3465 results about "Identification device" patented technology

The invention relates to the technical field of digital marketing, and discloses an omni-channel marketing funnel intelligent attribution model and an automatic budget distribution system, and the model comprises a data collection module which is used for collecting data through a contact recording device and a user identification device which are disposed at a marketing terminal, and a behavior tracking device and a channel classification device which are disposed at a user side. Acquiring information such as multi-channel marketing contact interaction data, user behavior data and channel types; the path analysis module realizes data path analysis through time sequence synchronization of a time alignment unit, feature matching of a path association unit and dynamic adjustment of a computing power scheduling unit; the attribution calculation module generates the conversion attribution weight of each channel based on the matching data; and the budget mapping module establishes a dynamic mapping relationship between the weight and the budget and updates the dynamic mapping relationship. The system outputs the attribution result through the model application module, and the budget execution module distributes the budget according to the dynamic mapping, so that the channel contribution can be accurately evaluated, the scientific distribution of the marketing budget is realized, and the marketing efficiency and the rate of return on investment are improved.

The invention discloses an extreme sea condition parameter identification system based on deep learning, and relates to the technical field of ship navigation auxiliary equipment, in particular to a self-adaptive sea condition identification device which is used for acquiring image data and inertial measurement data of a current sea condition; the wave field visual depth estimation module is used for extracting visible light image features and infrared image features of a wave area from image data of the current sea condition, fusing the extracted visible light image features and infrared image features, using an encoder-decoder architecture and fusing an energy function to obtain a pixel-level wave height field, and outputting the pixel-level wave height field. The three-dimensional reconstruction of the wave surface is realized; the multi-modal data fusion module uses a filter dynamic model and a cost function to eliminate space-time asynchronous errors between inertial measurement data and visual perception data, performs multi-modal data fusion, and outputs wave field real-time parameterization information. According to the invention, the sea condition parameter real-time high-precision identification capability of the autonomous unmanned ship or the offshore carrying platform can be improved.

The invention relates to the technical field of artificial intelligence and biomedical sensing, and discloses a cognitive disorder risk identification device and method integrating multi-modal physiological data, and the device comprises an EEG module, an eye movement module, an fNIRS module, an edge calculation module and an acceleration sensor; the EEG module collects EEG data, the eye movement module collects eye movement eye-tracing data, and the fNIRS module collects near infrared spectrum fNIRS data and inputs the data to the edge calculation module; the edge calculation module runs the multi-modal space-time attention fusion model to output a cognitive impairment risk assessment result by using the multi-modal space-time attention fusion model; the acceleration sensor operates based on an operation dynamic filtering algorithm of a motion accelerometer to inhibit signal drift caused by head motion. According to the invention, through the modularized head-mounted multi-mode edge device, the physiological data is collected and edge end processing and cognitive disorder recognition and screening are carried out in combination with the edge calculation module, so that early recognition and screening of neurodegenerative diseases can be conveniently and effectively carried out at low cost.

Disclosed are a device and method for detecting and identifying shallow-stratum foreign objects based on distributed acoustic sensing. The device includes a vibrating sensitivity-enhanced fiber optic cable, a distributed acoustic sensing demodulator, a vibrator system, a vibration data processing unit, a velocity structure inversion unit and an AI-aided locating and identification unit. The distributed acoustic sensing demodulator transmits vibration signals to the vibration data processing unit for preprocessing to obtain waveform signals; the velocity structure inversion unit performs inversion to obtain the shallow-stratum underground velocity structure; positions of shallow-stratum foreign objects are identified through the underground velocity structure and abnormal waveforms; and the types of shallow-stratum foreign objects are identified. A distributed acoustic sensing method for fiber optic cables is used to obtain vibration signals, velocity imaging is performed on a shallow-stratum velocity structure, and AI is utilized to achieve locating and type identification of shallow-stratum underground foreign objects.

