323 results about "Aircraft maintenance" patented technology

The invention discloses an ACM data analysis method and a data monitoring system, and belongs to the technical field of aircraft maintenance, and the method comprises the steps: constructing an ACM data set, setting a feature engineering processing method, carrying out coupling feature extraction through setting a dynamic window and calculating a dynamic correlation coefficient, dividing working conditions, eliminating fluctuation interference, and generating a structured time series data set; the method comprises the steps of obtaining ACM reference data of aircrafts of the same model, setting a reference fault judgment method, judging latest data in a structured time sequence data set, screening abnormal parameters, judging whether the ACM breaks down or not by combining an actual temperature adjusting effect, reducing single-parameter misjudgment, setting a coupling fault positioning method, diagnosing the faulty ACM, and distinguishing true faults and false anomalies. Meanwhile, a prediction scheduling method is set, fault prediction, health state prediction and service life evaluation are carried out on the fault-free ACM, the probability of sudden faults is reduced, and non-planned flight stopping is reduced.

The invention discloses grinding equipment with a surface self-adaption function for civil aircraft maintenance, and relates to the technical field of grinding equipment, the grinding equipment comprises a grinding mechanism, a self-adaption mechanism and a positioning mechanism, the grinding mechanism is fixedly connected with the self-adaption mechanism, and the self-adaption mechanism is fixedly connected with the positioning mechanism. The grinding mechanism is used for driving a grinding disc to work, and flexible grinding of the surfaces of different areas can be achieved. The self-adaptive mechanism is composed of a self-adaptive assembly, an expanding and contracting assembly and a rotating assembly, the grinding disc has the flexible adjusting capacity when making contact with the surface of a workpiece, the expanding and contracting assembly achieves expanding and contracting, the rotating assembly drives an expanding and contracting block to revolve, and therefore the adaptability of the grinding disc on the complex curved surface is guaranteed. And the positioning mechanism is used for positioning parts needing to be maintained, so that the purposes of adapting to complex curved surfaces, improving the polishing precision and efficiency, avoiding the problem of difficult attachment and ensuring the maintenance quality and the operation safety are achieved.

The invention discloses an aircraft maintenance knowledge management and intelligent recommendation method based on a knowledge graph, and the method comprises the following steps: carrying out the multi-source collection of aircraft maintenance data, and carrying out the classification and coding of the maintenance data, extracting an entity and a type thereof by using a domain self-adaptive entity recognition model according to a splicing vector spliced by the classified coding data; constructing an entity co-occurrence graph according to the entities, performing relation extraction, attribute extraction and logic generation according to the entity co-occurrence graph, and constructing a knowledge graph according to the entities, the entity types, the entity relations, the entity attributes and the entity logic; aircraft fault problems, environmental conditions and maintenance preferences are manually input, and an aircraft fault maintenance scheme is intelligently recommended according to manual input and the knowledge graph; and carrying out resource conflict detection according to the recommended aircraft fault maintenance scheme, and regularly updating the knowledge graph. According to the intelligent maintenance recommendation method provided by the invention, the knowledge graph composed of multi-source maintenance data and multi-factor training are provided, and the accuracy of intelligent recommendation is improved.

The invention relates to a damage assessment method and device for a composite material structure and electronic equipment, and relates to the technical field of aircraft maintenance, and the method comprises the steps: obtaining an aircraft typical structure operation and maintenance database and an actual service environment database; extracting structure damage characteristics from the aircraft typical structure operation and maintenance database, and extracting service environment factor data of the aircraft from the actual service environment database; performing clustering analysis on the extracted service environment factor data to obtain a clustering analysis result, and performing correlation analysis on the extracted structure damage features and the clustering analysis result to obtain a correlation analysis result; and based on the correlation analysis result, constructing an evaluation index system, and performing damage evaluation on the composite material structure of the aircraft by using the evaluation index system. According to the scheme, various environmental factors and structural damage characteristics can be comprehensively considered, the service reliability and safety of the structure are evaluated more accurately, a more reliable basis is provided for structure maintenance decision, and potential risks for flight safety are reduced.

