234results about How to "Achieve alignment" patented technology

The embodiment of the invention provides a smart store data processing method and device based on multi-dimensional data analysis, which innovatively realizes alignment and mapping of spatial-temporal feature sequences by collecting sensor, intelligent terminal and social media data. And performing multi-dimensional data fusion based on the feature weight coefficient, and constructing a commodity recommendation model by using a convolutional neural network and a recurrent neural network. The system continuously optimizes the model performance through incremental learning, and realizes personalized commodity recommendation and store operation trend analysis. And meanwhile, a marketing decision optimization model is introduced, intelligent evaluation and dynamic optimization are performed on a marketing strategy, and the model is continuously updated through feedback data. According to the method, the limitation of traditional single data analysis is broken through, and a comprehensive data processing solution is provided for precision marketing of the smart store.

The invention belongs to the technical field of sea wave height prediction, and discloses a sea wave height prediction method and system based on a large language model and a medium, and the method comprises the steps: S1, geographic position coding: carrying out geographic position coding on sea wave height data, and generating sea wave height data fused with geographic position information; s2, a step of ocean wave height semantic feature coding based on an attention mechanism: carrying out self-coding on the ocean wave height data output in the step S1, outputting ocean wave self-coding features, carrying out self-coding on ocean wave physical field features, outputting word vector features, and realizing interaction between the ocean wave self-coding features and the word vector features by utilizing the cross-modal attention mechanism; outputting domain-specific semantic features; and S3, a step of large-scale language model prediction based on sea wave height domain cue word driving: inputting the domain specific semantic features into a large-scale language model, and outputting prediction features. According to the method, sea wave complex spatial-temporal change information is effectively mined, and accurate prediction of the sea wave height is realized.

The invention relates to the technical field of laser processing, in particular to multi-axis ultrafast laser and ultrasonic combined processing equipment. The five-axis linkage machining equipment is used for simultaneously or independently moving in five different axial directions of an X axis, a Y axis, a Z axis, an A axis and a B axis, and a workpiece to be machined is clamped on the workbench; the laser generator is mounted on a cross beam of the five-axis linkage processing equipment; the ultrasonic vibration main shaft is mounted on a Z-axis mounting seat in the five-axis linkage machining equipment; the four-axis small motion platform is mounted on a Z-axis mounting seat in the five-axis linkage machining equipment and is used for accurately adjusting the spatial position of the galvanometer and the rotating angle of a laser beam, so that the four-axis small motion platform and the ultrasonic vibration main shaft cutter form combined machining with different laser incident angles; the three-dimensional scanner is used for obtaining the six-degree-of-freedom point cloud model of the workpiece to be machined. A three-dimensional scanner, a galvanometer and an ultrasonic vibration main shaft are integrated in five-axis linkage machining equipment, so that the equipment compactness and the operation convenience are improved; therefore, the ultra-fast laser is suitable for hard light path transmission.

The invention discloses a model training method and a data alignment method, and the method comprises the steps: training a time sequence feature extractor through a time sequence data set, inputting the time sequence data set into the trained time sequence feature extractor, and obtaining time sequence feature vector mapping; obtaining text feature vector mapping corresponding to the time sequence data set by using a text data label of the time sequence data set; constructing a first loss function by using time sequence feature vector mapping and text feature vector mapping, and adjusting model parameters by taking minimization of the first loss function as a target to obtain a trained data alignment model; the time sequence features of the time sequence data are extracted by using the time sequence feature extractor, so that the data alignment model can realize alignment of the time sequence data and the text data, and data of different sources and types are effectively fused.

The invention discloses a polyp segmentation method and system based on edge detection and multi-scale fusion, and the method comprises the steps: obtaining polyp image data, carrying out the feature extraction of the polyp image data through a backbone network, and obtaining primary features; performing convolution connection on the primary features to obtain polyp global multi-scale feature information; edge information of the polyp global multi-scale feature information is further extracted and fused, and polyp edge local feature information and final polyp edge global feature information are obtained; and performing feature interaction and fusion on the final polyp edge global feature information to obtain interaction features and a final polyp feature map. According to the method, edge detection and feature extraction are combined, and the polyp segmentation precision is improved through feature fusion and enhancement; a space and channel attention mechanism is adopted to strengthen features, details are supplemented during up-sampling, and the recognition and segmentation accuracy is improved. Compared with a baseline model, the method has higher segmentation accuracy and generalization, and has important clinical application value.