The invention discloses a train positioning method and system. The method comprises the steps that when a train drives into an inactive area, first positioning information of the train is determined according to an ultra-wideband signal of the train; mapping the first positioning information of the train to a station map, and determining track section occupation information of the train; when the train drives into an activation area, acquiring point cloud data detected by the train in real time; according to the point cloud data and the station yard map, determining second positioning information of identification equipment of the activation area; and according to the second positioning information, carrying out intrusion detection on the train to obtain a train intrusion result. According to the embodiment of the invention, the accuracy of train positioning can be improved.

The invention belongs to the technical field of radar human body tracking and recognition, and particularly relates to a rotary millimeter wave radar human body tracking and recognition device and method. The millimeter-wave radar module is mounted on the rotating holder module, and the main beam direction of an antenna in the millimeter-wave radar module is perpendicular to the rotating shaft; the millimeter wave radar module is connected with the control module, and the embedded processor is internally provided with a point cloud data processing algorithm and an identity recognition neural network which are used for overcoming the influence of environmental noise and multipath effect on data quality. The problems of fixed field angle and limited monitoring range of the traditional millimeter wave radar are effectively solved; and through an improved data processing algorithm and an identity recognition neural network, the influence of environmental noise and a multipath effect on data quality is overcome, and the reliability and adaptability of the system in a complex scene are remarkably improved.

A system is provided for implementing trajectory analysis entry controls. A trajectory analysis entry control system is implemented in a vehicle, and supports remote and automatic entry control functions for the vehicle. For example the system triggers various automatic entry controls functions, such as remotely unlocking doors and / or a trunk of a vehicle, by tracking and analyzing a user's trajectory of movement while they are approaching the vehicle. A system includes a user identification device to identify whether a user is authorized to access the vehicle, such as a driver. The system also includes a trajectory tracking device that determines a trajectory of the user with respect to the vehicle. As the user's trajectory is determined to be approaching the vehicle, the trajectory tracking device further determines which entry point of the vehicle the user is approaching and automatically engages an automatic unlocking of that access point of the vehicle.

The invention provides a high-precision stainless steel weld defect recognition device based on a multi-round cross-modal attention mechanism. The high-precision stainless steel weld defect recognition device comprises an ultrasonic signal acquisition module, a data preprocessing module, a cross-modal defect recognition module and an online result display module, the ultrasonic signal acquisition module is used for synchronously acquiring an A scanning original waveform and workpiece position information corresponding to the A scanning original waveform; the data preprocessing module is used for preprocessing the A scanning original waveform, mapping a time sequence signal into a Gramb angle field two-dimensional image, and generating complementary time sequence image bimodal data; the cross-modal defect identification module sends the bimodal data into a deep learning network, extracts time sequence and spatial frequency features through a feature extraction neural network, reinforces correlation between the time sequence and spatial frequency features by means of multi-round cross-modal multi-head attention iteration interaction, and combines channel attention and focus loss strategies at the same time; and outputting a stable defect classification result under the condition that the sample categories are unbalanced.

The invention provides a boiler welding seam full-automatic detection system and method based on machine vision and an ultrasonic phased array, and relates to the technical field of boiler detection.The system comprises a six-axis mechanical arm unit, a multi-degree-of-freedom boiler fixing platform unit and a welding seam type recognition device; the boiler is arranged on the multi-degree-of-freedom boiler fixing platform unit and used for driving the boiler to do vertical motion, inclined motion and rotary motion, the six-axis mechanical arm unit is arranged on one side of the multi-degree-of-freedom boiler fixing platform unit, the welding seam type recognition device is arranged at the tail end of the six-axis mechanical arm unit, and the welding seam type recognition device is arranged on the other side of the multi-degree-of-freedom boiler fixing platform unit. And the six-axis mechanical arm unit is used for driving the welding seam type identification device to move and identifying a circular seam and a longitudinal seam of the boiler. According to the invention, full-process automation of boiler welding seam detection is realized, the detection efficiency and the defect detection rate are improved, the safety risk of manual detection is eliminated, and the detection quality consistency and the industry standardization level are remarkably improved.

