722results about How to "Increase weight" patented technology

The invention discloses a hanging basket transportation safety management method and system, and relates to the field of damage detection. Collecting weight data of the hanging basket; establishing a steel wire rope health state prediction model by using a multi-layer perceptron (MLP) algorithm, predicting the damage degree of the steel wire rope, and obtaining a health state prediction result of the steel wire rope; according to the health state prediction result of the steel wire rope, a bidirectional long-short-term memory neural network BiLSTM is used for prediction, and a damage trend prediction result of the steel wire rope in a future period of time is obtained; comparing the collected weight data of the hanging basket with a preset safety weight range to obtain a judgment result of whether the weight of the hanging basket exceeds the limit or not; according to the health state prediction result of the steel wire rope, the damage trend prediction result and the judgment result of whether the weight of the hanging basket exceeds the limit or not, a decision tree algorithm is adopted to generate a hanging basket operation control scheme; aiming at low safety of a hanging basket in the prior art, the safety of the hanging basket is improved.

The invention discloses an intelligent customer service method for adaptively adjusting an interaction strategy by using reinforcement learning, and the method comprises the following steps: S1, obtaining a natural language text inputted by a user, and generating a multi-dimensional state vector; s2, grouping the users by using a real-time dynamic clustering algorithm, and updating a clustering result; s3, generating an action space in a specific state, and enriching the action space in combination with a rule-based strategy and a learning-based strategy; s4, aggregating neighbor node features through a graph convolutional network, and extracting local features; s5, weighting adjacent node features by using a graph attention network, and dynamically allocating attention weights; s6, carrying out interaction strategy optimization by adopting a spiral ladder type deep exploration network, and optimizing action selection; and S7, combining online learning with an experience playback mechanism, continuously updating an interaction strategy, and making a quick response to dynamically changing user demands. According to the method, reinforcement learning, the graph neural network and the sentiment analysis technology are combined, and intelligent customer service interaction strategy self-adaptive adjustment and optimization are achieved.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle self-adaptive navigation system which comprises an inertial navigation system, a visible light sensor, a data fusion module, a database and a navigation control module. The inertial navigation system provides attitude, speed and acceleration data; the visible light sensor collects an image and obtains environment feature points through deep learning algorithm processing to realize visual positioning; and the data fusion module fuses two kinds of sensor data by using a dynamic weighted Kalman filtering algorithm, and dynamically adjusts the weight according to the environment to optimize the positioning information. The map library and the feature library store environment data to assist in positioning and dynamically update; the navigation control module generates an instruction according to the fused positioning information, and automatically adjusts a flight strategy by considering various factors based on an adaptive control algorithm. The system improves the positioning precision and environmental adaptability, enhances the flight safety and stability, is high in intelligence and autonomy degree, has flexibility and expandability, and can be widely applied to the field of unmanned aerial vehicles.

The invention relates to a micro-grid intelligent safety secondary voltage control method based on reinforcement learning, and belongs to the technical field of power grids. The method comprises the following steps: firstly, establishing a micro-grid secondary control model under hybrid network attack; a DoS attack defense network based on deep learning is designed, a self-adaptive FDI attack compensation state observer is designed, compensation for unknown FDI attacks is established, a self-adaptive law of compensation signals is designed, and estimation of the system state under network attacks is achieved. An evaluation-execution structure is constructed based on reinforcement learning, a virtual optimal controller and an actual optimal controller are designed in combination with a backstepping method, unknown parts in a system model, an evaluation network and an execution network are approximated by using a neural network, and a weight adjustment law is given. And introducing a log type barrier function into the performance index function, and constraining the output in a fixed constant interval to meet the constraint condition. The method can cope with DoS attacks and FDI attacks, and ensures stable control and safe operation of the secondary voltage of the micro-grid.

The invention belongs to the technical field of robot path planning, discloses an autonomous robot path planning method based on deep reinforcement learning, and aims at the problem that an agent is difficult to fully sense the environment in a complex dynamic environment, the State space of SAC is expanded and adjusted to enhance comprehensive sensing of an unknown environment and more flexible omnibearing obstacle avoidance. A heuristic reward function is designed, dynamic adjustment of reward values is achieved, and therefore the learning process of the robot is optimized. In order to solve the problems that the calculation complexity of an algorithm is increased and the convergence speed is reduced in a complex environment, the sample utilization rate is optimized in combination with a prior experience playback (PER) technology and a SumTree data structure. The weight of a high-value sample is increased through the PER technology, so that an intelligent agent can learn an effective strategy more quickly in the training process; and a SumTree data structure is introduced, so that the PER efficiency is further improved.

