CN113504783B - Disabled person boarding vehicle intelligent control system - Google Patents
Disabled person boarding vehicle intelligent control system Download PDFInfo
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0225—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving docking at a fixed facility, e.g. base station or loading bay
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
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Abstract
The invention discloses an intelligent control system of a boarding vehicle for disabled persons, which relates to the technical field of intelligent control and comprises a boarding vehicle butt joint control module, a prediction model establishing module, a historical error value prediction model establishing module, a database, a communication transmission module and an early warning module of the operation state of the boarding vehicle for disabled persons; the boarding vehicle docking control module is used for acquiring data when the disabled boarding vehicle is docked with an airplane cabin door; the prediction model establishing module is used for establishing a prediction model when the boarding vehicle for the disabled is in butt joint with the airplane cabin door according to the acquired data; the historical error value prediction model establishing module is used for predicting a next data error according to the comparison between the historical data error and the actual value and analyzing whether the next data error is in a standard range or not; the communication transmission module receives or sends data; the disabled person boarding vehicle operation state early warning module is used for acquiring the operation state of the disabled person boarding vehicle and giving an early warning prompt according to the operation state of the boarding vehicle.
Description
Technical Field
The invention relates to the technical field of intelligent control, in particular to an intelligent control system of a boarding vehicle for disabled people.
Background
With the rapid development of the country, more and more people select airplanes as a trip mode, the trip mode is simple, convenient and safe, and in order to ensure the trip safety of passengers, steps are usually arranged for passengers to board the airplanes; for the disabled or people who are inconvenient to go out, the disabled boarding vehicle is arranged for the disabled to board the airplane; the disabled person boarding vehicle needs to be driven to a designated position in advance and then is in butt joint with a cabin door of an airplane, wherein the boarding vehicle is provided with an boarding ladder capable of automatically ascending and descending, and passengers can conveniently go from the boarding vehicle to the airplane;
when the boarding vehicle for the disabled is butted with the airplane cabin door, various data during the butting with the airplane cabin door need to be strictly controlled, so that the boarding vehicle for the disabled is accurately butted with the airplane cabin door, no error is generated, and the safety of passengers is ensured; since the accuracy of various data needs to be strictly known, the data needs to be simulated to prevent errors. However, in the existing situation, the docking of the disabled boarding vehicle and the airplane cabin door is effectively controlled completely according to the experience of a master of the disabled boarding vehicle, and the method is difficult to ensure that the error is within a standard range and the safety of passengers is difficult to ensure; therefore, there is a need for improvements in this technology to achieve efficient control of data.
Disclosure of Invention
The invention aims to provide an intelligent control system of a boarding vehicle for disabled people, which aims to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an intelligent control system of a boarding vehicle for disabled people comprises a boarding vehicle docking control module, a prediction model building module, a historical error value prediction model building module, a database, a communication transmission module and an early warning module of the operation state of the boarding vehicle for disabled people;
the boarding vehicle docking control module acquires data when the disabled person boarding vehicle is docked with the airplane cabin door, so that the disabled person boarding vehicle and the airplane cabin door can be docked accurately according to the data;
the prediction model establishing module is used for establishing a prediction model when the disabled boarding vehicle is in butt joint with the airplane cabin door according to the acquired data, so that whether an error is generated when the disabled boarding vehicle is in butt joint with the airplane cabin door can be analyzed;
the historical error value prediction model establishing module is used for obtaining the difference value between the historical data and the actual value to obtain error data when detecting that the data in the prediction model has errors, predicting the next error data and analyzing whether the error of the next data is in a standard range or not;
the database stores historical data errors, actual values, data when the disabled boarding vehicle is in butt joint with an airplane cabin door, data of starting operation of the disabled boarding vehicle and data of arrival at an appointed position of the disabled boarding vehicle;
the communication transmission module is used for receiving or sending data;
the disabled person boarding vehicle operation state early warning module is used for acquiring the operation state of the disabled person boarding vehicle and giving early warning prompts according to the operation state of the boarding vehicle;
the prediction model building module is connected with the boarding vehicle docking control module; the historical error value prediction model establishing module is connected with the prediction model establishing module through the communication transmission module; the historical error value prediction model establishing module is connected with the disabled person boarding vehicle operation state early warning module; the boarding vehicle docking control module, the prediction model establishing module, the historical error value prediction model establishing module and the communication transmission module are connected with a database.