The invention relates to a method for manufacturing a low-wavefront-error double-blazed grating for electron beam gray lithography, which comprises the following steps of: decomposing dose parameters of an electron beam into average dose and dose difference, decomposing grating parameters into grating height and grating depth, and constructing a mathematical model between the average dose and the dose difference; through differential calculation and least square fitting, the relation between the dose parameter and the height and depth of the grating is optimized, and then high-precision manufacturing of the target grating is achieved. The method comprises the following specific steps: firstly, decomposing dose and grating parameters, and establishing a first mathematical model among grating height, depth and dose parameters; and then obtaining relational data through an experiment, performing optimization calculation by using the second mathematical model, and finally obtaining a dose parameter corresponding to the target grating. And finally, manufacturing the double-blazed grating with the low wavefront error according to the target parameters. According to the method, wavefront errors can be effectively reduced, the photoetching precision is improved, and the method has relatively good manufacturing consistency and is suitable for the production requirements of high-precision gratings.

The invention relates to the technical field of cross-modal fusion, and discloses an indoor positioning method, system and device based on cross-modal fusion and a medium, and the method comprises the steps: transmitting a positioning signal source to a plurality of sensors through a wireless transmission mode; carrying out feature extraction on the positioning signal source data received by the plurality of sensors by adopting a cross-modal factorization Hash mode and realizing common space mapping to generate Hash codes of the plurality of sensors; associating the hash codes of the plurality of sensors, and aligning the hash codes of the plurality of sensors; and introducing an attention mechanism to calculate the confidence of the aligned Hash codes, and carrying out feature fusion based on the confidence to realize position prediction. Cross-modal alignment is carried out in a CCA maximization mode, and alignment of positioning data of positioning frequencies and positioning precision of different information sources is achieved; an attention mechanism is introduced to calculate the feature confidence coefficient of the multi-modal data, multi-modal feature fusion is carried out, position prediction is obtained, and indoor fusion positioning of the non-homologous asynchronous data is achieved.

The invention relates to a tool clamp and method for a gear hobbing machine to machine splines at the ends of square shafts, and belongs to the technical field of machining of splines at the ends of the square shafts. According to the technical scheme, a positioning seat is arranged on the upper surface of a base, a horizontally-arranged fixing square groove is formed in the top of the positioning seat, the width of the fixing square groove is matched with the width of the front face of a square shaft to be machined, and the center of the fixing square groove and the center of a first tip are located on the same vertical line; a positioning ruler is arranged above the positioning seat and located between the square shaft and the clamping arm, a positioning square groove is formed in one side of the positioning ruler, and the width of the positioning square groove is matched with the width of the back face of the square shaft to be machined. The position of the square shaft is fixed through the tool clamp, it is ensured that the front face of the square shaft is aligned with a machine tool of a gear hobbing machine, it is ensured that starting points of machining are the same each time, and the tooth crest center line of circular shaft splines at the two ends of the square shaft is aligned with the front face center line of the square shaft or the tooth root center line of circular shafts at the two ends of the square shaft is aligned with the side face center line of the square shaft; the requirement that the square shaft end machining spline datum plane does not deviate is met.

The invention discloses a target detection method and device based on multi-modal fusion, electronic equipment and a medium, and the method comprises the steps: obtaining a first image set and a second image set, the first image set comprises a plurality of visible light images, and the second image set comprises a plurality of infrared images; performing data alignment operation on the first image set and the second image set to obtain a first feature image set corresponding to the first image set and a second feature image set corresponding to the second image set; performing feature fusion on the first feature image set and the second feature image set through a preset dual-scale image fusion algorithm to obtain a fused image set; and performing target detection on the fused image in the fused image set through a preset deep learning model to obtain the object category of the to-be-detected object and mark the bounding box of the to-be-detected object. In the embodiment of the invention, the accuracy of target detection can be improved, and the detection precision is further improved.