The invention is suitable for the field of intelligent customer service, and discloses an optimization method, system and device of an intelligent customer service system and a medium. Performing natural language processing on the dialogue content; according to the personalized characteristics of the user, adjusting the word segmentation spacing and the boundary of the semantic unit, and generating an optimized word segmentation and semantic analysis result; an emotion analysis model is applied to the optimized word segmentation and semantic analysis result, the emotion state of the user is recognized, and an emotion recognition result is obtained; identifying the question type of the user by adopting a classification model; and generating a reply suggestion in combination with the emotional state and the question type of the user. By identifying the personalized characteristics of the user and adjusting the word segmentation spacing and the semantic unit boundary of the dialogue content, not only can the coherence of expressing brief user semantic understanding be improved, but also the accuracy of redundant expression user semantic analysis can be enhanced, so that a more accurate word segmentation and semantic analysis result is generated.

A fruit ring weighing and sorting device and method, comprising a fruit ring conveyor, the fruit ring conveyor comprising a fruit conveying mechanism and a fruit weighing and turning mechanism; the fruit conveying mechanism comprises a turntable, the upper end of which is circumferentially covered with fruit receiving buckets; the fruit receiving bucket comprises a bucket cup, a turning frame and a base; one end of the bucket cup is supported by the turning frame, and the end away from the hinge point is hinged to the turning frame, the upper end of the turning frame is hinged to the base, and the lower end is clamped to the base through an elastic rotating member; the fruit weighing and turning mechanism comprises an annular plate fixedly mounted on the central axis, a plurality of toggle mechanisms are mounted on the upper end of the annular plate in the circumferential direction, a reset plate is provided at the lower end of the annular plate, a weighing sensor is embedded in the reset plate, and the weighing sensor supports and weighs the bucket cup. The fruit ring weighing and sorting device and method provided by the present invention can save floor space and facilitate transportation.

The invention discloses bifidobacterium animalis subsp. Lactis BLa79 as well as application, a product and a method thereof, and belongs to the technical field of microorganisms. The preservation number of the bifidobacterium animalis subsp. Lactis BLa79 is CGMCC (China General Microbiological Culture Collection Center) NO. 32426, and the preservation number of the bifidobacterium animalis subsp. Lactis BLa79 is CGMCC NO. 32426. Based on the strain, the invention also provides application and related products of the strain. The BLa79 strain has broad-spectrum antibacterial performance, has the function of regulating intestinal flora, can effectively relieve ulcerative colitis, and can relieve colitis by increasing body weight, reducing DAI score, reducing spleen index, inhibiting colonic atrophy, reducing proinflammatory factor level and promoting SIgA secretion.

The invention, which relates to the technical field of new energy power generation, discloses a new energy power generation scheduling optimization system comprising a multi-dimensional evaluation module, a dynamic weight adjustment module, a priority calculation and determination module, and a scheduling decision module. By establishing a multi-dimensional evaluation grade and a dynamic weight adjustment mechanism, the method can comprehensively and accurately evaluate the factors of the emergency degree of the energy demand, the power generation capacity of the power generation equipment and the operation state of the equipment, dynamically adjust the priority of each power generation equipment according to the real-time monitored data in different time periods, and ensure that the power generation capacity of the power generation equipment is greatly improved in the peak time period of the energy demand. Equipment which is high in power generation capacity, stable in operation and capable of responding quickly is scheduled preferentially, emergency energy requirements are met, power outage accidents are effectively avoided, new energy power generation can better adapt to complex and changeable energy requirements and power generation conditions due to the intelligent and accurate scheduling capacity, and more reliable energy supply is provided for users.

