CN117894213B - Virtual protection network-based anti-collision early warning communication system and method for protecting airplane traction - Google Patents
Virtual protection network-based anti-collision early warning communication system and method for protecting airplane traction Download PDFInfo
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- G—PHYSICS
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- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
- G08G5/04—Anti-collision systems
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
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Abstract
The invention provides a virtual protection network-based anti-collision early warning communication system and method for protecting airplane traction, which solve the problems of airport traction anti-collision and the like. The invention has the advantages of good obstacle avoidance effect, high automation degree and the like.
Description
Technical Field
The invention belongs to the technical field of airport safety management, and particularly relates to an anti-collision early warning communication system and method for protecting airplane traction based on a virtual protection network.
Background
The existing airport adopts an airplane tractor to guide the airplane to be accurately positioned. When an aircraft is parked at a corridor bridge or at a stand, a tractor is required to pull the aircraft to a runway or other designated location, including the towing of aircraft into and out of a maintenance hangar. The tractors are divided into a rod type tractor and a rodless type tractor according to different traction modes, and are divided into long-distance traction and short-distance traction according to the length of the traction distance. When traction operation is carried out, an organic crew is generally responsible for observing the situation around the aircraft, and when an obstacle is encountered, the tractor driver is commanded to brake, so that collision is avoided. The earphone director confirms that the aircraft is pulled in place, and after the aircraft reaches the stop position, the driver of the tractor is instructed to stop, the personnel on the aircraft are informed of setting the brake, the tractor is instructed to withdraw, and the wheel block is placed. However, the traction mode is highly dependent on-site personnel cooperativity, has higher technical requirements on tractor drivers, and has higher difficulty in the whole coordination process. In addition, when the airport is provided with an obstacle, the relative distance cannot be accurately judged by adopting a manual observation mode, meanwhile, the advancing speed of a tractor and the advancing inertia of different types of tractors cannot be judged, the braking distance is difficult to determine, the aircraft is easy to collide and damage, and larger property loss or hidden flight hazards are caused to the aircraft.
In order to solve the defects existing in the prior art, long-term exploration is performed, and various solutions are proposed. For example, chinese patent literature discloses an airport scene plane collision avoidance area analysis system and a collision avoidance method [202211511013.6], which includes a vehicle-mounted terminal, a vehicle-mounted positioning device, a vehicle-mounted wireless signal transceiver, a vehicle-mounted display device, a vehicle-mounted terminal, a vehicle-mounted wireless signal transceiver, a fixed ground station, a server, a data link, and a monitoring center; the airport fixed ground station is internally provided with a ground station wireless signal receiving and transmitting device and a network access module, and the ground station wireless signal receiving and transmitting device is connected with a server through the network access module; the server is electrically connected with the monitoring center.
The problem of aircraft collision early warning is solved to a certain extent to above-mentioned scheme, but this scheme still has a great deal of shortages, for example to airport staff's operation level requirement higher, difficult quick, accurate location aircraft removes scheduling problem.
Disclosure of Invention
The invention aims to solve the problems, and provides the anti-collision early warning communication system for protecting the airplane traction based on the virtual protection network, which is reasonable in design, effectively reduces the field operation difficulty and avoids collision.
The invention further aims to solve the problems, and provides a virtual protection network-based anti-collision early warning communication method for protecting airplane traction.
In order to achieve the above purpose, the present invention adopts the following technical scheme: the utility model provides a protection aircraft pulls anticollision early warning communication system based on virtual protection network, includes compound sensing mechanism, and compound sensing mechanism passes through multistage link gear and miniature synchronous car and is connected with ground service system, and ground service system is equipped with the route planning module.
In the virtual protection network-based aircraft traction anti-collision early warning communication system, the composite sensing mechanism comprises a vision acquisition component, an infrared sensor, an ultrasonic sensor and a radar component; the multi-stage linkage mechanism comprises a wireless transmission module, the wireless transmission module is connected with a signal processing module, the signal processing module is connected with a main control module, and the main control module is connected with an upper management platform; the ground service system comprises a ground command platform, wherein the ground command platform is provided with an audible and visual warning rod; the miniature synchronous car is equipped with audible and visual warning module and with wing, aircraft nose, the perpendicular synchronous laser sensor of tail, miniature synchronous car is equipped with automatic tracking module, miniature synchronous car adopts in-wheel motor drive.