The invention belongs to the field of automatic testing, and particularly relates to an automatic testing system and method for aviation fly-by-wire flight control equipment, and the system comprises a system self-inspection unit, a system resource unit, a system interface adaption unit, and a system testing control unit. And the system self-checking unit controls the automatic test system to execute a self-checking function through operation software. The test efficiency and the test coverage rate can be remarkably improved, the problem of function test omission can be effectively solved, the fault of the tested airborne avionics equipment is analyzed by adding the YMECA fault analysis module and combining the definition event and the structure function of the fault tree, qualitative analysis is carried out on the fault, a professional basis is provided for fault diagnosis, the maintenance difficulty is reduced, and the test efficiency is improved. The aircraft maintenance guarantee efficiency is improved, and joint test of a plurality of airborne avionics devices and parallel test of a plurality of airborne avionics devices of the same model in a fly-by-wire flight control system of a certain type of fighter can be realized.

The invention relates to a composite material structure damage probability assessment method and device and electronic equipment, and relates to the technical field of aircraft maintenance, and the method comprises the steps: obtaining the structure influence factor data of a to-be-assessed composite material structure; inputting the structure influence factor data into the trained random forest model, and performing damage probability evaluation processing on the to-be-evaluated composite material structure through all decision trees in the random forest model to generate an evaluation result; the evaluation results are subjected to voting processing, the evaluation result with the maximum voting number serves as a predicted structure damage evaluation result of the composite material structure to be evaluated, and the predicted structure damage evaluation result at least comprises slight damage, moderate damage and serious damage. According to the scheme, the limitation of a traditional method in the absence of sensor data is effectively overcome, and the damage prediction requirement under the condition of no sensor data or incomplete data is met.

The invention belongs to the field of aircraft maintenance, and particularly relates to a comprehensive maintenance management system for on-condition maintenance of an aero-engine. The system comprises a database used for storing historical data of an engine; the PHM module is used for generating engine state evaluation according to the engine state information and engine historical data; the RCM module is used for generating preventive maintenance suggestions according to historical data of the engine; the maintenance management unit is used for generating a maintenance decision according to engine historical data, engine state evaluation and preventive maintenance suggestions; the IETM module is used for calling a maintenance program or a troubleshooting program according to the maintenance decision, and is also used for generating maintenance resume information according to an engine maintenance result; the guarantee resource management module is used for generating guarantee resource information according to the maintenance decision; and the maintenance management unit is also used for generating maintenance evaluation information according to the maintenance decision, the maintenance resume information and the guarantee resource information, and updating historical data of the engine.

The invention discloses an aircraft surface damage three-dimensional positioning method, device and equipment, a medium and a product, and relates to the technical field of damage detection. The method comprises the steps of determining a damage detection result according to a target image based on a damage detection model; determining a three-dimensional coordinate of the damage point in a camera coordinate system by adopting a binocular vision positioning algorithm based on a pixel coordinate of a center point of a damage area contained in a damage detection result; based on the relative pose relation between the binocular camera and the aircraft, according to the three-dimensional coordinates of the damage point in the camera coordinate system, determining the three-dimensional coordinates of the damage point in the aircraft body coordinate system; and mapping the three-dimensional coordinates of the damage point in the aircraft body coordinate system to a three-dimensional point cloud model of the aircraft, and carrying out visualization processing to obtain a visualization display result. The invention aims to accurately determine the position of the damage on the aircraft body and improve the aircraft maintenance efficiency.

The invention relates to the technical field of aircraft maintenance, and particularly discloses a guide supporting structure for replacing large components of an aircraft. The longitudinal supporting seat can be movably arranged on the vehicle body in the horizontal direction; the linkage operation adjusting mechanism is arranged on the side wall of the longitudinal supporting seat and is used for providing two independent transmission powers with variable speeds for the longitudinal supporting seat; the lifting mechanism can be movably arranged on the longitudinal supporting seat in a sleeving mode in a lifting mode, the lifting mechanism is further provided with a rotatable retainer, the retainer is used for fixing an aircraft landing gear in a disassembly and assembly state, and lifting power of the lifting mechanism and rotating power of the retainer both come from the longitudinal supporting seat. According to the invention, multi-degree-of-freedom adjustment in a limited space is realized, and meanwhile, a guide supporting structure with high positioning precision and operation convenience is taken into account, so that the safety and efficiency of replacement operation of large components of an aircraft are improved.