The utility model discloses an impurity identification device and husked rice separator relates to grain processing technical field, wherein the impurity identification device includes frame, visual inspection subassembly and cleaning subassembly, the frame is used for being arranged in the discharge port of husked rice separator, visual inspection subassembly includes the casing, be equipped with the color camera in the casing, the cleaning subassembly is equipped with the cleaning subassembly. A detection opening is formed in one side of the shell, the detection opening is covered with a transparent cover plate, the cleaning assembly comprises a driving mechanism and a sweeping part arranged at the driving end of the driving mechanism, and the sweeping part can make reciprocating contact with the transparent cover plate to achieve cleaning; according to the technical scheme provided by the utility model, when husked rice analysis is carried out, the driving mechanism can regularly drive the sweeping piece to sweep the transparent cover plate of the shell so as to remove particulate matters, dust and the like attached to the surface of the transparent cover plate, so that the interference of dust and the like in the environment on camera detection is reduced, and the detection accuracy is improved. Therefore, the recognition accuracy of the visual camera in the impurity recognition process is improved.

Provided are a lithology identification method, a lithology identification device, an electronic apparatus and a non-transitory storage medium. The lithology identification method includes: obtaining a dataset, where the dataset includes feature sets and lithology labels, and each feature of the feature sets corresponds spatially one-to-one with a corresponding one of the lithology labels; performing locality preserving projections (LPP) on the dataset, to thereby obtain a preprocessed dataset; and constructing a machine learning model, and training the machine learning model by using the preprocessed dataset to obtain a recognition model for lithology identification, during a process for training the machine learning model, a distance constraint and a geological constraint are introduced sequentially.

A quadruped robot with multimodal capabilities and embodied large-scale models for use in a 5G nuclear power plant, characterized in that it comprises: a control module, a power module, a robot arm module, a power supply module, a sensor module, a heat sink, an audio module and a housing structure, wherein the control module, the power module, the robot arm module, the power supply module, the sensor module, the heat sink and the audio module are mounted on the housing structure, wherein the control module is respectively connected to the individual modules, iethe power module, the robot arm module, the power supply module, the sensor module, the heat sink and the audio module to control and communicate with the robot, wherein the sensor module comprises a depth camera, a laser sensor, a mobile phone recognition device, an infrared sensor, an ultrasonic sensor and a radiation dose chip, wherein the power module consists of a motor and an electronic speed controller and is thus responsible for the movement of the robot, wherein the robot arm module comprises a motor and a robot arm controller as well as an integrated NFC module on the robot arm, and wherein the power supply module comprises a battery, a power supply manager and a power supply display screen, while the audio module provides remote voice interaction.

To provide a new technique for enhancing interest.SOLUTION: The game apparatus includes an acquirer configured to acquire character string information relating to acquisition of a game element, a specifier configured to specify the game element from the character string information, a display controller configured to display one or more pieces of character string information acquired by the acquirer on a display in a selectable state, and a controller configured to control, based on selection of any one of the one or more pieces of character string information, the game element specified from the selected character string information to be in an acquisition state in the game.SELECTED DRAWING: Figure 8

The application discloses a sealing cover structure of a liquid storage box, which is installed at a delivery opening of the liquid storage box, and normally seals the delivery opening to form a closed chamber for storing additives in the liquid storage box. An identification device is arranged on the sealing cover structure to identify the type and / or amount of the additives in the liquid storage box. The application also provides a delivery device, wherein the delivery opening of the liquid storage box is provided with the sealing cover structure. The delivery device further comprises a delivery unit, which is connected to the inside of the liquid storage box through the sealing cover structure. Meanwhile, the application also provides a clothes treatment apparatus, which is provided with the delivery device to automatically deliver the additives. Through the above arrangement, the type and / or amount of the additives in the liquid storage box can be accurately identified based on the identification device.

