143results about How to "Real-time feedback" patented technology

The invention relates to the technical field of brain-computer interfaces, and discloses a self-adaptive dynamic feedback brain-computer interface training method and system based on virtual reality. The training method comprises the steps that a user performs motor imagery according to a training scene presented by the VR display device; the electroencephalogram acquisition equipment acquires electroencephalogram signals; configuring a data processing module, and operating a motor imagery continuous control model to calculate characteristic parameters by taking the electroencephalogram signals as input; under the condition that the task exists, the characteristic parameters are used as input, and a dynamic self-adaptive characteristic-feedback mapping model is operated to calculate control parameters; sending the control parameters to a functional electrical stimulation device to load electrical stimulation of corresponding intensity to the muscle to obtain tactile feedback; meanwhile, the dynamic adaptive feature-feedback mapping model is dynamically updated according to latest input feature parameters; the control parameters are sent to the VR display device to present visual feedback, and the user adjusts the motor imagery based on the visual feedback and the haptic feedback. The participation sense of the user and the training efficiency can be improved.

The invention discloses a child massage teaching auxiliary system based on artificial intelligence, and particularly relates to the technical field of massage auxiliary teaching, a Kalman filtering technology is adopted to effectively filter out large-amplitude interference in hand motion data, time-frequency analysis is carried out in combination with fast Fourier transform or wavelet transform, and frequency domain characteristics of microfibrillation signals are accurately captured; through fine micro-tremor signal analysis, noise interference is removed, the fine change of micro-tremor of the hands of a student is accurately identified, and the evaluation precision of the massage action stability is remarkably improved; and the integrated learning progress management module automatically adjusts teaching contents according to the learning progress and skill mastering conditions of the students, provides real-time feedback and forward excitation, provides excitation when the students have good performance, prompts and optimizes follow-up actions in real time when deviation occurs, helps the students to continuously improve skills, avoids error accumulation, and effectively improves the teaching effect.

The invention relates to the technical field of material storage management, in particular to a BIM-based construction site material monitoring management method and system. The method comprises the following steps: obtaining a construction project drawing; performing drawing information extraction on the construction project drawing to obtain construction project material information data and construction project structure data; performing construction project three-dimensional modeling on the construction project material information data and the construction project structure data to generate construction project three-dimensional modeling data; obtaining total construction material data; and carrying out material information modeling on the total construction material data by using a BIM technology to generate total construction material modeling data. According to the invention, accurate three-dimensional modeling, intelligent marking, regionalized storage and real-time allocation of the construction site materials are realized through the BIM technology, and the accuracy of construction site material monitoring management and the emergency response real-time performance are improved.

The invention discloses a mathematics virtual-real fusion teaching system. A scene construction module is used for constructing a virtual teaching scene by using a virtual reality technology according to teaching contents and learning requirements of students; the animation simulation module is used for creating a mathematical model and an animation in the virtual teaching scene by utilizing a three-dimensional modeling technology and an animation production technology; the data acquisition module is used for acquiring learning behavior data and physiological data of students through the intelligent teaching terminal and the wearable sensor to obtain learning feedback data; analyzing the learning feedback data by using a machine learning algorithm to obtain learning state data of the student; and the teaching feedback module is used for adjusting a teaching mode and a teaching scene in the virtual teaching scene according to the learning state data. Through virtual reality and augmented reality technologies, in combination with a highly vivid virtual teaching scene and an innovative interaction mode, mathematics learning is more vivid and interesting, and the learning interest of students is greatly improved.

The invention discloses an Internet of Things intelligent application method and device based on a large language model, belongs to the technical field of Internet of Things equipment, aims at solving the problems of complexity and inconvenience of user interaction, insufficient compatibility between equipment and poor security and privacy, and comprises the following steps: S1, demand analysis and system design; s2, data collection and preprocessing; s3, language model integration and processing; s4, intelligent decision making and automatic management; by setting the natural language processing module and the large language model, the natural language instruction of the user can be understood and generated through the natural language processing technology, so that the user can carry out equipment control and information query by using simple statements, the complexity of operation is reduced, and meanwhile, by combining the voice recognition technology, the user experience is improved. The user can interact with the Internet of Things system through voice, the model can accurately understand voice input, real-time feedback and operation execution are provided, and user experience and operation convenience are remarkably improved.

