16results about How to "Accurate spatial positioning" patented technology

The invention discloses a remote operation and maintenance and fault diagnosis method and system for an energy storage system, and relates to the field of fault diagnosis of energy storage equipment, a factory three-dimensional model is established, the binding relationship between a battery and the model is determined, data is collected from a battery management system, and after the steps of battery internal resistance estimation, data sequence labeling, abnormal value processing and Z-score standardization preprocessing, the fault diagnosis of the energy storage system is completed. And key characteristics of charge-discharge multiplying power and internal resistance change rate are extracted. And a multi-layer perceptron is selected to establish an artificial neural network model to realize a fault diagnosis prediction target. Once an abnormal battery is identified, the position of the abnormal battery in the plant global coordinate system is determined by means of coordinate information stored in the hash table. The fault prediction accuracy is improved by utilizing comprehensive data modeling, model parameters can be adaptively optimized, an abnormal battery is efficiently and accurately identified, and stable operation of an energy storage system is guaranteed.

This application relates to the technical field of lifting equipment, providing a lifting mechanism for painting automotive tailgates. The mechanism includes a base, a boom, a lifting drive device, and a counter-positioning device. The boom and lifting drive device achieve stable lifting of the automotive tailgate, while the counter-positioning device provides additional support and positioning, ensuring the tailgate's stability during painting. Furthermore, the boom employs a multi-arm structure and is equipped with locking components for angle adjustment. The bottom frame is equipped with a tensioning device and tension sensor to optimize the tension on the pull ropes, further improving lifting accuracy and safety. This application achieves the technical effect of improving the stability, accuracy, and ease of operation of automotive tailgate lifting, providing reliable support for painting processes.

The invention provides a cross-domain transfer learning laser ultrasonic layering defect detection method suitable for a composite material and application thereof.The method comprises the steps that firstly, multi-channel input containing a frequency domain, a time-frequency domain and Koopman operator characteristics is constructed for the problem of data distribution deviation caused by the batch difference of the composite material; secondly, extracting and fusing high-dimensional spatial-temporal features through a multi-channel attention mechanism and a graph convolutional network; and finally, migrating the defect features of the source domain to the target domain in combination with dynamic distribution self-adaption and domain adversarial training strategies. The method can effectively overcome model performance reduction caused by material attribute change, realizes high-precision layering defect identification and imaging under the condition of no target domain label, and is suitable for composite material detection in a complex industrial scene.

The application discloses a hydrogen-oxygen mutual string early warning method and system based on an intelligent membrane and a sensing bipolar plate, direct sensing of mechanical stress by the intelligent membrane realizes earliest early warning of membrane damage, early warning time is tens to hundreds of hours earlier than that of a traditional electrochemical monitoring method, and sufficient time window is provided for taking protective measures. Through distributed measurement of the sensing bipolar plate, fault positioning accuracy is improved from a stack level to a centimeter level, precise spatial positioning is realized, and maintenance cost is greatly reduced. Through multi-modal data fusion, limitations of single signal monitoring are overcome, normal working condition fluctuations and real fault precursors are effectively distinguished, based on precise positioning and early warning, maintenance of the fuel cell system is changed from regular maintenance or post-failure maintenance to state-based predictive maintenance, maintenance resource allocation is optimized, and system availability and full life cycle economy are improved.

The invention relates to the technical field of knitting processes, in particular to a general knitting simulation method and system for special-shaped structural parts based on a model reconstruction algorithm. The method comprises the following steps: acquiring three-dimensional model data of a core mold of the special-shaped structural part; through the three-dimensional model data, the center line of a core mold is extracted; according to the center line, the key section of the core mold is obtained; reconstructing a surface grid of the three-dimensional model of the core model by utilizing the key section; generating a yarn topology track based on kinematic characteristics by using the surface grid; and generating a fabric structure according to the yarn topology track. According to the method, through a model reconstruction algorithm and a kinematics method, redundant features of the complex special-shaped structural part core mold are effectively eliminated, and the precision and efficiency of weaving simulation are greatly improved; the error of the measurement result of the weaving experiment does not exceed 5 degrees, the actual production requirement is met, the method can be used for verifying the process design scheme in the actual production, and the high cost caused by sample piece trial-manufacture is reduced.

This invention discloses a method and system for machining curved workpieces. The machining method includes the following steps: setting theoretical three-dimensional coordinate information of the curved workpiece; setting a positioning base point, and ensuring that the contour corresponding to the theoretical three-dimensional coordinate information of the curved workpiece continuously passes through the positioning base point during movement; acquiring first target two-dimensional coordinate information and second target two-dimensional coordinate information; acquiring actual three-dimensional coordinate information; spatially positioning the curved workpiece; and machining the curved workpiece. This invention ensures that the contour corresponding to the theoretical three-dimensional coordinate information of the curved workpiece continuously passes through the positioning base point during movement, acquiring the actual three-dimensional coordinate information of the curved workpiece. This allows a multi-axis motion mechanism to quickly and accurately reposition the curved workpiece spatially based on the actual three-dimensional coordinate information, improving the positioning accuracy of the curved workpiece.