Furthermore, the boarding vehicle docking control module comprises a speed control unit, a distance control unit and a brake control data display unit;
the speed control unit is used for acquiring the running speed of the boarding vehicle for the disabled, and monitoring the boarding vehicle for the disabled if the running speed of the boarding vehicle for the disabled is detected to be lower than a preset standard speed;
the distance control unit measures the distance between the boarding vehicle for the disabled and an airplane cabin door through a sensor, and controls a clutch and a parking brake of the boarding vehicle for the disabled to perform emergency braking if the detected distance is smaller than a preset standard distance;
and the brake control data display unit acquires docking data for controlling the disabled boarding vehicle to move towards the direction of the airplane cabin door each time, so as to judge whether the disabled boarding vehicle is completely communicated with the airplane cabin door interface.
Further, the historical error value prediction model establishing module comprises a historical error value obtaining unit, an error value processing unit and an error value output unit;
the historical error value acquisition unit acquires historical data from a database and sends the acquired data to the error value processing unit;
the error value processing unit obtains an error value according to the difference value between the historical data and the actual value, and predicts the next error value through a unary linear regression model;
and the error value output unit outputs the error and compensates the error if the next predicted error value is detected to be larger than the standard error range.
The communication transmission module comprises a data sending unit and a data receiving unit;
the data sending unit is used for transmitting the data stored in the database to the terminal and effectively controlling the boarding vehicle for the disabled to be in butt joint with the cabin door of the airplane through the terminal;
the data receiving unit receives the data and updates the data in the database so as to control the boarding vehicle for the disabled to be effectively butted with the airplane cabin door and ensure the safety of the disabled.
Further, the prediction model when the disabled person boarding vehicle is in butt joint with the airplane door is a gray prediction model,
the prediction of the model comprises the following steps:
s01: extracting an original data sequence Z when the disabled boarding vehicle stored in the database starts to limit the vehicle speed to a preset standard vehicle speed and the disabled boarding vehicle is in butt joint with an airplane cabin door0，Z0＝{z0(1)，z0(2)，z0(3)...z0(m)}；
S02: the original data sequence is accumulated and added once to generate a new sequence Z1，
Z1＝{z1(1),z1(2),z1(3)...z1(m) }; and establish a differential equation
S03: to Z1Taking the average value of adjacent vectors to obtain
Generating a parameter vector from a differential equation
And estimating by adopting a least square method, specifically:
wherein: p, Y is a vector matrix;
namely, it is
Y＝[z1(2),z1(3),z1(4),...,z1(k)]T；
S04: vector of parameters
Substitution results in a GM (1, N) model, which can be expressed as:
to yield Z1Analog value of
S05: according to
Obtaining an analog value
The formula is as follows:
Further, data in the database are called, and the set of actual docking results obtained when the boarding vehicle for the disabled moves to the airplane cabin door by the same distance is W ═ W1,w2,w3...wmAnd obtaining an error result set which is H ═ H according to the prediction result set and the actual result set1,h2,h3...hm}；
Hi|Wi-Qi|；
When H is detectedi>In HL, the disabled person can get on the vehicle and the airplane cabin door with large butt joint errorThreatens the life of the disabled, and the error needs to be corrected and compensated; when H is detectedi<When the height of the airplane door is HL, the fact that the butt joint error of the boarding vehicle for the disabled and the airplane door is small is shown, the error is within a preset standard range, and the life of the disabled cannot be threatened; wherein HiIs the actual data when the disabled person boarding vehicle is in butt joint with the airplane cabin door when the ith step is moved, WiThe prediction data is the prediction data when the disabled person boarding vehicle is in butt joint with the airplane cabin door when the ith step is moved.