The invention provides a visual aiding system and method for visually impaired people based on a multi-mode large model, intelligent glasses and application software. The system comprises a multi-mode large model, blind-helping application software and intelligent glasses, enables a visually impaired person to ask questions through simple voice, achieves the recognition of all things such as environment, obstacles, text information, road names / shop names, flowers and plants, and feeds back the questions to the visually impaired person through voice. According to the scheme, the visually impaired person can conveniently and quickly see all information around the person in a hearing mode, then the independence of work and life is greatly improved, and the visual impaired person has wide application prospects and huge social value.

The invention discloses an equipment instrument quality interpretation device based on AI vision, and relates to the field of computer vision and artificial intelligence. Comprising an optical acquisition system, an image processing unit, an intelligent detection unit and a data management unit, the optical acquisition system acquires image or video information of equipment and instruments through a camera or an image sensor, is matched with a corresponding light source to enable the acquired image to have no shadow, and is connected with the image processing unit through a network; the image processing unit preprocesses the acquired image; the intelligent detection unit extracts features related to target quality from the preprocessed image by using a deep learning algorithm; and the data management unit stores the data and sends an interpretation result to a user through the feedback module according to the quality interpretation result, the user performs corresponding operation according to the interpretation result, and real-time quality detection is realized by utilizing efficient image processing and AI interpretation algorithms, so that the detection efficiency is remarkably improved, and the requirements of a high-rhythm production line are met.

The invention relates to an intervertebral disc degenerative change analysis system based on multi-dimensional information. The system comprises a data processing module, a modifiable factor processing module, a circular RNA data processing module, a biomarker processing module, an image processing module, a treatment information processing module, a diagnostic feature anchoring module, a model generation module and a change analysis module. Anchoring is carried out on circular RNA, biomarkers, treatment information and modifiable factors through image information to form an anchoring network, and a reliable and effective basis can be provided for disease course analysis through big data and a large number of research results, so that each doctor has a targeted expectation and understanding on the disease course of a patient in the diagnosis stage; the method has the advantages that an interventional therapy scheme can be arranged in advance or the condition of a patient can be observed in real time, research results can be collected and fed back in time through big data, the information utilization rate is increased, and an information dimension integration scheme for degenerative disease recognition is created, and the accuracy of recognition results is improved.

The invention provides an intelligent identification method for unfavorable geologic bodies while drilling based on multi-modal fusion. The method comprises the steps of data collection, data preprocessing, feature extraction, modal common and private feature extraction, modal fusion and unfavorable geologic body identification. According to the method, the multi-modal while-drilling data set is formed by collecting the four modal data of the drilling machine operation parameters, the while-drilling vibration parameters, the while-drilling acoustic signals and the while-drilling resistivity imaging graph, the complementarity of different data sources can be fully utilized by the multi-modal data, and more comprehensive analysis is provided for recognition of the unfavorable geologic body; according to the technology, the accuracy and reliability of identification can be improved, the anti-noise capability can be enhanced through cross validation of different data modes, and environmental interference signals are filtered out; besides, multi-modal fusion can adapt to more complex geological environments, and particularly under the condition that multiple geological anomalies coexist, potential unfavorable geologic bodies can be better identified, real-time and accurate feedback can be provided, and technical support is provided for construction under complex geological conditions.

The invention relates to a discrete dust treatment system and method, and belongs to the technical field of dedusting, the discrete dust treatment system comprises a machine body assembly, the machine body assembly is provided with an air inlet, an air outlet and a first opening, and the machine body assembly is provided with a first mounting cavity and a second mounting cavity; the filter cartridge assembly is arranged on the machine body assembly and located in the first mounting cavity, the filter cartridge assembly is provided with a filter cavity and a second opening, and the air inlet, the first mounting cavity, the filter cavity, the second opening, the first opening and the second mounting cavity are sequentially communicated; the blowing assembly is arranged on the machine body assembly, the blowing assembly is provided with an air inlet and an air outlet, the air inlet is communicated with an external air source, the air outlet is communicated with the filtering cavity, the blowing assembly is provided with an air conveying channel, and the air inlet, the air conveying channel and the air outlet are sequentially communicated. According to the discrete dust treatment system disclosed by the invention, the dust on the surface of the filter cartridge assembly is instantly blown through the blowing assembly, so that the dust cleaning efficiency is greatly improved.

