372 results about "Civil aviation" patented technology

The invention discloses a civil aviation airport ground guarantee resource scheduling method and device and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a real-time flight plan, and constructing a guarantee resource coupling network based on the real-time flight plan and a predefined guarantee flow rule base; performing conflict prediction and conflict influence analysis on the guarantee work of the future flight by traversing the guarantee resource coupling network, and generating a structured conflict early warning report; triggering an on-demand scheduling mechanism of a virtual resource pool for querying and allocating available resources on demand according to the structured conflict early warning report, querying available shared guarantee resources in the virtual resource pool, and generating a conflict resolution scheme which can be directly executed; and executing the conflict resolution scheme, monitoring an execution result through the Internet of Things data, feeding back the execution result to the guarantee resource coupling network, and calibrating a duration parameter in the guarantee resource coupling network. Through the constructed support resource coupling network, the prospective performance and the cooperative robustness of ground support scheduling are improved.

The invention provides a civil aviation pilot on-duty physiological early warning method based on LSTM and GBDT. The civil aviation pilot on-duty physiological early warning method comprises the following steps that S1, multi-source physiological data and associated information are collected; s2, data preprocessing and quality verification; s3, carrying out engineering construction on the physiological features and the associated features; s4, training and optimizing an anomaly recognition model; s5, carrying out real-time physiological anomaly recognition before attendance; s6, multi-level early warning triggering and information pushing are carried out; s7, performing early warning feedback and model iterative optimization; and S8, performing abnormal event tracing and data closed-loop updating. The limitation of a single model is overcome through multi-algorithm fusion, and the recognition accuracy in a complex scene is improved; a hierarchical early warning and closed loop optimization mechanism is established, safety guarantee and operation efficiency are considered, a standardized and landing technical scheme can be provided for civil aviation pilot health management system construction, and reduction of flight safety risks caused by physiological abnormalities is assisted.

The invention relates to the technical field of GPS interference source monitoring and troubleshooting, in particular to a civil aviation GPS interference source monitoring and troubleshooting method and system. The method comprises the following steps: acquiring track position data, attitude parameter data, GPS signal receiving data and interference detection performance parameters of a plurality of aircrafts, and establishing aircraft nodes and interference nodes; generating a common edge between any two aircraft nodes, generating a corresponding special edge between each interference node and the aircraft node within a preset influence radius, and constructing a space-time interference propagation topological graph at each moment; calculating an interference behavior characteristic parameter to obtain an interference behavior characteristic parameter vector, and calculating and outputting an interference behavior type identifier and an interference evolution trend vector corresponding to each interference node by using an interference behavior evolution trend inversion algorithm; and predicting an early warning interference source and generating an interference early warning result. According to the invention, real-time positioning, behavior identification and future influence range prediction of multiple types of interference sources in the civil aviation airspace are realized.

The invention relates to the technical field of passenger service, and discloses a construction method and device of a dynamic extension word bank, equipment and a medium. The method comprises the following steps: acquiring multi-source heterogeneous original knowledge data related to civil aviation passenger service, and converting the multi-source heterogeneous original knowledge data into a standard format text; processing the unstructured data in the standard format text based on the adaptive word segmentation model and the stop word list to obtain a plurality of candidate words; performing multi-dimensional corpus feature quantitative analysis on each candidate word to determine candidate keywords; and performing similarity calculation based on the entity word segmentation and the candidate keywords, determining effective candidate keywords, and adding the effective candidate keywords into the dynamic expansion word bank. By means of the method and device, the technical problems that in the prior art, a word bank used by a civil aviation service system is usually based on a static vocabulary or depends on manual compiling and updating, the static word bank cannot be updated in real time, the characteristics of the civil aviation field cannot be flexibly handled, and the maintenance cost is high due to manual updating and maintenance are solved.

The invention discloses a method and system for privacy data protection in a big data analysis process, and relates to the technical field of civil aviation data security and privacy protection, and the method comprises the steps: obtaining civil aviation multi-source heterogeneous data, extracting passenger identity features, travel track features and consumption behavior features, and generating a structured feature matrix; extracting an association relationship between fields through a convolutional neural network, calculating a field sensitivity initial value, generating a field sensitivity weight in combination with a field uniqueness index and the sensitivity initial value, and generating a privacy level mapping table containing the field sensitivity weight according to the sensitivity weight; calculating query sensitivity and a privacy budget parameter, generating a differential privacy noise parameter and a homomorphic encryption key, and generating a hierarchical protection strategy; performing noise injection and ciphertext conversion on the original data to generate a desensitized data set; passenger flow statistics is executed through secret state calculation, and a public analysis result is generated. Over protection of low-sensitivity data is avoided, and sufficient safety of high-sensitivity data is ensured.