A method for aircraft maintenance scheduling includes using a scheduling environment as a reinforcement learning (RL) environment to simulate an operational concept, train an RL agent, and generate aircraft maintenance decisions and explanations; providing a decomposed reward Deep Q-Network (drDQN) algorithm, wherein the drDQN algorithm includes a first Deep Q-Network (DQN) and a second DQN; using the first DQN to maximize a mission accomplishment objective; using the second DQN to minimize a maintenance cost objective; providing a trained drDQN agent; using the trained drDQN agent to obtain the aircraft maintenance decisions and corresponding mission accomplishment and maintenance cost rewards; using a scheduling module to arrange aircraft maintenance activities; and using an explainable module to get reasons to detail why the decisions are made and present tradeoffs between the decisions and non-selected alternatives.

The invention belongs to the technical field of aircraft maintenance, and particularly discloses aircraft maintenance belly skin dismounting and mounting equipment which comprises supporting levers arranged in pairs and moving wheels on the lower portions of the supporting levers, the two supporting levers are connected together through a plurality of bidirectional hydraulic rods, the bidirectional hydraulic rods are fixed to a middle lever, and telescopic hydraulic cylinders are arranged on the lower wall of the middle lever in an array mode. The lower end of the telescopic hydraulic cylinder is provided with a vacuum suction cup, supporting rods are arranged on the upper wall of the supporting lever in an array mode, the upper ends of the supporting rods are connected together through a transverse lever, lifting assemblies are arranged on the supporting lever and the transverse lever, self-matching adjusting assemblies are arranged on the lifting assemblies, and an automatic contour adapting assembly is arranged between every two opposite self-matching adjusting assemblies. The connecting blocks are sequentially connected through the curable connecting assemblies to form a chain-shaped structure, the chain-shaped structure is automatically attached to the surface of the airplane belly skin according to the shape of the airplane belly skin, fixing of the positions of the connecting blocks is automatically completed, and deformation of the airplane belly skin in the hoisting process is avoided.

The invention relates to the technical field of composite material digital detection, in particular to a composite material skin grinding amount calculation method based on clustering analysis and a symbolic distance field, which specifically comprises the following steps: acquiring three-dimensional measurement data of the surface of a composite material skin, and designing a three-dimensional measurement point feature descriptor; based on the feature descriptors, a clustering analysis algorithm is designed, and a grinding area three-dimensional measuring point class and a non-grinding area three-dimensional measuring point class are divided; aiming at the three-dimensional measuring points of the non-grinding area, carrying out implicit curved surface reconstruction based on a radial basis function; aiming at the three-dimensional measuring point of the grinding area, a grinding area symbol distance field is constructed, and the symbol distance is the grinding amount of the measuring point; according to the method, the problem that in the prior art, profile tolerance estimation cannot be obtained during aircraft CAD mathematical model is solved, the grinding allowance of the aircraft skin repairing area can be accurately analyzed, and aircraft maintenance personnel are guided to conduct grinding. Compared with a traditional method for judging the profile tolerance based on manual touch, the method has the advantages that interference of human subjective factors is eliminated, the grinding allowance is quantified, and the precision is higher.

The invention relates to the technical field of aircraft health management, and discloses a system and a method for realizing aircraft health management. The method comprises the following steps: acquiring health data of each monitoring point on an aircraft and state information of each ground processing node; processing based on the data and information to obtain a target monitoring point cluster of each ground processing node; then health data sent by the target monitoring point cluster is subjected to preprocessing configuration, and cluster health data of all ground processing nodes are gathered after preprocessing and uploaded to a health database to-be-stored interface; and finally, synchronously acquiring operation data of each storage interface through a to-be-stored interface of the health database for analysis, and performing distributed storage management on the cluster health data. The method can provide a scientific basis for aircraft maintenance, effectively improves the safety, reliability and operation efficiency of the aircraft, reduces the operation cost, and has an important application value in the field of aircraft health management.