After error is corrected and compensated, the next error data of the last error data in the historical error data is predicted through a unitary linear regression model, and the prediction formula is as follows:
wherein D isiIs a dependent variable, ViIt is referred to as the independent variable,
refers to the intercept of the dependent variable Y,
refers to slope, β refers to random error;
to obtain:
by mixing
Substituting the result into a linear regression equation to obtain a predicted error value, and updating the error value into a database;
and if the deviation between the error value and the last error in the historical data is detected to be greater than the first preset deviation value, returning to the last error step through the communication transmission module, namely controlling the disabled person to climb the locomotive and the airplane cabin door to be in butt joint with the last data again, and further correcting the data.
The early warning module for the operation state of the disabled boarding vehicle comprises a disabled boarding vehicle operation indicating unit, a disabled boarding vehicle allocating unit and a monitoring early warning prompting unit;
the operation indicating unit of the disabled boarding vehicle is used for acquiring data when the disabled boarding vehicle starts to operate and the disabled boarding vehicle reaches a specified position to start operation, and if the disabled boarding vehicle is detected to reach the specified position, the data is sent to a dispatching center of the disabled boarding vehicle through a communication transmission module;
the allocation center of the boarding vehicle for the disabled schedules the boarding vehicle for the disabled and different airplane cabin doors to operate according to the time when the boarding vehicle for the disabled arrives at the designated position, the time error when the boarding vehicle for the disabled is in butt joint with the airplane cabin doors and the flight passenger information;
the monitoring and early warning prompting unit monitors according to the steps that the disabled boarding vehicle starts to run and the disabled boarding vehicle arrives at the designated position to start working, and if the situation that the disabled boarding vehicle is in error in butt joint with the airplane cabin door is detected, early warning and prompting are carried out to prevent errors, so that the life safety of the disabled is threatened.
The data in the database is obtained by a number of sensors.
Compared with the prior art, the invention has the following beneficial effects:
1. the method uses a grey prediction model, and carries out simulation according to data generated by the distance of the disabled boarding vehicle and the airplane door moving once, so that the deviation degree of an actual value and a predicted value can be analyzed, a scheme can be adopted to correct in time when the deviation occurs, the data when the disabled boarding vehicle is in butt joint with the airplane door can be ensured to be in a standard range, and meanwhile, the prediction precision is improved;
2. simulating errors generated by the predicted data and the actual values when the vehicle for controlling the disabled person to board the vehicle to move forwards by using a unitary linear regression model through a gray prediction model, and obtaining a historical error data set; the last error data in the historical error data is obtained and the next error data is predicted for simulation, so that the precision of the whole error model is improved, the error in the prediction process is reduced, the precision of the disabled person boarding vehicle in butt joint with the airplane cabin door is improved, and the safety of the disabled person on the boarding ladder is ensured;
3. the disabled boarding vehicle operation state early warning module is used for scheduling the disabled boarding vehicle to be effectively butted with different airplane cabin doors according to the time when the disabled boarding vehicle runs to the designated position, the time error when the disabled boarding vehicle is butted with the airplane cabin doors and flight passenger information, so that the disabled boarding vehicle can be effectively arranged.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of the module composition of an intelligent control system of a boarding vehicle for disabled persons according to the invention;
fig. 2 is a schematic diagram of the gray prediction model step of the intelligent control system of the disabled boarding vehicle.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides the following technical solutions:
an intelligent control system of a boarding vehicle for disabled people comprises a boarding vehicle docking control module, a prediction model building module, a historical error value prediction model building module, a database, a communication transmission module and an early warning module of the operation state of the boarding vehicle for disabled people;
the boarding vehicle docking control module acquires data when the disabled person boarding vehicle is docked with the airplane cabin door, so that the disabled person boarding vehicle and the airplane cabin door can be docked accurately according to the data;
the prediction model establishing module is used for establishing a prediction model when the disabled boarding vehicle is in butt joint with the airplane cabin door according to the acquired data, so that whether an error is generated when the disabled boarding vehicle is in butt joint with the airplane cabin door can be analyzed;
the historical error value prediction model establishing module is used for obtaining the difference value between the historical data and the actual value to obtain error data when detecting that the data in the prediction model has errors, predicting the next error data and analyzing whether the error of the next data is in a standard range or not;
the database stores historical data errors, actual values, data when the disabled boarding vehicle is in butt joint with an airplane cabin door, data of starting operation of the disabled boarding vehicle and data of arrival at an appointed position of the disabled boarding vehicle;
the communication transmission module is used for receiving or sending data;
the disabled person boarding vehicle operation state early warning module is used for acquiring the operation state of the disabled person boarding vehicle and giving early warning prompts according to the operation state of the boarding vehicle;
the prediction model building module is connected with the boarding vehicle docking control module; the historical error value prediction model establishing module is connected with the prediction model establishing module through the communication transmission module; the historical error value prediction model establishing module is connected with the disabled person boarding vehicle operation state early warning module; the boarding vehicle docking control module, the prediction model establishing module, the historical error value prediction model establishing module and the communication transmission module are connected with a database.
Furthermore, the boarding vehicle docking control module comprises a speed control unit, a distance control unit and a brake control data display unit;
the speed control unit is used for acquiring the running speed of the boarding vehicle for the disabled, and monitoring the boarding vehicle for the disabled if the running speed of the boarding vehicle for the disabled is detected to be lower than a preset standard speed;
the distance control unit measures the distance between the boarding vehicle for the disabled and an airplane cabin door through a sensor, and controls a clutch and a parking brake of the boarding vehicle for the disabled to perform emergency braking if the detected distance is smaller than a preset standard distance;
and the brake control data display unit acquires docking data for controlling the disabled boarding vehicle to move towards the direction of the airplane cabin door each time, so as to judge whether the disabled boarding vehicle is completely communicated with the airplane cabin door interface.
Further, the historical error value prediction model establishing module comprises a historical error value obtaining unit, an error value processing unit and an error value output unit;
the historical error value acquisition unit acquires historical data from a database and sends the acquired data to the error value processing unit;
the error value processing unit obtains an error value according to the difference value between the historical data and the actual value, and predicts the next error value through a unary linear regression model;
and the error value output unit outputs the error and compensates the error if the next predicted error value is detected to be larger than the standard error range.
The communication transmission module comprises a data sending unit and a data receiving unit;
the data sending unit is used for transmitting the data stored in the database to the terminal and effectively controlling the boarding vehicle for the disabled to be in butt joint with the cabin door of the airplane through the terminal;
the data receiving unit receives the data and updates the data in the database so as to control the boarding vehicle for the disabled to be effectively butted with the airplane cabin door and ensure the safety of the disabled.