The invention discloses a flight flow intelligent prediction and air traffic collaborative optimization system based on big data, and relates to the technical field of air traffic management. Comprising the steps that a data acquisition module acquires multi-source data from a civil aviation database and aligns the multi-source data to generate a fusion data matrix; the traffic prediction module extracts traffic feature vectors, generates a feature similarity matrix by calculating distribution differences, and generates a basic traffic prediction result based on migration prediction model parameters; the disturbance correction module detects a sudden disturbance event based on real-time weather and airspace state data and corrects a basic prediction result; the capacity adjusting module generates a capacity adjusting scheme when the capacity deviation value exceeds a threshold value according to the correction result and the airport operation capability data; and the collaborative optimization module finally generates a multi-airport collaborative scheduling scheme through a game equilibrium algorithm based on the correction result, the capacity scheme and the regional coordination data. According to the invention, the accuracy of flight flow prediction and the efficiency of multi-airport collaborative management are effectively improved.

The invention discloses a civil aviation risk cause network association analysis method based on a semantic enhancement model, and the method comprises the steps: building an EnhancedBertLdaModel model fusing BERT semantic representation and quality adaptive adjustment, and achieving the high-precision topic mining of a civil aviation risk event text; designing an improved Apriori algorithm which introduces a factor number adaptive threshold mechanism, and dynamically capturing a strong correlation cause rule; and constructing an optimized Logistic regression model and cause association network, quantifying risk contribution through multi-source feature fusion, and identifying a core risk path. According to the method, deep semantic analysis and dynamic rule mining are fused, civil aviation risk causes can be comprehensively identified, multi-source data features are fused, and contribution of the multi-source data features to the risk is quantified; by improving the algorithm, the analysis complexity is reduced, and the accuracy and stability of the result are improved, so that the purposes of precisely mining and quantifying civil aviation risk causes are achieved, and a scientific decision basis is provided for civil aviation safety management.

The invention provides a civil aviation fleet-oriented maintenance plan and work package integrated optimization method, which comprises the following steps of: firstly, taking minimization of total maintenance cost as a target function; constructing a mathematical planning model for integrated optimization of the fleet maintenance plan and the work package by taking a maintenance item number constraint, a maintenance item and maintenance work package corresponding relation constraint, a maintenance resource constraint, a maintenance interval constraint, a variable relation constraint, a variable value constraint and the like as constraint conditions; then, auxiliary variables are introduced to carry out linearization processing on the established mathematical programming model; and finally, solving the linearized mathematical programming model by adopting a differential evolution-adaptive large-scale neighborhood search two-stage heuristic algorithm, namely, continuously iteratively solving through a designed two-stage interaction strategy, so as to achieve the purpose of integrated optimization. According to the method, the dual goals of reducing the total maintenance cost and improving the maintenance scheme making efficiency are achieved, and a scientific solution is provided for the complex optimization problem in civil aviation maintenance management.

The invention provides an intelligent civil aircraft separated emergency flight data storage system facing flight accident scenes. The system collects multi-source data such as flight parameters, audios, videos and data links, carries out preprocessing and semantic modeling on the multi-source data, and extracts multi-modal feature information; multi-modal features are fused based on a modal perception attention mechanism and a diagnosis feedback readjustment mechanism, and intelligent diagnosis of a current flight state is realized in combination with a semantic consistency discrimination mechanism. When the flight state is judged to be abnormal or accident, starting a satellite communication channel to carry out remote emergency transmission on key data; and when the flight state is judged to be normal, performing modular hierarchical storage on the acquired data according to the data type. And the separated emergency data transmission subsystem is immediately started under the extreme conditions of power failure of the main system and the like. According to the method, strategies such as multi-mode intelligent diagnosis and multi-level storage are fused, and the flight data acquisition efficiency and the flight safety guarantee capability are remarkably improved.

