110 results about "Airport security" patented technology

The invention relates to the technical field of airport safety management, in particular to an airport safety management method and system, and the method comprises the steps: obtaining various data of airport operation in real time through a multi-source heterogeneous data collection module, carrying out the feature fusion processing through a dynamic risk assessment model, generating a three-dimensional risk thermodynamic diagram, and outputting a risk level and a type identifier; triggering a hierarchical response mechanism, generating a resource configuration scheme through a resource scheduling optimization algorithm, and sending a scheduling instruction; in the emergency disposal stage, a multi-terminal collaborative platform is used for monitoring the disposal effect, when the risk diffusion coefficient exceeds a preset threshold value, a cross-department collaborative disposal protocol is started, and the resource allocation weight is dynamically adjusted. According to the method, the risk detection precision is improved through multi-source data fusion and space-time correlation analysis, multi-target optimization configuration is realized by adopting a dynamic resource scheduling matrix, a closed-loop mechanism of hierarchical response and cross-department co-processing is constructed, the traceability of the process is enhanced in combination with digital twin and block chain technologies, and the airport safety management level is effectively improved.

The invention relates to the technical field of airport safety guarantee, and discloses an FOD recognition system and method based on machine vision. The system comprises a multispectral image acquisition module, a dynamic environment adaptive preprocessing module, a multi-attention feature extraction module, a multi-modal data fusion module, a multi-stage verification decision module and a real-time alarm and closed-loop control module. Pavement data are acquired through multi-modal image acquisition, after preprocessing, feature extraction and fusion, multi-stage verification decision is carried out to detect foreign objects, and finally real-time alarm and elimination are realized. The system can effectively overcome complex environmental interference, accurately identify foreign objects, quickly process and improve the safety and operation efficiency of the airfield pavement, and has the advantages of high identification precision, strong adaptability, good reliability and the like.

The invention discloses a civil aviation airport security method and system based on multi-source perception and dynamic risk assessment, and the method comprises the steps: building a personnel-article-scene ternary relation model through collecting multi-source data such as video monitoring, face recognition, luggage scanning and sound signals; based on an abnormal matching mode of the model, dynamic risk assessment is carried out by combining real-time people flow density and historical event thermodynamic distribution, and a dynamic risk calibration map is generated; an identification strategy parameter is configured according to the risk level, a self-adaptive strategy set is formed and applied to the intelligent terminal, target identification and behavior tracking are achieved, and a security and protection system is automatically linked when a triggering condition is met; according to the method, the behavior-article-scene ternary relation model is constructed, so that multi-source data collaborative analysis is realized, the limitation of traditional single-mode detection is overcome, the abnormal behavior recognition accuracy in a complex scene is remarkably improved, and the false alarm rate is effectively reduced.

The invention relates to the technical field of airport safety monitoring, and discloses an airport video data real-time analysis system. The system comprises a video stream spatial-temporal feature modeling module, a behavior trajectory map construction module, an abnormal region association analysis module, a risk level semantic judgment module and a situation structure visualization module. According to the method, multi-scale spatial-temporal feature analysis is carried out on an airport monitoring video stream, a multi-dimensional behavior trajectory map is established, abnormal behavior region association is analyzed, risk level semantics are judged, and finally an airport global risk situation thermodynamic distribution map is generated. According to the system, the whole process processing from video data acquisition to risk situation visualization is realized, the abnormal behavior area can be accurately identified, the risk level and category are clear, comprehensive and visual situation information is provided for airport safety management, and the intelligent level of airport safety management is improved.

The invention relates to the technical field of airport safety protection, and discloses an airport bird strike prevention method and system based on multi-sensor fusion. The method comprises the steps of collecting airport peripheral airspace radar detection, radio detection, laser monitoring, weather and other multi-mode sensor data, and performing time synchronization and space registration to generate a fusion data stream; features are extracted based on a dynamic weight distribution algorithm, target types are identified by using a multi-modal classification model, and birds and unmanned aerial vehicles are distinguished; constructing a dynamic risk assessment model based on a Markov chain to generate an intrusion risk level; and when the risk level exceeds a preset threshold value, triggering a multi-level alarm strategy and linking the expelling equipment to execute a self-adaptive expelling instruction. According to the method and system, through multi-sensor fusion, the monitoring precision is improved, the target is accurately recognized, the risk is evaluated in real time, efficient alarming and expelling are achieved, the airport bird strike prevention capacity is effectively improved, and aviation safety is guaranteed.

