the mixing barrel is fixedly connected with supporting legs. According to the premixing device for preparing the high-temperature-resistant castable, through accurate meshing transmission of a first bevel gear, a second bevel gear and a third bevel gear, reverse synchronous rotation of a first stirring blade and a second stirring blade is achieved, compared with a traditional single stirring shaft structure, the stirring blades rotating in the reverse direction can form complex material convective circulation in the mixing barrel, and the mixing efficiency is improved. A single track of material movement is broken through, stirring dead angles are greatly reduced, meanwhile, the design that a first bevel gear and a third bevel gear are the same in size and rotating speed ensures that bidirectional stirring force is balanced, the problem that local materials are excessively or insufficiently mixed is solved, and finally various raw materials of the high-temperature-resistant castable reach extremely high mixing uniformity. And a stable raw material basis is provided for key indexes such as high temperature resistance and strength performance of subsequent castable.

The present application belongs to the technical field of complex materials, and relates to a multifunctional complex material for visual monitoring of ammonia, a preparation method and application thereof.The multifunctional complex material for visual monitoring of ammonia prepared by the present application has a chemical formula of Na2Cu(C6S2O6NH5)2(H2O)2.The present application further provides a preparation method of the multifunctional complex material.The multifunctional complex material prepared has excellent antibacterial performance, ultraviolet absorption performance and reversible ammonia response color change performance, can be reused, and has a simple preparation process, is environment-friendly, is low in cost, is suitable for large-scale production, and has a wide application prospect in the fields of visual monitoring of ammonia, antibacterial materials, ultraviolet absorption materials and environmental safety.

The invention relates to the technical field of unloading equipment, in particular to an auxiliary unloading device of a heavy unloading vehicle, which comprises a support frame, a vibration pushing assembly and an adjusting mechanism. The vibration pushing assembly drives an eccentric wheel to rotate through a driving motor, so that a sliding block reciprocates in a guide groove, a push plate and a vibration plate are pushed to vibrate periodically, and material attachment is prevented. The adjusting mechanism drives a lead screw to rotate through an adjusting motor to adjust the height and angle of the auxiliary scraper to adapt to different material states. The problems that discharging is not thorough, blocking is prone to occurring, and the structural reliability is poor can be effectively solved, and the discharging device is suitable for efficient discharging operation under various complex material states and has high adaptability and practicability.

The utility model discloses a kind of push-up type use chuck's air cylinder, it is related to chuck air cylinder technical field, including cylinder body, chuck of clamping shaft type workpiece is sleeved in the cylinder body, the outer wall of chuck is sleeved with the cylinder barrel seat fixed in the inside of cylinder body.The utility model transports gas in cylinder body by outside air pump, makes push sleeve upwardly rise (clamping) or downwardly lower (loosen), chuck realizes the purpose of clamping to workpiece or material, so that its clamping force is stable, because the position of chuck is fixed, the action of chuck is only clamping or loosening, to ensure that each time mounting position is consistent, and then improve the machining efficiency of workpiece, while the chuck in the inside can be conveniently taken out and replaced corresponding specification use, to reduce use cost, and different push sleeve can be used, replace different forms of standard chuck (for example ER chuck, BT chuck, numerical control lathe chuck and diversification), so that the chuck air cylinder can realize diversification, complex material clamping.