The invention discloses a civil aviation element configuration optimization method based on mixed integer dynamic programming. The method comprises the following steps: S1, constructing a Chinese civil aviation core element and carbon emission spatial-temporal characteristic database; s2, establishing a mixed integer dynamic programming model with the purpose of minimizing the total cost of the system in the programming period; and S3, establishing decision variables, constraint conditions and a fusion solution algorithm framework required by the mixed integer dynamic programming model. And S4, based on the fusion solution algorithm framework, solving the mixed integer dynamic programming model by using a mathematical programming solver integrated with a robust optimization module so as to obtain a civil aviation core element dynamic configuration scheme which is optimal in total system cost in multiple periods in the future and meets the uncertainty scene. According to the method provided by the invention, a multi-source data fusion algorithm is optimized, a carbon emission measuring and calculating method is deepened, and solver parameters are adjusted, so that the collaborative requirements of improving the operation efficiency and reducing the carbon emission from the perspective of carbon cost are met.

The invention discloses an airborne environment monitoring and obstacle early warning system and an implementation method, and relates to the field of civil aviation auxiliary flight systems, the airborne environment monitoring and obstacle early warning system comprises hardware composition modules including a foresight sensing module, a lateral camera module, a millimeter wave radar system, an airborne computing platform, a cockpit display system and a positioning and attitude sensing module; the data synchronization and coordinate conversion module aligns all sensor data to an aircraft body coordinate system; the sensing algorithm module comprises a sensor data acquisition and preprocessing module, a feature extraction module, a coordinate conversion to BEV coordinate system module, a feature fusion module, a target detection module, an attitude correction module, an early warning logic module and a parameter configuration module; and the state adaptation module dynamically adjusts the perception strategy based on the flight stage. The method has the advantages that the sensing ability of the aircraft to the surrounding environment in the sliding and flying process is improved, a pilot is assisted in recognizing obstacles, and collision accidents are prevented.

The invention discloses an aircraft fire simulation and fire extinguishing rescue evaluation system, and belongs to the technical field of aircraft safety. The system comprises an aircraft parameter input module, a fire scene simulation calculation module, a fire extinguishing and rescue strategy deduction module, a multi-dimensional effect evaluation module and a result output and optimization suggestion module, and all the modules realize data interaction through standardized data interfaces. And a closed-loop system of parameter input, dynamic simulation, rescue deduction, quantitative evaluation and optimization feedback is formed. The method solves the problems of inaccurate fire simulation and lack of dynamic quantification of rescue evaluation of a traditional system, can realize accurate reproduction of aircraft fire scenes and scientific evaluation of rescue schemes, provides data support for emergency decision making, and is suitable for fire emergency disposal research of various aircrafts such as civil aviation airliners and freight aircrafts.

The invention discloses a hierarchical prediction method and system for civil aviation passenger transport demands based on multi-source heterogeneous data, and the method comprises the steps: constructing a civil aviation passenger transport demand driving feature library, and constructing the civil aviation passenger transport demand driving feature library according to hierarchical items and upper and lower hierarchies of hierarchical feature items; constructing a civil aviation passenger transport demand level combination prediction model comprising a plurality of level item prediction sub-models; extracting causal association time series data taking daily passenger flow as a dependent variable and hierarchical feature item data as an independent variable in the historical feature data subset, and inputting the causal association time series data into a hierarchical item prediction sub-model for feature time series data prediction training; and the civil aviation passenger transport demand level combination prediction model sequentially outputs daily passenger flow volume corresponding to each level from bottom to top according to the level items. According to the method, daily passenger flow prediction according to multiple attribution levels of airlines, airports, cities and countries is realized, passenger flow demand data from macroscopic to microscopic linkage constraints can be obtained, and hierarchical rich data is provided for civil aviation management parties so as to improve the guarantee service capability.

The invention discloses a civil aviation passenger-oriented cross-institution privacy protection portrait fusion method and system, and the method comprises the steps: obtaining stored original passenger data from at least two aviation institutions, the original passenger data comprising passenger basic attributes, flight transaction records, travel track sequences and terminal and behavior preference information; privacy protection processing is carried out on the original passenger data of each aviation institution, and the privacy protection processing comprises differential privacy processing and k-anonymization processing, so that a local desensitization data set corresponding to each aviation institution is generated; a neutral cooperation platform including a trusted execution environment and a block chain account book is constructed, the trusted execution environment provides a secure enclave, and the block chain account book is used for recording a model exchange event. According to the method and the system, on the premise of strictly protecting data privacy and security, efficient and credible fusion and collaborative mining of passenger portraits across aviation institutions are realized.

