829results about How to "Improve fineness" patented technology

The invention relates to the technical field of unmanned aerial vehicles, in particular to a flight mission planning and management system and method for cooperation of multiple unmanned aerial vehicles, and the method comprises the steps: decomposing a flight region of an unmanned aerial vehicle based on a flight mission of the unmanned aerial vehicle, and dividing the flight region; path planning is carried out in the flight area of the unmanned aerial vehicle, global flight path planning is carried out by adopting a genetic algorithm, and local flight path planning is carried out by adopting an A * algorithm after the global path planning; an obstacle avoidance strategy of the unmanned aerial vehicle in the flight process is constructed, and after the obstacle avoidance strategy is triggered, local flight path planning is carried out again; according to unmanned aerial vehicle flight task constraints, a priority judgment criterion of multiple unmanned aerial vehicle tasks is formulated, and unmanned aerial vehicle resources are allocated and dispatched. The intelligent level of unmanned aerial vehicle task planning can be remarkably improved, the adaptability to complex environments is enhanced, flight safety and efficient task execution are ensured, and a landing technical support is provided for actual application of the unmanned aerial vehicle.

The invention discloses a coastal port pile foundation structure load calculation method based on a coupling mode, and the method comprises the steps: a hydrodynamic module which evaluates the load and mechanical properties of a port pile foundation structure under different environment conditions; the water power module at least comprises an atmospheric mode module, a sea wave mode module, an ocean mode module and a coupler module; wherein the coupler module exchanges and synchronizes data among the atmosphere mode module, the sea wave mode module and the ocean mode module; the data conversion module is used for converting the wind field data, the wave field data and the flow field data obtained by the hydrodynamic force module into aerodynamic force and hydrodynamic force input files of the pile foundation structure; the finite element analysis module is used for receiving the aerodynamic force and hydrodynamic force input files, establishing a port pile foundation structure model and calculating stress distribution and displacement response of a pile foundation structure, and simulation results output by the finite element analysis module include but not limited to a stress nephogram, displacement field distribution and a buckling phenomenon of a pile foundation.

The invention provides an intelligent statistical analysis method and system for the implementation progress of a production project, and the method comprises the steps: carrying out the initial classification of all task lists in the production project, and constructing a directed acyclic task graph according to the initially classified task lists to represent the dependency relationship between tasks; performing data acquisition on the execution state of the task according to the initial monitoring granularity of each task, and judging whether the actual progress of each task deviates from the planned progress or not according to the acquired data; behavior data of each project role is collected, then the behavior deviation of each role is calculated based on regularization, the cooperation efficiency among the roles is calculated according to the behavior deviation of each role, and then task allocation and progress management are dynamically adjusted. Re-optimizing the task priority and resource allocation according to a dynamic adjustment result; and feeding back to a project manager after the optimization task is executed, and providing intelligent decision support. The system has higher intelligence and real-time reaction capability.

The invention discloses a damage effect evaluation system and method based on a large model, and relates to the technical field of nuclear explosion damage, computational grids adapting to different complexities are generated based on a self-adaptive grid technology, a computational domain is determined and the grids of a complex terrain area are refined by introducing a high-precision three-dimensional terrain model, and the damage effect evaluation method based on the large model is obtained. The local simulation precision is improved; meanwhile, a thicker grid is used in a simpler area, so that computing resources are saved, and the fineness of the model and the simulation accuracy are remarkably improved; through multi-scale coupling and multi-physics field coupling technologies, macroscale CFD simulation and microscale DEM simulation are combined, and thermal effect, radiation effect and structural mechanics coupling simulation are introduced; comprehensively analyzing shock waves, heat conduction, radiation propagation and comprehensive influences thereof on buildings and terrains; and the comprehensiveness and accuracy of evaluation are improved, so that the evaluation result has more practical significance.