A rubber coating for a radiofrequency identification device for a tyre characterized in that it comprises: (a) 100 phr of at least one diene-based elastomer; (b) at least one chemical according to formula (1) wherein the chemical comprises in its structure at least the structure of the 2,2′-methylenediphenol, and wherein the 2,2′-methylenediphenol may be substituted in ortho, para, meta position or any combination thereof with an aliphatic, linear or branched, hydrocarbon chain comprising from 1 to 10 C atoms, or may be polymerized in ortho, para, meta position or any combination thereof with one or more additional alkylphenol units. A radiofrequency identification (RFID) module for a tyre comprising a radiofrequency identification device surrounded by a rubber coating, a tyre or a tyre retread comprising such radiofrequency identification module, and use of a rubber coating for surrounding a radiofrequency identification device.

A system for charging a plurality of worker devices for use by a plurality of users is disclosed. The system includes one or more charging stations, each charging station including a plurality of storage housings, one or more detection devices, and an identification device, and a controller. The controller is configured to selectively lock and unlock the plurality of worker devices in the plurality of storage housings of the one or more charging stations, electrically charge the plurality of worker devices when locked in the plurality of storage housings of the one or more charging stations, and validate an identity of the plurality of users with the identification device of the one or more charging stations when the plurality of users removes or returns the plurality of worker devices to the plurality of storage housings of the one or more charging stations.

The invention discloses an interactive security management monitoring system for a smart cemetery, and relates to the technical field of smart cemetery. The system comprises a multi-source data fusion system and a dynamic risk assessment system, the multi-source data fusion system comprises an Internet of Things sensing layer composed of a parking management module, an intelligent monitoring module and a fire early warning module, and the parking management module is integrated with a license plate recognition device and a parking space reservation unit. Through a multi-source data fusion system, cross-protocol data integration and real-time interaction of parking management, intelligent monitoring and a fire early warning module are realized, a data transmission channel between heterogeneous equipment is opened based on a LoRaWAN communication protocol, vehicle space-time information, human body behavior characteristics and environmental parameters are fused into a unified data stream, and the data stream is integrated into a whole. The traffic flow scheduling efficiency and the fire prejudgment accuracy in the peak period of tomb sweeping are remarkably improved, and the problems of emergency resource mismatching and response delay caused by module isolation of a traditional system are thoroughly solved.

The invention discloses a quantitative recognition device for the number and size of bubbles at a rotating impeller of a multiphase pump. The quantitative recognition device comprises a two-phase flow experiment system, the multiphase pump, a high-speed camera, a light source and the like. The preprocessing and data analysis system and the deep learning system are arranged in the computer; the two-phase flow experiment system and the image acquisition system are electrically connected with the computer through lines. The invention further discloses a quantitative recognition method for the number and size of the bubbles at the rotating impeller of the multiphase pump. According to the method, the problems of low blistering recognition precision, low efficiency and large error caused by the existing manual measurement method are solved, and a reference method is provided for exploring the influence of gas distribution at the impeller in the multiphase pump on pump operation and optimizing design of the multiphase pump.

A tunnel disease identification device based on carrying an image comparison component and a use method, the tunnel disease identification device comprises a safety helmet (1) worn on the head of an operator, a sensor group arranged on the safety helmet (1), and a controller (8) arranged on the sensor group, the sensor group is supported by the safety helmet (1), and the controller (8) is connected with the controller (8) through the sensor group. According to the invention, through the arrangement of the sensor group, prominent information of the inner wall of the tunnel is picked up, data processing and storage of information transmitted by the sensor group are realized through the controller (8), and identification color difference information of tunnel diseases is picked up. The technical problems that a detector uses an illuminating lamp to irradiate the inner wall of a tunnel and the eyes of the detector observe and recognize water seepage points are solved, and therefore the tunnel disease recognition effect is improved.

The invention relates to the technical field of magnetic suspension bearings, and discloses a rotor rotation direction recognition device and method based on a magnetic suspension bearing system.The rotor rotation direction recognition device based on the magnetic suspension bearing system comprises a rotor body, a driving unit, an axial positioning unit, a radial positioning unit and a displacement monitoring unit; the displacement monitoring unit comprises an annular mounting plate mounted in the radial positioning unit, a substrate is fixedly connected to the annular mounting plate, a plurality of rotation direction monitoring sensors are mounted on the substrate, and the permanent magnet I is matched with the plurality of rotation direction monitoring sensors to monitor the rotation direction of the rotor main body. According to the rotor rotation direction recognition device based on the magnetic suspension bearing system, a permanent magnet I interacts with a plurality of rotation direction monitoring sensors in sequence when rotating along with a rotor main body, so that signal values output by the rotation direction monitoring sensors are changed, and the rotation direction of the rotor main body is judged through a rotation direction judgment module in a controller.

