280results about How to "Accurate separation" patented technology

The invention relates to the technical field of gallium nitride gate drivers, and discloses a design method and system of a gallium nitride gate driver, and the method comprises the steps: carrying out the working signal collection of the gallium nitride gate driver, obtaining original waveform sampling data, and building a signal integrity model under the action of electromagnetic interference; separating the original waveform sampling data into an effective driving signal, a low-frequency interference signal and a high-frequency noise signal, and extracting characteristic parameters to obtain a signal characteristic parameter set; switching time and circuit power consumption are set as optimization variables, constraint conditions are set according to the signal integrity model, and an optimization objective function is obtained; performing online identification and optimization calculation on the driving parameters to obtain a driving control parameter sequence; according to the method, the adaptive capacity of the driver to the change of the working condition is improved, and meanwhile, the stability and the reliability of the driving waveform are ensured.

The invention relates to the technical field of television image communication, in particular to a user information input method and system in an intelligent television all-in-one machine. The method comprises the following steps: collecting a user image, carrying out white balance correction and focusing processing, generating a moving object focusing image, carrying out identification and attention tendency analysis on a character in the focusing image, obtaining character tendency data, analyzing a historical interaction image, identifying an interaction mode and constructing a user intention prediction model, and obtaining a user intention prediction result. And when the tendency data shows that the user preferences the television content, intention drilling and auxiliary adjustment are performed on the current image based on the prediction model, predicted user input information is generated, logic conflicts in the predicted information are detected, feedback optimization is performed, and final user input information is output. According to the invention, a more accurate and more flexible user information input method is realized.

The invention relates to the technical field of signal processing, in particular to an unmanned aerial vehicle self-noise filtering method and system based on multichannel time-frequency spatial filtering. The method comprises the following steps: acquiring a multi-channel noise-containing sound signal by using a microphone array carried by an unmanned aerial vehicle, and performing short-time Fourier transform to obtain a frequency domain signal; estimating a ratio mask by using a deep neural network, and performing logarithm normalization processing on the frequency domain signal; remodeling the sound signal to match the FFT length of the time-frequency spatial filter, and constructing the time-frequency spatial filter in combination with the multi-channel ratio mask; removing the self-noise of the unmanned aerial vehicle by using the filter and obtaining a target sound signal; and finally, converting the frequency domain signal into a time domain signal through inverse short-time Fourier transform. Through innovative fusion of multi-channel acquisition, deep learning and time-frequency space filtering, the self-noise of the unmanned aerial vehicle in a complex environment is accurately filtered, and the accuracy and efficiency of transformer substation noise monitoring are remarkably improved. Reliable acoustic data are provided for state monitoring of the power equipment, and the method has important engineering application value.

The invention relates to the technical field of lithium battery recovery, in particular to a waste lithium battery recovery method based on multistage crushing and intelligent sorting. Performing soaking discharge treatment on the waste lithium battery, and constructing a discharge detection model; then carrying out multi-stage crushing on the discharged lithium battery by adopting first-stage shearing crushing, second-stage impact crushing and third-stage grinding crushing, and grading and screening crushed particles; an electrode material sorting model is constructed by acquiring spectrum and element information of a crushed material and combining a deep learning model, so that intelligent sorting of an electrode material and a non-electrode material is realized; and after separation, performing multi-frequency vibration layering on the non-electrode material particles, and further separating positive and negative electrode materials from the electrode material particles by adopting an electrostatic separation technology. According to the method, multiple physical sorting modes and an artificial intelligence technology are comprehensively utilized, and efficient and accurate recycling and resource utilization of the waste lithium batteries are achieved.

The invention relates to the technical field of stamping part surface detection, in particular to a stamping part surface detection method and a welding slag cleaning device.The detection method is based on three-dimensional point cloud data processing, is not affected by environment light changes, can more accurately separate a defect area from a background, and is high in detection accuracy. The welding slag can be effectively identified even at a complex geometrical shape or a deep concave position, comprehensive detection of a stamping part with a complex shape can be realized, and the accuracy and the efficiency of detection are remarkably improved; by presetting the basic threshold value and dynamically adjusting according to the reflection characteristics, it can be guaranteed that the stamping part can obtain stable detection and cleaning results under the detection conditions of different light environments.

