121results about How to "Realize identification" patented technology

The invention discloses a liquid storage type micro-fluidic chip and a working method thereof. The chip comprises a chip body, a sealing film and gum, the sealing film and the back adhesive are respectively bonded on the front surface and the back surface of the chip body; a plurality of solution storage cavities are formed in the chip body, outflow runners at the bottoms of the solution storage cavities are connected with corresponding first runners, sealing partition pieces are arranged on the first runners, the outflow runners and the corresponding first runners are blocked through the sealing partition pieces, and the first runners are communicated with second runners through corresponding gum runners. The whole experiment process does not need to be externally connected with a reagent bottle, the purposes of instant detection, preparation and sample separation of the micro-fluidic chip can be achieved, the detection time is greatly shortened, and the experiment steps are simplified. Waste liquid generated in the experiment process flows into the waste liquid cavity, and cross contamination of a laboratory is avoided. The chip provided by the invention can be used for identifying the species of pathogenic microorganisms.

The invention discloses a bearing vibration signal processing model construction method, a model and a signal classification method, which are used for constructing time domain and frequency domain loss functions by calculating a plurality of feature vector distances so as to train an encoder. According to the method, by minimizing the difference value of different distances in the time domain and frequency domain loss functions, an encoder can be guided to extract similar feature representations in signals, so that the similar feature representations are gathered in a feature space, and dissimilar features are separated. When a trained encoder (a convolutional neural network with an attention mechanism) processes a vibration signal of an unknown fault type, some feature representations in the signal are different from those of other signals, so that the feature representations are gathered in a feature space and are far away from the feature representations of other signals, and the fault detection accuracy is improved. Therefore, the recognition of the vibration signal of the unknown fault type is effectively realized.

The invention relates to the technical field of visual inspection, in particular to a stamping part defect detection method based on vision, which comprises the following steps: S1, shooting setting; s2, synchronizing video streams; s3, acquiring a part bounding box and a hole position bounding box; s4, associating part bounding boxes belonging to the same stamping part among the frame part images, and associating hole position bounding boxes belonging to the same screw hole position; s5, correspondingly associating the bounding boxes of the target parts belonging to the same stamping part in the part image; s6, when a hole position boundary frame matched with the view angle template image of the corresponding view angle exists in any target detection image under any view angle, determining that a screw hole position exists; and when the matched hole position boundary frame is not found in the target detection image under the corresponding visual angle in the visual angle template images of all the visual angles, the screw hole position is missing. The stamping part defect detection device can be used for defect detection of stamping parts in the conveying process, the consistency of detection results is improved, and the detection efficiency is improved.

The invention discloses a distributed dynamic load identification method and a distributed dynamic load identification system based on a Transform framework. The method comprises the following steps: constructing a response-excitation data set in a mode of combining simulation and test, calculating a corresponding load, forming a response matrix # imgabs0 #, performing orthogonal polynomial order selection according to the highest order required by orthogonal polynomial decomposition of a load sample in the data set, and calculating an orthogonal polynomial value matrix L; performing model training on a Transform neural network architecture model according to the response matrix # imgabs1 # and the orthogonal polynomial value matrix L, wherein the model mainly comprises an embedded layer, an encoder and a decoder; and inputting a response signal by using the trained network model to obtain a corresponding distributed load. According to the method, the mapping from the limited response signal to the distributed dynamic load is directly constructed, the problem that a traditional distributed dynamic load method is not qualitative in the inversion process is effectively solved, and the method has good precision in identification of various distributed dynamic loads.

The invention relates to a double-fed fan high-low voltage ride-through control parameter identification method and system, and the method comprises the steps: analyzing a high-low voltage ride-through threshold value according to simulation data outputted by a pre-constructed double-fed fan control structured model; the high-low voltage ride-through threshold value is used as a voltage initial value of high-low voltage ride-through control, a high-low voltage ride-through control mode of the double-fed fan is identified, and a high-low voltage ride-through strategy is formulated; and on the basis of a high-low voltage ride-through strategy, identifying each parameter in the control link to obtain each control parameter value in the control link. According to the scheme, a set of complete method for identifying the fault ride-through control mode and the control parameters is formed based on the doubly-fed fan control structured model, and identification of the control parameters can be rapidly and effectively achieved.