The invention relates to the technical field of acceleration signal recognition, in particular to an acceleration signal recognition method and device, and the method comprises the following steps: carrying out the first-order numerical differential operation of a three-axis acceleration signal based on a collected original three-axis acceleration signal, and obtaining a movement speed sequence of the signal; according to the method, first-order and second-order numerical differential operation is carried out on an original three-axis acceleration signal, and the speed change and the impact change of the signal are extracted at the same time and combined to form a kinematic feature set, so that the dynamic features of the motion state can be fully expressed in the two dimensions of speed and impact. The Euclidean distance between the to-be-identified signal and the motion template is calculated based on the kinematic feature set to form the basic distance matrix, and the constraint cost matrix is constructed in combination with the speed sequence and the impact signal, so that the constraint on the kinematic consistency in the signal comparison process is enhanced, and the matching path is more reasonable.

The invention provides a tunnel crack image acquisition and detection device and method, and the device comprises a rail car which is provided with a distance detection mechanism; the image acquisition device comprises an image acquisition module and a steering adjustment module, the image acquisition module is mounted at the top of the rail car through the steering adjustment module, and the steering adjustment module is used for driving the image acquisition module to steer so as to adjust the orientation of the image acquisition module; the crack identification device is arranged at the front end of the image acquisition module and is used for identifying the crack and determining the position of the crack; and the control module is electrically connected with the steering adjustment module, the crack recognition device and the distance detection mechanism, and is used for controlling the steering adjustment module to drive the image acquisition module to steer after the crack is recognized, so that the image acquisition module is aligned with the crack position. The device provided by the invention is simple in structure and low in maintenance cost, does not need to configure a plurality of industrial cameras and lenses, and saves the system cost.

To identify the presence or absence of an abnormal area with high accuracy.SOLUTION: An identification device (2) includes: an acquisition unit (70) configured to acquire a first image (3); a generation unit (10) configured to perform semantic segmentation on the first image to generate a second image (4) that is an image after segmentation; and an identification unit (40) configured to identify the presence or absence of an abnormal area in the second image. The identification device uses a loss function in a generation model of the generation unit, a loss function in an identification model of the identification unit, and referenced multi-task learning for training the generation unit and the identification unit.SELECTED DRAWING: Figure 2

The invention discloses a train number, train container number and train type recognition device, which relates to the technical field of train recognition and comprises an edge disturbance sensing module, a fusion feature analysis module, a structure guide reconstruction module, a path evaluation recognition module and a dynamic path regulation and control module. And the structure guide reconstruction module is used for carrying out channel reordering and space adaptive amplification on the image based on the determined morphological fusion features, enhancing character structure coherence and boundary closure by utilizing a fusion feature guide reconstruction network, and extracting real container number character structure features from the image. According to the invention, by introducing multi-scale disturbance perception, morphological fusion feature analysis, structure guide reconstruction and dynamic path regulation and control mechanisms, accurate extraction and stable identification of a real character structure in a complex corrosion interference environment are realized, and the accuracy and robustness of container number identification are improved.

The invention discloses a numerical control machine tool cutter management system which comprises a hardware layer, a system layer, a function module and a system interface. The hardware layer is composed of a numerical control machine tool, a tool presetting instrument, a tool recognition device, a tool setting instrument, a bar code scanning gun, an industrial computer, a server and the like and is used for data acquisition, transmission and storage. The system layer comprises tool management software, a database management system, data acquisition and monitoring software and a manufacturing execution system interface, and full life cycle management of tools is achieved. The system is provided with a tool basic data management module, an inventory management module, a service life management module, a circulation management module, an abrasion monitoring and compensation module, a purchase plan management module, a performance parameter management module and other functional modules, and operation and display are carried out through a system interface. The system can improve the tool management efficiency and precision, reduce the tool cost, improve the machining quality and the production efficiency, and is suitable for efficient tool management of numerical control machining enterprises.