The invention provides a training method of an aircraft maintenance simulation model and an aircraft maintenance simulation method, relates to the technical field of aircraft maintenance simulation, and aims to predict future evolution of aircraft maintenance so as to improve authenticity of aircraft maintenance simulation. The method comprises the following steps: acquiring training data related to maintenance simulation; training a maintenance simulation model based on the training data; the aircraft maintenance simulation model comprises a video word segmentation device, a multi-modal input encoder, a multi-modal token sequence and a multi-modal output encoder, wherein the video word segmentation device is used for encoding videos related to aircraft maintenance simulation into a video token sequence; the multi-modal input encoder is used for encoding multi-modal input data related to aircraft maintenance into a multi-modal token sequence; the potential action model is used for determining a potential action representation of a maintenance action based on the video token sequence and the multi-modal token sequence, and the dynamic prediction model is used for predicting a prediction token at the next moment based on the video token sequence, the multi-modal token sequence and the potential action representation so as to simulate a maintenance scene at the next moment.

The invention discloses a shipboard aircraft maintenance process simulation method and system based on virtual reality, and relates to the technical field of analogue simulation. According to the method, the environment sensing data packets of the shipboard aircraft and the maintenance environment are collected through the multi-modal sensor array, the shipboard aircraft maintenance simulation space is constructed based on the environment sensing data packets, and the regional maintenance step association network under different maintenance events is established according to the maintenance event records; mapping the regional maintenance step associated networks to the surface of a shipboard aircraft maintenance simulation space, and matching the regional maintenance step associated networks with one another to obtain a maintenance step associated network; and a user performs communication interaction with the shipboard aircraft maintenance simulation space through the VR equipment, collects a user interaction process through the VR equipment, inputs a user interaction action into the maintenance step association network, and further outputs a corresponding special reference scheme to judge whether the user interaction process is compliant or not.

The invention relates to the technical field of radio testing, in particular to a radio comprehensive detector which comprises a main control part, an upper computer part and a radio frequency part. The main control part is composed of an MCU and an FPGA in a cooperative mode, the MCU communicates with an upper computer through a communication interface, and the FPGA is connected with the radio frequency part through a parallel bus and is provided with a PS mode program loading interface; the radio frequency part adopts a zero intermediate frequency software radio architecture and comprises a receiving channel and a transmitting channel; the upper computer part comprises a touch screen and is connected with the main control board through a communication interface, communication navigation signals of an airplane, a ship, a control tower and a satellite can be simulated, and function testing of 17 types of radio airborne equipment such as a short wave / ultra-short wave radio station, a microwave / instrument landing system and a radio altimeter is completed; the outfield maintenance targets of single-person carrying, single-person operation and single-person flying are achieved, and the universality, efficiency and environmental adaptability of maintenance are remarkably improved.

The invention relates to the field of aircraft maintenance, in particular to an intelligent aviation kerosene and bactericide mixed filling device which comprises a shell and an oil conveying pipeline, the oil conveying pipeline penetrates through the shell, and a fuel oil input connector and a fuel oil output connector are arranged at the two ends of the oil conveying pipeline correspondingly; the bactericide distribution bin is communicated with one end of the bactericide conveying pipeline, the other end of the bactericide conveying pipeline is inserted into the oil conveying pipeline and connected with a three-stage impeller with holes, the three-stage impeller with the holes and the oil conveying pipeline are coaxially arranged, and a fuel oil flow sensor is embedded in the oil conveying pipeline and used for detecting the oil amount in the oil conveying pipeline. An electromagnetic valve and an electromagnetic diaphragm metering pump are installed on the bactericide conveying pipeline, a controller is installed in the shell, the controller is electrically connected with the fuel flow sensor, the electromagnetic valve and the electromagnetic diaphragm metering pump, in the refueling process, kerosene and a bactericide can be intelligently controlled to be mixed, and the mixing effect is guaranteed.