The invention discloses an adapter card identification method and device, electronic equipment and a computer readable storage medium, the method and device are applied to a substrate management controller, the substrate management controller and a basic input and output system are both in communication connection with a preset storage medium, and the method comprises the steps that an adapter card physical link information table is traversed, and a target adapter card is determined; determining a target serial number corresponding to the target riser card in the riser card white list; determining a target storage medium channel corresponding to the target serial number in the riser card static information table; reading through the target storage medium channel to obtain a real serial number of the target riser card; if the real serial number is consistent with the target serial number, target static information corresponding to the target serial number in the riser card static information table is written into a preset storage medium to be read by the basic input and output system, and the target riser card is recognized by the basic input and output system. According to the technical scheme, the automatic identification of the adapter card by the basic input / output system in the server is realized through the baseboard management controller.

The present invention provides an intelligent dredging robot and a dredging management method for an elevated bridge deck drainage system, which belongs to the technical field of robots, and specifically comprises: based on the sequence of dredging treatment of drainage systems at different potential danger locations, a plurality of dredging treatment schemes are generated; the treatment time of different potential danger locations under different dredging treatment schemes is determined based on the distribution data of different potential danger locations; the treatment time effectiveness of different dredging treatment schemes and the available treatment schemes under the dredging treatment schemes are determined in combination with the water accumulation risks at different potential danger locations; based on the historical traffic flow data, the treatment time effectiveness and the treatment time effectiveness of the available treatment schemes at different potential danger locations, the dredging treatment schemes among the available treatment schemes are determined; and the dredging treatment schemes and the dredging robots are used to dredge the drainage system at the potential danger location, thereby avoiding the impact of water on the elevated bridge surface on traffic.

This invention provides a method for identifying battery degradation parameters and estimating battery health status, relating to the field of battery health management technology. This invention constructs an explicit physical correlation between the battery's voltage dynamic response and degradation parameters through an electrochemical model; it significantly improves computational efficiency by replacing the complex calculation process in the electrochemical model with a surrogate model based on a neural network; it achieves identification of battery micro-degradation parameters through self-supervised learning of voltage reconstruction based on physical mechanisms; and it estimates battery state of health (SOH) based on these mechanism-transparent micro-degradation parameters, significantly improving the interpretability and accuracy of battery SOH estimation.

This invention discloses a method utilizing nuclear magnetic resonance double-T E The method for classifying water flooding levels in well logging is as follows: First, the transverse relaxation rate of nuclear magnetic resonance (NMR), the geometric mean of the mobile fluid portion of the T2 spectrum, and the double T2 spectrum are calculated sequentially using NMR logging data. E The geometric mean difference of the mobile fluid portion of the T2 spectrum was measured. Then, the porosity of different components was obtained by inversion of echo data under long waiting times and short echo intervals. Finally, the percentage content of macroporous components in the total porosity was plotted against the T2 spectrum. E Cross plot of geometric mean difference of the mobile fluid portion of T2 spectrum and plotting of array induced resistivity AT90 and double T E The cross plot of the geometric mean difference of the mobile fluid portion of the T2 spectrum is measured to identify the flooding level of the flooded layer: unflooded layer, low flooded layer, medium flooded layer, and high flooded layer.

This invention discloses an intelligent voiceprint anti-counterfeiting method, device, and equipment based on hops signals. It collects the voiceprint signals generated by hops hitting the bottle wall, then denoises the signals and extracts PLP features. These feature signals are then input into a CNN-GMM-HMM voiceprint model for training to construct an original standard database. After collecting sample voiceprint signals, they are preprocessed and then matched and identified with the voiceprint information in the standard database to achieve authenticity verification. Compared to traditional identification methods, this method can identify genuine and counterfeit liquor faster and more accurately, greatly improving work efficiency while helping to ensure the quality and safety of liquor.