A virtual protection network-based anti-collision early warning communication method for protecting airplane traction comprises the following steps:
S1: detecting a model, and establishing an airplane model;
S2: setting task constraint, and generating a virtual protection network with a corresponding model size;
s3: planning a traction path of the aircraft and the miniature synchronous vehicle by adopting a fuzzy logic algorithm;
s4: establishing a safety model;
s5: performing a simulation experiment;
S6: and carrying out multistage linkage command, and synchronously guiding a traveling path for the aircraft wing, the aircraft nose and the aircraft tail by the miniature synchronous vehicle.
In the above method for protecting aircraft traction anti-collision early warning communication based on virtual protection network, step S1 includes the following steps:
s11: three-dimensional scanning is carried out on the aircraft, and three-dimensional coordinates of the surface points of the aircraft are recorded;
s12: denoising, slowing down and registering the three-dimensional point cloud, and unifying all the point clouds to the same coordinate system;
s13: removing point clouds of the repeated area, and performing thinning simplification treatment on the point clouds of the non-key area;
S14: and (3) dividing the point cloud data, respectively modeling, and finally finishing the digital-to-analog combination.
In the above method for protecting aircraft traction anti-collision early warning communication based on virtual protection network, the task constraint conditions in step S2 are as follows:
Where a i,min and a i,max are the minimum and maximum acceleration, respectively, of the aircraft towing, and C 1 is the minimum deceleration of the aircraft towing brake.
In the above method for protecting aircraft traction anti-collision early warning communication based on virtual protection network, the virtual protection network judgment-to-collision judgment process in step S2 is as follows:
S21: detecting whether interference collision targets exist around the aircraft, if so, entering a step S22, otherwise, normally advancing and maintaining an original advancing path;
S22: judging whether the relative target distance is greater than a braking critical distance, if so, judging whether the relative target distance is in a safe traveling area, otherwise, entering a step S23; if the vehicle is in the safe traveling area, the vehicle normally travels and carries out dangerous warning, otherwise, the vehicle enters step S24;
s23: judging whether the relative target distance is larger than the steering critical distance, if so, judging whether the task constraint condition is met, otherwise, carrying out emergency braking; if the task constraint condition is met, normally changing the path and re-planning the path, otherwise, emergency braking;
s24: judging whether the vehicle is in an emergency alarm area, if so, carrying out emergency alarm and intermittent braking, and if not, carrying out danger warning and pre-braking.
In the above anti-collision early warning communication method for protecting the aircraft traction based on the virtual protection network, step S3 takes the initial aircraft traction position as the origin of coordinates and establishes a coordinate axis xoy, and the included angle between the connecting line of the aircraft and the target position and the x axis is theta, and the derivative of the traction time is the angular velocity omega; the angle between the speed direction of the aircraft and the x-axis is alpha, and the angle between the aircraft and the target position is phi=alpha-theta.
In the above method for protecting aircraft traction anti-collision early warning communication based on virtual protection network, step S3 includes the following steps:
S31: performing target searching, and inputting the distance D between the aircraft and the target position and the angle phi between the aircraft and the target position into a fuzzy processing system to obtain the speed V GS and the angular speed omega GS of the aircraft towards the target position;
S32: performing obstacle avoidance, namely inputting distances d L、dF and d R between the end points of the obstacles and the aircraft into a fuzzy processing system to obtain a speed V OA and an angular speed omega OA when the aircraft tows to avoid the obstacles;
S33: and (3) data fusion is carried out, the aircraft traction speed and the aircraft angular speed in the step S31 and the step S32 are fused, and the fused parameter tau is obtained through a fuzzy processing system, so that the aircraft traction speed and the aircraft angular speed are determined.
In the above method for protecting aircraft traction anti-collision early warning communication based on virtual protection network, step S4 includes the following steps:
s41: collecting road condition information and tractor driving parameters;
s42: calculating the complexity of a dynamic environment and a static environment through a complexity model;
s43: calculating a dangerous judgment index through the traction speed and the distance;
s44: judging whether the complexity of the current environment exceeds an early warning threshold value, if so, carrying out early warning, otherwise, not carrying out early warning.