The invention discloses a visual and three-dimensional modeling luggage automatic identification method, equipment, a medium and a product. The method comprises the following steps: firstly, carrying out dynamic multi-view scanning on luggage entering a scanning area of a conveyor belt to obtain a multi-view image, carrying out deep learning to obtain three-dimensional point cloud data, and fusing the three-dimensional point cloud data with X-ray transmission density data to form a preliminary three-dimensional model; whether the model is complete or not is judged by combining geometric closure and material density continuity, and if not, features are extracted through an adversarial generative network, and occlusion area point cloud data are predicted for complementation; and finally, matching the complementation model features with a dangerous goods feature library, and judging whether the dangerous goods are dangerous goods or not. By implementing the technical scheme provided by the invention, the information of the articles in the luggage can be comprehensively obtained, the complete and accurate three-dimensional model can be constructed, whether the articles are dangerous articles or not can be efficiently and accurately judged, and the efficiency and the safety of aviation security inspection are improved.

The invention relates to the technical field of airport safety monitoring, and discloses an image-based airport runway foreign matter intelligent detection and clearance auxiliary processing system and method. The acquisition module is used for acquiring original image data of a runway and a clearance area in real time through a high-definition camera; adopting an improved YOLOv11 target detection algorithm to identify birds, unmanned aerial vehicles or foreign matter targets in the clearance area; an improved YOLOv11 backbone is used as a main body feature extractor, and original image data is converted into a multi-scale feature map; the neck assembly combines feature maps of different scales and transmits the feature maps to the head assembly for prediction; the head assembly performs target prediction based on the reconstructed feature map; wherein a C2f block in the YOLOv11 neck assembly is replaced by a C3k2 block, and an intersection stage part and a space attention block are introduced; and a bird repelling or cleaning module is dispatched according to the detection result. According to the invention, the monitoring efficiency can be effectively improved, the detection precision is improved, clearance auxiliary processing is optimized, and the safety of the airport runway is improved.

The invention discloses a fixed dual-runway FOD detection method based on multi-source circumferential scanning, and belongs to the technical field of data fusion detection, and the method specifically comprises the steps: synchronously obtaining dual-runway multi-polarization echo data through a fixed circumferential scanning rada; performing time-varying clutter suppression by combining an adaptive clutter cancellation method matched with a dynamic background template and a runway material feature library, and generating a time-frequency domain three-dimensional feature matrix through time-frequency analysis; synchronously collecting and preprocessing image data, and marking a target area through a constant false alarm rate algorithm and image detection; a multi-source data geographic coordinate mapping model is established, data registration and cross validation are completed under a runway physical coordinate system, and real-time tracking of a real FOD target is realized based on radar and image fusion data through multi-dimensional confirmation of radar polarization / micro-motion features and image visual features; according to the method, the FOD detection accuracy and the position identification precision are improved through multi-source data fusion, the false alarm rate is effectively reduced, and a guarantee is provided for safe operation of an airport.

The invention relates to the technical field of airport safety guarantee, and particularly discloses an airport bird situation monitoring and early warning bird repelling equipment linkage control method comprising the following steps: obtaining bird situation data vectors collected by sensors, calculating fused bird situation data vectors, and obtaining bird flock information; constructing a bird situation risk assessment model based on machine learning, combining the fused bird situation data with an aircraft take-off and landing plan, a runway use state and airport surrounding environment information to form an input feature vector, calculating a risk value through a risk assessment function, and dividing risk levels according to the risk value; according to a risk grade result of the risk assessment module, corresponding bird repelling equipment is controlled to work according to a hierarchical linkage bird repelling strategy; and in the bird repelling process, the risk level is re-evaluated according to the new bird situation data, the parameters of the bird repelling equipment are adjusted, and the bird repelling strategy is optimized by using a reinforcement learning algorithm. According to the invention, the defects of monitoring range and precision of a single sensor are effectively overcome, and the reliability of bird monitoring is greatly improved.

The invention relates to the technical field of airport safety monitoring, in particular to an airport runway intrusion identification method based on an ESNB algorithm, and the method comprises the steps: constructing an airport runway intrusion data set; the method comprises the following steps: constructing an improved Inception U-Net network, and obtaining a teacher network based on the improved Inception U-Net network; based on the teacher network, obtaining an optimal student network through a multi-objective evolutionary algorithm; based on the teacher network and the airport runway intrusion data set, performing knowledge distillation on the optimal student network to obtain an ESNB network; according to the scheme, the ESNB network is deployed in an airport and is used for airport runway intrusion recognition, and the problems that existing airport runway intrusion recognition is low in efficiency and high in computing power requirement can be effectively solved.

