97results about How to "Realize screening" patented technology

The invention discloses an energy storage power station state evaluation method and system based on real-time demand analysis, and relates to the technical field of power station state evaluation, and the method comprises the steps: obtaining the real-time operation data of an energy storage power station; the real-time operation data comprises voltage data, current data, temperature data and power data; based on the real-time operation data, establishing an energy storage power station real-time evaluation index system under the demand of a power grid system; and based on the energy storage power station real-time evaluation index system, establishing an energy storage power station performance comprehensive evaluation model, and performing energy storage power station state evaluation according to the energy storage power station performance comprehensive evaluation model. According to the method, operation data are acquired from multiple dimensions of a PCS converter, a battery body and a PCC point, a systematic evaluation index system of four requirements of power grid frequency modulation, peak regulation, voltage regulation and power oscillation suppression is combined, and an evaluation method of combining dynamic fuzzy comprehensive evaluation and adaptive weight dynamic adjustment is adopted; and comprehensive and accurate evaluation of the state of the energy storage power station is realized.

The invention provides a target detection method and system based on a remote sensing image, and belongs to the technical field of radio detection, and the method specifically comprises the steps: carrying out the determination of a detection deviation target in detection targets through a detection deviation condition, and obtaining the distribution data of the detection deviation target in a target region, and combining detection deviation conditions of different detection deviation targets to determine that the detection accuracy of the target area does not meet requirements, combining different types of spectrums to construct a plurality of spectrum detection combinations, and obtaining the detection deviation conditions of the detection deviation targets in different spectrum detection combinations. And the target detection strategy of the target area is determined by using the detection deviation conditions of different spectrum detection combinations and the spectrum composition data, so that the accuracy of target detection processing is improved.

The invention provides a data center energy-saving control method and system and a storage medium, and belongs to the technical field of data centers, and the method specifically comprises the steps: carrying out the determination of a reference time period group in similar time period groups of a server through the time distribution data of divided time periods in different similar time period groups, dividing the divided time periods into different time periods based on the time of the divided time periods in different reference time period groups, and determining the server with abnormal heat dissipation in the servers according to the change data of the temperature monitoring data of the servers in different time periods in each reference time period group. When it is determined that there is no abnormal heat dissipation server whose data processing amount fluctuates according to the change condition of the data processing amount of the abnormal heat dissipation server in the data center at different dates, a temperature control strategy of a temperature control device of the data center is determined according to the data processing amount of the abnormal heat dissipation server at different dates. And the energy consumption of temperature control is reduced.

The invention provides a supplier inventory selling method and system for long-tail commodities, and belongs to the technical field of selling management, and the method specifically comprises the steps: a performance list generation module is responsible for generating a performance list according to commodity information and customer information in a sales list, and a supply list generation module is responsible for splitting the performance list according to supply warehouses, and storing the split performance list in a database; the purchase order generation module is responsible for generating a goods supply order, generating a purchase supply order according to a mapping relationship among warehouses, goods and suppliers in the goods supply order and a mapping relationship drive, and the purchase order generation module is responsible for carrying out aggregation operation on all purchase supply orders of the same supplier to generate a batch of purchase supply orders of supplier dimensions; and the purchase supply list of the supplier dimension is issued to generate the purchase list in a one-to-one manner, and the delivery processing module is responsible for delivering the commodity to the ordering customer according to the data of the purchase list and the supplier inventory selling strategy corresponding to the commodity, so that the material cost of the platform is reduced.

The invention discloses a method for carrying out model parameter optimization on model test errors of a wave energy device, and particularly relates to the technical field of model parameter optimization, comprising the following steps: S1, collecting long-term accumulated test data of the wave energy device, and establishing a test database; s2, carrying out orthogonal test design; and S3, Bayesian parameter optimization: carrying out training optimization on variable factors based on a machine learning method of a Bayesian Gaussian process so as to reduce a scale effect of a model test. According to the method, the next model parameter is optimized and selected through the existing model test parameters, so that the scale effect of the wave energy device model is minimized, iteration sample points are continuously and automatically selected through a small number of selected sample points by means of a machine learning optimization method, the cost of the model test is reduced, and the test efficiency is improved.