In the above method for protecting aircraft traction anti-collision early warning communication based on virtual protection network, step S5 includes the following steps:
S51: simulation parameter settings including aircraft type, length, width, mass, braking mode, braking deceleration, braking response time, initial travel speed;
s52: performing a brake simulation experiment, counting a brake distance, and judging whether collision occurs;
s53: and selecting parameter settings meeting the anti-collision requirements as standard parameters.
In the above method for protecting aircraft traction anti-collision early warning communication based on virtual protection network, step S6 includes the following steps:
S61: the aircraft is parked, and the mini-type synchronous vehicle moves to the lower part of the wing, the nose and the tail of the aircraft;
S62: the laser sensor on the miniature synchronous vehicle vertically emits laser and receives the reflection of the aircraft body, and automatically follows the aircraft to move through the tracking angle deviation, so that the vertical positioning with the specified point of the aircraft body is always kept;
S63: the tractor drives the airplane to move, the guardian holds the acousto-optic warning bar to guide the tractor, and the commander guides the tractor to move along a traction path through the ground command platform;
S64: the miniature synchronous vehicle synchronously moves along with the airplane body, and the position of the miniature synchronous vehicle is consistent with the designated point of the airplane body in real time in the vertical direction;
S65: the commander and the guardian observe the position of the miniature synchronous vehicle, judge the horizontal direction of the aircraft body part positioned by the miniature synchronous vehicle, and if obstacles exist around the miniature synchronous vehicle, the acousto-optic warning module carries out induction warning.
In the above-mentioned method for protecting the aircraft from traction and collision pre-warning communication based on the virtual protection network, in step S62, the micro-synchronous vehicle receives the laser sensor sensing signal by the automatic tracking module, the automatic tracking module controls the hub motor and drives the micro-synchronous vehicle to move towards any direction, and the ground command platform controls the position of the micro-synchronous vehicle and adjusts the position of the specified point of the aircraft body through the multi-stage linkage mechanism.
Compared with the prior art, the invention has the advantages that: establishing a multi-stage linkage mechanism, providing a path planning module for a traction vehicle, and judging the direction of the aircraft body by utilizing a miniature synchronous vehicle, so that the on-site command difficulty is reduced; establishing a corresponding virtual protection net by judging the relative distance between the aircraft and the obstacle target, reserving a sufficient buffer zone for the movement of the aircraft, pre-judging the inertia generated during the traction of different aircraft, determining the braking advance time, and ensuring the traction safety of the aircraft; and a fuzzy logic algorithm is introduced to plan a corresponding optimal anti-collision traction path for the aircraft, and meanwhile, the inertia of the aircraft is considered, so that the simulation experiment accuracy is improved.
Drawings
FIG. 1 is a system block diagram of the present invention;
FIG. 2 is a schematic diagram of the method of the present invention;
FIG. 3 is a diagram of a collision determination process of the present invention;
FIG. 4 is a schematic diagram of a security model of the present invention;
FIG. 5 is a field layout of the present invention;
In the figure, a composite sensing mechanism 1, a vision acquisition assembly 11, an infrared sensor 12, an ultrasonic sensor 13, a radar assembly 14, a multi-stage linkage mechanism 2, a wireless transmission module 21, a signal processing module 22, a main control module 23, an upper management platform 24, a ground service system 3, a ground command platform 31, an acousto-optic warning rod 32, a micro synchronous vehicle 33, a laser sensor 34, an acousto-optic warning module 35, an automatic tracking module 36 and a path planning module 4.
Detailed Description
The invention will be described in further detail with reference to the drawings and the detailed description.
As shown in fig. 1-5, a virtual protection network-based anti-collision early warning communication system for protecting airplane traction comprises a composite sensing mechanism 1 which is loaded on a tractor and an airplane, wherein the composite sensing mechanism 1 can be used for scanning airplane surface information besides sensing surrounding environment conditions. The composite sensing mechanism 1 is connected with the ground service system 3 through the multi-stage linkage mechanism 2, and is guided by the ground service system 3 in a site command way and used for warning aircraft traction personnel, except that the ground service system 3 is provided with a path planning module 4, and the path planning module 4 is used for planning the path of the aircraft and a target position, and the aircraft is guided by the ground service system 3 to travel along a fixed route, so that obstacles are effectively avoided.
