85results about How to "Realize identification" patented technology

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.

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 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 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 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.

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.

This invention discloses a method for decomposing noise sources in aero-engine components, comprising the following steps: S1, spatial sound source analysis; acquiring noise input at each measurement point, constructing a covariance matrix and performing singular value decomposition; obtaining the number of eigenvalues ​​reaching a set contribution threshold; S2, extracting broadband time-domain components and pure audio-domain components; removing discrete pure-tone periodic components to obtain stationary random broadband components; processing the total noise and broadband noise separately using a Hanning window-applied discrete Fourier transform and subtracting them to obtain the spectrum of the pure-tone noise components; S3, adaptive signal decomposition filtering; S4, sound source directivity identification; S5, sound source separation; S6, noise component identification; S7, amplitude calibration; S8, sound source merging. This invention can accurately decompose fan noise and jet noise from engine noise, enabling accurate assessment of the contribution of modern turbofan engine noise sources at different frequencies and angles.

The invention provides a federated learning-driven cross-mine intelligent risk identification method. Comprising the steps of mine multi-source operation image collection and mine risk event data set construction, mine intelligent risk perception and event recognition model construction, federated learning-based distributed mine risk model training and parameter optimization, model deployment and mine intelligent risk recognition. According to the method, through multi-layer feature coding and cross-scale collaborative modeling, the risk events of the key working area of the mine are accurately positioned and classified, and comprehensive identification of the risk events of the mine can be realized; federated learning and an adaptive sparse parameter communication method are adopted, cross-mine model training can be completed without concentrating original image data, and mine data privacy and distributed training efficiency are guaranteed; meanwhile, the comprehensive risk level of the whole image is generated in real time in combination with multi-event features and a global risk comprehensive evaluation mechanism, a direct quantitative decision basis is provided for mine safety management and instant early warning, and accuracy and operability are improved.

The application discloses a bronchoscope supply-demand dynamic matching method based on multi-source data fusion, comprising: collecting multi-source heterogeneous data and performing fusion processing to obtain a device feature matrix, a demand feature matrix and an environment feature vector; determining a score calculation strategy according to a comparison result of a historical matching data accumulation amount and a preset threshold, determining a device availability score and a demand urgency score based on the device feature matrix and the demand feature matrix according to the score calculation strategy; constructing a device queue and a demand queue, attaching an initial scene label to each demand and performing identification, and outputting a standardized scene type; outputting an optimal matching scheme through a reinforcement learning intelligent agent based on the device queue, the demand queue, the standardized scene type and the environment feature vector; performing intelligent scheduling based on the optimal matching scheme, updating the queue based on external real-time events, and if both queues are non-empty at the same time, obtaining a new optimal matching scheme, otherwise, keeping a waiting state. The application can improve matching efficiency and accuracy.

The application relates to the technical field of artificial intelligence, and provides an intelligent question answering method, which comprises the following steps: performing speech recognition on user voice to obtain recognized text; performing semantic recognition on the recognized text to obtain a semantic recognition result; performing pronoun replacement on the recognized text to obtain text information; performing style recognition on the user voice and the text information to obtain a user style; performing style text generation on the user voice, the user style and the information to obtain a reply style and reply text; and performing speech generation on the reply style and the reply text to obtain a reply voice. The application is applied to an intelligent customer service or assistant scene. The application performs speech recognition through a preset question answering model, thereby improving the accuracy and efficiency of speech recognition. The accuracy of voice content and style recognition is ensured through pronoun replacement, thereby improving the accuracy and efficiency of generated styles and texts, and further ensuring that the generated reply voice conforms to the user style.

The invention provides an AI alarm system based on safety management, and belongs to the technical field of intelligent alarm. The AI alarm system based on safety management comprises a monitoring camera, a data center and a protection cabin. The protection cabin comprises a shell, a window protection plate and a driver. And the internal space of the shell is used for installing a monitoring camera. The front end wall of the shell is provided with a view window for the monitoring camera to acquire image data. The window protection plate is arranged on the visual field window so as to shield the visual field window. And the window protection plate is made of a colorless transparent material. The window protection plate is in transmission fit with the driver, and the driver is used for driving the window protection plate to move in the direction perpendicular to the central axis of the view window. The monitoring camera is electrically connected with the data center. The accuracy of the obtained image data can be effectively improved, and the alarm misjudgment rate is further reduced.