The invention discloses a civil aviation fleet maintenance decision-making method based on multi-body distributed hierarchical reinforcement learning, and the method comprises the steps: constructing a civil aviation fleet maintenance decision-making environment through fleet parametric modeling, and simulating a multi-aircraft multi-task scheduling and maintenance process in real operation; and key factors such as equipment degradation, maintenance resource constraint and task execution priority are fully considered. In the environment, a distributed hierarchical reinforcement learning algorithm is adopted: an upper-layer strategy is used for global maintenance resource allocation and task coordination, and a lower-layer strategy is used for local maintenance actions of a specific body. According to the method, a shared communication mechanism and a reward structure are introduced among multiple agents, so that the cooperation efficiency is improved, and the training convergence is accelerated. Experimental results show that the method is remarkably superior to a traditional heuristic method and a standard reinforcement learning algorithm in the aspects of task completion rate, maintenance cost control and system robustness, and high efficiency and reliability of civil aviation team maintenance are achieved.

The invention relates to the technical field of civil aircraft maintenance and repair, in particular to a flap health state prediction method based on transferable trend grouping autocorrelation comparative learning, which comprises the following steps of: firstly, mining a typical degradation trend from total data by utilizing a clustering algorithm; dividing the individual samples with differentiation into a plurality of trend data groups with high consistency; secondly, introducing an autocorrelation comparison mechanism into each group, capturing common time sequence dependence crossing a long period among samples, and constructing a plurality of pre-training models capable of representing a specific decline mode; then, dynamic matching is carried out according to the characteristics of the flap to be detected, and the most adaptive trend category and the pre-training model are selected; and finally, on the basis of a migration fine tuning strategy, a small amount of data is used for carrying out directional fine tuning on the pre-trained model, so that an exclusive prediction model of the flap is efficiently obtained, compared with the prior art, a model does not need to be built for each aircraft from zero, migration can be carried out on the basis of a limited model library, and effective management of the health state of the civil aircraft is achieved.

The utility model provides civil aviation security video monitoring equipment convenient to install, which belongs to the technical field of monitoring equipment and comprises an installation seat, a connecting assembly is fixedly installed in the center of the upper surface of the installation seat, a stand column is installed on the connecting assembly, and a camera body is installed at the top of the stand column through an installation assembly. According to the utility model, through the arrangement of the connecting assembly, when the camera body is installed, the installation seat is fixedly installed at the position where the camera body needs to be installed, then the locking bolt is screwed upwards, the locking bolt drives the limiting block to move upwards, then the stand column is grabbed and lifted upwards, and the pin shaft on the stand column slides upwards along the sliding groove, so that the camera body is installed. The vertical column is rotated along the direction of the open slot through the pin shaft until the horizontal height of the bottom of the vertical column is equal to the horizontal height of the bottom of the open slot, so that the vertical column is positioned in the open slot in an inclined manner, and then the camera body is mounted at the bottom of the vertical column through the mounting assembly; and the camera body can be installed at a high position without climbing.

This invention provides a cutting machine for processing civil aircraft parts, belonging to the field of laser cutting equipment technology. It includes a laser cutting table, a gantry frame one, and a gantry frame two. The key feature is that the gantry frame one is equipped with a parts loading / unloading component, which includes an articulated robot, a support frame, and several funnel-shaped silicone discs. It also includes an orientation control component, which comprises several guide frames movable within the support frame and an adjustable unit for moving the guide frames. The silicone discs are installed under the guide frames. A detection component is installed between the guide frames and the silicone discs to detect the load at the lower end of the silicone discs. This invention, through the installation of the parts loading / unloading component, achieves self-loading and unloading of sheet metal, greatly reducing labor intensity and improving processing efficiency. Adjusting the orientation of each silicone disc allows the parts loading / unloading component to lift sheet metal of various specifications.

This invention discloses an automatic generation and evaluation method for airborne system signal monitoring voting strategies, comprising: Step 1, matching at least one pre-selected monitoring voting strategy from a monitoring voting algorithm simulation model library based on the attribute characteristics of the input signal; Step 2, evaluating whether the security of processing the input signal using the monitoring voting strategy meets the security target requirements of the voting value based on the signal availability data and signal integrity data of the input signal, and the matched monitoring voting strategy, thereby obtaining a recommended monitoring voting strategy; wherein, the monitoring voting algorithm simulation model library is pre-configured and includes multiple simulation models, with different simulation models representing different monitoring voting algorithms. The technical solution provided by this invention solves the problem that traditional monitoring voting strategies are no longer suitable for the rapid iteration and process assurance processes of civil aviation R&D.