Further, the prediction model of the disabled person boarding vehicle when the disabled person boarding vehicle is docked with the airplane door is a gray prediction model, and the prediction of the model comprises the following steps:
s01: extracting an original data sequence Z when the disabled boarding vehicle stored in the database starts to limit the vehicle speed to a preset standard vehicle speed and the disabled boarding vehicle is in butt joint with an airplane cabin door0，Z0＝{z0(1)，z0(2)，z0(3)...z0(m)}；
S02: the original data sequence is accumulated and added once to generate a new sequence Z1，
Z1＝{z1(1),z1(2),z1(3)...z1(m) }; and establish a differential equation
S03: to Z1Taking the average value of adjacent vectors to obtain
Generating a parameter vector from a differential equation
And estimating by adopting a least square method, specifically:
namely, it is
Y＝[z1(2),z1(3),z1(4),...,z1(k)]T；
S04: vector of parameters
Substitution results in a GM (1, N) model, which can be expressed as:
to yield Z1Analog value of
S05: according to
Obtaining an analog value
The formula is as follows:
will simulate the value
Marking the prediction result when the disabled boarding vehicle is in butt joint with the airplane cabin door as Q, storing the Q value in a database, and obtaining a set of butt joint prediction results obtained when the disabled boarding vehicle moves to the airplane cabin door for the same distance every time when the disabled boarding vehicle moves to the airplane cabin door as Q ═ Q1，q2，q3...qmM is the number of moves, qmMeans a prediction result when moving m times;
the data of the disabled boarding vehicle in butt joint with the airplane cabin door is simulated through the grey prediction model, the real-time data of the current disabled boarding vehicle in butt joint with the airplane cabin door can be judged, whether the disabled boarding vehicle can be accurately in butt joint with the airplane cabin door or not can be analyzed, the scheme can be timely adjusted according to the data, the disabled boarding vehicle can return to the previous step, the distance between the airplane cabin doors is well controlled, and safety accidents are avoided.
Furthermore, data in the database is called to obtainThe practical butt joint result set when the boarding vehicle for the disabled moves to the airplane cabin door by the same distance is W ═ W1，w2，w3...wmAnd obtaining an error result set which is H ═ H according to the prediction result set and the actual result set1，h2，h3...hm}；
Hi＝|Wi-Qi|；
When H is detectediWhen the height is more than HL, the butt joint error between the boarding vehicle and the airplane cabin door of the disabled is large, the life of the disabled is threatened, and the error needs to be corrected and compensated; when H is detectediWhen the current position is less than HL, the docking error between the boarding vehicle and the airplane cabin door of the disabled is small, the error is within the preset standard range, and the life of the disabled cannot be threatened; wherein HiIs the actual data when the disabled person boarding vehicle is in butt joint with the airplane cabin door when the ith step is moved, WiThe prediction data is the prediction data when the disabled person boarding vehicle is in butt joint with the airplane cabin door when the ith step is moved.
After error is corrected and compensated, the next error data of the last error data in the historical error data is predicted through a unitary linear regression model, and the prediction formula is as follows:
wherein D isiIs a dependent variable, ViIt is referred to as the independent variable,
refers to the intercept of the dependent variable Y,
refers to slope, β refers to random error;
to obtain:
by mixing
Substituting the result into a linear regression equation to obtain a predicted error value, and updating the error value into a database;
if the deviation of the error value from the last error in the historical data is larger than a first preset deviation value, returning to the last error step through the communication transmission module, namely controlling the disabled person to climb the locomotive and re-dock the last data with the airplane cabin door, and further correcting the data;
because the method only relates to the factor of the error value, a unitary linear regression equation is used for fitting, and the method is different from other methods in that the method is simple and convenient, easy to calculate and small in predicted error. In this process, since the predicted data calculated by the gray prediction model has an error compared with the actual data, and although the error is compensated and corrected, it cannot represent whether the next data still has an error, a corresponding model is provided to fit the data to determine the deviation of the next error from the actual value.