The invention belongs to the technical field of image processing, and discloses a transformer fault detection method based on an improved YOLOv8 model. Aiming at the problems of inaccuracy in feature extraction, low precision, poor real-time detection capability and the like existing in fault detection of a traditional transformer fault detection method, the invention establishes a transformer fault detection model based on an improved YOLOV8 model architecture, a self-calibration convolution defogging module is introduced, a generative adversarial network (GAN) and a multi-source data fusion network structure are added, a BiFPN structure is used, an ASPP module is replaced by an ASPFCSPC module, and a YOLOV8 model architecture is improved, so that the feature extraction capability of a transformer fault detection model is enhanced, the calculation complexity of the model is reduced, and the fault detection efficiency of the transformer is improved. The transformer fault detection precision, accuracy and real-time detection capability are improved, and the stability and adaptability of the model are enhanced.

The invention relates to the technical field of data processing, and discloses an ocean current simulation method and system based on a three-dimensional temperature-salinity value. The method comprises the following steps: carrying out line calculation and adaptive mesh refinement processing on a three-dimensional temperature and salt field simulation model to obtain a model operation scheme; performing three-dimensional visualization processing on the three-dimensional temperature and salt field initial data set and the model operation scheme to obtain dynamic three-dimensional temperature and salt field visualization data, and analyzing the dynamic three-dimensional temperature and salt field visualization data to obtain three-dimensional structure data and evolution process data of the key ocean phenomenon; performing data assimilation processing on the multi-source real-time observation data, the three-dimensional structure data and the evolution process data to obtain a fusion data set; and performing ocean current prediction calculation on the fused data set to obtain a three-dimensional ocean current prediction field, and performing uncertainty quantitative analysis on the three-dimensional ocean current prediction field to obtain ocean current simulation probability distribution data. According to the invention, the accuracy and timeliness of ocean current simulation based on the three-dimensional temperature-salinity value are improved.

The invention provides a face sketch synthesis method and system based on perceptual loss, and relates to the technical field of image processing, the quality of face sketch synthesis is improved by introducing a strategy based on perceptual loss, high and low frequency features of a face image are extracted by adopting a VGG19 network, and weighted fusion of cross-resolution features is realized through an NSRM module. Therefore, the details and overall perception of the facial features are effectively captured and reserved on different scales, the fineness of the image is improved on the local details, the consistency and the natural sense of the image are enhanced on the global features, the distance between the generated image and the real image in the feature space can be better matched by using the perception loss, and the image quality is improved. And comprehensive optimization is carried out in combination with various losses such as adversarial loss and spectral consistency loss, so that the parameters of the generator and the discriminator are adjusted more efficiently in the training process.

The invention relates to a high-voltage cable intelligent inspection method and system based on multimode identification, and the method comprises the steps: deploying an intelligent identifier and cable monitoring equipment according to the equipment characteristics and environmental conditions in a high-voltage cable line; reading identification data of the intelligent identification through a double-frequency reading device, and collecting cable state monitoring data through a cable monitoring device; the information is uploaded to the Internet of Things cloud platform; carrying out fusion analysis on the received data in the cloud platform, evaluating the health condition of the cable in combination with a historical record and a fault recognition model, and generating an inspection result; and displaying the inspection result through the intelligent monitoring center, calculating the risk score of each device according to the identification data, the cable state monitoring data and the fault risk prediction result, and dynamically adjusting the optimal inspection route and the inspection frequency. Compared with the prior art, unique identification and multi-dimensional information storage of the cable and accessory equipment of the cable are achieved, and the fineness and comprehensiveness of cable operation state monitoring are improved.