The application of the animal bifidobacterium subsp. Lactis BX-245 in relieving the inflammatory bowel disease is characterized in that the animal bifidobacterium subsp. Lactis BX-245 is preserved in the China General Microbiological Culture Collection Center (CGMCC), and the preservation number is CGMCC No.26973. The invention also discloses an application of the animal bifidobacterium subsp. Lactis BX-245 in relieving the inflammatory bowel disease. The research aims at discussing the relieving effect of the animal bifidobacterium subsp. Lactis BX-245 on IBD mice induced by dextran sodium sulfate (DSS), and 6-week male C57BL / 6J mice which normally eat and drink water are randomly divided into a normal group (NC group), a model group (IBD group), a common yoghourt (FM group), an animal bifidobacterium subsp. Lactis BX-245 bacterial powder group (BX-245 group) and BX-245 yoghourt (BFM group). The relieving effect of the animal bifidobacterium subsp. Lactis BX-245 and the fermented milk of the animal bifidobacterium subsp. Lactis BX-245 on the symptom of the mouse inflammatory bowel disease is evaluated through weight change, immune factors, targeted metabonomics and metagenomics, and data support is provided for application of the animal bifidobacterium subsp. Lactis BX-245 in products.

The invention discloses a method for targeted creation of a fast-growing new tilapia strain, and belongs to the technical field of fish cultivation. The method specifically comprises the following steps: (1) taking a fragment, as shown in SEQ ID NO.1, on a third exon of a pomc gene as a gRNA target sequence; (2) designing and synthesizing a gRNA primer sequence; (3) amplifying by adopting the gRNA primer sequence and the gRNA plasmid, and then transcribing and purifying to obtain a gRNA fragment; (4) transferring the gRNA fragments into fertilized eggs of tilapia mossambica through gene editing to obtain F0-generation positive fish; and (5) hybridizing the F0-generation positive male fish with the wild-type female fish, screening out F1-generation parent fish, and culturing the F1-generation parent fish to obtain F2-generation tilapia with homozygous deletion mutation. According to the invention, the pomc homozygous knockout line is established in the Nile tilapia mossambica for the first time, the new fast-growing line is a complete gene function deletion model, the cost is lower, the efficiency is higher, and the phenotype can be stably inherited.

The invention belongs to the technical field of federated learning, and particularly relates to a decentralized federated learning method and system oriented to a computing power network. The method comprises the steps that a model demand side in a computing power network uploads a federated learning task to a block chain network, screening computing power nodes according to a reputation score and a data score, and taking the screened computing power nodes as computing nodes to participate in training; the trained local model is verified through the block chain network and then is sent to a model demand side; and the model demander uses a weighted aggregation algorithm based on data fairness to aggregate the local models received in the current round and updates the global model by using an aggregation result. According to the method, the block chain is combined with federated learning under the background of the computing power network, and the universality of the model and the fairness of data are improved while the availability of the federated learning model and the node training enthusiasm are ensured.

The invention relates to the technical field of intelligent emotion recognition, in particular to a multi-modal emotion analysis method based on cross-modal attention, and the method comprises the steps: obtaining a to-be-analyzed video segment; the to-be-analyzed video segment is input into a preset multi-mode sentiment analysis model, a sentiment analysis result is output, and the multi-mode sentiment analysis model comprises an input layer used for extracting features of the to-be-analyzed video segment; the single-mode feature extraction layer is used for performing single-mode context information extraction on the features to obtain single-mode context features; the cross-modal interaction layer is used for performing cross-modal feature interaction on the single-modal context features to obtain a plurality of bimodal joint features; the multi-modal fusion layer is used for carrying out fusion processing on the bimodal joint features to obtain cross-modal interaction features; and the output layer is used for splicing the single-modal context features and the cross-modal interaction features, obtaining multi-modal fusion features and outputting an emotion analysis result. According to the invention, the emotion tendency of the speaker can be reflected more accurately.

The invention belongs to the technical field of microorganisms, and particularly relates to probiotic characteristics of lactic acid bacteria and a relieving effect of a metagen of the lactic acid bacteria on pulmonary fibrosis. The invention discloses pediococcus pentosaceus ZFML001, and the preservation number of the pediococcus pentosaceus ZFML001 is CCTCC (China Center for Type Culture Collection) NO: M 2024601. The invention also provides a metagen prepared from the pediococcus pentosaceus ZFML001 at the same time, and provides an application of the metagen in preparation of a medicine for relieving or assisting in treatment of pulmonary fibrosis. The invention further provides the application of the metagen in preparation of a medicine for relieving or assisting in treatment of pulmonary fibrosis.