The invention discloses a glacier jump prediction and data sample enhancement management method, particularly relates to the field of glacier remote sensing monitoring, is used for solving the problem of accurate identification and processing of surface moraine covering type glacier local albedo abnormal effect, and aims at solving the problem of accurate identification and processing of the glacier local albedo abnormal effect by comprehensively analyzing the coupling relationship between spectrum and temperature and the spatial sensitivity of temperature gradient. And accurate identification and processing of the moraine covering glacier local albedo abnormal effect are realized. According to the method, main causes of albedo abnormity can be effectively distinguished, and an abnormal area is corrected in a targeted manner by scientifically selecting an optical and thermal infrared remote sensing fusion mode or an optical and radar remote sensing fusion mode, so that the glacier identification precision and the jump prediction accuracy are remarkably improved. Through multi-level remote sensing data correction and feature extraction, a high-precision data foundation is laid for subsequent analysis; in the process of generating an enhanced sample and optimizing a prediction model, the reliability and response speed of glacier jump prediction are further improved.

The invention relates to the technical field of ecological management, in particular to a mine management soil remediation device which comprises an upper shell, a lower shell is fixedly mounted at the bottom of the upper shell, a water tank is fixedly mounted at the top of the upper shell, a separation mechanism is mounted in the upper shell, a smashing mechanism is mounted in the lower shell, and a soil remediation mechanism is mounted in the smashing mechanism. A spraying mechanism is installed between the lower shell and the water tank, an output mechanism is installed in the lower shell and located at the bottom of the smashing mechanism, and a driving mechanism is installed among the separating mechanism, the smashing mechanism and the spraying mechanism. The separating mechanism comprises a first separating roller, a second separating roller and a first bevel gear. According to the mine soil remediation device, stones in mine soil are effectively separated and crushed, the function of agent spraying is combined, the mine soil remediation efficiency and quality are improved, the equipment maintenance cost is reduced, and effective remediation of the mine soil and improvement of the ecological environment are achieved.

The invention relates to a process for gradient extraction of seaweed protein, algin and fucoidin in brown algae. The invention relates to a process for extracting seaweed protein, algin and fucoidin in brown algae, which comprises the following steps: carrying out superfine grinding on seaweed, adding water for extraction, filtering and separating to obtain water extraction filtrate, repeatedly dissolving the water extraction filtrate in the next batch of superfine ground seaweed, and circulating for 7 times to obtain saturated or supersaturated water extraction filtrate; adjusting the pH value of the water extraction filtrate to be acidic, and filtering and separating through a micro-filtration membrane to obtain seaweed protein and first filtrate; adding calcium chloride into the first filtrate, and settling to obtain algin and supernate; filtering the supernate through a polyethersulfone composite membrane to obtain a fucoidin concentrated solution; and carrying out spray drying on the concentrated solution to obtain fucoidin powder. The method solves the problem that other functional components are wasted due to the fact that only a single component can be extracted in an existing brown algae functional component extraction method, and also solves the problems of secondary pollution, poor product quality and high cost in an existing extraction method.

The invention discloses a desliming device for mining and beneficiation operation, and relates to the technical field of mineral engineering, in particular to a desliming device for mining and beneficiation operation, which comprises a main machine body, a U-shaped groove is attached and connected to the top of the main machine body, and a flow dividing box is arranged at one end of the main machine body; and a hydrocyclone is arranged between the main machine body and the flow dividing box. According to the desliming device for mining and beneficiation operation, fine separation of minerals with different densities and particle sizes is achieved through stirring of the U-shaped groove, screening of the sieve plate, separation of the hydrocyclone and extrusion of the mesh belt, the desliming quality is improved, finally, final solid-liquid separation is achieved through relative movement and extrusion of the upper mesh belt and the lower mesh belt, and the desliming efficiency is improved. By means of the device, it is ensured that substances in different phase states are separated and treated according to an expected mode, the convenience and the environmental protection property of subsequent treatment are improved, the problem that silt is difficult to clean in traditional equipment is solved through the convenient cleaning mode of all the parts, and the fault risk and secondary pollution caused by silt residues of the equipment are reduced.