The invention provides an exercise risk dynamic identification system for a cardiac patient, and relates to the technical field of data processing. A user side; the server comprises a reference data matching module which is used for receiving the pre-exercise type and the pre-exercise duration, and analyzing the index by combining the body detection information and the environment temperature to obtain a reference index interval; the reference data verification module sends the reference index interval to the medical node to obtain a verified index interval; the alarm end comprises a dynamic comparison module used for carrying out risk analysis on the detection value based on the approved index interval to obtain risk levels; and an early warning device. By means of the exercise risk monitoring method and device, the technical problems that due to the fact that traditional exercise risk monitoring equipment usually conducts monitoring and early warning based on a fixed threshold value, the phenomena of erroneous judgment and missed judgment frequently occur, and the accuracy and reliability of monitoring and early warning are poor can be solved, the target of accurate monitoring and early warning can be achieved, and the effect of effectively guaranteeing the exercise safety of a patient is achieved.

The invention belongs to the technical field of live-action three-dimensional model construction, and particularly relates to a live-action three-dimensional model construction method based on ground multi-source heterogeneous point cloud fusion. The method comprises the steps of unmanned aerial vehicle image acquisition and three-dimensional modeling, ground multi-source heterogeneous point cloud data acquisition, ground multi-source heterogeneous point cloud registration, ground fusion point cloud processing, and unmanned aerial vehicle image three-dimensional model and ground fusion point cloud space registration and fusion modeling. According to the method, the unmanned aerial vehicle image and the ground multi-source heterogeneous point cloud are fused, so that the problem of detail missing in large-range scene modeling is solved. The high precision of the ground point cloud and the wide coverage of the unmanned aerial vehicle image are combined, and the integrity and fineness of the model are significantly improved. In addition, the point cloud color endowing technology enhances the sense of reality of the model, and provides efficient and reliable technical support for the fields of smart cities, cultural heritage protection and the like.

The invention relates to the technical field of film processing, and particularly discloses a plastic film processing waste recovery device which comprises a recovery box, a feeding port is formed in the top end of the recovery box, and the recovery box comprises a primary crushing mechanism used for primary crushing and a cleaning mechanism used for preventing winding. In the using process, through mutual cooperation of the primary crushing mechanism and the secondary crushing mechanism, waste materials can be further crushed into smaller shapes, gradual refining treatment on the waste materials can be achieved in a multi-stage crushing mode, the crushing uniformity and fineness are improved, the quality of recycled products is improved, and the recycling efficiency is improved. Through mutual cooperation of the primary crushing mechanism and the cleaning mechanism, waste remaining in notches between the crushing teeth can be scraped away in time, so that cleanliness between the crushing teeth is kept, it is guaranteed that the crushing rollers can continuously and efficiently conduct crushing work, normal operation of equipment is guaranteed, the shutdown maintenance time is shortened, and the production efficiency is improved. And the working efficiency and the reliability of the device are improved.

The invention belongs to the technical field of point cloud semantic segmentation, and discloses a power corridor laser point cloud semantic segmentation method and system collected by an unmanned aerial vehicle, and the method comprises the steps: collecting laser point cloud and image data; reconstructing point cloud data based on the image data to obtain an image point cloud, performing spatial registration on the laser point cloud and the image point cloud, and projecting the registered laser point cloud onto the image; operating the image data to obtain a depth image and a normal image, and performing fusion operation on the depth image, the normal image, the image and the projected laser point cloud to obtain multimode fusion data; and carrying out two-dimensional semantic segmentation on the multi-mode fusion data, and carrying out back projection operation on a segmentation result to obtain a three-dimensional point cloud semantic segmentation result. According to the method, the visible light image of the power corridor and the laser point cloud data are fused, high-precision semantic segmentation of the laser point cloud is realized by using the appearance information contained in the visible light image, and the accuracy, efficiency and fineness of semantic segmentation of the laser point cloud of the power corridor are improved.