The early warning module for the operation state of the disabled boarding vehicle comprises a disabled boarding vehicle operation indicating unit, a disabled boarding vehicle allocating unit and a monitoring early warning prompting unit;
the operation indicating unit of the disabled boarding vehicle is used for acquiring data when the disabled boarding vehicle starts to operate and the disabled boarding vehicle reaches a specified position to start operation, and if the disabled boarding vehicle is detected to reach the specified position, the data is sent to a dispatching center of the disabled boarding vehicle through a communication transmission module;
the allocation center of the boarding vehicle for the disabled schedules the boarding vehicle for the disabled and different airplane cabin doors to operate according to the time when the boarding vehicle for the disabled arrives at the designated position, the time error when the boarding vehicle for the disabled is in butt joint with the airplane cabin doors and the flight passenger information;
the monitoring early warning prompting unit is used for monitoring according to the steps that the disabled boarding vehicle starts to run and the disabled boarding vehicle arrives at a specified position to start operation, and if the situation that the disabled boarding vehicle is in butt joint with the airplane cabin door to cause an error is detected, early warning and prompting are carried out to prevent the error from occurring, so that the life safety of the disabled is threatened;
the number of the boarding vehicles for the disabled does not correspond to the cabin door of each airplane, and the operation can be started only after the airline company determines that the disabled all reach the aviation waiting area, so that the next boarding vehicle for the disabled is reasonably allocated to be in butt joint with the cabin door of the airplane according to the residence time and the error time of each boarding vehicle for the disabled; if the disabled person is not conveyed to the airplane to be seated when the fact that the takeoff time of part of the airplanes in the airplane is close is detected, the airplane can be in butt joint with the boarding vehicle of the disabled person in advance or preferentially; if the airplane is detected to take off at a later time, the disabled boarding vehicle can be arranged to wait for standby nearby, and the disabled boarding vehicle can be reasonably arranged and controlled to operate.
The data in the database are obtained through a plurality of sensors;
the sensors used in the database include: sensors such as ultrasonic sensors, wireless remote control assemblies, etc.; the ultrasonic sensor is used for measuring the distance between the ultrasonic sensor and the door of the airplane, and the wireless remote control assembly is used for monitoring and alarming.
Example (b): when the disabled boarding vehicle moves to the airplane door within a standard distance range, the speed of the disabled boarding vehicle is limited to be below 5km/h, a clutch and a parking brake of the disabled boarding vehicle are controlled to judge whether accurate butt joint can be carried out or not, when the disabled boarding vehicle is detected to be capable of being controlled to be connected with the airplane door, data during each butt joint are obtained, when an error is detected to be generated when the disabled boarding vehicle is in butt joint with the airplane door according to the current mode, the disabled boarding vehicle is controlled to be far away from one end of the airplane door, simulation is carried out through a grey prediction model according to the obtained data, and the method specifically comprises the following steps:
s01: extracting an original data sequence Z when the disabled boarding vehicle stored in the database starts to limit the vehicle speed to a preset standard vehicle speed and the disabled boarding vehicle is in butt joint with an airplane cabin door0，Z0＝{z0(1)，z0(2)}；
S02: the original data sequence is accumulated and added once to generate a new sequence Z1，Z1＝{z1(1),z1(2) }; and establish a differential equation
S03: to Z1Taking the average value of adjacent vectors to obtain
Generating a parameter vector from a differential equation
And estimating by adopting a least square method, specifically:
wherein: p, Y is a vector matrix;
namely, it is
Y＝[z1(2),z1(3)]T；
S04: vector of parameters
Substitution results in a GM (1, N) model, which can be expressed as:
to yield Z1Analog value of
S05: according to
Obtaining an analog value
The formula is as follows:
will simulate the value
The prediction result when the disabled boarding vehicle is butted with the airplane cabin door is recorded as Q, the Q value is stored in a database, and the predicted butting result set obtained when the disabled boarding vehicle moves to the airplane cabin door for the same distance every time is Q ═ Q1，q2Where m is the number of moves, q is 80, 82.5mMeans a prediction result when moving m times;
the actual results were specifically obtained as follows: w {75, 82 };
calling data in the database to obtain a set of actual docking results when the boarding car for the disabled moves to the airplane cabin door by the same distance, wherein the set of actual docking results is W ═ W1，w2And obtaining an error result set H { H } according to the prediction result set and the actual result set1，h25, 0.5; standard error HI ═ 1.5
H1＝|W1-Q1|＝5；
H2＝|W2-Q2|＝0.5;
Therefore, the H1 is analyzed to have a large error, so that the danger is caused to the life of the disabled, and the error needs to be compensated;
the analyzed error of H2 is in a standard range, does not threaten the life of the disabled, and can be accurately butted with the airplane cabin door.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The utility model provides a disabled person boarding car intelligence control system which characterized in that: the system comprises a boarding vehicle docking control module, a prediction model building module, a historical error value prediction model building module, a database, a communication transmission module and a disabled person boarding vehicle operation state early warning module;