This invention belongs to the fields of cultural relic protection and computer vision technology. Addressing the problems of low efficiency, poor accuracy, and lack of spatial positioning in traditional methods for detecting defects in ancient city walls, this invention discloses an intelligent detection method and system for surface defects of ancient city walls based on 3D reconstruction. The method includes: processing the texture information of a loaded 3D reconstructed model of the ancient city wall using a multi-strategy texture restoration method; analyzing the model's geometric structure to determine the wall's orientation and dimensional parameters; generating virtual camera positions based on geometric features and a meshed serpentine scanning strategy; rendering RGB and depth images at each virtual camera position; performing defect detection using a YOLO model; mapping the 2D detection results to 3D space to generate 3D defect marker color blocks; and fusing multi-viewpoint results to output the detection results of surface defects on the ancient city wall. This invention achieves efficient, accurate, and automated detection of defects in ancient city walls, providing effective technical support for cultural relic protection.

The application discloses a device and a method for correcting visual errors of camera observation of particle sedimentation process, comprising an experimental setting module, an image acquisition module, a data processing module, a size correction module and the like, through the experimental setting module and the image acquisition module, only a ruler needs to be set and an image is shot, and the error correction can be completed by combining simple analysis of the data processing module, without complex equipment or tedious operation, so that the experimental implementation difficulty and the requirement for professional skills of the operator are significantly reduced; moreover, the whole device is easy to build, low in cost, and common equipment of a ruler and a camera is used, expensive instruments such as high-precision optical sensors are avoided, resource utilization is further optimized in combination with a modular design, experimental cost is reduced, and the device has higher economy and popularization and application value.

The application discloses a kind of traditional village fire scene cascade failure road vulnerability assessment method, it is related to building group fire prevention and control and personnel evacuation technical field.Firstly, the spatial vector data of traditional village building group, single building and road is acquired, and building group fire spread network and road network are constructed;Subsequently, the road vulnerability assessment system is constructed, and the accessibility index is introduced to dynamically represent the road traffic efficiency, and the vulnerability index is defined to quantify the influence of disaster on road system;Finally, a multi-layer network cascade failure simulation framework is proposed, which can quantify the dynamic cascade failure process and generate multi-scenario vulnerability heat map to locate high-risk areas.The application fully considers the influence of traditional village building fire on road network, establishes a fire-road double-layer coupled network model, realizes dynamic quantification, and provides a scientific decision-making tool for traditional village building fire and road evacuation risk, which has important application value for improving the resilience of traditional village.

The invention discloses a dual-channel frequency-dividing earphone, comprising a coaxial front cavity, a rear cavity, a speaker, a conduit, and a tuning paper, wherein the interior of the conduit is a first sound outlet channel, the space between the outer periphery of the conduit and the inner wall of the front cavity is a second sound outlet channel, the tuning paper pasted on the sound outlet of the front cavity is 100-400 mesh, and the tuning paper pasted on the front end of the conduit is 500-1000 mesh. The invention has a simple structure, realizes effective separation of medium and low frequencies from medium and high frequencies, thereby achieving improvement of sound quality, making the spatial sense of music better, the spatial positioning more accurate, and the sense of hierarchy stronger, and having a more immersive auditory effect in listening to music, watching movies, playing games, and VR; the bass part is more condensed, making the bass more solid and thick in the sense of hearing, enhancing the bass effect, and having a strong sound restoration.

The application discloses a highway pavement damage self-recognition method and system based on deep learning, and relates to the technical field of road damage detection. The method comprises the following steps: continuously collecting images along the highway to construct an original pavement image sequence; performing multi-scale feature analysis on the sequence to draw a feature map; traversing the feature map to detect and generate a candidate damage area, and obtaining an initial recognition result through bidirectional analysis; constructing a pavement three-dimensional space based on three-dimensional mapping of the image sequence, synchronously positioning the result, and determining the damage spatial position; and generating a pavement condition report through position information inversion verification. The technical problem that the existing pavement damage detection is easily affected by light, noise and scale changes in the continuous collection scene, resulting in missed detection and false detection of the damage area, and cannot accurately position, is solved, the technical effects of improving the accuracy of damage recognition through multi-scale feature analysis and bidirectional verification of the candidate area, and realizing accurate positioning and automatic evaluation of the damage through three-dimensional space mapping and inversion verification, are achieved.