Specifically, the composite sensing mechanism 1 in the application comprises a vision acquisition component 11, an infrared sensor 12, an ultrasonic sensor 13 and a radar component 14; the above-mentioned multiple sensing components are mutually combined to improve the collection precision to airport environment, scan the aircraft surface simultaneously and gather three-dimensional point cloud information, and the relative distance of aircraft and barrier is judged in real time to compound sensing mechanism 1 in tractor and aircraft advancing process.
The multi-stage linkage mechanism 2 is used for data transmission and specifically comprises a wireless transmission module 21, wherein the wireless transmission module 21 is connected with a signal processing module 22 for analog-to-digital conversion, the signal processing module 22 is connected with a main control module 23, and the main control module 23 is connected with an upper management platform 24, so that collected sensing data are uploaded in time and are subjected to command communication with the ground service system 3 through the multi-stage linkage mechanism 2; the ground service system 3 comprises a ground command platform 31, the ground command platform 31 is provided with an audible and visual warning rod 32, ground staff instructs a guiding tractor through the audible and visual warning rod 32 and dredges airport staff, and when an abnormal condition occurs, the ground command platform 31 generates an alarm signal and the audible and visual warning rod 32 carries out audible and visual warning. The ground commanding platform 31 is also provided with a micro-synchronous vehicle 33, the micro-synchronous vehicle 33 is provided with a laser sensor 34 and an acousto-optic warning module 35, the micro-synchronous vehicle 33 is utilized to position the parts, such as the wings, the tail and the like, of the airplane which are easy to collide, and the micro-synchronous vehicle 33 moves synchronously with the airplane body under the control of the automatic tracking module 36.
In the application, the micro synchronous vehicle 33 is usually driven by an in-wheel motor, and each wheel foot of the micro synchronous vehicle 33 can independently rotate to support the micro synchronous vehicle 33 to horizontally move towards any direction. The laser sensor 34 of the micro synchronous vehicle 33 is provided with a corresponding balancing instrument, and the running on the slope and uneven road surface is ensured by adopting a negative feedback adjustment mode, the laser emitting end of the laser sensor 34 of the micro synchronous vehicle 33 is always kept vertical relative to the horizontal plane, and the micro synchronous vehicle 33 is ensured to vertically position the aircraft wings, the aircraft nose and the aircraft tail.
The tractor driver, commander and guardian listen to the superior command through the multi-level linkage mechanism 2, wherein a path planning module 4 equipped by the ground service system 3 utilizes a fuzzy logic algorithm to automatically generate a traction path, and in the process that the tractor tows the aircraft, the inertia of the aircraft and the tractor is needed to be considered, the corresponding buffer distance is reserved, and the virtual protection network planned on the periphery of the aircraft cannot be invaded by obstacles.
A virtual protection network-based anti-collision early warning communication method for protecting airplane traction is provided, wherein a passive anti-collision mode is generally adopted for airplane traction in the existing airport, and the situation around the airplane is visually observed by a guardian, so that observation dead angles are unavoidable in the mode. In order to eliminate the observation dead angle and accurately control the relative distance between the airplane and the obstacle, the application actively prevents collision by arranging the virtual protection net, and links the virtual protection net, the tractor and the airplane, and comprises the following steps:
s1: determining the size of an airplane by detecting the machine type, and establishing an airplane model;
S2: setting task constraint, and generating a corresponding virtual protection network according to the size of the machine type;
s3: planning a traction path of the aircraft and the micro synchronous vehicle 33 by adopting a fuzzy logic algorithm;
s4: establishing a safety model and setting a corresponding alarm flow;
S5: performing a simulation experiment to determine proper parameters of airplane traction;
S6: and the multi-stage linkage command is carried out, and the whole process does not need human intervention.
In depth, step S1 of collecting point cloud data by using the composite sensing mechanism 1 mounted on an aircraft, a tractor or the like, includes the steps of:
s11: three-dimensional scanning is carried out on the aircraft, three-dimensional coordinates of points on the surface of the aircraft are recorded, and if the aircraft digital model exists, the digital model is directly imported and fitted with the point cloud;
s12: denoising, slowing down and registering the three-dimensional point cloud, and unifying all the point clouds to the same coordinate system; noise points and external points are removed from the preprocessed point cloud data, so that the point cloud data is simplified;
S13: removing point clouds of the repeated area, and performing thinning simplification processing on the point clouds of the non-key area so as to improve the data operation speed and the modeling efficiency;
S14: and then the point cloud data are segmented and modeled respectively, finally, a digital-to-analog combination is completed, and repeated point cloud scanning is carried out on key parts such as the aircraft nose and the like, so that the fitting precision of the key parts is improved.