The invention provides a civil aviation product airworthiness conformity inspection system and method based on artificial intelligence. Auxiliary inspection can be carried out before an airworthiness conformity inspection engineer carries out inspection. The system comprises a classification module used for obtaining different types of airworthiness conformity verification reports and determining the types of the airworthiness conformity verification reports according to the report names of the airworthiness conformity verification reports; the checking module is used for inputting the airworthiness conformity verification report into a corresponding report checking model according to the category, the report checking model carries out comparative analysis on the text content of the airworthiness conformity verification report and the airworthiness conformity report compilation standard corresponding to the category based on the artificial intelligence technology, and a conformity checking result is output, the category of each airworthiness conformity verification report corresponds to one report inspection model; and the conclusion output module is used for receiving the conformity check result and outputting the conformity check result according to the structured statement to form a check result document.

The application discloses a kind of multi-mode multi-dangerous point's acceleration task test flight spectrum compilation method and system considering, belong to aero-engine acceleration task test flight spectrum technical field, comprising: the stress and temperature distribution of acquisition component under different load, working condition;Select the key characteristics of multiple component operation Check point as potential dangerous point for analysis;The fatigue and creep damage of each check point selected is calculated and evaluated respectively;Statistical analysis of the speed change rate distribution characteristics in long-term life test flight spectrum, determine the slow car state to maximum state switching rate;Compare the damage values of different failure modes of each check point;The multi-mode multi-dangerous point's acceleration task test flight spectrum compilation method and system considering, it is suitable for most military or civilian aero-engine acceleration task test flight spectrum compilation, can accurately reflect the damage state of component in actual service process, provides strong support for the optimization of acceleration task test flight spectrum.

The invention provides a civil aviation data processing system and method and electronic equipment, and the system comprises a data collection module which is used for obtaining various civil aviation operation data; the flight planning module is used for determining a flight plan based on the real-time operation data; the simulation operation module is used for calculating operation index data according to the historical operation data and the flight plan; the analysis module is used for generating an operation index increment corresponding to the operation index data and calculating a total state increment based on the operation index increment; and the feedback optimization module is used for controlling the analysis module to update the total state increment based on the operation index increment when the total state increment does not meet the preset threshold range, so that the updated total state increment meets the preset threshold range. According to the method, data fusion and linkage processing in multiple business fields are realized, information islands are eliminated, cross-department data sharing and business collaboration are realized, the total state increment can be automatically iteratively updated, and the timeliness and accuracy of civil aviation data processing are improved.

The invention relates to the technical field of air traffic control, in particular to a multi-mode fusion real-time intelligent monitoring system for air traffic control command. According to the method, a three-dimensional intelligent analysis system of interface situation analysis-voice instruction recognition and understanding-air traffic control information fusion is constructed, and a safety monitoring closed loop of an air traffic control command whole process is realized on the premise that an existing system architecture is not changed; and real-time deduction and risk early warning of the airspace security situation are realized. The generated early warning information is synchronously pushed to a radar controller, an assistant controller and a main controller in a standardized visual and audio coding form through a newly-added safety information prompting module, a three-in-one cooperative cognitive space is constructed, the problem of information asymmetry among multiple seats and multiple on-duty roles in a traditional mode is effectively solved, and the safety of the system is improved. And important technical guarantee is provided for safe operation of civil and aviation pipes.

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 relates to the technical field of rotor shaft repairing, and discloses a rotor shaft repairing device for civil aviation maintenance and a laser cladding repairing method. The rotor shaft repairing device for civil aviation maintenance comprises a clamping mechanism, the clamping mechanism comprises a moving assembly and a supporting assembly, and the moving assembly is arranged on a rack and can move in the length direction of the rack; the supporting assembly is arranged on the moving assembly and used for supporting the rotor shaft. In the moving process of the moving assembly, the supporting assembly abuts against the surface of the rotor shaft all the time. The laser cladding repair method comprises the following steps: step 300, judging whether the distance between the repaired part of the rotor shaft and the end part of the diameter shaft section meets a first preset distance or not; and if yes, the clamping mechanism is moved to the to-be-repaired shaft section, and if not, the clamping mechanism is moved to the adjacent shaft section, and a second preset distance is kept. According to the technical scheme, the technical problem that geometric interference or function failure exists in the shaft shoulder position of a rotor shaft repairing device in the prior art is solved.