The invention belongs to the field of food processing equipment, and particularly relates to a meat paste making device for food processing, which comprises a base plate and the like, the base plate is an assembly carrier of the device, the two supporting columns are symmetrically and fixedly connected to the base plate, the supporting seat is installed on the two supporting columns in a sliding mode, and a plurality of limiting blocks are annularly arranged on the top face of the supporting seat at intervals. The discharging barrel is placed on the supporting seat through the limiting block, an opening is formed in the top of the discharging barrel, and the discharging barrel is a muddy meat making container; the hammering mechanism is arranged at the upper parts of the two supporting columns, and the hammering mechanism is used for hammering meat paste in the discharging barrel. Minced meat is hammered alternately through two hammering blocks in the hammering mechanism, the making efficiency of the minced meat in the discharging barrel is effectively improved, the discharging barrel can be gradually lifted along with hammering of the minced meat in cooperation with the lifting mechanism, it is ensured that the hammering blocks can effectively act on the minced meat in the whole hammering process, and the problem that hammering is not in place is avoided.

The invention relates to a cloth flaw detection method based on high-frequency feature constraint and edge entropy minimization, and the method comprises the steps: 1, collecting a flawless and abnormal cloth training picture data set, carrying out the initialization of hyper-parameters, and carrying out the initialization and fine adjustment of model parameters; 2, randomly sampling an image sample x, obtaining vector quantized image features through a feature encoder, generating flaw noise through an anomaly generator, adding the flaw noise into original features of an image, respectively inputting features with anomalies into an image reconstruction decoder and an image restoration decoder, and carrying out image reconstruction; and reconstructing an abnormal image and an abnormal image respectively, and the like. The detection method has the advantages that the high-frequency feature constraint module and the edge entropy minimization module are introduced, so that the cloth defect anomaly detection accuracy is remarkably improved; and the high-frequency feature constraint module converts the real image and the reconstructed image into frequency domain representation by using discrete Fourier transform.

The invention discloses a tea leaf crushing device for tea leaf production, and relates to the technical field of tea leaf production, the tea leaf crushing device comprises a barrel, a material box is arranged on one side of the top of the barrel, a positioning rod is fixedly connected to the top of an inner cavity of the barrel, a crushing assembly is arranged at the bottom end of the positioning rod, a driving rod is rotatably connected to the positioning rod, and a discharging assembly is arranged at the bottom end of the driving rod. According to the tea leaf crushing device for tea leaf production, through linkage of the driving gear driven by the servo motor, the gear ring, the self-rotating gear, the crushing cutter and other components, the cutting speed and frequency of the crushing cutter are improved, the cutting path is complex and changeable, hard parts and irregular shapes of tea leaves can be more effectively penetrated, and the tea leaf crushing effect is improved. And the time and energy required by crushing are greatly reduced, and the crushing efficiency is remarkably improved.

The embodiment of the invention discloses an action video generation method, a related device and a medium, and the method comprises the steps: obtaining a target audio associated with a target virtual character, and coding the target audio into a target audio feature; target guide content associated with the target virtual character is obtained, the target guide content and a preset prompt text are input into a preset large language model for text prediction, at least one semantic tag used for describing the target virtual character is generated, and the semantic tag is encoded into a semantic tag feature; de-noising the preset noise feature by using a diffusion model according to the target audio feature and the semantic tag feature to obtain a target action sequence; and generating a target action video of the target virtual character based on the target action sequence. According to the method and the device, the action data better conforming to the characteristics of the virtual character can be generated, the fineness and the accuracy of the generated action data are improved, and the method and the device can be widely applied to scenes such as virtual character modeling and virtual character driving.

The invention provides a function adaptive test method and system for an electro-tricycle controller, and relates to the technical field of tricycle function test, and the method comprises the steps: carrying out the scene analysis according to a road surface impact factor and an environment impact factor, and constructing a plurality of scene parameter groups; performing simulation modeling according to the vehicle attribute information and the plurality of scene parameter groups to generate a plurality of driving twin models; executing vehicle load simulation by using the plurality of driving twinborn models to meet a predetermined performance index and a predetermined risk threshold as a constraint, and determining a plurality of maximum adaptive loads; and constructing a scene-load matching library to execute a subsequent freight task. According to the invention, the technical problem that the maximum load of the tricycle cannot be accurately analyzed in combination with an application scene in an existing freight tricycle function test method, so that the adaptation degree of the maximum load and the scene is low, and the freight safety of the tricycle is influenced can be solved, and the purposes of ensuring the operation stability and safety of the tricycle and goods and improving the freight safety are achieved. And the service life of the vehicle is prolonged.