The invention discloses a particle swarm optimization-based flywheel-lithium battery hybrid energy storage system participation secondary frequency modulation capacity configuration method, which comprises the steps of establishing a regional power grid frequency modulation dynamic model based on ACE distribution and ARR distribution, and comprehensively considering an ACE signal distribution mode and an ARR signal distribution mode to determine a frequency modulation power instruction distributed by a hybrid energy storage system; a first-order low-pass filter is used for carrying out high and low frequency division on a frequency modulation power signal distributed by the hybrid energy storage system, a high-frequency component is distributed to flywheel energy storage for response, a low-frequency component is distributed to a lithium battery for response, and the high-frequency component and the low-frequency component serve as reference power of flywheel energy storage and lithium battery energy storage; the charging and discharging power of hybrid energy storage is adjusted and controlled by considering different energy storage SOC reconstruction domains; a hybrid energy storage capacity configuration model with the maximum hybrid energy storage participation frequency modulation income as the target is established based on the whole life cycle, and a particle swarm optimization algorithm is adopted for solving; the overall economical efficiency and safety of the hybrid energy storage system participating in frequency modulation are effectively improved.

The invention relates to the technical field of drilling waste treatment, in particular to a drilling slag slurry multi-stage circulation treatment system and method.The drilling slag slurry multi-stage circulation treatment system comprises an automatic grading module, a dynamic monitoring module, a slurry purification module, a separation optimization module, a waste slag classification recycling module and an intelligent control module; wherein the automatic grading module comprises a particle identification unit and a variable frequency grading unit; the particle identification unit is used for carrying out real-time detection on the size, the form and the density of particles in the drilling slag and the slurry through a multispectral sensor; the variable-frequency grading unit is used for adjusting the grading speed according to the detection data provided by the particle identification unit and carrying out dynamic grading on the particles; the dynamic monitoring module comprises an online sensor and a data analysis unit; according to the invention, through intelligent monitoring and automatic adjustment technologies, efficient grading, filtering and separation of drilling slag slurry and intelligent classification of waste slag are realized, and efficient operation of the system, improvement of the resource recovery rate and reduction of environmental pollution are ensured.

The invention discloses a reservoir area hydro-fluctuation belt rock crack image recognition method based on a deep learning network, and the method comprises the steps: S1, constructing a rock crack segmentation model, and training the rock crack segmentation model through employing a pre-processed rock crack image sample set; s2, recognizing a rock crack region in the target image by using a rock crack segmentation model to obtain a first type of recognition result; s3, on the basis of coordinate positions, pixel values and color space attributes of pixel points in the image, optimizing the first type of recognition result through a crack mask optimization algorithm of multi-algorithm weighted fusion to obtain a second type of recognition result; and S4, aiming at the second type of identification result, measuring the width of the rock crack through a maximum inscribed circle method and an orthogonal projection method so as to obtain geometric representation information of the rock crack. According to the invention, automatic identification of the geometric representation information of the rock crack image of the hydro-fluctuation belt can be realized, and the intelligent and informatization level of reservoir area hydro-fluctuation belt bank slope rock crack detection is improved.

The invention discloses a vital sign monitoring method based on multilayer variational mode decomposition and reconstruction, which comprises the following steps: sending a radar microwave signal to a target human body, receiving a path of returned radar microwave reflection signal, and extracting frequency domain characteristics of the radar microwave reflection signal; judging whether the current human body is in a resting state or not according to the radar microwave reflection signals, and if so, extracting the radar microwave reflection signals in the resting state; carrying out respiratory signal and heart rate signal separation reconstruction on the radar microwave reflection signal in the resting state to obtain a reconstructed respiratory signal and a reconstructed heart rate signal; phase data of the reconstructed respiration signals and the reconstructed heart rate signals are extracted respectively, wavelet transformation is conducted on the phase data of the respiration signals and the phase data of the heart rate signals respectively, respiration phase characteristics and heart rate phase characteristics are obtained, and the respiration frequency and the heart rate are calculated according to the respiration phase characteristics and the heart rate phase characteristics.