The invention provides a multi-view video processing method and a related device. According to the method, feature recognition is carried out on audios collected from multiple visual angles, after the audios are aligned, display timestamp information is printed on each path of video, multiple video codes with different definitions are carried out, and transmission is carried out through a multicast protocol in the mode of the same or different IPs and different ports. And the live broadcast terminal obtains the corresponding live broadcast video stream according to the own playing capability, so that multi-view video decoding and synchronous playing are realized. The audio and picture synchronization problem of the multi-view video is solved through an audio synchronization technology based on feature recognition, multicast transmission, terminal capability matching and the like, and the requirements of various types of terminals with different capabilities for playing the multi-view video are met. The method is suitable for realizing multi-view video live broadcast through a multicast protocol, and provides a solution for a multicast service scene in the field of articulated naturality web.

The invention relates to the technical field of end socket detection, and provides a pressure vessel end socket verification and measurement device which comprises a bottom fixing base, an automatic feeding assembly, an external detection assembly and an internal detection assembly, the top of the bottom fixing base is fixedly connected with a working bottom plate, automatic conveying and processing of end sockets are achieved through the automatic feeding assembly, and the detection efficiency is improved. The next magnetic suction cup synchronously sucks the detected end socket, after the suction action is completed, the magnetic suction cup system integrally and stably moves towards the direction of the feeding conveying belt, the end socket which is detected to be qualified is accurately placed on the feeding conveying belt, and meanwhile, the next end socket to be detected is placed on the object placing plate so as to facilitate follow-up monitoring; and for the end socket which is detected to be unqualified, the magnetic suction cup continues to move forwards and is accurately aligned with the material collecting frame to put the end socket into the material collecting frame, full-automatic operation is achieved in the whole logistics process, and the automation level and the detection efficiency of the device are remarkably improved.

The present invention relates to a wafer alignment method and related devices, the alignment method comprising: selecting a suitable alignment mark in a chip of a wafer to establish a work menu, and recording the position of the alignment mark and the size of the chip; using a pre-aligner to perform pre-alignment on the wafer, placing the wafer on a chuck, and recording the target angle of the wafer; performing rough alignment of the wafer; and performing fine alignment of the wafer. The wafer alignment method and related devices provided by the present invention improve the search efficiency of the alignment mark in the subsequent precise alignment step by performing rough alignment on the wafer; and perform precise alignment through the alignment mark at the far end of the wafer to improve the alignment accuracy of the wafer.

The invention relates to the technical field of vibration test data processing and analysis systems, in particular to a multi-sensor fusion vibration test data processing and analysis system and method. A vibration data preprocessing unit; the vibration data fusion unit is connected with the vibration data preprocessing unit and is used for displaying the vibration data corresponding to different measurement quantities, measurement conditions and data acquisition lengths in the same oscillogram in different colors and performing time alignment according to a set time window; a signal analysis and feature extraction unit; and the signal analysis information display unit is connected with the signal analysis and feature extraction unit and used for completing vibration time domain analysis, frequency domain analysis, time domain and frequency domain waveform switching and a time-frequency diagram function, and the accuracy and reliability of fault recognition are remarkably improved by combining multi-sensor data and an advanced feature extraction algorithm. The system not only can automatically detect and alarm abnormal vibration, but also can provide detailed fault positioning information.