The invention discloses an underground diaphragm wall steel bar lap joint bending resistance calculation method based on big data, and belongs to the technical field of underground engineering design. In order to solve the problems that the condition change of a construction site is difficult to respond in real time, the construction parameters are difficult to dynamically adjust and the complex construction environment is difficult to adapt, the data set quality and the bending resistance prediction precision are effectively improved through multi-source data acquisition and key feature screening, and a physical prediction model of a steel bar lap joint is established. According to the method, factors such as stress transmission and binding power are comprehensively considered, so that the model has good adaptability under different working conditions, model parameters are dynamically adjusted, the model responds to changes of environments and construction errors in real time, the weight is automatically adjusted when monitoring data fluctuates, accurate prediction of the bending resistance is achieved, potential failure risks are effectively prevented, and the construction quality is improved. And a failure mode pre-judgment and multi-level risk management mechanism helps a construction team to quickly identify a high-risk area and flexibly adjust a construction scheme.

The invention provides a digital twin city construction and operation optimization method based on cloud computing and a big data technology. The method comprises the following steps: optimizing layout of various sensor devices through a particle swarm optimization algorithm and an adaptive sampling algorithm, and adjusting acquisition frequency; establishing a distributed database, and realizing uniform distribution and efficient access of data in the distributed database through a load balancing algorithm; mining a time rule of urban operation by using a time sequence model, and discovering association between different data; a city model is constructed by using a city three-dimensional live-action fusion modeling method which takes unmanned aerial vehicle oblique photography as a main part and takes ground laser radar as an auxiliary part, different areas in a city are identified by applying a machine learning method, and a refined model of each field of the city is constructed; real-time simulation of a city operation state is realized through virtual reality and augmented reality technologies; the system is continuously optimized by using an online learning algorithm, so that the system continuously learns and adapts to a new data mode in the operation process, and the construction and operation optimization capability of the system is improved.

The invention discloses an intelligent directional and quantitative smell generation method in virtual reality olfaction interaction, and relates to the technical field of virtual reality. The invention provides an intelligent, directional and quantitative smell generation method in order to solve the technical problems that in smell generation work in virtual reality in the prior art, the variety and generation precision of smell are limited, an accurate smell concentration control mechanism is lacked, and interactive linkage with user actions and a virtual environment is lacked. In combination with an odor molecule dynamic combination technology, a deep learning prediction model, closed-loop concentration control and a spatial orientation transmission system, richer, personalized and immersive olfactory interaction experience is provided. Comprising a smell synthesis module, a digital smell control unit, an intelligent smell prediction model, a directional smell transmission system and a virtual wind field simulation module. The method is suitable for being applied to the work of intelligent directional and quantitative smell generation in virtual reality olfaction interaction.

The invention discloses a map generation method and device, a medium, equipment and a computer program product, and the method comprises the steps: receiving a target image for generating a map, and obtaining a three-dimensional model corresponding to the target image; rendering the three-dimensional model based on a plurality of preset rendering angles to obtain a rendering normal view of the three-dimensional model at each rendering angle; generating a normal feature and a physical rendering feature corresponding to the three-dimensional model at each rendering angle based on the rendering normal view, the target image and an image generation model; the vertexes of the three-dimensional model are updated based on a target normal view corresponding to the normal features, an updated target three-dimensional model is obtained, and the vertexes corresponding to the target normal view are the same as the vertexes corresponding to the target three-dimensional model; and generating a target UV map corresponding to the target three-dimensional model based on the target three-dimensional model and a target view corresponding to the physical rendering feature.

