16results about How to "Accurate automatic identification" patented technology

The invention belongs to the technical field of underwater acoustic communication reconnaissance and artificial intelligence edge computing, and discloses a sea area signal reconnaissance method and device based on deep learning. According to the method, a constructed lightweight LeNet-5 hierarchical convolutional neural network model is embedded and deployed into an STM32H743 microcontroller through an X-Cube-AI tool to process underwater acoustic signals, automatic identification and classified modulation are performed on underwater signals of active sonar signals and non-cooperative communication signals in real time, and the underwater signals are used for analysis of recovered sea area information. According to the method, deep-level features can be automatically learned from the time-frequency graph, better robustness is achieved for noise and a complex marine environment, and the recognition accuracy is higher.

The application relates to a bridge modal parameter automatic identification method and system considering multi-channel information, which comprises the following steps: S1, generating a stability diagram by directly analyzing multi-channel monitoring signals by using COV-SSI, automatically extracting stable axes by combining a DBSCAN clustering algorithm, and realizing automatic identification of modal frequencies; S2, decomposing multi-channel monitoring data by using MvFIF to generate an intrinsic modal function (IMF) group with modal alignment characteristics; S3, calculating the instantaneous frequency and bandwidth of the IMF in step S2 by using HHT, screening out an IMF component containing a target modal frequency, and performing linear reconstruction; and S4, taking the multi-channel monitoring data after the reconstruction in step S3 as system input of the COV-SSI algorithm, calculating a system matrix and an output matrix, and calculating modal damping ratios by using eigenvalue decomposition; the method can consider the space-time correlation between multi-channel data, realize synchronous decomposition of multi-channel monitoring data, and realize automatic and accurate identification of structural modal parameters under different noise levels.

The invention provides a secondary image deviation measurement system, and relates to the technical field of measurement. The secondary image deviation measuring system comprises a light source which is arranged on the first side of the glass to be measured and is used for emitting light; the image position obtaining device is arranged on the second side, opposite to the first side, of the glass to be detected, the image position obtaining device and the light source are coaxially arranged, and the light source forms a main image and an auxiliary image on the image position obtaining device through the glass to be detected; the image position obtaining device is used for determining the main image coordinates and the auxiliary image coordinates and obtaining an auxiliary image deviation value according to the main image coordinates and the auxiliary image coordinates. Therefore, the secondary image deviation measurement system provided by the invention can realize automatic identification of the secondary image deviation value quickly and accurately, can realize dynamic measurement, and is high in automation degree, convenient to use and high in measurement accuracy.

The present invention relates to a multi-modal telescopic forklift attachment identification method and system, wherein an electronic tag is provided on the attachment, a first identification result is obtained by identifying the electronic tag, an attachment image is acquired, a second identification result is obtained by visually identifying the attachment image, and the attachment of the telescopic forklift is identified according to the first identification result and the second identification result. The present invention not only enables the telescopic forklift to cope with more complex and changeable working environments, but also ensures the reliability of attachment identification.

The invention discloses a long-distance underwater tunnel traffic accident sensing method based on computer vision. The method specifically comprises the following steps: step 1, detecting vehicles in a tunnel; 2, tracking a plurality of detected vehicle targets, and obtaining the track and appearance characteristics of a tracked vehicle; 3, judging whether the vehicle is in a static state or not according to the vehicle track obtained in the step 2; 4, whether the vehicle in the static state is damaged or not is judged according to the appearance characteristics in the step 2; and if there is damage, determining that a traffic accident occurs. According to the invention, accurate and automatic identification of vehicle accidents in the tunnel is successfully realized.

The invention discloses a motor load state identification method and device, and a motor control chip. The method comprises the steps of obtaining a rotor acceleration when a motor is started; under the condition that the motor is determined to be in a no-load state according to the rotor acceleration, acquiring a bus current and a motor rotating speed in a motor operation process; and checking the no-load state of the motor according to the bus current and the rotating speed of the motor to determine the final load state of the motor. According to the method, the load state of the motor can be simply, accurately and automatically identified.

The invention provides a serial port equipment management method and device, electronic equipment and a computer readable storage medium, and is applied to the technical field of computers, and the method comprises the following steps: identifying serial port equipment accessed to the electronic equipment through a first configuration program of a first operating system; identifying a target serial port device which can be used by an application program of the second operating system; in response to triggering of a configuration control in an interface of the first configuration program, calling a second configuration program of a second operating system running in the compatible application program through the first configuration program so as to configure a device registry of the second operating system provided by the compatible application program according to the information of the target serial port device; and realizing access use of the target serial port equipment in the second operating system based on the information in the equipment registry through the compatible application program. The whole configuration process can be automatically carried out by a program, so that the convenience of identifying and using the serial port equipment is improved.

This manual provides data processing methods for stray animals and target animals. When the stray animal terminal detects a target stray animal within a preset range, it collects a target image containing the target stray animal and sends the image to a cloud server. Upon receiving the target image, the cloud server first uses a preset animal identification model to process the image and determine the target stray animal's identity information. Then, based on the target stray animal's identity information, it determines whether the target stray animal meets preset restrictions. If the target stray animal meets the preset restrictions, it sends a restriction command to the stray animal terminal. The stray animal terminal receives and responds to the restriction command, confining the target stray animal within the terminal. This allows for accurate and intelligent automatic identification and restriction of stray animals that meet the preset restrictions, facilitating subsequent processing.