The invention discloses a banknote processing method and device, a storage medium and electronic equipment. Relates to the field of artificial intelligence, and the method comprises the steps: carrying out the image collection of each put banknote under the condition that the banknote is detected to be put into a banknote inlet of a banknote counting machine, and obtaining a banknote image; processing the banknote image through a banknote identification model to obtain banknote information of the banknote image, the banknote information including at least one of the following: a banknote denomination and a region to which the banknote belongs; determining a target anti-counterfeiting detection model matched with the banknote information from a plurality of anti-counterfeiting detection models; performing anti-counterfeiting detection on the banknote image through the target anti-counterfeiting detection model to obtain a first detection result; and based on the first detection result of the banknotes put in the banknote inlet, determining the number and the total amount of the normal banknotes put in the banknote inlet. According to the invention, the problem of low currency counting accuracy in the prior art is solved.

The invention discloses an operator precision verification method and device, a general-purpose computing chip, equipment and a medium. The method comprises the steps that a user computing task instruction in a computing scene is loaded and executed; when a calling instruction for a target interface of a target user operator in the user operator library is executed, real-time task data are extracted, and the target interface is called; based on the real-time task data, obtaining a precision self-checking result according to a first execution result of the programmable computing unit IP on the target user operator and a second execution result of the standard computing unit IP on the target standard operator; and returning the first execution result and the precision self-checking result, and continuing to execute the next task instruction. According to the method, the correctness of the user operator is verified based on user input by synchronously executing the standard operator through the standard calculation unit IP, so that the test process fully covers any user scene, the identification of potential problems is realized, the universality and effectiveness of operator precision verification are improved, and the reliability of a chip is improved.

The utility model relates to a throw-in type high-temperature dew point measuring sensor, which comprises a shell and a crystal resonator, a flange-shaped fixing part is formed on the outer wall of the shell, the shell is limited into an upper part and a lower part by the fixing part, and the lower half part of the shell is inserted into a gas environment or a cavity to be detected; an air chamber for refrigeration is formed in the shell, and the air chamber is provided with an air inlet and an air outlet; the bottom of the shell is provided with a containing cavity communicated with the air chamber, the crystal resonator is fixed in the containing cavity, and the crystal resonator outputs resonant frequency parameters or equivalent electrical parameters of the crystal resonator through a first lead. According to the invention, the method can achieve the judgment of the dew formation moment in a high-temperature environment, and achieves the measurement of the dew point temperature on the basis.

The invention discloses a distribution network automation feeder terminal switching method, system and device with a fault self-diagnosis function and a medium. The method comprises the steps that an original electrical signal is collected through an input interface unit; intermediate information data are obtained through the signal processing module; electrical characteristics are collected through a main control module to obtain an interface type identification result, adaptive adjustment is carried out on the intermediate information data, and an adaptive signal is obtained and output; and acquiring and analyzing the digital signal to obtain device operation state information, performing fault diagnosis in combination with the interface type identification result, and triggering an alarm when abnormality is diagnosed. Intelligent conversion is achieved by integrating multiple interfaces, the problem that equipment interfaces of multiple manufacturers are incompatible is solved, the tedious operation of equipping multiple adapters on site is avoided, the accuracy and stability of cross-interface signal transmission are guaranteed, and the operation reliability, operation and maintenance convenience and system overall safety of the device in a complex environment are improved.

The present invention provides a SAR working mode recognition method, device, equipment and medium. The method includes: obtaining a signal pulse string group of a spaceborne SAR, the signal pulse string group includes at least one signal pulse string; performing data preprocessing on each signal pulse string to obtain an azimuth time-frequency diagram sequence of the signal pulse string group; extracting the intensity variation characteristics along the azimuth time axis from the azimuth time-frequency diagram sequence, the intensity variation characteristics characterizing the receiving power intensity variation characteristics of the SAR working mode; extracting the Doppler time-frequency curve motion characteristics from the azimuth time-frequency diagram sequence, the Doppler time-frequency curve motion characteristics characterizing the Doppler course motion characteristics of the SAR working mode; determining the working mode of the spaceborne SAR according to at least one of the intensity variation characteristics and the Doppler time-frequency curve motion characteristics.

The present application provides a kind of splashing slag protects furnace and jumps slag information identification method, device, equipment and storage medium, the method is by obtaining initial image and to be identified image, based on the initial network model of labeled initial image is trained, obtains the output result of jump slag identification model, the output result includes multiple different labels, different label in output result is assigned to different pixel value, to obtain target jump slag image, identify target jump slag area in target jump slag image, to obtain the jump slag information of to be identified image;By image construction image recognition model, the intelligent identification of to be identified jump slag image is carried out, realizes the identification of converter jump slag particle, improves its identification accuracy, reduces the input of manpower, and provides reliable data source for other intelligent processing.