the boarding vehicle docking control module is used for acquiring data when the disabled boarding vehicle is docked with an airplane cabin door;
the prediction model establishing module is used for establishing a prediction model when the boarding vehicle for the disabled is in butt joint with the airplane cabin door according to the acquired data;
the historical error value prediction model establishing module is used for obtaining the difference value between the historical data and the actual value to obtain error data and predicting the next error data if errors exist in the data in the prediction model;
the database stores historical data errors, actual values, data when the disabled boarding vehicle is in butt joint with an airplane cabin door, data of starting operation of the disabled boarding vehicle and data of arrival at an appointed position of the disabled boarding vehicle;
the communication transmission module is used for receiving or sending data;
the disabled person boarding vehicle operation state early warning module is used for acquiring the operation state of the disabled person boarding vehicle and giving early warning prompts according to the operation state of the boarding vehicle;
the prediction model building module is connected with the boarding vehicle docking control module; the historical error value prediction model establishing module is connected with the prediction model establishing module through the communication transmission module; the historical error value prediction model establishing module is connected with the disabled person boarding vehicle operation state early warning module; the boarding vehicle docking control module, the prediction model establishing module, the historical error value prediction model establishing module and the communication transmission module are connected with a database.
2. The intelligent control system of the disabled boarding vehicle as claimed in claim 1, wherein: the boarding vehicle docking control module comprises a speed control unit, a distance control unit and a brake control data display unit;
the speed control unit is used for acquiring the running speed of the boarding vehicle for the disabled, and monitoring the boarding vehicle for the disabled if the running speed of the boarding vehicle for the disabled is detected to be lower than a preset standard speed;
the distance control unit measures the distance between the boarding vehicle for the disabled and an airplane cabin door through a sensor, and controls a clutch and a parking brake of the boarding vehicle for the disabled to perform emergency braking if the detected distance is smaller than a preset standard distance;
and the brake control data display unit is used for acquiring docking data for controlling the disabled person boarding vehicle to move towards the direction of the airplane cabin door each time.
3. The intelligent control system of the disabled boarding vehicle as claimed in claim 1, wherein: the historical error value prediction model establishing module comprises a historical error value obtaining unit, an error value processing unit and an error value output unit;
the historical error value acquisition unit acquires historical data from a database and sends the acquired data to the error value processing unit;
the error value processing unit obtains an error value according to the difference value between the historical data and the actual value, and predicts the next error value through a unary linear regression model;
and the error value output unit outputs the error and compensates the error if the next predicted error value is detected to be larger than the standard error range.
4. The intelligent control system of the disabled boarding vehicle as claimed in claim 1, wherein: the communication transmission module comprises a data sending unit and a data receiving unit;
the data sending unit is used for transmitting the data stored in the database to the terminal and effectively controlling the boarding vehicle for the disabled to be in butt joint with the cabin door of the airplane through the terminal;
and the data receiving unit receives the data and updates the data in the database.
5. The intelligent control system of the disabled boarding vehicle as claimed in claim 1, wherein: the prediction model of the disabled person boarding vehicle when being in butt joint with the airplane door is a gray prediction model, and the prediction of the model comprises the following steps:
s01: extracting an original data sequence Z when the disabled boarding vehicle stored in the database starts to limit the vehicle speed to a preset standard vehicle speed and the disabled boarding vehicle is in butt joint with an airplane cabin door0，Z0＝{z0(1)，z0(2)，z0(3)...z0(m)}；
S02: the original data sequence is accumulated and added once to generate a new sequence Z1，Z1＝{z1(1),z1(2),z1(3)...z1(m) }; and establish a differential equation
S03: to Z1Taking the average value of adjacent vectors to obtain
Generating a parameter vector from a differential equation
And estimating by adopting a least square method, specifically:
wherein: p, Y is a vector matrix;
namely, it is
Y＝[z1(2),z1(3),z1(4),...,z1(k)]T；
S04: vector of parameters
Substitution results in a GM (1, N) model, which can be expressed as:
to yield Z1Analog value of
S05: according to
Obtaining an analog value
The formula is as follows:
will simulate the value
Marking the prediction result when the disabled boarding vehicle is in butt joint with the airplane cabin door as Q, storing the Q value in a database, and obtaining a set of butt joint prediction results obtained when the disabled boarding vehicle moves to the airplane cabin door for the same distance every time when the disabled boarding vehicle moves to the airplane cabin door as Q ═ Q1,q2,q3...qmM is the number of moves, qmRefers to the prediction result when moving m times.