Further, since the inertia of the aircraft itself needs to be considered, the task constraint conditions in step S2 are as follows:
Where a i,min and a i,max are the minimum and maximum acceleration, respectively, of the aircraft towing, and C 1 is the minimum deceleration of the aircraft towing brake. The constraint conditions are set mainly for the purpose of ensuring that the speed of the aircraft drops to 0 within the desired braking distance, in order to avoid collisions, when it encounters a stationary obstacle during the towing of the aircraft, without taking into account the magnitude of its braking force, only its acceleration range.
Furthermore, the braking distance of the anti-collision of the aircraft increases exponentially along with the moving speed and the mass increase, and the conventional braking measures cannot meet the anti-collision requirement, so the application also introduces steering avoidance, and the virtual protection network judgment process in the step S2 is as follows:
S21: detecting whether interference collision targets exist around the aircraft, if so, entering a step S22, otherwise, normally advancing and maintaining an original advancing path;
S22: judging whether the relative target distance is greater than a braking critical distance, if so, judging whether the relative target distance is in a safe traveling area, otherwise, entering a step S23; if the vehicle is in the safe traveling area, the vehicle normally travels and carries out dangerous warning, otherwise, the vehicle enters step S24;
s23: judging whether the relative target distance is larger than the steering critical distance, if so, judging whether the task constraint condition is met, otherwise, carrying out emergency braking; if the task constraint condition is met, normally changing the path and re-planning the path, otherwise, emergency braking;
s24: judging whether the vehicle is in an emergency alarm area, if so, carrying out emergency alarm and intermittent braking, and if not, carrying out danger warning and pre-braking. The anti-collision measures combine the self braking and steering avoidance of the tractor and the aircraft, and the corresponding anti-collision measures are formulated by predicting the traction movement track, so that the steering avoidance safety is improved by the applied constraint conditions.
In addition, step S3 uses the initial position of the aircraft traction as the origin of coordinates and establishes coordinate axis xoy, assuming that the aircraft traction speed is V, the angle between the line connecting the aircraft and the target position and the x axis is θ, and the derivative of the aircraft traction time is angular speed ω; the angle between the speed direction of the aircraft and the x-axis is alpha, the angle between the aircraft and the target position is phi=alpha-theta, and a specific model is as follows:
meanwhile, step S3 includes the steps of:
S31: the target searching is carried out, the distance D between the airplane and the target position and the angle phi between the airplane and the target position are input into a fuzzy processing system, and the speed V CS and the angular speed omega CS of the airplane and the traction vehicle facing the target position are obtained, wherein the algorithm is as follows:
S32: performing obstacle avoidance, namely inputting distances d L、dF and d R between the end points of the obstacles and the aircraft into a fuzzy processing system to obtain a speed V OA and an angular speed omega OA when the aircraft tows to avoid the obstacles;
S33: data fusion is carried out, the aircraft traction speed and the aircraft angular speed in the step S31 and the step S32 are fused, the fused parameter tau is obtained through a fuzzy processing system, and then the aircraft traction speed and the aircraft angular speed are determined, wherein the fusion expression is as follows:
The fuzzy logic algorithm has good path-finding capability facing the obstacle.
Visibly, step S4 comprises the steps of:
s41: collecting road condition information and tractor driving parameters;
s42: calculating the complexity of a dynamic environment and a static environment through a complexity model;
S43: the risk judgment index is calculated through the traction speed and the distance, and the risk assessment model is as follows:
Where TTC is the time of collision, d s is the relative distance of the aircraft from the obstacle, v rel is the distance of the aircraft, where the obstacle includes a fixed obstacle and a moving obstacle, and v rel may be the relative speed of the aircraft and the moving obstacle.