The invention provides a combined fleet intelligent early warning method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining fleet navigation data, route sea condition data and cargo state data of a fleet, calculating the shaking angle of a ship body when the ship passes through a preset route according to the fleet navigation data and the route sea condition data, and calculating the cargo state of the ship according to the calculated shaking angle; according to the ship body state data and the cargo state data, the cargo gravity center position is determined, the gravity center deviation between the cargo gravity center and the ship gravity center is obtained, and the cargo stability of the cargo is calculated. Analyzing whether the cargo has a risk of leaving the storage position, obtaining a cargo risk assessment result, identifying a high-risk leg on a preset route and the cargo with potential safety hazards, generating early warning information, avoiding the high-risk leg, adjusting the preset route, and generating a safe route. Intelligent early warning can be carried out according to the sea condition data.

The invention discloses a rock mass fracture prediction method and device and a storage medium. A deep learning technology is utilized to accurately predict rock mass fractures. According to the method, data continuity is optimized by constructing a data set and applying an image interpolation algorithm, and then learning and verification are performed by using a space-time prediction network. The network captures the spatial and time dependency relationship between the feature maps through a self-attention mechanism, and realizes accurate capture of the dynamic change of the fracture. The technology not only improves the prediction precision and efficiency, but also significantly improves the resolution.

The invention provides a hollow slab internal mold construction system, and relates to the technical field of building construction. A first construction result acquisition module; the initial construction parameter optimization module is used for scanning the first construction result through a laser scanner, analyzing and determining first concrete compactness deviation and first construction deviation, optimizing initial construction parameters and determining first optimal construction parameters; and the construction operation module is used for executing the construction operation of the second pouring interval according to the first optimal construction parameters until the preset construction period is completed. By means of the method, the technical problems that in an existing method, due to the fact that accuracy and timeliness of construction parameter regulation and control are insufficient, overall construction errors are seriously accumulated, and overall construction quality is affected can be solved, pouring parameters and vibration parameters can be rapidly and accurately adjusted, construction management and control fineness and intelligence are improved, and construction efficiency is improved. Therefore, the problem of construction regulation lag is effectively solved, and the construction precision and the construction quality are remarkably improved.

The invention relates to a vehicle abnormal position correction method, system and device based on road network position information and a medium, and the method comprises the steps: collecting and processing road network map information, tracking a vehicle position, and storing the vehicle position as a historical position point set; when the number of the historical position points exceeds a set threshold value, whether the vehicle is in an abnormal deviation state or not is judged according to the scene where the vehicle is located and the relative position relation between the vehicle and the road and road section range; if the vehicle is in the abnormal deviation state, acquiring a latest position point from a historical position point set, and predicting and covering the position of the vehicle; if not, front and back position abnormal state identification is carried out; and when the front and back positions are identified to be abnormal, obtaining the latest position point from the historical position point set, and predicting and covering the position of the vehicle. According to the invention, by fully utilizing and fusing a plurality of data sources, designing an innovative judgment rule and adopting a refined exception handling mode, the accuracy of vehicle position judgment and the fineness of exception handling are remarkably improved.

The invention relates to the technical field of transient heat conduction, in particular to a composite material transient heat conduction and thermal stress simulation method based on a two-dimensional arbitrary polygon hybrid finite element, which comprises the following steps: S1, determining an analysis model and material attributes, and establishing a transient heat conduction basic equation including boundary and initial conditions; s2, constructing and expanding a generalized variational functional, processing boundary conditions in combination with a Lagrange multiplier method, and discretizing a solution domain into a plurality of independent units; s3, adopting hypothetical temperature field, heat flux field and thermal stress field functions, introducing a discrete finite element format, and deducing a corresponding finite element equation from a functional; and S4, solving a transient temperature field through programming, introducing the transient temperature field into stress analysis, and finally obtaining temperature and stress distribution of the material at different time points. According to the method, temperature distribution and thermal stress of transient heat conduction are solved by hybridizing heat flux finite elements, and a new way is provided for transient heat conduction and thermal stress analysis of the composite material.