The invention discloses an airport terminal security check passenger number hourly prediction method comprising the following steps: 1) preprocessing security check passenger flow characteristic data and terminal historical security check passenger data, and merging the preprocessed security check passenger flow characteristic data and terminal historical security check passenger data into a passenger security check number prediction data set; 2) constructing an NBMT-OneNet-based hourly security check passenger number prediction model; 3) training the hourly security check passenger number prediction model by using the passenger security check number prediction data set; and 4) obtaining security check passenger data and security check passenger flow characteristic data of the terminal to be predicted in the past T time period, and inputting the data into the hourly security check passenger quantity prediction model to obtain security check passenger data in the future T'time period. According to the characteristics of hourly airport security check data, the N-BEATS model and the MTGNN model are used for capturing the complex correlation between the time sequence trend and the variable, and the accuracy of the prediction result is effectively improved.

The invention belongs to the technical field of airport security and protection, and relates to an airport boundary intrusion alarm system based on millimeter-wave radar and video analysis, and the system comprises a data collection module which is used for obtaining target point cloud data and video data; the preprocessing and feature extraction module is used for preprocessing video frames of the target point cloud data and the video data and extracting radar features and image features; the multi-modal feature fusion module is used for realizing fusion of the radar features and the image features through an attention mechanism by using a Transform network so as to obtain fusion features; the intrusion target detection and recognition module is used for recognizing and positioning an intrusion target and classifying and judging intrusion behaviors; and the alarm and linkage module is used for giving an alarm and recording related data of the intrusion behavior. According to the invention, the intrusion behavior can be accurately detected in real time, the false alarm and missing alarm conditions can be reduced, the automation and intelligence level of airport boundary safety management is improved, and a solid guarantee is provided for the safe operation of an airport.

The invention relates to the technical field of aerial target detection, in particular to an aerial target detection method based on image recognition. Comprising the steps of image acquisition and preprocessing, target detection, target classification, target tracking, data storage, alarm and feedback and the like. According to the invention, technologies of deep learning, multispectral imaging and the like are combined, the defects of a traditional detection technology are effectively overcome, and the detection precision of low-altitude, low-speed and small targets is improved; the requirement of real-time monitoring is met while the detection precision is ensured; effective detection can be carried out at night and in a complex environment, and the adaptability of the system under different illumination conditions is improved; a target tracking algorithm is optimized, continuous and stable tracking of multiple targets can be realized, and target motion trails can be accurately output; the system integrates detection, identification, storage and alarm, and is suitable for various application scenes such as airport security, important facility protection, city management and the like.

The invention relates to the technical field of data processing, in particular to an intelligent analysis method and system for airport security check data. The method comprises the following steps: acquiring airport multi-source security check data; performing security check data preliminary analysis according to the airport multi-source security check data to obtain security check characteristic sequence data; performing behavior mutation feature association according to the security check characteristic sequence data to obtain security check mutation feature association data, and performing cross-modal feature association according to the security check characteristic sequence data to obtain security check cross-modal feature association data; performing mutation behavior threat level evaluation according to the security check mutation feature associated data to obtain first security check danger data, and performing cross-modal threat level evaluation according to the security check cross-modal feature associated data to obtain second security check danger data; and performing security check decision-making auxiliary operation according to the first security check danger data and the second security check danger data. According to the invention, through quantitative threat and intelligent decision support, the intelligent level and efficiency of airport security check are greatly improved.

The invention discloses an airport aircraft variable anti-collision protection area construction early warning method and system and electronic equipment. The method comprises the steps that S1, a multi-level anti-collision protection area basic standard model of an aircraft is constructed in an airport map model; s2, collecting motion sequence data of the aircraft in a time period t1 before the current moment, and inputting the motion sequence data into the LSTM data prediction model to predict motion sequence data of the aircraft in a time period t2 after the current moment; s3, extracting motion sequence data of the time period t1 to adjust the sizes of the emergency collision avoidance area, the early warning monitoring area and the adjacent risk area; collecting the vehicle speed in the vehicle motion sequence data and the speed and course data in the motion sequence data in the time period t2 to calculate the relative distance and the relative speed of the vehicle and the aircraft; and S4, the anti-collision early warning system judges and predicts whether falling into an adjacent risk area, an early warning monitoring area and an emergency collision avoidance area. According to the method, prospective anti-collision technical analysis is realized, and the airport safety operation margin is improved.