In addition, the aircraft traction state is evaluated by introducing the risk factors, so that the subsequent anti-collision treatment is more refined:
wherein f d is a dangerous factor, D w is a safety early warning distance, D b is an emergency braking distance, D is an actual distance between the aircraft and the obstacle, and the aircraft is in a safety state when f d is less than 0; when f d is more than or equal to 0 and less than 0.5, entering an alarm state; when f d is more than or equal to 0.5 and less than 1, the upper level takes over the airplane and the tractor; when f d is more than or equal to 1, the airplane and the tractor enter an emergency braking state;
s44: judging whether the complexity of the current environment exceeds an early warning threshold value, if so, carrying out early warning, otherwise, not carrying out early warning.
It is apparent that step S5 includes the steps of:
S51: simulation parameter settings including aircraft type, length, width, mass, braking mode, braking deceleration, braking response time, initial travel speed; the braking deceleration needs to consider the friction coefficient with the ground, the braking response time corresponds to the braking mode one by one, and different airplanes and tractors select initial travelling speeds within 5-20 km/h;
S52: performing a brake simulation experiment, counting a brake distance, judging whether collision occurs, and taking the response time of a traction person into consideration in the simulation experiment process, and introducing a brake abnormal condition comprising brake moment drop and failure state;
S53: finally, parameter settings meeting the anti-collision requirements are selected as standard parameters, and the operation of subsequent traction personnel refers to corresponding standard regulations.
In addition, since the vision of the commander and the guardian is limited, the horizontal orientation of the wing, tail, and other key parts of the fuselage cannot be accurately determined, and therefore the mini-synchronous vehicle 33 is used for indirect guidance, wherein step S6 includes the following steps:
S61: the aircraft is parked, the micro synchronous vehicle 33 moves to the lower part of the aircraft body, and a plurality of micro synchronous vehicles 33 are usually adopted to move to the positions which are easy to collide, such as wings, tail and the like;
s62: determining a positioning point of an aircraft body, vertically transmitting laser by a laser sensor 34 on the micro synchronous vehicle 33 and receiving the reflection of the aircraft body, vertically positioning the micro synchronous vehicle 33 and the specified point of the aircraft body, and generating a virtual plumb line between the micro synchronous vehicle 33 and the aircraft body in a laser reflection mode;
S63: the tractor driver controls the tractor to drive the airplane to move, and the guardian holds the acousto-optic warning rod 32 to guide the tractor, and the tractor usually stands at wing tips of wings at two sides, and randomly moves the wings to observe the safety state of the periphery; the commander directs the tractor to move along the traction path through the ground command platform 31, the commander keeps in contact with personnel on the aircraft and the driver of the tractor, stands at the aircraft nose and keeps a distance from the tractor, and the surrounding condition is observed at any time in the traction process;
S64: the micro synchronous vehicle 33 moves synchronously with the aircraft body, the position of the micro synchronous vehicle 33 is consistent with the specified point of the aircraft body in real time in the vertical direction, and the adopted micro synchronous vehicle 33 adopts automatic following and is provided with a corresponding driving structure and a sensing structure for feedback control;
S65: the director and guardian observe the position of the micro synchronous vehicle 33, and judge the horizontal orientation of the aircraft body part positioned by the micro synchronous vehicle 33, wherein the orientation of the micro synchronous vehicle 33 is the horizontal orientation of important parts such as wings. If there is an obstacle around the micro-synchronous car 33, the acousto-optic warning module 35 carries out induction warning, and if the commander and the guardian observe personnel injury or aircraft collision risk, a suspension traction warning is sent through the multi-stage linkage mechanism 2.
The micro synchronous car 33 receives the sensing signal of the laser sensor 34 by the automatic tracking module 36, the automatic tracking module 36 controls the wheel hub motor and drives the micro synchronous car 33 to move towards any direction, and the ground command platform 31 controls the position of the micro synchronous car 33 and adjusts the position of a specified point of the aircraft body through the multi-stage linkage mechanism 2.
In the application, the micro synchronous vehicle 33 adopts an automatic following mode, and the horizontal direction of the micro synchronous vehicle 33 can be adjusted by adopting a remote control mode, so that the micro synchronous vehicle 33 and other parts of the aircraft body which are easy to collide are secondarily and vertically positioned, and as the micro synchronous vehicle 33 is provided with the acousto-optic warning module 35, surrounding personnel are warned when collision risk exists.