The invention discloses a machining method and system for a curved-surface workpiece. The machining method comprises the steps that theoretical three-dimensional coordinate information of a curved surface workpiece is set; a positioning base point is set, and the contour corresponding to the theoretical three-dimensional coordinate information of the curved surface workpiece continuously passes through the positioning base point in the moving process; obtaining first target two-dimensional coordinate information and second target two-dimensional coordinate information; acquiring actual three-dimensional coordinate information; performing spatial positioning on the curved surface workpiece; and the curved surface workpiece is machined. In the moving process, the contour corresponding to the theoretical three-dimensional coordinate information of the curved-surface workpiece continuously passes through the positioning base point, the actual three-dimensional coordinate information of the curved-surface workpiece is obtained, and therefore rapid and accurate space positioning is conducted on the curved-surface workpiece again through the multi-axis moving mechanism according to the actual three-dimensional coordinate information; and the positioning precision of the curved-surface workpiece is improved.

The invention discloses a galvanometer driving control method and system based on deflection synchronous analysis, and relates to the technical field of galvanometer driving control, and the method comprises the steps: obtaining galvanometer driving system data, obtaining a galvanometer driving reference position and a displacement influence coefficient according to the galvanometer driving system data, obtaining target track information, and obtaining a galvanometer driving reference position according to the target track information; and sorting the track ordinates according to a target track sequence to obtain a track Y-axis displacement sequence. According to the invention, through the central position of the motor rotating shaft, the galvanometer driving coordinate system is constructed and the reference position is determined, accurate space positioning of galvanometer motion is realized, a unified space basis is provided for subsequent multi-axis deflection synchronous control, and quantitative characterization of multi-axis coupling interference is realized through fitting a curvilinear equation and obtaining a displacement influence coefficient. The feature target trajectory is split through the extreme point, and the deflection initial correction amount is calculated in a segmented manner, so that the correction efficiency is improved, and the stability and reliability of galvanometer driving control are ensured.

The invention discloses a watermelon fusarium wilt identification method fusing leaf image features and a storage medium, and relates to the technical field of plant disease intelligent identification, and the method comprises the steps: collecting an original digital image of a leaf, and constructing a multi-level analysis structure; performing multi-channel spectrum separation on the image to extract spectrum components in different physiological states, and generating a composite characteristic spectrum fusing appearance and deep physiological information by using a characteristic growth model; performing region deconstruction and feature matching on the map according to a multi-level structure, calculating pathogen conformity indexes of each region, and fusing to generate overall infection probability mapping; carrying out spatial clustering on the mapping to identify a scab core area, and constructing a disease development topology network based on a spatial form relation of the scab core area; and outputting an identification conclusion in combination with the network structure parameters and probability mapping. According to the method, the detection sensitivity of early diseases can be improved, and analysis of disease spatial distribution modes and development trends can be realized.

The utility model discloses a fixing device convenient for circuit board maintenance, which comprises a support rod, a fixing assembly is arranged on the support rod, the fixing assembly comprises a top plate and a limiting block, the top plate is arranged on the support rod, the limiting block is arranged on the top plate, a guide rod is arranged on the limiting block, and the guide rod is arranged on the top plate. A sliding clamping block is arranged on the guide rod in a sliding connection mode, a fixing block is installed between the guide rod and the top plate, a supporting assembly is arranged on the supporting rod and comprises a rotating plate and a rotating column, the rotating plate is rotationally connected to the supporting rod, the rotating column is installed on the rotating plate, and the rotating plate is fixedly connected to the supporting rod. And a rotating seat is mounted on the supporting rod, so that the technical problems of complicated operation and poor convenience in the aspect of circuit board fixing operation of traditional equipment in the existing fixing device technology facilitating circuit board maintenance mentioned in the background technology are solved.

The invention discloses a natural resource monitoring-oriented low-altitude unmanned aerial vehicle panoramic intelligent early warning method and device, and belongs to the field of natural resource intelligent inspection. The system is composed of an unmanned aerial vehicle, a ground station end and a cloud end, comprises a data acquisition unit, a data processing unit, a model training unit, a reasoning detection unit, a spatial positioning unit and the like, and is composed of six links of panoramic data acquisition, sample labeling, variable-scale sparse small target detection network construction and training, panoramic projection transformation and target reasoning, suspected target spatial positioning and device integration. And full-process automation and rapid intelligent early warning of natural resource monitoring are realized. Natural resource suspected illegal early warning targets with geographic coordinates can be accurately extracted, and the method is suitable for scenes such as natural resource daily monitoring and cultivated land protection, and has the characteristics of high practicability and strong universality.