The invention provides a child adolescent posture adverse risk prediction system and method, and the system comprises a first collection module which is used for collecting the gait data of a child during walking and running; the second acquisition module is used for acquiring plantar pressure distribution data of the child in dynamic and static states; the third acquisition module is used for acquiring human body measurement data; the fourth acquisition module is used for acquiring three-dimensional posture image data of the child; the fifth acquisition module is used for acquiring daily physical activity data of the children; and the processing module is used for collecting the gait data, the plantar pressure distribution data, the human body measurement data, the three-dimensional posture image data and the daily physical activity data to obtain preprocessed data, and inputting the preprocessed data into a pre-constructed LASSO regression model to obtain a corresponding posture adverse risk prediction result. The method has the beneficial effects that the accuracy of poor attitude analysis can be improved, large-scale and real-time attitude risk monitoring is realized, the limitation of environmental conditions is relieved, and an evaluation result is fed back in real time.

The invention discloses a vacuum high-temperature furnace cooling intelligent control system and a control method thereof, relates to the field of high-temperature furnace cooling regulation and control, and solves the problems that an existing high-temperature furnace temperature monitoring and control method is low in accuracy and difficult to accurately control. The temperature detection module is used for detecting the water supply temperature in real time and feeding back a temperature detection signal; the flow detection module is used for detecting the water return flow in real time and feeding back a flow detection signal; the cooling control module is used for receiving and responding to the temperature detection signal and the flow detection signal so as to control the cooling water system to regulate and control operation parameters; according to the intelligent cooling control system for the vacuum high-temperature furnace and the control method of the intelligent cooling control system, accurate temperature and flow information can be obtained through detection, operation parameters can be adjusted in time in real time, and normal operation of a cooling water system is guaranteed.

The invention provides a shooting action real-time evaluation and simulation method and system based on dynamic adjustment, and relates to the field of intelligent shooting training and evaluation. The method comprises the steps that various sensors are used for collecting data in the shooting process, such as acceleration, angular velocity, gun barrel pressure and attitude data; based on the data, a dynamic model of shooting actions is established, and human body actions, firearm recoil and air resistance are comprehensively considered; evaluating and updating the dynamic model in real time through a Kalman filter; using a self-adaptive control algorithm to correct action errors and optimize a control strategy; real-time simulation of shooting actions is carried out on the basis of dynamic adjustment; feedback optimization is carried out according to the simulation result, model parameters are adjusted, input is controlled, and the accuracy and stability of the shooting action are improved. According to the method, the precision and efficiency of shooting training can be improved, and the good self-adaptive adjusting capacity is achieved.

The invention discloses a combined purification monitoring method and a combined purification monitoring system for food-grade carbon dioxide, and relates to the technical field of purification monitoring, and the combined purification monitoring method comprises the following steps: carrying out purification analysis on a purification process, carrying out sequential decomposition on purification steps, and establishing step association of the purification steps; configuring an integrated monitoring platform, and configuring a monitoring sensor on each purification step; step monitoring of the purification process is executed, and a real-time feedback data stream is established and returned to the integrated monitoring platform; carrying out independent verification analysis on the returned data based on an independent verification network, and establishing a purification early warning result; performing combined purification fitting analysis on the step purification early warning result and the step association, and establishing a pre-analysis result; and completing joint purification monitoring according to a pre-analysis result and a step purification early warning result. The technical problems of insufficient real-time monitoring and weak early warning capability in the prior art are solved, and the technical effects of dynamic monitoring and abnormal early warning of the food-grade carbon dioxide purification process are realized.

The invention relates to a control system and method for a marine underwater monitoring robot, and the system comprises a main control module which carries out the compression and coding of collected operation environment data and motion posture data according to a video data compression protocol, compressed and coded operation environment data and motion attitude data are sent to a control center through a wireless communication module, the control center feeds attitude control information back to a main control module according to requirements, and the main control module controls the motion state of the robot through a motion control module after receiving the attitude control information; the environment information acquisition module is used for acquiring a video signal, turbidity and temperature of a working environment; the attitude information acquisition module is used for acquiring collision sonar, pressure, depth and motion state information of the current robot; a wireless communication module; and the motion control module controls the robot to operate according to the expected posture. The system can realize depth-keeping control and attitude control, and the motion control capability is relatively ideal.