In summary, the principle of this embodiment is as follows: the method comprises the steps of building an aircraft model, generating a virtual protection net, generating a traction path through a fuzzy logic algorithm, ensuring that the virtual protection net cannot interfere with an obstacle in the aircraft traction process, and guiding traction personnel through multistage linkage command of a miniature synchronous vehicle, so that the aircraft entity cannot collide with the obstacle.
The specific embodiments described herein are offered by way of example only to illustrate the spirit of the invention. Those skilled in the art may make various modifications or additions to the described embodiments or substitutions thereof without departing from the spirit of the invention or exceeding the scope of the invention as defined in the accompanying claims.
Although terms of the composite sensing mechanism 1, the vision collecting assembly 11, the infrared sensor 12, the ultrasonic sensor 13, the radar assembly 14, the multi-stage linkage mechanism 2, the wireless transmission module 21, the signal processing module 22, the main control module 23, the upper management platform 24, the ground service system 3, the ground command platform 31, the acousto-optic warning bar 32, the micro-synchronous car 33, the laser sensor 34, the acousto-optic warning module 35, the automatic tracking module 36, the path planning module 4, etc. are used more herein, the possibility of using other terms is not excluded. These terms are used merely for convenience in describing and explaining the nature of the invention; they are to be interpreted as any additional limitation that is not inconsistent with the spirit of the present invention.
Claims (7)
1. The utility model provides a protection aircraft traction anticollision early warning communication method based on virtual protection network which is characterized in that the method comprises the following steps:
S1: detecting a model, and establishing an airplane model;
S2: setting task constraint, and generating a virtual protection network with a corresponding model size, wherein the task constraint conditions are as follows:
；
Wherein the method comprises the steps of AndThe minimum acceleration and the maximum acceleration of the aircraft traction,For the minimum deceleration of the aircraft traction braking, the virtual protection network judgment and collision judgment process in the step S2 is as follows:
S21: detecting whether interference collision targets exist around the aircraft, if so, entering a step S22, otherwise, normally advancing and maintaining an original advancing path;
S22: judging whether the relative target distance is greater than a braking critical distance, if so, judging whether the relative target distance is in a safe traveling area, otherwise, entering a step S23; if the vehicle is in the safe traveling area, the vehicle normally travels and carries out dangerous warning, otherwise, the vehicle enters step S24;
s23: judging whether the relative target distance is larger than the steering critical distance, if so, judging whether the task constraint condition is met, otherwise, carrying out emergency braking; if the task constraint condition is met, normally changing the path and re-planning the path, otherwise, emergency braking;
S24: judging whether the vehicle is in an emergency alarm area, if so, carrying out emergency alarm and intermittent braking, and if not, carrying out danger warning and pre-braking;
s3: planning a traction path of the aircraft and the miniature synchronous vehicle (33) by adopting a fuzzy logic algorithm;
s4: establishing a safety model;
s5: performing a simulation experiment;
S6: and carrying out multistage linkage command, and synchronously guiding a traveling path for the wings, the nose and the tail of the airplane by a miniature synchronous vehicle (33).
2. The method for communication of protecting aircraft traction collision avoidance warning based on virtual protection network according to claim 1, wherein the step S1 comprises the following steps:
s11: three-dimensional scanning is carried out on the aircraft, and three-dimensional coordinates of the surface points of the aircraft are recorded;
s12: denoising, slowing down and registering the three-dimensional point cloud, and unifying all the point clouds to the same coordinate system;
s13: removing point clouds of the repeated area, and performing thinning simplification treatment on the point clouds of the non-key area;
S14: and (3) dividing the point cloud data, respectively modeling, and finally finishing the digital-to-analog combination.
3. The method for protecting an aircraft from traction collision warning communication based on a virtual protection network according to claim 1, wherein the step S3 uses an aircraft traction starting position as an origin of coordinates and establishes the coordinatesAssume that the aircraft towing speed isAircraft and target position linkThe included angle of the axes isThe derivative with traction time is the angular velocity; Speed direction of aircraftThe included angle of the axes isThe angle between the plane and the target position isThe step S3 comprises the following steps:
s31: searching target, and determining the distance between the plane and the target position And the angle of the aircraft to the target positionInputting the fuzzy processing system to obtain the speed of the airplane towards the target positionAngular velocity；
S32: obstacle avoidance is performed, and the distance between the end point of the obstacle and the airplane is calculated、AndInputting the fuzzy processing system to obtain the speed of the airplane when the airplane is towed to avoid the obstacleAngular velocity；
S33: data fusion is carried out, the speed and the angular speed of the airplane traction in the step S31 and the step S32 are fused, and the fused parameters are obtained through a fuzzy processing systemAnd further determines the aircraft towing speed and angular velocity.