This invention provides a method, electronic device, and storage medium for generating knowledge graphs in the civil aviation field based on a caching mechanism, relating to the field of knowledge graph generation technology. The method includes: obtaining the historical knowledge graph set RA corresponding to the target user ID; obtaining the maximum similarity RX between the target task and the historical task corresponding to each historical knowledge graph in RA. max If RX max >RY, then RX max The corresponding historical knowledge graph is determined as the initial knowledge graph of the target task corresponding to the target user ID; the target knowledge graph corresponding to the target user ID is generated; the cache lifespan of the knowledge graphs corresponding to the historical tasks of the same type as the target task in the historical knowledge graph library is adjusted according to the execution frequency, execution time and execution quality of the target task and each historical task of the same type as the target task; the present invention can improve the overall response speed and data timeliness of knowledge graph generation.

The application belongs to the field of civil aviation logistics application, and specifically discloses an electric tilting driving device and an electric tilting system, wherein the electric tilting driving device comprises a driving tilting support, a guide plate rotatably connected to the driving tilting support, and a driving assembly for driving the guide plate to rotate, and a guide groove is formed in the guide plate; the guide groove is closed in the circumferential direction, and the guide groove comprises a middle guide part, a tilting guide part and a limiting guide part; the guide wheels are two and are arranged to control the guide plate to deflect in different directions, respectively, the rotation axis of the shift fork and the rotation axis of the guide plate are parallel and located in the same vertical plane, and the movement track of the guide wheels revolving around the rotation axis of the shift fork and the movement track of the tilting guide part revolving around the rotation axis of the guide plate have overlapping parts. By adopting the scheme, the problems of the existing electric tilting device, such as inflexible tilting or return, jamming and blocking, can be solved.

The invention provides an airport severe convective cloud evolution monitoring method and system based on stationary satellite multispectral characteristics, and relates to the technical field of civil aviation meteorological monitoring and early warning, and the method comprises the steps: obtaining multispectral remote sensing data of an airport monitored by a stationary satellite in real time and in a preset range; performing radiometric calibration and geometric calibration on the multispectral remote sensing data to obtain a calibrated multispectral image; extracting visible light reflectivity and infrared brightness temperature based on the calibrated multispectral image, and generating gridding feature data through spatial resampling; and based on the gridding feature data, performing semantic segmentation by adopting a full convolutional neural network integrating spatial pyramid pooling and dense up-sampling convolution so as to identify and locate a target cloud cluster with strong convection features. According to the invention, the severe convective cloud cluster is identified based on the stationary satellite data, after topographic correction and evolution prediction, graded early warning is generated in real time by fusing the airport operation state, a full-chain monitoring early warning technology is formed, and the meteorological safety guarantee capability of the airport is improved.

The utility model relates to the technical field of civil aviation equipment, in particular to a connecting device of a boarding bridge airport pickup port, which comprises a connecting pull rod and a safety pull rod, the first end of the safety pull rod is connected with an upper connecting plate, and the second end of the safety pull rod is connected with a top plate through a limiting plate; the limiting plate is arranged on the top plate, a through hole is formed in the limiting plate, the second end of the safety pull rod penetrates through the through hole and extends to the side, away from the boarding bridge, of the limiting plate, a limiting block is arranged at the second end of the safety pull rod, the size of the limiting block is larger than that of the through hole, and the limiting block and the limiting plate are arranged at intervals. The safety pull rod is not stressed in the normal working process of the airport pickup port, once the connecting pull rod is broken, the limiting block can prevent the second end of the safety pull rod from disengaging from the through hole of the limiting plate, then when the connecting pull rod is broken, connecting force is provided for the airport pickup port and the connecting port, and the problem that the airport pickup port falls off due to breakage of the connecting pull rod is solved. And the safety of the boarding bridge arrival gate is improved.

The invention discloses a method for predicting civil aviation carbon emission based on civil aviation core element configuration. The method comprises the following steps: S1, constructing a Chinese civil aviation development scene in a predetermined time period; s2, solving spatial-temporal evolution configuration of civil aviation core elements in the predetermined time period under different scenes based on the Chinese civil aviation development scene in the predetermined time period; s3, on the basis of the civil aviation core element configuration result, civil aviation CO2 emissions under different scenes are measured and calculated through a bottom-up method, and the emission peak level and time are determined; and S4, comparing the element configuration and emission results of different scenes, and analyzing the application effect of the carbon emission reduction means. Through coupling of scene analysis and a decision support system, collaborative prediction of element configuration and carbon emission is realized. According to the embodiment of the invention, a technical method for deeply coupling core element configuration, multi-scenario analysis and carbon emission prediction can be constructed, so that the prediction accuracy of civil aviation carbon emission can be effectively improved.