The invention relates to an ion regulation inhibitor for preventing slurry from covering, application and a lepidolite ore beneficiation method. The invention discloses an ion regulation inhibitor for preventing slime from covering. The ion regulation inhibitor comprises a starch inhibitor, a sodium salt inhibitor and a metal ion regulator. The invention provides application of the ion regulation inhibitor capable of preventing the slime from covering in ore dressing of lepidolite ore. The invention provides a beneficiation method of lepidolite ore. The beneficiation method comprises the following steps: adding water into ore powder of the lepidolite ore to prepare ore pulp; a pH regulator, a collecting agent and the ion regulation inhibitor are added into the ore pulp for roughing, and roughing concentrate and roughing tailings are obtained; the ion regulation inhibitor is added into the roughing concentrate for concentration, and lepidolite concentrate is obtained; and a collecting agent is added into the roughing tailings for scavenging, and flotation tailings are obtained. The problems that an existing lepidolite ore beneficiation method is large in lithium ore loss, low in beneficiation efficiency and complex in process are solved.

The invention belongs to the technical field of fault diagnosis, and particularly relates to a gearbox fault diagnosis method and system based on cyclic pulse characteristic decomposition, and the method comprises the steps: constructing a new dictionary matrix, namely a cyclic pulse dictionary matrix, to accurately estimate a pulse cycle period contained in a signal formed by mixing a plurality of periodic pulse signals; a Goertzel algorithm is adopted to obtain corresponding frequency amplitudes according to the magnitude sequence of the energy values of the pulse cycle periods; and separating and reconstructing the CPCC corresponding to the pulse cycle period, and decomposing the signal into a plurality of CPCCs. According to the invention, the cyclic pulse dictionary matrix is constructed to carry out sparse representation on the pulse cycle period of the periodic pulse signal, and the cycle period of the fault pulse characteristic in the gear vibration signal is accurately estimated; the Goertzel algorithm is adopted to decompose and reconstruct the CPCC in the gear vibration signal according to the pulse cycle period, and the decomposed CPCC contains abundant periodic pulse characteristic information.

The invention discloses a switch cabinet safety detection method based on big data. The method comprises the steps of data acquisition, data preprocessing, data reconstruction, detection data clustering processing and switch cabinet safety detection. The invention belongs to the technical field of switch cabinet detection, and particularly relates to a switch cabinet safety detection method based on big data, and the method carries out the data reconstruction of the safety detection data of a switch cabinet through introducing a comparison learning target, and facilitates the precise recognition of the fault type of the switch cabinet. The alignment of potential space of the safety detection data of the switch cabinet is improved through three constraints, so that the safety detection accuracy of the switch cabinet is improved; local density is calculated by introducing multi-scale density and dynamic distance weight, noise point elimination is carried out based on a self-adaptive dynamic threshold value, processing of switch cabinet safety detection data is realized based on gravitation balance state determination, and accurate separation of an abnormal state and a normal state is ensured. And the switch cabinet fault detection and classification efficiency is high.

The invention relates to the technical field of wind lidar measurement, and discloses a wind lidar data quality control method comprising the following steps: collecting wind lidar echo signals in a period of time, the wind lidar echo signals comprising atmospheric reflection signals and noise signals; carrying out average power spectrum estimation processing on the original echo signal; gaussian filtering processing is carried out on the average power spectrum so as to suppress obvious and burst noise and interference signals, and a calculation result is used for replacing an original power spectrum numerical value; the filtered power spectrum is obtained, a least square method mathematical optimization method is adopted, model parameters of optimal fitting given power spectrum data points are searched, a prediction model adopts a low-order polynomial, and whole range gate sequence data are selected for prediction fitting. Through power spectrum estimation and noise frequency domain statistical characteristic analysis, the signal and the noise can be distinguished more accurately, so that the influence of the noise on a measurement result is effectively reduced.