The invention discloses a radar radiation source individual identification method based on an incremental neural network, and the method comprises the steps: firstly obtaining a radar radiation source data sample, and extracting the time-frequency features and bispectrum features of the radar radiation source data sample; secondly, on the basis of the ResNet1D network, a radar radiation source individual recognition network model is constructed in combination with efficient channel attention ECA and a self-organizing incremental learning neural network SOINN; and finally, combining the time-frequency features and the bispectrum features into a dual-channel sample, training and testing through a radar radiation source individual identification network model, outputting a radar radiation source individual identification result, and completing radar radiation source individual identification. The method achieves the screening of useful features, improves the learning capability of the features, improves the recognition precision, and completes the precise recognition of a radar radiation source individual.

The utility model discloses a husked rice separating device for rice production, which comprises a box body, a collecting box, a cover plate, a feeding port, a feeding component and a screening component, the feeding component is arranged on the lower side of the feeding port, a driving plate can be driven by a motor I to drive a driving lever to rotate so as to control the movement of a grooved wheel, a shaft lever can drive a baffle plate to rotate at regular time, and the screening component is arranged below the feeding port. Therefore, quantitative feeding of the husked rice mixture is achieved, and the situation that follow-up screening operation is affected due to accumulation of the husked rice mixture is avoided; a screening assembly is arranged in the box body, a cam can be driven to rotate by starting a second motor, a push plate is pushed by the cam to start to move, a fixed rod drives a screening frame to do reciprocating motion in the front-back direction, and screening of the husked rice mixture is achieved in cooperation with a telescopic rod and a spring; and meanwhile, under the cooperation effect of the multiple speed reduction strips, the vibration screening effect of the screening frame can be further enhanced, and the machining efficiency is improved.

The utility model discloses a continuous tea processing device, including the grinding disc, the outer side of grinding disc is equipped with the casing, casing lower part fixedly connected with the falling platform, the falling platform lower part fixedly connected with first falling cylinder, the grinding disc lower part fixedly connected with second falling cylinder, second falling cylinder is equipped with in first falling cylinder inside, second falling cylinder lower part fixedly connected with first connecting panel, first connecting panel outer side fixedly connected with the gear ring, the gear ring lower part rotatablely connected with the screening box, the screening box upper part is equipped with the feed inlet of facing first falling cylinder, the screening box one side fixedly connected with second connecting panel, second connecting panel lower part fixedly connected with first motor, first motor power end penetrates second connecting panel fixedly connected with the gear, the gear is engaged with the gear ring, can prevent the tea of grinding disc upper part remanence, causes the tea cleaning difficult, causes the tea waste.

The present invention provides a method and system for measuring the complexity of an online transaction processing system, which belongs to the field of financial information technology, and specifically comprises: based on the analysis results of transaction links of cross-system transactions, determining the transaction links between different application systems of different cross-system transactions, and determining the complex system transactions in the cross-system transactions in combination with the operation data of the application systems involved in the transaction links, determining the transaction processing complexity coefficients of different complex system transactions based on the call data of the transaction links between different application systems of different complex system transactions, acquiring the historical execution data of different complex system transactions, and combining the transaction processing complexity coefficients of different complex system transactions to measure the complexity of the online transaction processing system, and determining whether the complexity of the online transaction processing system meets the requirements through the measurement results, thereby improving the accuracy of the measurement results of the complexity of the online transaction processing system.