This application discloses a method and apparatus for constructing a multi-scale adaptive gating MambaPlus network, belonging to the field of artificial intelligence and machine learning technology. The method includes: initializing the network configuration and constructing the basic structure; preprocessing the input data to generate a standard dataset; mapping the input data to the hidden space via an input mapping layer, and extracting backbone features from the Mamba backbone; constructing at least two parallel scale branches in the hidden space to obtain a multi-scale feature set; inputting the backbone features and multi-scale features into an adaptive gating module, dynamically allocating weights and adaptively fusing them through a hierarchical gating mechanism to generate fused features; further enhancing the features through cross-scale attention and feedforward enhancement, and then superimposing the residuals to generate the final discriminative features; finally, completing category prediction and model training evaluation. This application, while retaining the advantages of Mamba's long-range dependency modeling, addresses the problems of insufficient utilization of multi-scale information, poor adaptive feature fusion, and low robustness in complex scenarios.

The invention relates to the field of safety supervision, in particular to a food safety supervision system based on a cloud platform, and the system comprises a collection module which collects a contour diagram of a package and a morphological diagram of target food; the fitting degree analysis module is used for determining the contour coincidence degree and the edge distance according to the contour map and the form map, and determining whether the fitting degree of the target food and the package is qualified or not based on the contour coincidence degree and the edge distance; the shake risk analysis module is used for detecting the package with qualified fitting degree to obtain the deformation degree and the distribution condition of the package folds in the transportation process so as to determine whether the shake risk is qualified or not; the packaging material evaluation module is used for carrying out migration test on the package with the qualified shaking risk so as to evaluate the material safety of the package according to the migration condition of substances in the packaging material to the food; and the safety determination module determines that the target food in the package is safe food according to the fitting degree, the shaking risk and the material safety. And comprehensive guarantee is provided for food safety.

The invention discloses a vertical swing rolling machine, and relates to the technical field of metal part machining, the vertical swing rolling machine comprises a vertical frame, a swing rolling device and a half shaft main body, the swing rolling device comprises a swing rolling head, and the vertical swing rolling machine further comprises a straightening assembly; the straightening assembly comprises a rotary forging groove, a steam base, a polishing part, a supporting cylinder and a driving part. The steam seat is fixed on the supporting cylinder, and the steam seat is a hollow circular ring body; the rotary forging groove is a hollow cylinder with a large round opening in one end and a small round opening in the other end and is located above the steam base, and the bottom of the rotary forging groove abuts against the steam base; the half shaft main body comprises a rod part and an end part, and the end part is fixed at one end of the rod part; a straightening cylinder is fixed to the inner side of the steam base and is a hollow cylinder with the two ends open, and the outer diameter of the rod portion abuts against the inner diameter of the straightening cylinder. An opening of the straightening cylinder coincides with a small round opening of the rotary forging groove. The rod part can be straightened in the feeding process, and meanwhile water vapor is used for pushing the polishing part to complete polishing operation on the rod part.

The invention discloses an automatic alignment gap fitting device which comprises a rack, a bottom film unwinding roller, a to-be-compounded film unwinding and stripping mechanism, a UVW adjusting platform, a visual identification module and a compounding mechanism, and the automatic alignment gap fitting device collects position data of a to-be-compounded film and a bottom film through the visual identification module; according to the collected position data, the moving seat of the UVW adjusting platform is controlled to move to align the to-be-composited film and the bottom film, when the to-be-composited film and the bottom film are in a parallel state and position deviation occurs, translation alignment of the to-be-composited film and the bottom film can be achieved, the undesirable phenomena of distortion, bubbles and the like caused by distortion of the to-be-composited film are avoided, and the quality of the to-be-composited film is improved. And precise alignment and precise compounding are realized.

The invention discloses photovoltaic heterojunction component butyl rubber cushion block hole plugging equipment which comprises a component conveying device, a butyl rubber cushion block feeding device, a transfer conveying platform, a carrying mechanism and a carrying and placing device located above the component conveying device. The carrying and placing device comprises an XZ-axis driving module, a mounting beam and a plurality of carrying and placing units, wherein the mounting beam is driven by the XZ-axis driving module to move in the XZ direction, and the carrying and placing units are movably arranged on the mounting beam. And the carrying and placing unit comprises a taking and placing mechanism for sucking and placing the butyl rubber cushion block, a lead straightening mechanism for straightening a lead on the assembly, and a visual inspection camera. The butyl rubber cushion block with viscosity can be placed on the lead, the sealing and waterproof effects are achieved at the notch of the lead, the structure is simple, the production efficiency is high, the production cost is low, assemblies of different sizes can be adapted, the straightening quality of the lead can be improved, and therefore the butyl rubber cushion block can be accurately placed on the lead.