The invention relates to a novel pulse neural network synaptic weight adjustment method, and belongs to the field of artificial intelligence. Firstly, a traditional pulse time sequence dependence plasticity rule is improved based on the distribution trend of a Gaussian function, so that the weight change corresponding to the optimized synaptic plasticity rule when the time interval tends to 0 is larger, and when the time interval is gradually increased, the weight change is in an accelerated descending trend; the method comprises the following steps: firstly, performing synaptic weight local regulation on a neuron model to improve the local regulation capability of the synaptic plasticity of the neuron, then introducing reinforcement learning, associating Q learning with the synaptic plasticity in the neuron model, and realizing the global regulation and control of the plasticity on the basis of the synaptic weight local regulation. According to the above synaptic plasticity rule, the spiking neural network constructed based on Leaky Integrating and Fire is subjected to weight adjustment, so that the spiking neural network has better performance.

The invention discloses a helicopter low-noise flight path design method and a related device, and relates to the technical field of helicopter path planning, and the method comprises the steps: adding the accumulated sound exposure level of a local or specific region into an evaluation function of a path optimization algorithm, and improving the weight of the accumulated sound exposure level. Therefore, a path capable of effectively reducing the noise level of the target area or the whole area is selected, and the influence of noise on the surrounding environment is reduced to the maximum extent.

The utility model discloses a duckbilled 220kv quick suspension grounding wire device, which relates to the technical field of grounding wire devices and comprises an insulating rod, an operating rod connected with the insulating rod, a screw rod connected with a clamping block, an arc-shaped block fixedly provided with a special-shaped rod and a connecting rod, a clamping block fixedly provided with a stop lever, a tongue-shaped rod connected with a first spring and a movable block, and an inserting rod inserted with an inserting groove. A spring II is fixed on the connecting block; the insulating rod is held by a hand, the cable is attached to the special-shaped rod through the special-shaped rod, the cable makes contact with the arc-shaped face of the tongue-shaped rod, the insulating rod is moved, the tongue-shaped rod moves downwards, the cable penetrates through the tongue-shaped rod, the tongue-shaped rod returns to the original position, the rotating disc is rotated to enable the arc-shaped block to clamp the cable, the arc-shaped block drives the special-shaped rod to press the tongue-shaped rod downwards, the inserting groove and the inserting rod are connected, and hanging of the grounding wire device is completed. The problem that a wire clamp of a grounding wire is not easy to hang due to a small opening is solved, the situation that the clamping effect is improved by increasing the dead weight of an insulating rod is avoided, and the burden caused by the insulating rod is reduced.

The invention discloses a multi-head self-attention mechanism-based disease and insect pest identification method for an improved residual network. The method comprises the following steps of: acquiring data; preprocessing the data; a multi-head self-attention mechanism is added behind the residual network, and an improved residual network model is formed; the trained model is evaluated; the trained weight file is transferred into the raspberry Pi, and the raspberry Pi is connected with a camera, so that the plant diseases and insect pests of the trees can be detected in real time. According to the method, a multi-head self-attention mechanism is added on the basis of a ResNet18 network structure, projection matrixes of different queries, keys and values are used each time to generate different attention sub-spaces, and finally outputs of all the sub-spaces are spliced together to form final output, so that the weight of key feature information is enhanced, and the recognition precision of the model is further improved. The method is used for preventing and treating forestry diseases and insect pests, improves forestry income and has wide research and market application prospects.

The invention provides a resource scheduling method and device and electronic device.The method comprises the steps that when a first thread of an application is detected, in the ith period of the first thread, a key thread list corresponding to the ith period is obtained according to a thread wakeup relation, the key thread list comprises one or more key threads related to the first thread, and i is a natural number and is equal to 1, 2, 3, 4,...; and resource scheduling is carried out based on the key thread list corresponding to the ith period. According to the method, the device and the electronic equipment, the key thread related to the running task is determined from the threads related to the running task through the thread wakeup relation in the system, the recognition process of the key thread does not depend on subjective judgment of an application developer, the key thread related to the running task can be accurately recognized, and the recognition efficiency of the key thread is improved. And thus, resource supply can be preferentially guaranteed for the determined key thread, so that better scheduling of resources is achieved.