4. The method for communication of protecting aircraft traction collision avoidance warning based on virtual protection network according to claim 1, wherein the step S4 comprises the following steps:
s41: collecting road condition information and tractor driving parameters;
s42: calculating the complexity of a dynamic environment and a static environment through a complexity model;
s43: calculating a dangerous judgment index through the traction speed and the distance;
s44: judging whether the complexity of the current environment exceeds an early warning threshold value, if so, carrying out early warning, otherwise, not carrying out early warning.
5. The method for communication of protecting aircraft traction collision avoidance warning based on virtual protection network according to claim 1, wherein the step S5 comprises the following steps:
S51: simulation parameter settings including aircraft type, length, width, mass, braking mode, braking deceleration, braking response time, initial travel speed;
s52: performing a brake simulation experiment, counting a brake distance, and judging whether collision occurs;
s53: and selecting parameter settings meeting the anti-collision requirements as standard parameters.
6. The method for communication of protecting aircraft traction collision avoidance warning based on virtual protection network according to claim 1, wherein step S6 comprises the steps of:
S61: the aircraft is parked, and the mini-type synchronous vehicle (33) moves to the lower part of the aircraft body;
S62: a laser sensor (34) on the miniature synchronous vehicle (33) vertically emits laser and receives the reflection of the aircraft body, and automatically follows the aircraft to move through tracking angle deviation, so that the vertical positioning with the specified point of the aircraft body is always kept;
S63: the tractor drives the airplane to move, the guardian holds the acousto-optic warning bar (32) to guide the tractor, and the commander guides the tractor to move along a traction path through the ground command platform (31);
S64: the miniature synchronous vehicle (33) synchronously moves along with the airplane body, and the position of the miniature synchronous vehicle is consistent with the designated point of the airplane body in real time in the vertical direction;
S65: the commander and guardians observe the position of the miniature synchronous vehicle (33), judge the horizontal position of the aircraft organism position that miniature synchronous vehicle (33) was located, if there is the barrier around miniature synchronous vehicle (33), audible and visual warning module (35) carries out the response warning.
7. The method for protecting an aircraft from traction and collision pre-warning communication based on a virtual protection network according to claim 6, wherein in the step S62, the micro-synchronous vehicle (33) receives the sensing signal of the laser sensor (34) by the automatic tracking module (36), the automatic tracking module (36) controls the in-wheel motor and drives the micro-synchronous vehicle (33) to move towards any direction, and the ground command platform (31) controls the position of the micro-synchronous vehicle (33) and adjusts the position of a specified point of the aircraft body through the multi-stage linkage mechanism (2).
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| DE102017123198A1 (en) * | 2017-10-06 | 2019-04-11 | Airbus Operations Gmbh | System and method for navigating an aircraft in a hall |
| US10535276B2 (en) * | 2017-12-04 | 2020-01-14 | Ge Aviation Systems Llc | Route planning and movement of an aircraft on the ground based on a navigation model trained to increase aircraft operational efficiency |
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| CN111846270A (en) * | 2020-07-19 | 2020-10-30 | 广州白云空港设备技术发展有限公司 | Aircraft ground traction anti-collision system based on crawling robot technology |
| CN112947074B (en) * | 2021-01-29 | 2022-11-29 | 中国人民解放军军事科学院战争研究院 | Trajectory planning method of rod-towed aircraft system based on virtual aircraft extraction strategy |
| CN113378741B (en) * | 2021-06-21 | 2023-03-24 | 中新国际联合研究院 | Auxiliary sensing method and system for aircraft tractor based on multi-source sensor |
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| CN116300971B (en) * | 2023-05-17 | 2023-09-01 | 中国民航大学 | Traction sliding control method and device for civil aircraft, tractor and storage medium |
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