The invention provides a detection alignment device and assembly equipment of an optical module, the detection alignment device is provided with a detection station, and the detection alignment device comprises a detection module arranged on one side of the detection station; the motion module is provided with an image module and a bearing module, and the motion module can be switched between a first state and a second state; wherein the image module is suitable for providing a detection image, and the bearing module is suitable for bearing a display screen of an optical module; when the motion module is in the first state, the image module corresponds to the position of the detection station, and the detection module is matched with the image module to detect the lens assembly located at the detection station; when the moving module is in the second state, the bearing module corresponds to the position of the detection station so that the detection module can detect an optical module formed by the lens assembly and the display screen, and the moving module can adjust the position of the display screen according to the detection result of the optical module so as to be aligned with the optical module.

The utility model discloses an angle magnification optical diffraction experiment device. Comprising a one-dimensional optical slide rail, and a helium-neon laser, a one-dimensional arrangement lens group and a receiving measurement assembly which are sequentially arranged at intervals along an optical axis from an object side to an image side, and samples used for diffraction experiments are arranged among lenses in the one-dimensional arrangement lens group along the optical axis direction. The one-dimensional arrangement lens group, the receiving and measuring assembly and the sample are slidably mounted on the one-dimensional optical slide rail; and the helium-neon laser and the one-dimensional optical slide rail are both arranged on the top surface of the optical platform. According to the utility model, through the beam expanding light path and the angle amplification light path which are formed by the lens group, the diameter of the laser beam and the diffraction angle are respectively enlarged, so that diffraction spots of a macroscopic object are clearly visible on a naked eye resolution scale, the device can be used for displaying diffraction and interference phenomena of various large-size structures, and the whole set of device is simple, compact and convenient to use. The device is clear in structure, has high flexibility, and can be widely applied to physical optical experiment teaching.

The invention discloses a domain adaptation WiFi human body sensing method based on a comparative learning model, and the method comprises the steps: taking pre-collected data as source domain data when a human body sensing model based on WiFi CSI is trained, taking the data of a place where practical application is deployed as target domain data, and carrying out the training of a human body sensing model based on WiFi CSI; the method comprises the following steps: firstly, learning a migration corresponding relation between a source domain and a target domain by adopting an unsupervised generative adversarial network model, and obtaining a feature extractor of WiFi CSI data; and the CDCL model constructs positive and negative samples by using a data enhancement method to carry out comparative learning to obtain accurate data representation of a sub-domain and realize fine-grained domain self-adaption. According to the technical scheme of the invention, various environmental interference factors can be eliminated at the same time, the difference between the sub-domains of each environmental interference domain is eliminated, fine-grained domain alignment is realized, the interference of sub-domain superposition of various environmental domains is eliminated, and the accuracy of WiFi-based human body perception and the reliability of the system are improved.

The invention discloses a tunnel surrounding rock stability diagnosis method based on TBM multi-modal data fusion. The method comprises the steps of 1, dividing surrounding rock stability types; step 2, preparing TBM (Tunnel Boring Machine) multi-modal data; step 3, carrying out space-time alignment and fusion on the TBM multi-modal data; step 4, multi-modal data null value and duplicate value filling; 5, multi-modal data feature extraction based on the excavation and tunneling section; step 6, constructing a TBM multi-modal feature database based on the tunneling section; 7, constructing a tunnel surrounding rock stability prediction model; and step 8, tunnel surrounding rock stability field diagnosis application. According to the method, the alignment accuracy of different modal data is guaranteed based on time and space information, the modal data with low data null value degree and high data null value degree are repaired and complemented through the nearest neighbor null value filling and linear interpolation method, and the method can be suitable for fusion of different monitoring modals in the tunnel engineering construction process; rapid diagnosis of on-site surrounding rock stability can be realized, and construction environment safety is guaranteed.