The invention discloses a petroleum pipe microscopic fracture morphology identification method, system and device and a medium, and belongs to the technical field of failure analysis image process.The method comprises the steps that a deep learning classification network with a residual module is constructed and trained, and a deep learning classification network loaded with a network connection weight matrix is obtained; and finally, the deep learning classification network is utilized to efficiently and accurately identify the to-be-tested object region image. According to the method, massive data sets can be quickly processed and analyzed by using the high-speed processing capability of a modern computer, so that the efficiency is greatly improved. Compared with a traditional method, the automatic fracture classification method can reduce subjective interference of people and enhance reliability and consistency of results. And meanwhile, the identification method is simple, engineering application integration is facilitated, and good practicability and expansibility are achieved.

The invention discloses an Internet of Things equipment position sensing and superposed pilot frequency transmission method, which relates to the technical field of Internet of Things, and comprises the following steps: firstly, constructing a wireless frame structure comprising two parts of position sensing and superposed pilot frequency transmission; secondly, based on a wireless frame structure, a user carries out position estimation according to a base station pilot signal reflected by a reconfigurable intelligent surface RIS; then, on the basis of a position estimation result, a closed expression of the uplink reachable rate of the user is established; then, according to the closed expression, constructing a weighting and rate maximization problem for optimizing the RIS phase, and solving by utilizing a genetic algorithm to obtain an optimized RIS phase; then, based on the optimized RIS phase, the user sends a pilot frequency and a data superposition signal, and the base station performs channel estimation after receiving the superposition signal; and based on the channel estimation result, the base station performs data detection by adopting a maximum ratio merging detector. According to the method, under the condition that spectrum resources and transmission power are limited, the UE position can be accurately obtained, and the system transmission rate is remarkably improved.

The invention discloses an IMU (inertial measurement unit) attitude estimation method based on rolling window variance detection, which comprises the following steps: acquiring acceleration data and gyroscope data from an inertial measurement unit, the acceleration data being used for providing gravity direction information, and the gyroscope data being used for providing angular velocity information of a sensor; generating a rotation matrix by using gyroscope data, and calculating an Euler angle based on the rotation matrix; attitude estimation is performed by fusing an Euler angle generated from gyroscope data and an attitude angle calculated from gravitational acceleration. According to the method, a rolling window variance detection mechanism is adopted, the vibration degree of the environment where the IMU is located can be detected in real time, the weight of acceleration data is dynamically adjusted according to the vibration strength, and when it is detected that the vibration is high, the influence of accelerometer data in attitude estimation is reduced, so that the interference of the vibration on attitude estimation is reduced; under the condition of weak vibration, the weight of the acceleration data is increased, and the accuracy and stability of attitude estimation are improved.

The invention discloses an application of probiotics Blauria winteriae in the preparation of a medicine or food for improving or treating the inflammatory bowel disease of children, and relates to the field of medicines or foods for improving or treating the inflammatory bowel disease of children. According to the invention, the probiotic Blauria wexlerae is used as an effective component to be prepared into medically and food acceptable dosage forms, so that the children inflammatory bowel disease can be obviously improved or treated, and the application value of the probiotic is improved.

The invention discloses a structural variation marker based on an ARL13B gene and applied to Wenchang chicken breeding and a detection method of the structural variation marker, and relates to agricultural bioengineering, the sequence of the structural variation molecular marker is SEQ ID No: 01, and the structural variation molecular marker is located on a Wenchang chicken gene reference genome ASM4043665v1, Gallus gallus chick; the molecular marker is characterized in that the position of Genbank: GCA040436655.1 is CM080655.1: 108497195-108497244, and the molecular marker with the structural variation is a deletion site; at the same week age, the weight of an individual with the deletion structure variation marker sequence is obviously higher than that of a non-deletion individual, and the molecular marker obtained by the invention can be applied to Wenchang chicken breeding.

The invention discloses a split type suction pile anchoring foundation and an offshore construction method, and relates to the technical field of ocean engineering, and the split type suction pile anchoring foundation comprises a suction pile structure and a buoyancy tank structure; an apron board structure and a lug plate structure are arranged on the side wall of the suction pile structure; a drainage pipeline penetrates through the top of the suction pile structure and communicates with the interior of the suction pile structure and the water suction pump. A balance weight cabin and a ballast tank are arranged in the buoyancy tank structure, and a pressure discharging and loading system is arranged in the ballast tank; the supporting leg structures are arranged at the bottom of the buoyancy tank structure, and the buoyancy tank structure is pressed on the apron board structure through the supporting leg structures; a first eye plate connected with a mooring rope or a mooring chain is arranged on the outer side wall of the buoyancy tank structure. The technical problems that due to the fact that a traditional suction pile anchoring foundation is limited by the dead weight, the depth of penetrating into soil in the soil conditions such as sandy soil is insufficient, enough pressure difference cannot be generated in the closed space formed by the cylinder wall and soil in the space outside the cylinder wall, and the suction barrel reaches the preset installation depth and the designed tensile strength and the designed pulling strength are solved.