This application provides a data redundancy identification method, apparatus, electronic device, and storage medium. The data redundancy identification method includes: obtaining fields to be identified from at least two data tables in a preset database; obtaining the support level of the fields to be identified; and identifying reasonable redundant fields among the fields to be identified based on the support level of the fields to be identified, wherein reasonable redundant fields refer to fields whose frequency of occurrence is higher than a preset value. This application implements the identification of reasonable redundant fields.

The invention relates to the technical field of image data processing, in particular to an intelligent identification method and system for an osteoporosis area, and the method comprises the following steps: extracting edge sharpness and texture uniformity parameters from a two-dimensional image, adjusting the gray threshold of the image, and segmenting an osteoporosis candidate area. According to the invention, through integration of image data processing and three-dimensional modeling, the ability of analyzing the osteoporosis area is improved. When a two-dimensional image is processed, edge sharpness and texture uniformity parameters are extracted, and a gray threshold is adjusted, so that an osteoporosis candidate region is identified, a foreground and a background in the image are isolated, and a segmentation result is further refined by using intensity difference and connectivity between pixel points; therefore, high-precision data are provided in bone tissue structure and bone mineral density analysis. And the two-dimensional image is converted into the three-dimensional voxels, and the three-dimensional model is constructed, so that the analysis depth is increased, and the evaluation of the structural stability and the stress point is more comprehensive.

The invention belongs to the technical field of mechanical intelligent operation and maintenance, and discloses a mechanical equipment fault identification method and device and a storage medium in the technical field of mechanical equipment intelligent operation and maintenance, and the method comprises the steps: extracting a domain global feature of a vibration signal, extracting an intra-domain classification feature of the domain global feature through an intra-domain classification feature extractor, extracting inter-domain classification features of the vibration signals through the inter-domain feature extractor, performing numerical value addition operation on the inter-domain classification features and the intra-domain classification features to obtain recombination classification features, and inputting the inter-domain classification features, the intra-domain classification features and the recombination classification features into a fault classifier to obtain a fault type prediction probability; and obtaining a corresponding fault type ordinal number through the maximum value of the fault type prediction probability, thereby realizing identification of the fault type. According to the invention, the technical problem that the fault identification accuracy of the mechanical equipment is reduced due to the fact that a novel fault is wrongly identified as an existing fault type can be solved.

The utility model belongs to the technical field of license plate recognition equipment, particularly relates to intelligent community license plate recognition equipment, and aims to solve the problems of poor environmental adaptability, low recognition rate and insufficient control flexibility of traditional equipment proposed in the background technology, and provides the following scheme: the intelligent community license plate recognition equipment comprises a box body, and the outer wall of the top of the box body is fixedly connected with a binocular camera through a screw; stand columns are installed on the outer wall of the bottom of the box. Through cooperation of the millimeter-wave radar, the binocular camera, the temperature and humidity sensor and the illumination intensity sensor, high-precision license plate recognition under all-weather and multi-environment conditions is realized, the misjudgment rate is reduced, the license plate recognition device has the characteristic of multi-mode environment perception, the sliding structure of the stop lever and the compensation lever is matched with the fastening knob, the length of the stop lever can be flexibly adjusted, and the reliability of the license plate recognition device is improved. And moreover, the mounting sleeve, the protective cover plate and the box body are integrally designed, so that the wind resistance, dust prevention and weather resistance of the equipment are enhanced, and the service life is prolonged.

This invention discloses an early warning method and system for high and low voltage switchgear, belonging to the field of power system automation. The method includes: constructing a multi-dimensional sensing network to collect multi-source heterogeneous data such as temperature rise, partial discharge, mechanical characteristics, and environmental conditions in real time; preprocessing the data and aligning it with spatiotemporal features, and dynamically correcting the sensitivity threshold of the partial discharge criterion based on humidity or pressure change rate; extracting multi-dimensional fault feature vectors and dynamically assigning weights to each component according to operating conditions and environmental conditions; inputting the weighted feature vectors into a long short-term memory network integrating an attention mechanism to generate a multi-timescale predicted trajectory of the operating state; comparing the predicted trajectory with preset multi-level state thresholds in real time, and executing a three-level early warning judgment (attention, abnormal, and severe) and corresponding linkage protection strategies. This invention can reduce the risk of false alarms and missed alarms, providing reliable support for the intelligent operation and maintenance of high and low voltage switchgear.