The application discloses a machine learning algorithm for screening of metal elements in a diatomic catalyst full cycle based on product yield prediction and application thereof, and the algorithm comprises the following steps: (1) collecting attribute features of metal elements in the diatomic catalyst as a feature space 1; (2) preliminarily screening the attribute features according to comprehensive scores of feature importance to obtain a feature space 2; (3) performing feature operation processing on the feature space 2 to generate a multivariate descriptor space matrix; (4) performing dimension reduction processing on the multivariate descriptor space matrix by combining a gradient boosting regression model with a recursive feature elimination algorithm; (5) further screening to obtain an interpretable descriptor by using a least absolute shrinkage and selection operator; and (6) applying the interpretable descriptor to a random forest regression model to screen a catalyst for a propane dehydrogenation reaction to prepare propylene. The application can solve the problem that a traditional descriptor is difficult to directly predict a catalytic product yield.

This invention relates to the field of graphite waste treatment technology, and more particularly to a method for preparing special graphite materials from isostatic pressing graphite waste, comprising the following steps: waste collection: firstly, the waste generated from isostatic pressing graphite production is collected and processed centrally; waste treatment: the collected waste is centrally fed into a purification module, where impurities are screened and removed; waste crushing: after the isostatic pressing graphite waste has been screened, it is pushed into a crushing device for crushing; material proportioning, pressing, primary calcination, and graphitization treatment; this invention, by processing the waste from isostatic pressing graphite production through the screening and purification processes described above, followed by crushing, can then be proportioned, fed into a mixing pot, and then pressed, calcined, and graphitized to produce special graphite materials, thus avoiding environmental pollution from waste and achieving full utilization of resources.

The invention discloses a method for bifluorescence quantitative detection of epithelial cells of a lacrimal gland organ and application. The method comprises the following steps: providing a mouse lacrimal gland organ; a recombinant adeno-associated virus combination is added to the organoid, the combination comprising: a first AAV vector comprising a promoter specifically driving the expression of alveolar epithelial cells and a first fluorescent protein coding sequence; the second AAV vector contains a promoter for specifically driving expression of myoepithelial cells and a second fluorescent protein coding sequence; according to the method, the two cells can be visually distinguished, and by calculating the fluorescence area or the number of the cells, the alveolar / muscular epithelial cell proportion is established as a damage index, so that high-throughput drug screening is realized.

The utility model relates to a screening device for grain and oil processing, which comprises a bottom frame, the top of the bottom frame is fixedly connected with a shell, the shell is internally provided with a screen drum, the top of the bottom frame is provided with a driving mechanism, one side of the screen drum is provided with a dust falling mechanism, and the driving mechanism comprises a first motor fixedly connected to the top of the bottom frame. One end of the first motor is fixedly connected with a linkage assembly, the outer surface of the shell is fixedly connected with a movable wheel, one end of the linkage assembly is connected with the movable wheel, one end of the shell is fixedly connected with a feeding hopper, the other end of the shell is fixedly connected with a discharging hopper, and the feeding hopper and the discharging hopper are both in an inclined state. According to the screening device for grain and oil processing, the driving mechanism is arranged, power is transmitted to the movable wheel through the linkage assembly, the movable wheel rolls in the rolling groove in the outer surface of the screen drum, and therefore the screen drum is driven to rotate stably, and grain screening can be achieved through the driving mode.

The invention discloses a fission yield experiment data screening method, and relates to the technical field of nuclear data evaluation.The method comprises the steps that S1, fission yield experiment data are obtained from an EXOR database, and the experiment data are grouped; s2, fitting each group of fission yield experimental data by adopting a Zp model, and determining model parameters; the fission yield is calculated according to the determined model parameters, so that a yield calculation value is obtained; s3, calculating the deviation between the fission yield experiment data and the fission yield calculation value obtained in the step S2; and S4, screening the experimental data according to the deviation obtained in the step S3. According to the method provided by the invention, the evaluation efficiency can be effectively improved, the research period is shortened, and technical support is provided for further establishing an experimental database.