The invention relates to the technical field of power equipment safety prevention and control, and discloses an intelligent fire prevention control method for a flame-retardant material of a power transmission and distribution complete switch, which comprises a DMC flame-retardant material dynamic performance data acquisition step, a DMC flame-retardant material parameter optimization step, a DMC flame-retardant material dynamic feedback regulation and control step and a closed-loop control step. Through combined monitoring of multi-dimensional parameters such as pyrolysis rate # imgabs0 #, carbonization layer thickness # imgabs1 # and environment adaptive variable # imgabs2 #, comprehensive dynamic perception of the performance of the DMC flame-retardant material is realized, accurate evaluation of fire risk is completed through an optimization formula # imgabs3 #, error deviation at the previous moment is fed back in real time through a dynamic correction value # imgabs4 #, a closed-loop regulation and control mechanism is formed, and the flame-retardant performance of the DMC flame-retardant material is improved. And the fire risk assessment precision and the response speed are obviously improved.

The invention discloses an oral cavity CBCT image classification method and device, electronic equipment and a storage medium, and the method comprises the steps: inputting a to-be-classified oral cavity CBCT image into an oral cavity CBCT image processing model, so as to enable the oral cavity CBCT image processing model to generate segmentation information in a segmentation sub-model, and determining a classification image corresponding to the to-be-classified oral cavity CBCT image in the classification sub-model according to the segmentation information. Wherein the segmentation sub-model improves a SwinUnet network model, and adds a residual module to improve the learning ability of the network model; the classification sub-model improves an original 3D-Unet network model, and an attention mechanism module is added to enable the network to selectively learn features of a key area. By implementing the method, the specific structure category of the oral cavity CBCT image can be clearly divided, and the accuracy of a classification result is ensured.

The invention relates to the technical field of microorganisms, in particular to lactobacillus rhamnosus capable of preventing or treating inflammatory bowel diseases and promoting digestion and application of the lactobacillus rhamnosus, and belongs to the technical field of biological medicine. The invention provides a strain of lactobacillus rhamnosus R7970, wherein the preservation number of the lactobacillus rhamnosus R7970 is CGMCC (China General Microbiological Culture Collection Center) 22244, and the preservation number of the lactobacillus rhamnosus R7970 is CGMCC 22244. The lactobacillus rhamnosus R7970 can be used for effectively preventing inflammatory enteritis (IBD) and has a prevention effect on intestinal inflammation, and meanwhile, the lactobacillus rhamnosus R7970 can be used for improving the nutrition digestion and absorption functions of intestinal tracts. Therefore, the lactobacillus rhamnosus R7970 can be applied to prevention of IBD, can be used for preparing probiotic preparations, common foods, health foods and biological pharmacy for improving intestinal health, is convenient for industrial production, and has great popularization value.

The invention discloses organic silicon resin production equipment, and relates to the technical field of production. The device comprises a device body, a driving assembly is arranged at the top of the device body, a supporting assembly is arranged at the bottom of the device body, an electric telescopic rotating column is rotationally installed at the top of the inner wall of the device body, and an arc-shaped groove is formed in the outer wall of the electric telescopic rotating column; a filter plate is fixedly mounted on the outer wall of the telescopic end of the electric telescopic rotary column, and an anti-sticking device for avoiding non-uniform stirring of raw materials is arranged on the periphery of the electric telescopic rotary column. Through cooperation of an electric telescopic rotating column, a stirring block and a filter plate, the stirring block dynamically stirs raw materials, and the stirring effect is improved by turning over the center of the raw materials through the cambered surface treatment of the stirring block; and meanwhile, the filter plate moves dynamically to remove impurities in the raw materials, so that the removal effect on small-particle impurities is improved, and the purity and quality of the materials are guaranteed.