The invention provides a civil aircraft fault information retrieval method and system based on a knowledge graph and vector retrieval. The method comprises the following steps: firstly, carrying out batch vectorization processing on knowledge in a knowledge graph library, and constructing a vector index library; after a user query is received, the system preprocesses the user query and extracts information by adopting a hybrid strategy: special codes are accurately matched and recognized through a dictionary, and meanwhile, natural language description is converted into query vectors by utilizing a deep semantic model. Then, the system executes two kinds of retrieval in parallel: one is structured graph query based on accurate information, and the other is semantic similarity search in a vector index database; and finally, performing intelligent fusion and sorting on results returned by the two kinds of retrieval. By combining the accuracy of structured query and the recall capability of vector retrieval, the problems of various expressions, fuzzy semantics and the like in civil aircraft fault information query are effectively solved, the accuracy and comprehensiveness of fault information retrieval are remarkably improved, and more accurate and efficient decision support is provided for aircraft maintenance personnel.

The utility model discloses a handheld tool for aircraft maintenance, which comprises a shell and a motor, the motor is fixedly mounted in the shell, the output end of the motor is connected with a screwdriver blade through a connector, and a track is fixedly mounted on the outer surface of the shell. The screw driver has the advantages that the suction cup and the connecting rod are adopted, when the aircraft shell is overhauled and disassembled, the screw driver head can be inserted into a cutter groove of a screw cap of the aircraft shell, then the suction cup and the surface of the aircraft shell are adsorbed and fixed, the motor can be started to drive the screw driver head to rotate, and then a screw is disassembled; the connecting rod and the suction cup resist torsion generated during rotation, workers are prevented from slipping out of the hands, maintenance and disassembly by the workers are greatly facilitated, use convenience is improved, meanwhile, the characteristic that the surface of an airplane shell is smooth is utilized, the suction cup is adopted for fixing, mounting and disassembly are convenient, fixing stability is high, the workers do not need to tightly abut against the device vigorously, and use is convenient. The use is more flexible and labor-saving.

The invention relates to an aircraft maintenance stand scheduling method based on a graph neural network and reinforcement learning, and relates to the technical field of aircraft maintenance stand scheduling. Comprising the steps of constructing a space-time coupling heterogeneous graph model based on a disjunction graph of a maintenance project and a space topological graph of a maintenance machine position, designing an adaptive time window division method for increasing and decreasing nodes and edges in a dynamic scene, discretizing a large-scale dynamic heterogeneous graph into static sub-graphs, and improving the calculation efficiency. And designing a reinforcement learning framework in combination with the two-channel graph attention network and the gated cycle space-time memory network to realize dynamic solution of the sub-graph. Compared with the prior art, the problems that space-time coupling constraint modeling is insufficient in a high-density maintenance scene, the multi-target collaborative optimization effect is limited, and a dynamic scene is difficult to adapt can be solved.

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 invention discloses an aircraft maintenance scheme optimization analysis method and system, and relates to the technical field of maintenance optimization, and the method comprises the following steps: building a maintenance demand prediction model of aircraft parts based on a random forest regression model; carrying out fault mode and effect analysis on key parts of the aircraft, and calculating a fault risk priority number to quantify the risk of the fault; analyzing the maintenance historical data to obtain a fault maintenance period and maintenance cost data; constructing a maintenance scheme evaluation model based on a machine learning algorithm, and analyzing the optimization effect of the maintenance scheme; and carrying out comparative analysis on the maintenance scheme evaluation data and the maintenance demand prediction value, and adjusting decision tree parameters in the random forest regression model. According to the method, the problem that in the prior art, the requirements of airline companies for high efficiency, accuracy and cost effectiveness of aircraft maintenance are difficult to meet is solved, the maintenance process is optimized in a scientific and reasonable mode, and the reliability and operation and maintenance benefits of aircrafts are improved.