This invention discloses a hovering method and system for firefighting drones based on laser guidance and reliable fusion, relating to the field of drone hovering control technology. By deploying laser guidance devices in the high-altitude firefighting operation area, a stable spatial guidance reference is established to guide the drone into the target hovering area and continuously receive coded laser beams. Based on this, laser reception features are extracted and a link reliability factor is calculated to assess the reliability of laser deviation observation information and suppress anomalies. Simultaneously, the laser deviation observations are aligned with the attitude, velocity, and altitude information output by the inertial navigation unit using a time reference and coordinate consistency correction to form a fused data set. Through adaptive reliable fusion and consistency constraints, a hovering error vector for hovering control is constructed, driving the flight control unit to dynamically adjust the drone's hovering position, thereby improving the stability and reliability of drone hovering positioning during high-altitude firefighting operations.

The utility model provides a kind of plastic granule mixing equipment of plastic product processing, including conical mixing cylinder, gear sieve plate one, gear sieve plate two, multiple stirring rods, conical mixing cavity is opened in conical mixing cylinder inside, conical mixing cylinder bottom end fixed connection bolt base, bolt base is opened on and is discharged groove, bolt base is fixedly connected in equipment feed cylinder top end by multiple fixed bolts. By driving assembly one drives gear sieve plate one to rotate in clockwise direction, simultaneously by driving assembly two drives gear sieve plate two to rotate in counterclockwise direction, then adjust the filter hole spacing between gear sieve plate one and gear sieve plate two, the stepless continuous adjustment of filter hole spacing can be realized by the synergistic effect of bidirectional rotation, without replacing sieve plate can be adapted from microgranule to coarse granule Full-specification plastic raw material, in dynamic adjustment process, filter hole edge produces slight shearing force to particle, can break a small amount of soft agglomerate particle, realize the dual function of screening and preliminary dispersion.

The invention discloses a ship operation data backtracking method based on an error correction algorithm, which relates to the field of maritime engineering, solves the problem of high error rate of ship operation data abnormity backtracking, and comprises the following steps: setting a track monitoring area of a target ship in the navigation process, analyzing ship navigation data based on the track monitoring area, and determining the ship operation data according to the analyzed ship navigation data. Obtaining an optimized ship track of the target ship; the optimized ship track is analyzed, the target ship is classified according to the historical track of the historical ship, and the historical ship of the same category as the target ship is obtained; analyzing the ship operation data, judging an abnormal condition of the ship operation data corresponding to the target ship in combination with historical operation data, and generating a corresponding abnormal signal; after the abnormal signal is received, a ship operation function is constructed according to the historical operation data of the same type of historical ships, abnormity backtracking is conducted on the ship operation data of the target ship based on the ship operation function, and accurate backtracking of the ship operation data is achieved.

The utility model relates to the technical field of machine-made sand preparation, in particular to a machine-made sand classifying and screening device which comprises a vertical cylinder, a quantitative feeding mechanism, a driving mechanism, a sound insulation mechanism, a classifying screen mechanism, a supporting mechanism and a finished product machine-made sand recycling mechanism. A sound insulation mechanism is arranged on the outer wall of the vertical cylinder, the vertical cylinder is connected with the ground through a supporting mechanism, the classifying screen mechanism comprises screen meshes which are sequentially arranged in the vertical cylinder from top to bottom, a finished product machine-made sand recycling mechanism is connected to the outer wall, where one end of each screen mesh is located, of the vertical cylinder, and the mesh number of the screen meshes is sequentially increased from top to bottom. The top end of the vertical cylinder is connected with a feeding pipe, and the feeding pipe is provided with a quantitative feeding mechanism. The vertical space can be fully utilized, environmental pollution is reduced, the automation level of the device is provided, the screening quality is guaranteed, and multi-level grading screening can be achieved.