Provided is an external environment recognition device capable of determining a place where a host vehicle can safely evacuate at the time of recognition of a specific vehicle by using a plurality of cameras in combination even in a vehicle not equipped with a distance sensor such as a radar, a LiDAR, an ultrasonic sensor, or an infrared sensor. Therefore, an external environment recognition device includes: a plurality of cameras installed so as to have a plurality of stereo vision regions in which at least a part of a visual field region overlaps around a host vehicle; a three-dimensional information generation unit that generates three-dimensional information by performing stereo matching processing in each of the plurality of stereo vision regions; a three-dimensional information accumulation unit that accumulates the three-dimensional information generated during traveling of the host vehicle in time series; and a three-dimensional information update unit that updates the three-dimensional information accumulated in the three-dimensional information accumulation unit using three-dimensional information newly generated by the three-dimensional information generation unit.

The invention relates to the field of computer vision, and particularly discloses an artificial intelligence-based accumulated water depth monitoring and recognition device, which comprises a high-definition camera for continuously acquiring road surface image data of a monitoring area; the image processing module is used for receiving and processing image data of the high-definition camera; the image processing module comprises an image preprocessing unit and a ponding area identification unit, the image preprocessing unit is used for graying and denoising the image, and the ponding area identification unit is used for identifying the ponding range. According to the ponding depth monitoring and identifying device based on artificial intelligence, the Mask R-CNN model is adopted to accurately identify and process the floaters, an improved U-Net architecture attention mechanism is combined, the floaters are effectively prevented from interfering ponding area identification and depth calculation, the problem that the floaters are misjudged to be ponding areas in the prior art is solved, and the accuracy of ponding area identification and depth calculation is improved. And errors caused by floating objects can be accurately compensated during depth calculation.

The invention discloses an intelligent express sorting machine system based on'end-edge-cloud 'cooperation and a sorting method, and relates to the technical field of logistics automation. According to the system, the multi-mode recognition device, the intelligent self-adaptive regulation and control device, the equipment connection and management module, the self-adaptive sorting execution mechanism and the logistics data intelligent analysis system work cooperatively. The multi-modal identification device integrates image identification and radio frequency identification technologies, so that the parcel identification accuracy is improved; the intelligent self-adaptive regulation and control device monitors and adjusts the working states of the conveyor belt and the sorting port in real time; the equipment connection and management module realizes deep connection between the equipment and the cloud, thereby facilitating remote monitoring and management; the self-adaptive sorting execution mechanism flexibly processes different types of packages; and the logistics data intelligent analysis system mines data value to optimize operation. The problems that an existing express sorting technology is low in efficiency, poor in accuracy, weak in adaptability and the like are solved, efficient, accurate and intelligent express sorting is achieved, and the requirements of the modern logistics industry are met.

The invention provides a sueding machine operation deviation recognition device based on digital twinning, and relates to the technical field of operation deviation recognition. Assigning values to the operation control parameters of the sueding machine; performing control quality evaluation on the operation control parameter assignment result; performing control optimization based on the operation control parameter assignment result to obtain a reference operation control parameter; performing monitoring reference configuration on the digital twinborn model of the sueding machine, and comparing and outputting an operation deviation coefficient of the sueding machine; when the operation deviation coefficient of the sueding machine is larger than or equal to an operation deviation coefficient threshold value, an abnormal operation signal of the sueding machine is generated and sent to a user side. According to the method and the device, the technical problem that stable operation of the sueding machine is further affected due to low accuracy and efficiency of obtaining the operation abnormity or deviation in the prior art can be solved, the technical target of improving the accuracy and efficiency of the operation abnormity or deviation is achieved, and the technical effect of stable operation of the sueding machine is achieved.