The invention provides a group-type multi-role-playing virtual simulation training method and system and a medium, and the method comprises the steps: carrying out the simulation training in response to a virtual simulation training scene selected by at least one teacher user, and determining the number and types of roles participating in the virtual simulation training scene; n of the M trainees apply to participate in the virtual simulation training scene, the N trainees are allocated as roles, the mapping relation between the roles and the N trainees is determined, and scoring permissions of the remaining Q trainees are configured; recording training process data of N trainees participating in group training; obtaining evaluation data of roles played by the Q user students on the N student users; obtaining an evaluation score of each student user participating in the virtual simulation training scene according to the mapping relation; and finally, based on the obtained Q evaluation scores, determining training scores of the user trainees participating in training.

The invention discloses an FCT automatic detection system of a production line ECU and a detection method thereof, and belongs to the field of vehicle brake control and automatic detection. The FCT automatic detection system comprises an industrial personal computer, a test unit, an execution unit, a programmable power supply and an FCT detection device; the FCT detection equipment comprises a translation test bench, a to-be-detected ECU positioned and connected to the translation test bench, and a lifting test mechanism arranged right above the to-be-detected ECU, the lifting test mechanism comprises a pressing unit and a test needle bed arranged at the output end of the bottom of the pressing unit, and the industrial personal computer is connected with a PCBA board of the to-be-detected ECU through the test unit, an execution unit and the test needle bed in sequence. The ECU to be tested is also connected with the industrial personal computer through a CAN bus and a programmable power supply. By adopting the FCT automatic detection system for the ECU of the production line and the detection method thereof, full-automatic testing of the ECU can be realized, excessive human intervention is not needed, the automation degree is high, and the FCT automatic detection system has the advantages of high accuracy of test data, high efficiency and the like.

The invention discloses a music emotion adjusting system and method based on content generated by artificial intelligence. According to the method, on the basis of the music style and emotional state preferred by the user, the personalized customized music is generated by using the AIGC technology; meanwhile, by monitoring EEG signals of the user, detecting emotional changes of the user and establishing a mapping relation among music styles, emotional states and music elements, music of different styles and emotional tendencies is dynamically generated according to emotional requirements of the user, so that the problem that copyright and individuation are insufficient in a traditional music therapy is solved, and the user experience is improved. Meanwhile, the emotion monitoring method based on the electroencephalogram can feed back emotion changes of the user more scientifically, more objectively and in real time, and the accuracy of emotion adjustment is improved.

The invention relates to the technical field of English homework correction, in particular to an English composition correction system based on an AI large model. Comprising the following steps: step 1, input and acquisition: inputting student compositions, directly uploading electronic editions, and uploading scanned paper boards; 2, pre-processing questions, and dividing the questions into two parts, namely, a proposal composition and a non-proposal composition according to the questions; step 3, setting a prompt project; respectively establishing judgment prompt projects according to the proposal composition and the non-proposal composition; 4, inputting the preprocessing content into an LLM large model; and step 5, the LLM model refers to the prompt project and combines data in the LLM model to judge the composition to obtain a comprehensive result. The data in the LLM model is learned and trained in advance to reach the composition judgment level for judging the examination degree. The prompt projects comprise a central thought prompt project, a question-cutting prompt project, an off-question judgment prompt project, a grammar vocabulary prompt project, a clear prompt project, a score prompt project and a guidance LLM model for judgment.

The invention discloses a steel plate drilling automatic online detection system based on machine vision, and relates to the technical field of steel plate drilling machining systems. The system comprises a control system module, the input end of the control system module is electrically connected with an image processing module, the input end of the image processing module is electrically connected with an image acquisition module, and the output end and the input end of the control system module are electrically connected with a deep learning module. The output end and the input end of the control system module are electrically connected with a data processing module. According to the invention, the deep learning module uses a deep learning algorithm to train a large number of drilling images, automatically learns the characteristics and modes of drilling, improves the accuracy and robustness of detection, can continuously optimize the performance of itself, adapts to different types of steel plates and drilling requirements, and improves the accuracy and robustness of detection. And the intelligent diagnosis module is combined with an expert system and data analysis to perform intelligent diagnosis on a detection result.

The invention discloses a closed-loop ultrasonic regulation and control system for a targeted deep brain area. A bio-electricity signal collector collects bio-electricity signals of a detection target and uploads the bio-electricity signals to a main control unit. The main control unit identifies the bio-electricity signal and outputs an excitation signal to the signal generator after identifying a characteristic electric signal. The signal generator generates an ultrasonic waveform signal according to the ultrasonic parameter. Signals are amplified by a power amplifier and then input to an ultrasonic transducer, corresponding mechanical waveforms are output under voltage excitation, then bioelectricity signals are collected in real time for neural activity reaction after ultrasonic stimulation, and closed-loop ultrasonic regulation and control are achieved. According to the invention, electric signals are recorded at the same time, ultrasonic stimulation parameters are fed back in real time, a remarkable inhibition effect is generated on mouse epilepsy electroencephalogram, ultrasonic output energy is automatically adjusted, and the possibility of adverse reaction is reduced. The ultrasonic transducer is firmly fixed on the head of the mouse by the adaptive device, so that ultrasonic regulation and control on the freely moving mouse are realized, and the mouse is not limited by anesthesia stimulation.