The invention discloses an airport security check security situation awareness method and system based on deep learning, and relates to the technical field of image processing.The airport security check security situation awareness method comprises the steps that a first passenger picture matrix and a luggage picture set are constructed by collecting a continuous picture set and luggage pictures of passing airport security check passengers; dividing the first passenger picture matrix into a training matrix and a test matrix, and dividing the luggage picture set into a training set and a test set; setting a corresponding label matrix and a label set; training, testing and optimizing the CL network model and the CNN neural network model to obtain a final CL network model and a final CNN neural network model; respectively transmitting a passenger picture set and a luggage picture which are collected in real time to the final CL network model and the final CNN convolutional neural network model to obtain a security situation result and make a decision; and substituting the characteristics of the real-time abnormal passenger into the trained final recurrent neural network prediction model to obtain the safety situation of the real-time abnormal passenger, and making a decision.

The invention relates to a gate control method and device for an airport security check channel, equipment and a medium. The method comprises the steps of obtaining a current passenger inflow rate, a current passenger outflow rate, a gate change factor, a personnel change factor and a passenger satisfaction degree of an airport security check channel gate, determining a gate admission rate and a gate exit rate according to the data, obtaining a time interval of successive gate opening of the gate, and controlling the gate to execute corresponding operation. By adopting the method, the opening and closing speed of the gate can be dynamically adjusted, so that the visitor flow in the airport security check channel is controlled, and the high-efficiency management of the security check channel is realized.

The invention discloses an acousto-optic directional denial strategy system and method for airport safety, and relates to the technical field of bird repellency, an acousto-optic collaborative directional denial system is formed, sensors of different types are installed in the system, bird scales are classified, different acousto-optic frequency ranges are set for different bird scales, and therefore the bird repellency is improved. Marking danger levels, and constructing a four-dimensional expelling strategy library; giving different weights for different state data, and fusing different bird state data according to the weights to obtain a bird stress resistance index; the bird stress resistance index is judged through the repelling threshold value, and different repelling strategies are selected; setting an unpredictable time sequence modulation mechanism in a selected expelling strategy frequency range, and dynamically adjusting an acousto-optic emission time sequence and a sound wave frequency; counting the bird repelling failure rate, measuring the bird escape time during each repelling, calculating the resistance inhibition coefficient, judging the resistance inhibition coefficient, and updating the four-dimensional repelling strategy library.

The invention discloses a personnel training management system based on airport safety management, relates to the technical field of personnel training management, and solves the problems of low training efficiency, low pertinence and difficulty in quantitative evaluation of effects in the prior art. The method comprises the steps of obtaining training data related to airport safety management; constructing a knowledge graph based on the training data; obtaining the training content of the trainee based on the knowledge graph; the method comprises the following steps: acquiring training content of a corresponding post from a knowledge graph according to the post of a trainee and the responsibility of the corresponding post; the method comprises the steps of obtaining three-dimensional data of an airport management area; constructing a virtual reality three-dimensional model of the airport based on the three-dimensional data Performing analogue simulation assessment on the trainee based on the virtual reality three-dimensional model of the airport, and recording learning data of the trainee in real time in the assessment process; the training evaluation coefficient of the trainee is calculated through the learning data; and judging whether training is qualified or not based on the training evaluation coefficient and a preset threshold. The problem is solved.

The present invention relates to the technical field of airport security, and discloses a FOD recognition system and method based on machine vision. The system includes a multi-spectral image acquisition module, a dynamic environment adaptive preprocessing module, a multi-attention feature extraction module, a multi-modal data fusion module, a multi-level verification and decision-making module, and a real-time alarm and closed-loop control module. By acquiring pavement data through multi-modal image acquisition, after preprocessing, feature extraction and fusion, multi-level verification and decision-making are carried out to detect foreign objects, and finally real-time alarm and removal are realized. This system can effectively overcome the interference of complex environments, accurately identify foreign objects, process them quickly, improve the safety and operation efficiency of airport pavements, and has the advantages of high recognition accuracy, strong adaptability, good reliability, etc.