The application discloses a control method and system of a charging module and a charging system. The method comprises the following steps: collecting the operating parameters of the charging module; calculating the comprehensive discriminant value of the coupling multi-factor composite working condition according to the input voltage, output current, module temperature and battery state of charge; adjusting the power distribution ratio of the battery and the energy storage unit according to the comprehensive discriminant value; judging whether the charging module needs to switch the working condition according to the input voltage and output current and outputting the corresponding control signal to control the charging module; solving the first switching frequency with the maximum efficiency of the charging module as the target, adjusting the first switching frequency according to the current working condition to obtain the optimal switching frequency; performing adaptive PI adjustment on the current loop according to the output current to output the optimal switching duty ratio; and controlling the charging module according to the optimal switching frequency and the optimal switching duty ratio. The application enables the charging module to maintain high efficiency and stable operation within a wide input, wide output and wide load range.

The invention discloses a method for mapping a transformer substation secondary system logic signal to a 3D model optical port. The method comprises the steps that a GIM compressed file is analyzed, and MOD, PHM, DEV and CBM files are recombined into an XML file named GIM-Model. XML; all port nodes are positioned through unique identifier attributes, and the SDD file is queried through the unique identifiers to obtain the Port ID of the researched port and the iedName of the IED where the port is located; inquiring FCDA and ExtRef nodes in the SCD file, respectively obtaining the addresses of an output signal and an input signal, analyzing each signal address step by step, obtaining the engineering significance of the signal, and completing the process of mapping the signal to a 3D optical fiber port; the problem that a method for mapping signals in an SCD model to a port assembly in a GIM model does not exist in the prior art is solved; and errors and omissions are easily caused.

The invention provides a power transmission line insulator string identification method based on unmanned aerial vehicle oblique photography. A multi-rotor unmanned aerial vehicle carries a full-frame camera to collect oblique photography image data of a power transmission line and the surrounding environment of the power transmission line, and a YOLO deep learning model is utilized to perform automatic identification of an insulator string. The method aims at improving the automation level and accuracy of routing inspection, reducing the dependence on manpower and improving the operation efficiency. The method specifically comprises the steps of data acquisition, image preprocessing, three-dimensional modeling of the power transmission line and automatic identification of the insulator string. A method of combining deep learning and three-dimensional modeling is utilized to automatically identify an insulator string, and stable operation of a power transmission line is ensured.

This invention relates to the field of vehicle obstacle avoidance technology, and provides a vehicle obstacle avoidance method and apparatus. The vehicle obstacle avoidance method includes the following steps: acquiring laser radar data within a preset angle range ahead of the vehicle's direction of travel using a laser radar installed on the vehicle; generating a corresponding equivalent image based on the laser radar data; processing the equivalent image to identify obstacle information; and providing obstacle avoidance prompts or action control based on the obstacle information. This invention can accurately and automatically identify obstacles in the vehicle's direction of travel in low-light conditions and can take corresponding obstacle avoidance prompts or actions, thereby improving vehicle safety and saving labor costs.

The application provides a kind of based on deep learning's fissure automatic identification processing method and system, it is related to fissure identification technical field, the method includes: obtaining the image to be identified corresponding to target rock mass;Wherein, the image to be identified is generated by the cylinder obtained by drilling the inside of target rock mass;Target rock mass is any rock mass;The image to be identified is input to the preset fissure identification model, to obtain the fissure image corresponding to the image to be identified;Fissure image includes main trunk fissure and / or branch fissure;Judge whether main trunk fissure and / or branch fissure exist in fissure image;If main trunk fissure and branch fissure exist in fissure image, remove branch fissure, to obtain the main trunk fissure corresponding to target rock mass;Realize removing branch fissure in fissure image, only keep the purpose of main trunk fissure;To accurately identify the rock mass joint fissure automatically.

This invention discloses a vehicle violation monitoring method based on edge and cloud collaboration, comprising: real-time acquisition of video streams of a designated area via cameras; real-time reception of the video streams by an edge computing device, performing target detection on vehicles within the streams, and determining whether a preset event has been triggered based on the vehicle's status; if a preset event is triggered, capturing the corresponding video slice and uploading it to a central server; the central server performing semantic analysis on the video slices to generate a structured sequence of vehicle behavior events, matching the sequence of vehicle behavior events with preset violation rules; if a match is successful, determining that a violation has occurred, and generating an alarm message. This achieves a leap from "target detection" to "behavior understanding," facilitating traffic management.

The invention discloses a method and a device for identifying tampering of a software license, a storage medium and a product. The identification method comprises the following steps: segmenting a plurality of sequences from a license text corresponding to a to-be-identified software license; the sequence is used for representing information related to the license range of the software license; text features are extracted from each sequence, and corresponding license feature characters are obtained; wherein the license feature characters are used for representing key characters related to the license range; using the trained recurrent neural network model to identify whether the license feature characters corresponding to the plurality of sequences are tampered or not, and obtaining an identification result of whether the software license is tampered or not; in an iterative training process of the trained neural network model, predicting weight adjustment gradients of parameters corresponding to license feature characters in the recurrent neural network model based on a permutation feature importance method, and adjusting weights of the corresponding parameters based on the weight adjustment gradients of the parameters; and until the newest adjusted recurrent neural network model converges.

The present invention provides a roller thermal expansion analysis method, device and storage medium. The method is applied to a hot rolling production line. The method includes: based on the attribute information of each stand roller when rolling each strip steel and a preset thermal expansion prediction model, determining the thermal expansion of each stand roller when rolling each strip steel; based on the thermal expansion of each stand roller when rolling each strip steel, determining the N rolling roll periods included in the hot rolling process, where N is a positive integer; for each roll period in the N rolling roll periods, based on the thermal expansion of each stand roller when rolling each strip steel in the roll period, determining whether the thermal expansion of each stand roller converges. The above scheme can automatically identify each roll period in the hot rolling production line, and analyze and diagnose the thermal expansion of each stand roller in each roll period, providing a prerequisite guarantee for the quality control of subsequent products.