The application discloses an energy-saving sound-insulation building material melting and blending device and method, relates to the technical field of energy-saving sound-insulation building material melting and blending, and comprises a blending box. The energy-saving sound-insulation building material melting and blending device and method have the advantages that when raw material melting and blending operation is carried out, large-particle raw materials are located on the screening plate, in the melting and blending process, each heat conduction rod directly transmits heat at the heating layer to the material close to the center point of the screening plate, compared with the raw material melting and blending below, heat transmission above is faster, meanwhile, a forward and reverse motor is started, the forward and reverse motor drives stirring blades and annular cutting blades to cut and stir the large-particle raw materials in the preliminary melting state, so that the melting and blending degree of the large-particle raw materials above is close to the melting and blending degree of the small-particle raw materials below, the melting and blending time does not need to be prolonged according to the difference of particles, and the effect of accelerating the melting and blending progress of the raw materials is achieved.

This disclosure pertains to the field of batteries, specifically a method and system for early warning of thermal runaway in automotive power batteries. It involves collecting data on individual battery cell voltage, total voltage, current, and temperature to construct an original feature sequence. This sequence is then fused using multi-head one-dimensional convolution to integrate local temporal features at different time scales, generating a fused feature sequence. Temporal encoding is performed using a gated recurrent unit with an added anomaly response gate. Anomaly scores are calculated based on the degree to which the input features deviate from the historical mean, and the hidden state is updated accordingly. The output consists of a hidden state sequence and anomaly score sequence. A dual-channel attention module is used to calculate temporal and feature attention weights, which are then coupled through a Hadamard product to generate a coupled attention weight matrix. The hidden states are weighted and aggregated to obtain a context vector, which is decoded by a fully connected network to determine the thermal runaway risk probability. This probability, combined with the rate of change, generates an early warning threshold, enabling real-time and accurate thermal runaway early warning triggering.

The utility model relates to the technical field of soybean processing, and provides a soybean screening and cleaning device. The soybean screening and cleaning device comprises a water pool, a conveying net belt arranged in the water pool and a bubble generating device arranged in the water pool. The pool comprises a first part extending in the length direction of the pool and a second part inclining upwards. A baffle is arranged between the two opposite side walls in the width direction of the first part, and an overflow opening for water to flow out is formed. According to the soybean screening and cleaning device, through the arrangement of the pool, the bubble generating device, the baffle and the overflow port, bubbles generated by the bubble generating device can peel off fine impurities attached to the surfaces of soybeans, meanwhile, the pool can conduct flotation on the soybeans, impurities and bad soybeans with the same particle size as the soybeans are separated, and therefore the soybeans are screened and cleaned. Meanwhile, screening and cleaning of the soybeans are achieved. And floating impurities are intercepted through a baffle, so that the impurities are discharged through an overflow port, the impurities are prevented from being mixed into the soybeans again, and the screening effect on the soybeans is improved.

The invention provides a clinical data intelligent collection method and system and a storage medium, and belongs to the technical field of data analysis, and the method specifically comprises the steps: determining the change conditions of clinical data of different dimensions in a treatment process, determining a correlation coefficient between the clinical data of different dimensions and the disease type in combination with a correlation condition between the clinical data of different dimensions and the disease severity of the disease type, and obtaining a historical collection data volume of the clinical data of different dimensions in historical patients with different disease severity; and the acquisition strategies of the clinical data of different dimensions are determined in combination with the correlation coefficients of the clinical data of different dimensions and the disease types, so that the reliability of the acquisition result of the clinical data is ensured.

The invention relates to the technical field of reservoir scheduling, solves the technical problems that in the prior art, energy consumption of hydropower scheduling of a reservoir group is large, and an analysis result is not an optimal strategy, and particularly relates to a hydropower scheduling optimization method and system considering cascade reservoir group coupling. The method comprises the following steps: S1, acquiring a power generation function Emax of each hydropower station in the cascade reservoir group, and constraining related variables of the power generation function Emax to obtain a constraint condition set; according to the method, the power generation condition of the cascade reservoir group is comprehensively obtained through multiple limiting conditions, the water level and the power generation amount of the reservoir are more comprehensively measured, the optimal power generation strategy can be obtained, the influence of the water level of the reservoir group on the ecology can be monitored, and the power generation efficiency of the cascade reservoir group is improved. The survival condition of animals and plants around the reservoir is ensured, and the efficiency of reservoir group scheduling is improved.