The invention discloses a secondary screen cabinet wiring terminal alternating current and direct current voltage identification circuit and a separation and classification method, and relates to the technical field of power electronics and signal identification. According to the invention, firstly, a pre-amplification and AC / DC separation circuit mainly composed of a pre-amplification module, a high-pass filtering module and a low-pass filtering module is used for completing amplification and AC / DC separation after voltage signals of a secondary screen cabinet wiring terminal are acquired; converting the time sequence of the AC voltage signal into image data through a Grubby angle difference field; and then optimizing by using the image data through establishing and training a model based on a convolutional neural network, and continuously iterating to identify and classify the optimal parameter of the AC voltage signal of the secondary screen cabinet wiring terminal. Finally, after model training is completed, the test set is input into the model to determine the accuracy of the model.

The invention relates to a cell quantification method and device, computer equipment and a storage medium. The method comprises the following steps: extracting cell contour features of an endoscope cell image corresponding to a region of interest through a pre-constructed deep learning model, and separating a cell contour region corresponding to each cell in the endoscope cell image according to the cell contour features; classifying the cell contour region corresponding to each cell through the deep learning model to obtain a cell category of each cell; determining an overall cell quantification result corresponding to the endoscope cell image through the deep learning model according to the cell contour region of each cell; and performing depth feature extraction on the cell contour region of which the cell category is the abnormal cell through the deep learning model, and determining an abnormal cell quantification result according to the depth feature and the cell contour feature of the abnormal cell. By adopting the method, the abnormal condition of the cells can be accurately and efficiently judged.

The invention relates to a road infrastructure full-automatic inspection method, device and equipment based on an unmanned aerial vehicle group, and a medium thereof. The method aims at the problem that disease characteristics collected by unmanned aerial vehicles in traffic flow and vegetation shielding scenes are broken, and the method comprises the following steps of: decoupling texture and motion characteristics of a dynamic shielding area; feature maps of the effective area and the shielding area are separated; performing cross-frame splicing and continuous repair on the fracture features by using an optical flow constraint generation network, and reconstructing the geometric integrity of a shielded region; infrared data are fused to correct thermal deformation errors, and a high-precision continuous curved surface model is generated; and finally, based on a disease quantitative feature vector matching maintenance strategy, realizing full-process automation from data acquisition to decision output. According to the method, the continuous modeling precision and the maintenance decision reliability of pavement disease detection in the shielded environment are remarkably improved.

The invention discloses an energy-gathered ultrasonic scrubbing device and an argillaceous sandstone uranium deposit deep desliming system. The energy-gathered ultrasonic scrubbing device comprises a scrubbing barrel, a reverse stirring system, an energy-gathered ultrasonic vibrator and a slurry storage tank, the reverse stirring system is located in the scrubbing barrel and comprises a rotating shaft and at least four layers of reverse stirring blade structures arranged in the axial direction of the rotating shaft, each layer of reverse stirring blade structure comprises a plurality of blades arranged in the circumferential direction of the rotating shaft, and the inclination directions of the blades of every two adjacent layers of reverse stirring blade structures relative to the rotating shaft are opposite; the energy-gathered ultrasonic vibrator comprises an ultrasonic transduction device and an energy-gathered vibration conduction rod, the ultrasonic transduction device is fixed outside the scrubbing barrel, and the energy-gathered vibration conduction rod is connected with the ultrasonic transduction device and located inside the scrubbing barrel; and the discharge hole of the overflow slag discharge pipe of the scrubbing barrel directly guides the slurry to the slurry storage tank. According to the invention, mud-sand deep separation is realized under the combined action of multi-phase flow channel high-pressure scrubbing and low-frequency high-energy ultrasonic vibration, so that deep desliming of argillaceous sandstone uranium ore is realized.

The invention discloses an internal combustion engine fault diagnosis method and device based on time domain and frequency domain feature fusion, and relates to the technical field of fault detection, and the method comprises the steps: obtaining a vibration acceleration signal of an internal combustion engine during operation; based on a preset center frequency, a variational mode decomposition method is adopted to decompose the vibration acceleration signal to obtain a plurality of signal components, the sum of the broadband of the plurality of signal components is minimum, and the vibration acceleration signal can be obtained by reconstructing signal energy; and splicing the signal components, and inputting the obtained spliced signal and the vibration acceleration signal into a pre-trained fault prediction model to obtain a fault diagnosis result output by the fault prediction model. The method and the device are used for solving the problem of low prediction accuracy during fault diagnosis of the internal combustion engine in the prior art, and the accuracy of fault diagnosis is improved.