The invention relates to the technical field of membrane attachment, and provides a ceramic membrane coating, bonding and attaching device which comprises a basic rack, a first driving part, a pressing assembly, a second driving part, a vacuum adsorption assembly and a visual assembly, a top rack is fixedly installed on the upper portion of the basic rack through a supporting rack, and the first driving part is installed on the basic rack; a bearing frame is fixedly installed at the output end of the first driving part, a lower press-fit mold is arranged at the top of the bearing frame, a press-fit assembly is installed on the lower press-fit mold, the second driving part is installed on the top rack, a lifting frame is fixedly installed at the output end of the second driving part, and an upper press-fit mold is arranged at the bottom of the lifting frame. A vacuum adsorption assembly is installed at the bottom of the upper pressing mold, and a visual assembly is installed on the top rack and used for solving the technical problems that in the related technology, when multiple layers of diaphragms are pressed, local stress concentration can be formed on the surfaces of the ceramic diaphragms through adsorption holes, then indentations are generated, and the surface quality of finished products is reduced.

The invention provides an electrical equipment defect data labeling method and system based on cross-modal active learning, and belongs to the field of electrical equipment defect data labeling. S1, electrical equipment defect data is converted into multi-modal data, the multi-modal data is mapped to a unified feature space, and a multi-modal classification model is constructed; s2, part of samples are selected for labeling, and an initial training set is constructed; s3, training the multi-modal classification model, inputting an unlabeled sample in the multi-modal data into the multi-modal classification model, and outputting a prediction label; s4, according to an active learning strategy, selecting samples with annotation values from the multi-modal data for annotation to obtain annotation samples, adding the annotation samples into the initial training set, and repeating the steps S3 to S4 to meet annotation requirements or stop conditions; classifying the defect data of the power equipment by using the trained multi-modal classification model to obtain a final labeling result; the data labeling cost and workload are reduced, and the labeling accuracy is improved.

The invention discloses a multi-source domain rolling bearing fault diagnosis method and system based on a diffusion model. The diagnosis method comprises the steps that rolling bearing vibration signals under different rotating speed working conditions are collected; in the forward process of the diffusion model, converting a source domain label into a one-dimensional vector, and adding noise to destroy original distribution to obtain yT approximate to Gaussian distribution; replacing yT with a Gaussian distribution variable # imgabs0 # in a reverse process, learning noise distribution characteristics added in forward distribution through a noise prediction network, denoising # imgabs1 # step by step to obtain # imgabs2 # in the same distribution as y0, inputting source domain data into the noise prediction network to extract data characteristics, inputting target domain data into the noise prediction network, and outputting the target domain data into the noise prediction network; global noise priori and local noise priori corresponding to the target domain data are obtained; and inputting source domain data and target domain data into a noise prediction network, mapping source domain data features to a target domain by using a multi-source domain adaptive algorithm, learning noise distribution features related to the target domain data, and gradually denoising # imgabs3 # to obtain a fault type of the target domain data.

The utility model relates to the technical field of natural gas conveying pipelines, and discloses a long-distance natural gas conveying pipeline which comprises a gas conveying pipeline, connecting flanges are arranged at the two ends of the gas conveying pipeline, threaded holes are formed in the two connecting flanges, connecting bolts are installed in the threaded holes, and a sealing groove is formed in the end face of the connecting flange at any end. The end face of the connecting flange at the other end protrudes outwards to form a sealing protrusion matched with the sealing groove, the sealing grooves and the sealing protrusions of the two adjacent gas pipelines are installed in a butt joint mode, the sealing grooves and the sealing protrusions are provided with sealing structures, wedge-shaped tangent planes are formed in the outer edges of the connecting flanges, and the wedge-shaped tangent planes and the threaded holes are distributed in a staggered mode. The wedge-shaped sections of every two adjacent connecting flanges are combined to form a wedge-shaped notch, an opening of each wedge-shaped notch is gradually enlarged from inside to outside in the radial direction, a pressing structure is installed in each wedge-shaped notch, and the lower end of each pressing structure makes contact with the corresponding sealing structure. According to the utility model, the sealing performance of the joint of the underwater gas pipeline is enhanced, and the maintenance cost is reduced.