The device disclosed in the present invention for smoothly screening equal-length belts by gravity comprises a platform, a cylinder, a linear rail slider assembly, a small pulley, a large pulley and a weight. The lower part of the large centering shaft is mounted in the large connecting plate through an axial hole. A pressure gauge plate is fixed on the side of the large connecting plate. A dial indicator or a position sensor is fixed on the top of the platform. The large connecting plate is fixedly connected to the slider. The driving shaft fixed at the front end of the piston rod comprises a front limit section, a middle section and a rear limit section. A driving block is fixed on the large connecting plate. The driving handle at the lower part of the driving block is sleeved on the outer side of the middle section. One end of the chain is fixed on the chain fixing block, and the other end droops naturally and fixes the weight. The device can convert the tension force of the belt during use into the gravity of the weight, so as to prevent impact, smoothly measure and screen equal-length belts. The device is easy to operate and the screening results are reliable. By changing the position of the small connecting plate and the size of the weight, the measurement and screening of belts of different specifications can be achieved.

The invention belongs to the technical field of battery anomaly detection, and discloses a method for screening abnormal single batteries in a battery pack and a related device. The method for screening the abnormal single batteries in the battery pack comprises the following steps: acquiring a charge state and a polarization voltage based on acquired current and external voltage of each single battery at different moments; on the basis of the obtained charge state, obtaining the temperature of each battery monomer by using a change function of the model parameters along with the temperature and the charge state; based on the obtained polarization voltage, obtaining an open-circuit voltage of each battery monomer; and respectively calculating the average deviation, the standard score and the Euclidean distance of the charge state, the temperature and the open-circuit voltage of each battery monomer, obtaining characteristic quantities, and carrying out clustering analysis to obtain a screening result of the abnormal battery monomers. According to the technical scheme disclosed by the invention, the abnormal battery monomers in the battery pack can be screened, and the method has the advantages of relatively high efficiency, relatively low cost and relatively high reliability.

The utility model relates to the technical field of photovoltaic module production, in particular to a junction box turnover box shuffling and conveying mechanism and a photovoltaic module production system. The utility model provides a junction box turnover box shuffling and conveying mechanism which comprises a photovoltaic module junction box turnover box shuffling assembly and a photovoltaic module junction box vibration feeding assembly. The photovoltaic module junction box turnover box pouring assembly comprises a photovoltaic module junction box turnover box feeding line, a box turning structure and a photovoltaic module junction box feeding line; the turnover box structure is provided with an inlet and an outlet, the photovoltaic module junction box turnover box feeding line is arranged at the inlet, and the photovoltaic module junction box feeding line is arranged at the outlet; the box overturning structure automatically discharges materials, manpower is saved, the efficiency is high, the production efficiency is improved, meanwhile, the photovoltaic module junction boxes are conveyed to the photovoltaic module junction box vibration feeding assembly through the photovoltaic module junction box feeding line, and screening of the photovoltaic module junction boxes with the front faces facing upwards is achieved through vibration feeding.

This invention provides a method for manufacturing VDMOS. The method acquires an initial image of the VDMOS under test, determines the device model and pin count of the VDMOS based on the initial image, and obtains preset detection points and corresponding preset pressures on each pin according to the device model. Based on the preset detection points and preset pressures, the pressure heads in the upper and lower test groups are controlled to perform upper and lower compression tests on the pins of the VDMOS under test, obtaining a first detection result. Then, the pressure heads in the left and right test groups are called to perform left and right compression tests on the pins corresponding to the first detection result, obtaining a second detection result. This invention automatically matches test parameters by identifying the device model, and utilizes physical compression in the upper and lower and left and right directions combined with image analysis to detect the state of the pins under stress, thereby identifying pin defects and achieving the detection of the physical quality of the manufactured VDMOS.