The invention discloses a metro entrance and exit flood control equipment quick response method based on water level situation analysis, which comprises the following steps: acquiring water level data of different metro entrances and exits through monitoring video images, correcting image distortion by adopting inverse transparent transformation, extracting a water level line position by applying a threshold segmentation technology, and ensuring the monitoring precision; the water level change trend is predicted by combining a seasonal gating circulation unit neural network, a flood control measure model based on a decision-making tree is generated, rapid response of flood control equipment is achieved, and the bidirectional Bayesian decision-making model is used for evaluating the risk of subway entrance and exit flood disasters and making corresponding prevention and control measures. The real-time performance and accuracy of water level situation analysis and the response efficiency of flood control measures are improved, and the method has the advantages that the water level situation at the entrance and the exit of the subway can be accurately monitored in real time, different water level conditions are quickly responded through the decision-making tree model, and therefore the influence of flood on a subway system is effectively reduced, and the safety of passengers and facilities is guaranteed.

The invention provides a civil engineering construction waste treatment device, and relates to the technical field of civil engineering. The civil engineering construction waste treatment device comprises a smashing and impurity removing mechanism, a conveying belt is fixedly arranged at the upper end of the smashing and impurity removing mechanism, a sorting mechanism is arranged on the side, away from the conveying belt, of the smashing and impurity removing mechanism, and a conveying motor is fixedly arranged on one side of the conveying belt; a power shaft is arranged at the output end of the transmission motor through a speed reducer, first synchronous wheels are fixedly arranged at the two ends of the power shaft correspondingly, the smashing and impurity removing mechanism comprises a smashing frame, a translation plate is slidably arranged in one side of the smashing frame, a discharging plate is fixedly arranged on one side of the translation plate, and a filter screen is arranged in the discharging plate in a penetrating mode; telescopic side plates are fixedly arranged at the front and back positions of one side of the discharging plate. Waste materials fall into the corresponding classification frames according to the mass of the waste materials, preliminary and convenient waste material classification is achieved, and great convenience is provided for follow-up machining work.

The invention discloses an operation state control method applied to a centrifugal machine. A rotating shaft is driven to rotate according to a rotating speed median value so that mixed liquid can be evenly distributed into each set of rotating drums; after separation of n parts of mixed liquid is completed, a set of rotary drums with the best separation effect in centrifugal separation of each set of rotary drums is confirmed, and the optimal centrifugal force of mixed liquid separation is obtained through calculation; calculating the radius of the energy-saving rotary drum to obtain a corresponding energy-saving rotary drum sleeve, and configuring the optimal rotating speed of the rotating shaft according to the position of the rotary drum sleeve and the optimal centrifugal force; and the mixed liquid is guided to the fixed drum sleeve. And driving the rotating shaft to rotate according to the optimal rotating speed, and separating the mixed liquid. Mixed liquid can be separated at the same time through multiple centrifugal forces. Through one-time separation of a plurality of rotary drum sleeves, the most suitable separation rotary drum can be determined at the fastest speed, and the separation efficiency is improved. And only one set of drum sleeve is used for separation again, so that the efficiency is high, and meanwhile, energy is saved.

The invention discloses a superfine high-performance admixture system with a multi-stage separation dynamic screening function and a solid waste treatment operation method, and the system comprises a vibration crushing device which is used for crushing building solid waste into small blocks and obtaining the building solid waste small blocks; the first swash plate grinding device is used for grinding the small building solid waste blocks to obtain small solid waste particles; the solid waste grinding multi-stage separation dynamic powder selecting device is used for screening small solid waste particles and obtaining fine-particle-size materials; the second swash plate grinding device is used for carrying out secondary grinding on the fine-particle-size materials; and the solid waste ground powder material flow rate control partition board material cabin is used for carrying out wind separation on the materials. The treatment procedure is simple and efficient, the construction solid waste treatment operation is reasonable, the problems that the construction solid waste pollutes the environment, the treatment process is complex, and the cost is high are solved, and remarkable economic, environmental and social benefits are achieved.