The invention discloses a method for monitoring tail gas emission of an aircraft refueling vehicle, and solves the problem that PM quantitative data acquisition is inaccurate in a complex environment of an airport. The method comprises the following steps: stably sampling and removing aviation kerosene steam through a sampling probe integrating sensing and flow guide adjustment; synchronously detecting and deducting background gas interference; performing secondary dehumidification and constant-temperature pretreatment on the tail gas; the double detection units are linked to collect multi-dimensional data, and a nonlinear interference correction model is constructed through fusion; and adopting an exclusive calibration mode and marking invalid data. The method further comprises the design of wind speed adaptation, condensation backflow prevention, working condition and area label optimization, double-link encryption transmission, safe installation, optical signal compensation, graded maintenance and the like. The method can resist multiple environmental interferences, PM detection errors are controllable, data updating is efficient, and airport safety operation and compliance monitoring requirements are met.

The invention discloses an airport intelligent laser bird repelling system and method based on multi-sensor fusion, and relates to the technical field of airport safety protection, and the system comprises a flying bird coarse positioning module, a flying bird fine tracking module, a flying bird laser repelling module and a remote monitoring module. The flying bird coarse positioning module adopts a phased array millimeter wave radar to carry out wide area scanning on a designated area of an airport, and outputs coarse positioning coordinates of a flying bird. Then, the bird fine tracking module uses a laser scanning radar and a medium-wave infrared camera to cooperatively carry out high-precision tracking scanning on the bird in the target area, and outputs the three-dimensional coordinate of the bird in real time. The remote monitoring module displays an airport area map and a bird infrared image on an indoor console in real time, and provides a manual control interface for an operator at the same time. And finally, the bird laser repelling module controls a high-energy laser transmitter of the bird repelling machine to output a high-energy pulse laser beam to a bird body according to the three-dimensional coordinates of the bird, and the bird in the target area is accurately repelled.

The invention provides a civil aviation airport obstacle real-time detection method and system based on a visual scheme, and belongs to the technical field of civil aviation airport safety monitoring, and the method comprises the steps: obtaining multi-source sensing data in real time, including distance data of a millimeter wave radar, and image contrast data and humidity data of a visible light camera unit; a radar weight coefficient Wr and an image weight coefficient Wi are calculated based on the humidity data, Wr is in positive correlation with the humidity value, and Wi is in negative correlation with the humidity value; fusing the distance data, the image contrast data and the weight coefficient to calculate a real-time visibility value, and limiting the visibility value within a preset effective range; switching a neural network quantization mode according to the visibility value; and when the visibility value is greater than a first preset distance threshold value, activating a low-precision quantization mode and executing channel pruning. The problems of poor meteorological adaptability and unbalanced resource precision are solved.

The invention discloses an airport security check passenger flow prediction method, and relates to the technical field of airport passenger flow prediction. An SBC algorithm is combined with a heuristic iterative algorithm to obtain the passenger queuing time, and the time of arriving at a security check area is obtained; adopting a hierarchical clustering method to obtain each type of flight time period; and adopting an integrated learning algorithm based on a decision-making tree to fit the time distribution discrete points of arrival of the passengers in the security check area in each type of flight time period, obtaining the arrival distribution of the passengers, and completing the prediction of the security check passenger flow. According to the method, the difference between the security check time and the arrival time of passengers is considered, the time of arriving at the security check area is calculated to predict the passenger flow, and an optimization method combining an SBC algorithm of a non-stationary queuing theory and a heuristic iterative algorithm is provided to solve the time of arriving at the security check area. Flight time periods and passenger arrival distribution are clustered and fitted by adopting a hierarchical clustering method and an integrated learning algorithm based on a decision tree, and the accuracy of airport security check passenger flow prediction is effectively improved.

The invention provides an airport security check passenger flow volume prediction method and system, electronic equipment and a storage medium, and is applied to the technical field of airport security check. Target historical airport security check queuing data before target time is acquired; fusing the queue information of each target historical queue to obtain fused queue information of a target fused historical queue; performing empirical mode decomposition processing on fusion queue information of the target fusion historical queue to obtain a plurality of target data sequences and target residual components; determining a prediction model matched with the target data sequence, and performing airport security check passenger flow prediction according to the target data sequence or the target data sequence and the target residual component through the prediction model matched with the target data sequence to obtain a target prediction result; and determining the airport security check passenger flow volume corresponding to the target time according to each target prediction result, thereby being capable of adapting to unstable data, meeting actual requirements, and improving the accuracy of predicting the airport security check passenger flow volume at the same time.