The invention discloses a multi-factor-based deformation prediction method for shield construction crossing a building, and the method comprises the steps: building a multi-factor matrix through settlement data, inclination data, the distance between a construction tunnel face and a building, shield construction parameter data and geological information data of a construction region, which are obtained at a plurality of moments, and taking the multi-factor matrix as the input of a prediction model; the prediction value of the settlement data of the building is obtained, and the deformation prediction of the shield construction crossing the building based on multiple factors is realized. According to the method, through combination of the CNN and the LSTM model, not only can multi-factor characteristics be associated, but also the shield construction progress and the building deformation are associated through the factor of the distance between the shield construction and the building, and through the technologies, the construction risk can be effectively reduced, and the overall construction efficiency and economic benefits can be improved; and the settlement prediction is more intelligent, dynamic and refined. And the prediction precision and safety of the settlement of the adjacent building in the shield construction process can be greatly improved.

The invention discloses a stress detection method for graphene composite piezoelectric material integrated optical fiber sensing, and relates to the field of multi-mode sensor integration, and the method comprises the steps: generating a signal through a signal generator, and transmitting the signal to a composite flexible piezoelectric material through a power amplifier; the composite flexible piezoelectric material is used for generating ultrasonic waves, and the ultrasonic waves are conducted in the tested material; the fiber grating sensing and demodulation module is used for demodulating ultrasonic waves conducted in the tested material and transmitting the demodulated ultrasonic waves to the upper computer; the upper computer is used for displaying, storing and processing the demodulated ultrasonic signals, the stress borne by the detected material is obtained, and stress detection of the graphene composite piezoelectric material integrated optical fiber sensor is completed. According to the invention, the problems that the micro stress change in a complex structure cannot be detected in real time and the application environment is limited in the prior art are solved.

The invention relates to an intelligent self-learning visual inspection system which is composed of an acquisition system, a data engine, an iteration engine, a correction system, a detection system and an NG / OK judgment system, and the acquisition system is used for being responsible for image acquisition of a workpiece to be detected and transmitting a picture detected by a light source to the data engine or the correction system; the data engine is used for storing the data transmitted by the acquisition system and intelligently marking the data to form formatted data required by model iteration; and the detection system is used for sending a detection request to the iteration engine after detecting the picture transmitted by the correction system, and the iteration engine calls the current optimal model for reasoning after receiving the request of the detection system and returns a reasoning result to the detection system. According to the invention, an intelligent identification model in the aspect of computer vision is utilized to automatically discover internal defects of the to-be-detected product and calculate the size of the defects as a reference basis for product waste judgment.

The invention discloses a comprehensive heat transfer coefficient calculation method for the wall surface of a circumferential heating appliance, and the calculation method specifically comprises the following steps: A, carrying out the simplified coupling processing of a radiation heat transfer formula and a convective heat transfer formula according to the physical parameters of a heat dissipation assembly, and obtaining a comprehensive heat transfer coefficient model of the heat dissipation assembly; b, on the basis of the comprehensive heat transfer coefficient model, temperature simulation calculation is conducted on the wall surface temperature Tw of the outer wall of the heat dissipation assembly by means of the environment temperature T0 and the total heat transfer amount Q of the circumferential heating appliance; and C, the temperature simulation processing of the wall surface temperature Tw is presented through a visualization system. The comprehensive heat transfer coefficient calculation method is established by researching the comprehensive heat transfer coefficient of the wall surface of the circumferential heating appliance, convective heat transfer and radiative heat transfer calculation is simplified, the comprehensive heat transfer coefficient of the wall surface is directly set in non-gridding rapid simulation, the calculation time is greatly shortened compared with the prior art, the operation is simple, and the calculation efficiency is high. And rapid and efficient design optimization of the circumferential heating appliance is realized.