The invention discloses a homeland space planning data intelligent analysis method based on big data, and relates to the technical field of homeland space planning, and the method comprises the steps: collecting multi-source data, carrying out the quality screening, and forming a standardized data set. And setting a space element extraction rule based on a specific planning target, and mining key space elements from the standardized data. Constructing a big data analysis model, inputting key elements to calculate and obtain a spatial development tendency index, and generating a preliminary planning scheme according to the spatial development tendency index; and performing compliance verification on the scheme, generating evaluation data, and adjusting the scheme according to the evaluation data. And finally, performing space efficiency deduction calculation on the adjusted scheme, optimizing the scheme according to deduction result data, and outputting a final planning scheme. According to the method, the accuracy of data mining is improved through target-driven element extraction, and the perspectiveness and scientificity of a planning scheme are enhanced through dynamic efficiency simulation.

The invention discloses an SIM card tray automatic folding machine which comprises a machine frame, a workbench is installed on the machine frame, a feeding rotating carrying disc is arranged at one end of the workbench, and a supporting table which is horizontally arranged with the feeding rotating carrying disc is further arranged on the workbench. A material pushing mechanism used for pushing a material belt and a material fixing mechanism used for fixing the material belt are sequentially arranged on one side of the supporting table from left to right. The cutting and pressing mechanism is used for cutting off a reserved line on a material belt and a small connecting strip located on the side of the reserved line and then pressing the material belt, and the slidable breaking mechanism is arranged perpendicular to the material belt and used for breaking the connecting position between the material belts. According to the automatic material folding machine, segmentation separation of the material belt with the card support on the material belt is sequentially completed through actions of all the assemblies, the automation degree is high, time and labor are saved, the material belt is conveyed through the material pushing assembly and the material fixing assembly, conveying of a conveying belt is not needed any more, and cost is saved.

The invention relates to a preparation method of a microporous membrane based on PTFE (polytetrafluoroethylene) emulsion. The microporous membrane is obtained by taking the PTFE emulsion as a main body, mixing a water-soluble polymer material as a structural carrier, performing blade coating to form a membrane through a scraper blade, performing freeze pore forming and performing heat treatment. The PTFE membrane prepared by the method has a unique pore structure, and the thickness, porosity, section pore structure, membrane mechanical properties and the like of a membrane material can be regulated and controlled by regulating and controlling the composition of a structural carrier, blade coating conditions and freezing and sintering parameters. Compared with a PTFE membrane prepared through mechanical stretching, the method has the advantages of being simple in preparation process, uniform in pore structure, uniform in membrane thickness and the like, and can be suitable for precise separation of heterogeneous materials in a harsh separation environment.

The backrest left and right side plate production technology comprises the steps that firstly, a material plate is placed on a material conveying base of machining equipment, transverse push rods are used for driving movable side plates according to the width of the material plate, so that the two sets of movable side plates are clamped to the side edges of the material plate, and rolling wheels rotate to drive the material plate to move; 3, when the upper mold moves upwards, the material plate is moved to the position between the lower mold part and the upper mold part, the upper mold part is matched with the lower mold part through downward movement of the upper mold part, and shaping operation of a structural groove in the backrest side plate on the material plate is completed; and 3, when the upper mold part moves upwards, a material ejection frame is matched with a movable ejection head to complete separation operation between the backrest side plate and the upper mold. Meanwhile, a lower ejector rod is matched with a lifting push plate to eject a lower ejector column upwards, and separation operation of the lower mold and the backrest side plate is completed. The method comprises the steps that firstly, a material plate is placed on a material conveying base of machining equipment; a continuous stamping and shaping structure is arranged, stamping and shaping of the left side plate and the right side plate of the backrest can be continuously completed in the material conveying process, and the machining efficiency is improved.