The utility model discloses an elevator loose rope detection and weighing integrated device, which comprises a switch mounting piece, a trigger piece, a microswitch, a Hall switch and fasteners, rope heads on two sides of a double rope respectively penetrate through a car cross beam to be fixed, the switch mounting piece is fixed at the tail end of the rope head on one side through the fastener, the trigger piece is fixed at the tail end of the rope head on the other side through the fastener, and the microswitch is fixed on the other side of the switch mounting piece through the fastener. The microswitch is installed on the side, close to the trigger piece, of the switch installation piece through a fastener and connected into a safety circuit of the elevator. The Hall switch is installed on the other side, away from the trigger piece, of the switch installation piece through a fastener and connected into a weighing loop of the elevator. The magnet is attracted to the bottom of the cross beam of the car frame and right faces the Hall switch on the switch installation piece. Abnormal elongation of the elevator steel wire rope is monitored and recognized through the microswitch and the trigger piece on the switch installation piece, and elevator load recognition is achieved through the Hall switch and the magnet on the switch installation piece. The device is simple in structure, low in manufacturing, machining and assembling difficulty and extremely small in occupied space.

The invention belongs to the technical field of visual processing, and particularly discloses a power transmission line mechanical construction whole process dynamic monitoring system based on satellite remote sensing, which comprises a remote sensing image analysis module, a three-dimensional scene reconstruction module, a terrain ecological evaluation module, a line selection simulation measurement and calculation module, a layout rationality checking module and a comprehensive report generation module, each module can analyze a multi-angle three-dimensional satellite remote sensing image of a target construction area and extract a high-resolution orthoimage and a digital elevation model; reconstructing regional environment data, and generating a macroscopic live-action three-dimensional scene; evaluating terrain stability, identifying ecological environment elements, simulating and optimizing line selection in combination with the traffic demand of the power transmission and transformation project, and synchronously measuring and calculating road construction cost; synergistically analyzing the terrain gradient and stability, and checking the rationality of to-be-laid land such as tower footing; and finally integrating related results to form a comprehensive auxiliary monitoring report. The dynamic monitoring efficiency and accuracy of the whole mechanical construction process of the power transmission line can be remarkably improved.

The invention relates to a cable strut vibration main frequency identification method and device and terminal equipment, and the method comprises the steps: obtaining a spectrogram of cable strut vibration and the estimated main frequency of each order, and extracting the peak frequency and the spectrum peak of each peak point from a curve of the spectrogram according to a neighborhood interval to obtain a spectrum number set of each order; according to the estimated main frequency of each order, the peak frequency in the frequency spectrum number set and the frequency spectrum peak value, calculating to obtain a frequency overlap ratio; the peak frequency corresponding to the maximum frequency overlap ratio value is screened out from the frequency spectrum number set to serve as the main frequency of the order; performing correlation analysis on all the main frequencies of each order to obtain correlation coefficients; and determining the identification main frequency of each order of vibration of the cable rod according to the correlation coefficient. According to the method, the frequency overlap ratio is obtained by pre-estimating the main frequency, the peak frequency and the frequency spectrum peak value, the main frequency of the corresponding order is determined according to all the frequency overlap ratios of each order, then whether all the obtained main frequencies can serve as the identification main frequency of the vibration of each order of the cable strut is judged, and identification of the main frequency of the vibration of the cable strut is achieved.

An automatic modeling method for damaged concrete structure belongs to the technical field of artificial intelligence and building structure health assessment, and comprises the following steps: (1) collecting point cloud information of the damaged concrete structure, and performing two-dimensional slice dimension reduction processing on the point cloud information; (2) constructing a SDS-YOLO segmentation network optimized for sparse discrete features; (3) adopting a U-Net model to detect and extract the outer contour edge line of the mask information of instance segmentation; (4) adopting a surface reconstruction method based on an implicit function to construct an entity unit; and (5) extracting internal steel information by using an LLM, and finally realizing finite element modeling. The present application utilizes the instance segmentation and edge detection technology in deep learning to extract the outer contour information of the point cloud information slice, simultaneously utilizes the large language model LLM to extract the internal steel information of the concrete structure, and finally realizes the reconstruction of the entity unit, and analyzes the fire resistance and static behavior of the damaged structure.