This invention provides an optoelectronic co-packaging structure and its packaging method. Utilizing the excellent optical transparency, thermal stability, and electrical insulation of a glass substrate, it combines through-hole electrical interconnects for electrical signal transmission and through-hole optical interconnects for optical signal transmission. Furthermore, it integrates optical components through dual-surface grooves, solving the problems of low optical interconnect efficiency, poor heat dissipation, and limited integration in traditional optoelectronic co-packaging. This significantly improves the optical interconnect efficiency, heat dissipation performance, and integration of the optoelectronic co-packaging structure. The invention also uses grooves to limit the electrical components, achieving precise alignment and transmission of optical signals and reducing optical coupling loss. Simultaneously, the overlapping of the orthographic projections of the two grooves causes partial vertical overlap of the two optical components, optimizing the optical path and thus greatly enhancing signal fidelity.

The invention belongs to the technical field of anti-seepage wall construction, and specifically relates to a dock anti-seepage wall construction method that can adapt to various geological conditions, including measurement and positioning, prefabrication of concrete guide wall blocks, installation of concrete guide wall blocks, digging of groove holes by grooving equipment, cleaning of groove holes, and concrete pouring. Compared with the prior art, the advantages and positive effects of the invention are as follows: after the foundation groove of the anti-seepage wall guide wall in the invention is dug, a plurality of concrete guide wall blocks are tightly connected by sequentially inserting straight steel pipes or straight steel rods into the connection holes of a plurality of concrete guide wall blocks, and the longitudinal cross-sections of the two rows of concrete guide wall blocks are in a "┘└" shape; after the pouring is completed and the anti-seepage wall concrete reaches 75% of the design strength, the rows of concrete guide wall blocks are removed for circulation; through a concrete strength detection device at the bottom of a joint pipe, the strength of the concrete can be accurately detected, and when the concrete strength reaches a set value, the joint pipe is started to be pulled out to avoid the joint pipe being unable to be pulled out.

The utility model belongs to the technical field of precision detection equipment, and discloses a posture adjustable and contact force sensing detection platform, which comprises a base platform, a multi-axis displacement platform, a posture adjusting assembly and a contact detection assembly, the multi-axis displacement table is arranged on the base table and comprises an X-axis adjusting mechanism, a Y-axis adjusting mechanism and a Z-axis adjusting mechanism. The posture adjusting assembly comprises a base, an objective table and a first driving mechanism; the contact detection assembly is erected on the support and located above the objective table. The contact detection assembly comprises a probe seat, a supporting plate, a pressure sensor and a flexible hinge; the probe seat is connected with the supporting plate through the pressure sensor, and the supporting plate is connected with the support through the flexible hinge. According to the structural design, multi-axis displacement adjustment and alignment of the objective table and the probe seat can be conveniently and flexibly achieved, and then the alignment precision and stability between the probe and a tested piece on the objective table are effectively improved.

The present invention discloses a center alignment positioning method and system based on YOLOv8-RBT, the method comprising: obtaining a preprocessed image of a shaft part to be positioned; introducing a deformable convolution module, a bidirectional feature pyramid network structure and a fusion receptive field attention mechanism module to construct an improved YOLOv8-RBT model; performing target detection on the preprocessed image of the shaft part to be positioned based on the improved YOLOv8-RBT model to obtain the center position of the shaft part; coinciding the center position of the shaft part with the center coordinate of a center alignment device, controlling the center alignment device to tighten the shaft part, and obtaining the center alignment positioning result of the shaft part. The embodiment of the present invention can improve the accuracy of the position, size and angle of the shaft part detection and realize the center alignment of the shaft diameter of the shaft part within a preset range. As a center alignment positioning method and system based on YOLOv8-RBT, the present invention can be widely used in the field of workpiece alignment and positioning technology.