The intelligent twist lock for the container ship comprises a lock body master control box, an upper lock head driving box and a lower lock head driving box are arranged on the upper portion and the lower portion of the lock body master control box respectively, an upper lock head is arranged on the top of the upper lock head driving box in a sliding mode, and a lower lock head is arranged at the bottom of the lower lock head driving box in a sliding mode; an upper lock head driving assembly is arranged in the upper lock head driving box, and a lower lock head driving assembly is arranged in the lower lock head driving box. A lock body information chip convenient for a ship remote control platform to remotely operate the twist lock is arranged on the front side of the upper lock head driving box; the lock body information chip and the control module are additionally arranged on the twist lock, and the twist lock is in communication connection with the ship remote control platform, so that key data basis and equipment support are provided for intelligent stowage and yard automatic management of the container ship; the driving motor is matched with the precise spiral lifting and rotating mechanism, so that the whole process automation of locking and unlocking of the twist lock is realized, the working efficiency is greatly improved, and the labor intensity is reduced.

The present invention relates to the technical field of cloud platform construction, and in particular to a method for constructing an intravenous treatment management cloud platform. The method comprises the following steps: performing gene expression pathway enrichment analysis on the patient's venous system through gene sequencing technology, thereby obtaining gene expression data; performing gene expression spectrum analysis on the gene expression data and performing intravenous treatment response gene labeling, thereby obtaining a treatment response gene labeling set; using cloud computing technology to build an elastic computing resource scheduling system, thereby obtaining resource scheduling system data; performing node load balancing weight scaling based on resource scheduling system data and gene expression data, thereby obtaining resource balancing scaling data; performing multi-scale pyramid feature refinement on gene expression data, thereby obtaining gene image feature refinement data. The present invention realizes the method for constructing an intravenous treatment management cloud platform through node load balancing weight scaling and GPU heterogeneous computing acceleration processing.

The present invention discloses a multi-survey integrated surveying and mapping indoor and outdoor data automatic processing system and method, and relates to the technical field of automatic surveying and mapping; the technical key points are: by analyzing indoor and outdoor data in the surveying and mapping process, a three-dimensional task model is constructed, and also for environmental data in the surveying and mapping process, especially for the flight environment of unmanned aerial vehicles, a number of influence modes are constructed, the stability coefficient in the automatic surveying and mapping process is analyzed, and the optimal three-dimensional task model is selected; according to the three-dimensional task model, settlement parameters and deformation parameters are extracted, and a nonlinear fitting model is built to generate corresponding element time variation curves; different analysis strategies are executed according to the generated normal reference element values ​​and abnormal reference element values, and the three-dimensional task model is further calibrated to improve the precision and accuracy in the data acquisition process; at the same time, the process focuses on the whole process of the construction operation stage, avoiding the safety hazards caused by foundation settlement and building deformation.

The invention provides a psychological health assessment method based on image information. The method comprises the following steps: acquiring facial image data and sent voice data of a target user in a process of participating in a reaction game; filtering the facial image data to obtain a filtered image; constructing an image enhancement window, and traversing the filtered image by using the image enhancement window for denoising to obtain a denoised image; sequentially performing histogram equalization processing and face segmentation on the denoised image to obtain a face image; performing signal denoising and text conversion on the voice data to obtain text data; performing feature extraction on the face image and the text data, and fusing the extracted features to obtain fused features; and inputting the fusion features into a trained mental health assessment model to obtain an assessment result. The emotion change and psychological state of the target user can be more comprehensively captured through the analysis of the comprehensive facial image, and the accuracy and reliability of psychological health assessment are improved.

The application discloses a semiconductor wafer bin conveying system and a control method thereof, and relates to the technical field of semiconductor manufacturing automation. The system comprises a conveying unit and a material placing unit. The improvement lies in that the bottom of a wafer bin body is provided with three positioning grooves in isosceles triangle distribution, forming a mistaken orientation prevention structure; and the transfer frame and the material placing frame are respectively provided with a first set and a second set of limiting protrusions corresponding to the positioning grooves. The two sets of protrusions are configured to be selectively and sequentially clamped with the positioning grooves at the bottom of the same bin body during the conveying process, so that the anti-interference positioning handover from grabbing to placing is realized. The application eliminates the positioning collision risk between the conveying mechanism and the fixed station from the mechanical structure, and ensures the uniqueness of the direction of the wafer bin through the asymmetric geometric design. Meanwhile, the material placing frame can be integrated with elastic air supply and pressure sensing detection functions, realizing higher automation and reliability.