The invention relates to the technical field of airport safety protection, and discloses an airport bird strike and unmanned aerial vehicle intrusion prevention integrated fusion method and system. The method comprises the following steps: acquiring dynamic image data, radar monitoring data and runway use state data of an airport surrounding area; generating bird flock and unmanned aerial vehicle activity characteristic parameters by using a preset model, generating a fusion risk coefficient through multi-source data fusion processing, and dividing early warning levels; a dynamic prevention strategy is generated in combination with the data, and a bird repelling device and unmanned aerial vehicle countering equipment are controlled; and collecting equipment operation feedback data, updating an early warning level and adjusting a prevention strategy. The system comprises a data acquisition module, an identification analysis module, a strategy generation module, an equipment control module and a feedback adjustment module. According to the invention, integrated fusion of bird strike and unmanned aerial vehicle intrusion prevention is realized, the risk is accurately evaluated, the airport safety guarantee capability is improved, and the air transportation safety is guaranteed.

The utility model discloses an ultra-narrow frame display for airport security check, which comprises a narrow frame display and an aluminum alloy shell, the narrow frame display is packaged in the aluminum alloy shell, an all-aluminum metal back machine is integrally welded on the back of the aluminum alloy shell, and an industrial mainboard is fixed in the all-aluminum metal back machine. According to the ultra-narrow frame display for airport security check, the installation side wall and the all-aluminum metal back machine are arranged, the ultra-narrow frame display can be used in cooperation with airport security check equipment, the display carries the industrial mainboard and is fixed to the aluminum alloy shell through the installation side wall, the industrial mainboard is fixed to the all-aluminum metal back machine, and the stability and the anti-interference capacity of the mainboard are greatly improved; and the risk of vibration and falling and the equipment maintenance cost caused by damage are reduced, and the problems of poor reliability and stability of the display in long-time operation are solved for airport security check which is frequently used and has extremely high equipment security requirements.

The invention belongs to the technical field of monitoring airport entrance guard alarm, and discloses an alarm device and method for reducing forced door opening of an airport entrance guard. The device comprises a widened aluminum plate and a Hall element sensor with an enlarged area, the area of Hall element sensing equipment in the electromagnetic lock is doubled, and the width of an aluminum plate in the U-shaped clamp is doubled, so that the situation that an internal open circuit is formed in the Hall element due to slight displacement of an iron block of the electromagnetic lock caused by excessive force when a front-end user closes a door is avoided, and the occurrence of forced door opening alarm is reduced. According to the method disclosed by the invention, the front-end colleague can utilize the saved time to deal with faults of other systems, and meanwhile, a user of an airport security department can better supervise the user, so that the user is prevented from illegally using the access control, and the occurrence of air defense safety accidents is reduced.

The invention belongs to the technical field of civil aviation safety management, and discloses a civil aviation hidden danger information safety monitoring method and system. The method comprises the following steps: acquiring a created security check list library through a PC management end, and acquiring and creating check lists and check list editing and maintaining operation instructions in a corresponding department / department space; the PC management end executes sending of an inspection list and management configuration, generates an inspection task according to a sending period of the management configuration, and pushes the inspection task to an inspection module of the APP inspection end; and obtaining a safety check task editing operation instruction in the check module, carrying out safety check on the existing hidden danger information, and visually showing the safety check condition. According to the invention, airport safety inspection work requirements can be met, a method for checking, processing and supervising inspected hidden dangers is provided, various hidden dangers can be recorded and concluded, and hidden danger problems which occur repeatedly can be sorted and publicized.

The invention discloses a fast opening and closing door which can be widely applied to multiple different occasions such as airport security check, industrial factory buildings, logistics channels and cold chain workshops and comprises a door frame assembly. A curtain piece driving assembly is arranged on the door frame assembly; the curtain piece driving assembly is connected with the curtain piece transmission assembly and used for driving the curtain piece transmission assembly to move in the vertical direction. A door body is arranged on the curtain piece transmission assembly; the door body comprises a plurality of curtain sheets; the curtain piece transmission assembly comprises two parallel synchronous belts, and the multiple curtain pieces are arranged on the two synchronous belts. A driving shaft in the curtain piece driving assembly is used for synchronously driving the two synchronous belts to rotate, and vertical opening and closing of the door body are achieved. The fast opening and closing door is reasonable in structure, fast in opening and closing, high in stability, high in reliability, capable of effectively improving the operation efficiency of goods or personnel channels, especially suitable for high-frequency and crowded scenes, and beneficial to achieving fast, safe and reliable personnel or material passing.