6. The intelligent control system of the disabled boarding vehicle of claim 1 or 5, wherein: calling data in the database to obtain a set of actual docking results when the boarding car for the disabled moves to the airplane cabin door by the same distance, wherein the set of actual docking results is W ═ W1,w2,w3...wmAnd obtaining an error result set which is H ═ H according to the prediction result set and the actual result set1,h2,h3...hm}；
Hi＝|Wi-Qi|；
When H is detectedi>In HL, the fact that the docking error of the vehicle for the disabled person with the airplane cabin door is large can threaten the life of the disabled person, and the error needs to be corrected and compensated; when H is detectedi<In HL, the docking error of the boarding vehicle for the disabled and the airplane cabin door is small, the error is within the preset standard range, and the life of the disabled cannot be causedA threat; wherein HiIs the actual data when the disabled person boarding vehicle is in butt joint with the airplane cabin door when the ith step is moved, WiThe prediction data is the prediction data when the disabled person boarding vehicle is in butt joint with the airplane cabin door when the ith step is moved.
7. The intelligent control system of the disabled boarding vehicle of claim 6, wherein: after error is corrected and compensated, the next error data of the last error data in the historical error data is predicted through a unitary linear regression model, and the prediction formula is as follows:
wherein D isiIs a dependent variable, ViIt is referred to as the independent variable,
refers to the intercept of the dependent variable Y,
refers to slope, β refers to random error;
to obtain:
by mixing
Substituting the result into a linear regression equation to obtain a predicted error value, and updating the error value into a database;
and if the deviation between the error value and the last error in the historical data is detected to be greater than the first preset deviation value, returning to the last error step through the communication transmission module, namely controlling the disabled person to climb the locomotive and the airplane cabin door to be in butt joint with the last data again, and further correcting the data.
8. The intelligent control system of the disabled boarding vehicle as claimed in claim 1, wherein: the early warning module for the operation state of the disabled boarding vehicle comprises a disabled boarding vehicle operation indicating unit, a disabled boarding vehicle allocating unit and a monitoring early warning prompting unit;
the operation indicating unit of the disabled boarding vehicle is used for acquiring data when the disabled boarding vehicle starts to operate and the disabled boarding vehicle reaches a specified position to start operation, and if the disabled boarding vehicle is detected to reach the specified position, the data is sent to a dispatching center of the disabled boarding vehicle through a communication transmission module;
the allocation center of the boarding vehicle for the disabled schedules the boarding vehicle for the disabled and different airplane cabin doors to operate according to the time when the boarding vehicle for the disabled arrives at the designated position, the time error when the boarding vehicle for the disabled is in butt joint with the airplane cabin doors and the flight passenger information;
the monitoring and early warning prompting unit monitors according to the steps that the disabled boarding vehicle starts to run and the disabled boarding vehicle arrives at the designated position to start working, and if the situation that the disabled boarding vehicle is in error in butt joint with the airplane cabin door is detected, early warning and prompting are carried out to prevent errors, so that the life safety of the disabled is threatened.
9. The intelligent control system of the disabled boarding vehicle as claimed in claim 1, wherein: the data in the database is obtained by a number of sensors.
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