The invention belongs to the technical field of aircraft maintenance. The invention discloses an aircraft maintenance management method and system based on big data. The method comprises the following steps: a cloud data center constructs an aircraft operation knowledge graph, an aircraft operation analysis model and an aircraft maintenance guidance model by using a big data analysis method and an artificial intelligence algorithm according to collected historical aircraft operation knowledge big data and historical aircraft operation monitoring big data; the cloud data center is used for carrying out aircraft operation analysis by using an aircraft operation analysis model according to the real-time aircraft operation monitoring data to obtain a real-time aircraft operation analysis result; and the cloud data center carries out aircraft maintenance guidance by using an aircraft maintenance guidance model according to the real-time aircraft operation analysis result to obtain a real-time aircraft maintenance scheme, and sends the real-time aircraft maintenance scheme to the maintenance user terminal of the current aircraft. According to the invention, the problems of unstable maintenance quality and efficiency, poor management effect and lack of effective data analysis in the prior art are solved.

The invention relates to a multi-target aircraft dynamic scheduling method based on an entropy weight method and deep reinforcement learning, and the method comprises the steps: obtaining a to-be-maintained aircraft set, building a heterogeneous graph model based on a maintenance project set and a maintenance aircraft position set of each aircraft, carrying out the extraction of graph features through an encoder, carrying out the feature aggregation of the extracted nodes, and obtaining a multi-target aircraft dynamic scheduling model; aggregated feature vectors are obtained; obtaining a multi-target aircraft dynamic scheduling strategy based on the SAC network obtained by reinforcement learning training; a multi-target aircraft dynamic scheduling strategy is obtained by combining the SAC network obtained by reinforcement learning training, and in the training method of the SAC network, based on an entropy weight method, an aircraft maintenance aircraft position scheduling problem is converted into a Markov decision process, so that a multi-target aircraft maintenance aircraft position scheduling strategy can be obtained based on the obtained dynamic weight. While the flexibility of the SAC algorithm is brought into full play, it is guaranteed that multi-target balance and optimal action selection are balanced, dynamic scheduling is reasonably dealt with, and efficient coordination of multi-target optimization and real-time response of dynamic events under complex constraints are achieved.

This invention relates to an ultrasonic-assisted laser cleaning device for the inner wall of an air intake using negative pressure adsorption, belonging to the field of aircraft maintenance and surface treatment. It includes: a housing with an opening on one side of its working surface, and a flexible sealing member circumferentially disposed around the opening; a laser cleaning head disposed inside the housing; an ultrasonic amplitude transformer arranged in a ring around the laser cleaning area; an ultrasonic transducer connected to the ultrasonic amplitude transformer; a negative pressure suction unit connected to the housing for creating a negative pressure airflow field within the housing; and a high-pressure gas injection unit disposed opposite to the negative pressure suction unit for assisting in the formation of the airflow field. The ultrasonic amplitude transformer has a ring-shaped structure and is arranged in a ring array on the inner wall of the housing, with the ultrasonic transducer mounted thereon, converting electrical signals into ultrasonic vibrations via piezoelectric ceramics. This invention, by combining ultrasonic technology with laser cleaning, can adapt to cleaning areas with different radii of curvature, thereby achieving all-position cleaning.

The invention relates to the technical field of aircraft maintenance equipment, and discloses a jacking tool for aircraft maintenance, a limiting assembly is arranged on a jacking assembly, and the limiting assembly is used for clamping an undercarriage of a manned aircraft; the safety assembly is arranged on the inner side of the base and used for limiting the jacking assembly. Limiting of the other end of the second supporting arm can be relieved by pulling the first pull rod upwards to move, in the process that the other end of the second supporting arm resets and moves, the rotating base drives the first pull rod to move in the long through groove through the rotating shaft, and when the other end of the first pull rod abuts against the inner side inclined face of the guide groove, the first pull rod moves downwards; when the other end of the first pull rod is lower than the horizontal plane, the first tension spring drives the first pull rod to reset, so that one end of the first pull rod drives the limiting column to move and abut against the limiting toothed plate through the rotating shaft and the connecting frame, and therefore the device can be conveniently limited when used next time, and the using safety of the device can be guaranteed.