The invention discloses an implementation method for identifying handwrites and driving dialogues based on a visual model, and belongs to the technical field of artificial intelligence and intelligent interaction. According to the method, the technical problem that an existing handmade display scene lacks handmade identification and interaction functions is solved. According to the technical scheme, the method comprises the steps of training and deploying a visual identification model for handwritings; configuring a multi-stage identification model strategy; and executing a hand-made identification driving intelligent interaction process. Finally, the camera detects and recognizes the handshake, obtains a handshake brand IP image and a wearing detail feature tag set, and uses the tag set as a parameter to call a streaming end-to-end voice large model cloud service to drive immersive dialogue interaction conforming to the handshake style.

Embodiments of the present application disclose a financial contract recognition model updating method and device, equipment and a storage medium. The method comprises receiving a contract sample of a financial scene that has been labeled, training an initial model for contract financial scene detection through the contract sample, obtaining a contract financial scene detection model, combining the contract financial scene detection model and a contract financial business recognition model to obtain a financial contract recognition model, sending the model to a head office and at least one branch office, receiving a financial scene detection result of an actual contract generated in the branch office, retraining the financial contract recognition model in the branch office if the number of classification errors in the detection result is greater than a first preset number threshold, updating the financial contract recognition model of the head office if the number of branch offices that are retrained exceeds a second preset number threshold, and synchronizing the update result to the at least one branch office. The method realizes accurate recognition of multiple versions of new financial contracts.

The invention relates to the technical field of production and manufacturing, and discloses a vibroseis earth parameter identification method, device and equipment, and the method comprises the steps: obtaining a function model built based on the system parameters of a vibroseis system; on the basis of the function model, parameter vectors needing to be identified are determined through an index window function and by means of least square; solving process parameters of parameter vectors on the basis of the collected acceleration of the heavy hammer and the acceleration of the flat plate, and determining the parameter vector at the current moment; and based on the parameter vector at the current moment, identifying the earth damping coefficient and the earth elastic coefficient. According to the scheme of the invention, on the basis of the function model, the exponential window function is introduced, and the forgetting factor adapting to the time variation is added for the least square, so that the process parameters for solving through the acceleration of the heavy hammer and the acceleration of the flat plate can accurately reflect the system condition at the current moment, thereby reflecting the time variation of the data, and improving the accuracy of the calculation. And a guarantee is provided for the accuracy of subsequent data identification.

The application discloses a structural damage identification method based on a proxy model and an improved covariance matrix adaptive evolution strategy, and relates to the technical field of structural damage identification.The application comprises the following steps: obtaining a structure to be identified, constructing a finite element model of the structure to be identified, and respectively applying excitation to the structure to be identified and the finite element model to obtain a data set; a hybrid network model based on a convolutional neural network and a long short-term memory network is constructed, and the data set is used for training to obtain a proxy model; the proxy model is improved by using a covariance matrix adaptive evolution strategy based on a model gradient to obtain an optimal solution; a variational Bayesian model correction method is used to correct the optimal solution to obtain the most possible value of a structural damage geometric size parameter, so that damage geometric size and boundary information of the structure to be identified are determined.The application can efficiently and accurately identify structural damage geometric size information.

The application discloses an HDFS data landing method and device, an HDFS server and a computer readable storage medium, relates to the technical field of data processing, and comprises the following steps: an HDFS server acquires to-be-stored data sent by a client device; it is judged whether the to-be-stored data belongs to a target file block; wherein the target file block is a file block of an HBase WAL log; if yes, the to-be-stored data is added to a next flush queue and a response queue; if not, the to-be-stored data is added to the next flush queue, and after the target file block is flushed, the to-be-stored data is added to the response queue; by judging whether the to-be-stored data belongs to the target file block, the HBase WAL log is identified, the data of the WAL log can return response information when landing, the data landing of the direct response sequence flush based on the HBase WAL mechanism is realized, and the speed of HBase data storage is improved.