The application discloses a robust palm region of interest positioning method in a natural scene, and comprises the following steps: acquiring an input picture, detecting a palm region and a palm contour region in the input picture, and obtaining a palm region and contour region feature map; inputting the feature map into a palm region of interest positioning network model, performing regression on the feature map through a positioning network in the model, obtaining a posture correction parameter, performing spatial change on the palm region feature map, performing down-sampling and finger root amplification on the image, and generating an adjusted feature map; performing key point coordinate fusion regression on the adjusted feature map, obtaining a first key point coordinate, inversely transforming the coordinate into a coordinate system of the original input picture, obtaining a second key point coordinate; and extracting a palm region of interest image based on the second key point coordinate. The application does not need to remove the background through infrared imaging, can process problems such as translation and rotation in a large range, and realizes the non-contact palm region of interest positioning demand in a natural scene.

This invention discloses a method for locating stormwater and sewage mixing points and identifying pollution sources in drainage pipe networks based on particle swarm optimization (PSO) algorithm, belonging to the field of drainage pipe network monitoring and diagnosis technology. The method includes: acquiring basic data of the drainage pipe network and constructing a SWMM hydraulic and water quality model; deploying monitoring points to acquire real-time monitoring data; determining the range of pollution source parameters; initializing the particle swarm using the PSO algorithm and updating the model parameters; calling SWMM for simulation calculations; calculating the fitness value based on the objective function and updating the extreme values; checking the termination condition and outputting the optimal solution. This invention achieves multi-condition adaptive identification through the organic combination of the PSO algorithm and the SWMM model, effectively solving the problems of low positioning accuracy and poor computational efficiency in complex pipe networks using traditional methods. It has outstanding advantages such as high positioning accuracy, strong adaptability, and excellent computational efficiency, providing an effective technical means for the treatment of stormwater and sewage mixing in urban drainage pipe networks.

The tail gas purification and preheating control method comprises the following steps that the tail gas temperature of tail gas entering and / or exhausted out of a combustion unit is obtained, and the combustion unit is connected between an exhaust port of an engine and an air inlet of an absorption refrigeration system; acquiring working condition information of the engine; judging whether at least one of a preheating condition and a purification condition is met or not according to the tail gas temperature and the working condition information, and if yes, starting a combustion unit; if not, the current state is kept; wherein the preheating condition is that the temperature of the tail gas is smaller than or equal to the low-temperature critical temperature, and the low-temperature critical temperature ranges from 90 DEG C to 320 DEG C; the purification condition is that the working condition information indicates that the engine is in an instant acceleration working condition. According to the control method, whether the tail gas temperature reaches the low-temperature critical temperature or not and the working condition of the engine serve as the judgment basis, comprehensive recognition of the preheating requirement and the purification requirement is achieved, and a foundation is provided for differential control.

The invention provides a single-frequency cycle slip detection and restoration method and system for NLOS recognition in an urban sheltered environment, and the method comprises the steps: recognizing an NLOS signal of GNSS observation data through a self-supervision NLOS recognition model based on Transform, dividing the NLOS signal into a cycle slip-free data set and a suspicious data set, according to the method, on the basis of the cycle-slip-free data set, TDCP detection is carried out on suspicious cycle-slip data one by one, it is guaranteed that at most one suspicious satellite generates cycle slip in each detection, the defects of a traditional detection method are avoided, and if the cycle slip is detected, repair is carried out; according to the method, the feature robustness and the cross-scene generalization ability are improved through the space contrast learning and time feature extraction module, and the NLOS recognition precision is higher. And the cycle slip detection reliability and the positioning robustness of the single-frequency GNSS in a complex shielding environment are remarkably improved.

Embodiments of the present disclosure disclose a kind of intersection generation method, device, electronic equipment and computer readable storage medium, the method comprises: obtaining the high-precision map data in the preset road range, wherein the high-precision map data includes high-precision boundary lane line;Obtain the standard-precision map data matched with the high-precision map data, wherein the standard-precision map data includes standard-precision intersection node and standard-precision road section line;In response to the intersection of the standard-precision road section line connected with the standard-precision intersection node and the high-precision boundary lane line, then according to the standard-precision map data, generate target intersection at the intersection point of high-precision boundary lane line.This technical solution can accurately, timely and efficiently generate low-grade road intersection, so as to improve the freshness and completeness of high-precision map data, to assist the automatic driving car to accurately enter or exit corresponding intersection area, improve the user's use experience.

The application discloses a method and device for determining a source of an odor, equipment, a storage medium and a product, and relates to the technical field of air conditioning equipment control. The method comprises the following steps: obtaining a first TVOC concentration at an air inlet of air conditioning equipment and a second TVOC concentration at an air outlet of the air conditioning equipment; calculating a first difference between the first TVOC concentration and the second TVOC concentration; and determining whether the odor is from inside the air conditioning equipment or outside the air conditioning equipment based on the size relationship between the first difference and a preset threshold. The application can identify the source of an indoor odor.