The present invention discloses a wheel driving device, specifically relating to the technical field of aircraft maintenance equipment, and is used to solve the technical problem that the existing wheel driving device drives the aircraft wheels first and then conducts a brake test, which is different from the actual landing situation and cannot simulate the actual landing environment. The present invention includes a frame, on which a contact roller is installed. The contact roller is driven to rotate by a driving module installed on the frame. An asphalt concrete layer is arranged on the outer side of the contact roller, and the asphalt concrete layer is used to simulate the aircraft runway surface. The present invention provides a wheel driving device, which can simulate the actual braking environment, so that the test data of the working state of the aircraft wheel brake system can be closer to the actual value, providing strong data theoretical support for the research of the aircraft wheel brake system.

The application discloses a lifting steering device and a screwing detection device for aircraft maintenance applied by the lifting steering device, and belongs to the technical field of aircraft maintenance. The lifting steering device comprises a base, a threaded cavity is arranged on the base, a threaded block is arranged in the threaded cavity, the threaded block is installed at the lower end of a lifting rod, and the threaded block is engaged with the inner wall of the threaded cavity through threads. The upper end of the lifting rod is provided with a first driving wheel, a second driving wheel is arranged above the first driving wheel, and a gap is kept between the second driving wheel and the first driving wheel. The screwing detection device comprises a main shaft, a conversion box is installed on the main shaft, a second driving reduction motor is installed on the conversion box, the second driving reduction motor is connected with a first bevel gear in a power manner, and a second bevel gear is installed on one side of the first bevel gear. By controlling the forward and reverse rotation of each motor, the lifting, screwing and clamping operations of the working end in the equipment can be realized, so that the working end of the device reaches the construction area which is difficult to reach to perform detection and operation.

The present invention belongs to the field of aircraft maintenance technology, and specifically discloses an aircraft maintenance belly skin disassembly and assembly equipment, comprising a pair of support bars and a movable wheel at the bottom thereof, wherein the two support bars are connected together by a plurality of bidirectional hydraulic rods, the bidirectional hydraulic rods being fixed on an intermediate bar, the lower wall array of the intermediate bar being provided with a telescopic hydraulic cylinder, the lower end of the telescopic hydraulic cylinder being provided with a vacuum suction cup, the upper wall array of the support bars being provided with support bars, the upper ends of the support bars being connected together by a cross bar, the support bars and the cross bar being provided with a lifting assembly, the lifting assembly being provided with a self-matching adjustment assembly, and a contour automatic adaptation assembly being provided between the two opposite self-matching adjustment assemblies. The present invention connects the connecting blocks in sequence through a curable connecting assembly to form a chain-like structure, which is automatically attached to the surface of the belly skin according to the shape of the belly skin, and automatically completes the fixing of the position of the connecting blocks to avoid deformation of the belly skin during the lifting process.

The invention discloses a windshield wiper flyback angle measurement method and system based on multi-modal dynamic feature fusion, and relates to the field of aircraft maintenance and detection.The method comprises the steps that S1, when a windshield wiper is in a working state, corresponding original signals and auxiliary signals are obtained through a magnetic encoder module and a three-axis vibration accelerometer respectively; s2, a magnetic signal with vibration interference removed is obtained through a preprocessing module; s3, obtaining a real angle value through a compensation module; s4, the motion state classification module judges whether the current motion is normal swinging or abnormal shaking, and then outputs a corresponding effective angle sequence; s5, the detection module determines whether the effective angle sequence is an effective flyback angle or not; and S6, the evaluation module gives a corresponding final flyback angle and a credibility flag bit. The invention provides a windshield wiper flyback angle measuring method and system based on multi-modal dynamic feature fusion, which are used for capturing a rotation angle of a windshield wiper driving shaft in real time, calculating a dynamic flyback angle and realizing high-precision and high-reliability real-time monitoring.