The invention relates to the technical field of electricity meter scrap treatment, and discloses an electricity meter scrap crushing and sorting treatment device which comprises a machine body, a motor is fixedly connected to one side of the machine body, two crushing rollers are rotatably connected to the top in the machine body, and a first circular gear is fixedly connected to the side, away from the motor, of each crushing roller; the output end of the motor is connected with one of the crushing rollers, the two first circular gears are meshed, a rolling assembly, a separating assembly and a screening assembly are sequentially arranged in the machine body from top to bottom, a transmission assembly and a reciprocating assembly are arranged on the outer wall of the machine body, the rolling assembly comprises a rotating shaft, a rolling box and a fixing plate, and the rotating shaft is connected with the rolling box. And the rotating shaft is rotationally connected to the inner wall of the machine body. And through cooperation of the rotating shaft, the first bevel gear and the second bevel gear, the rolling rollers generate periodic left-right rolling action in the rolling box, the crushed materials are subjected to secondary rolling, and the particle size of the materials is refined.

The invention belongs to the technical field of waste gas treatment, particularly relates to a dust removal, desulfurization and decarbonization absorption and desorption device for ship tail gas and a use method of the dust removal, desulfurization and decarbonization absorption and desorption device, and aims to overcome the defects that in the prior art, when gas is treated, the gas cannot be detected and cannot be secondarily treated. A first treatment tank and a second treatment tank are fixedly mounted at the top of the base, the first treatment tank is located on one side of the second treatment tank, a first mounting cover is fixedly mounted on the inner wall of the top of one side of the first treatment tank, one side of the first mounting cover extends to the outer side of the first treatment tank, and one side of the first mounting cover fixedly communicates with an air connecting pipe; after the gas is treated, the treated gas can be detected, and if the treated gas does not reach the emission standard, the gas can be subjected to secondary treatment, so that the quality of the discharged gas reaches the emission standard.

The utility model discloses a two-stage coal blending system based on coking coal grading and grading crushing, and belongs to the technical field of coal storage and blending. The coal blending system comprises a hard coal silo, a two-stage screening and crushing mechanism, a coal blending bunker and a coal bunker, a discharging port of the hard coal silo is connected with a feeding port of the first-stage screening and crushing mechanism through a belt, and a discharging port of the first-stage screening and crushing mechanism is connected with a feeding port of the coal blending bunker through a belt; a discharging port of the coal blending bin is connected with a feeding port of the second-stage screening and crushing mechanism through a belt, and a discharging port of the second-stage screening and crushing mechanism is connected with a feeding port of the coal bin through a belt. By adopting the coal blending system disclosed by the utility model, the characteristics of various coals are effectively utilized, and various coking coals are matched according to a proportion, screened and then crushed, so that the mixing uniformity of the coals is improved, the phenomenon of coarse coal leakage in the coal blending process is improved, the coke quality is improved, and the coal blending cost is also reduced.

The invention belongs to the field of machining, and discloses an aviation gear part cleanliness control method, which comprehensively identifies and classifies cleanliness risk points in the whole machining process, and divides the cleanliness risk points into risk points of three key stages of pretreatment, intermediate treatment and packaging. In the pretreatment stage, initial pollution is effectively removed through polishing and oil stain particle cleaning; in the intermediate treatment stage, ultrasonic cleaning is combined with finishing machining to deeply clean and protect the surfaces of the parts, and meanwhile, a part box protective tool is adopted to ensure that secondary pollution in the turnover process is minimized; before packaging, the final cleanliness is ensured through demagnetization, residual magnetism inspection and a three-step cleaning method, and the grade is strictly evaluated. According to the method, the automation degree and the cleaning efficiency are greatly improved, the cleaning effect is remarkably improved, the cleaning cost is reduced, whole-process cleanliness control from part machining to packaging is achieved, and it is ensured that the cleanliness of aviation gear parts meets the strict requirement of the aviation field.