CN111125924B - Airplane landing automatic deceleration gear identification method based on QAR parameter feature extraction - Google Patents
Airplane landing automatic deceleration gear identification method based on QAR parameter feature extraction Download PDFInfo
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Abstract
The invention discloses a method for identifying an aircraft landing automatic deceleration gear based on QAR parameter characteristic extraction, which comprises the following steps: s1: extracting QAR parameters required by identifying the automatic deceleration gear; s2: carrying out data cleaning on the extracted QAR parameters; s3: extracting stage data of runway sliding after landing based on S2; s4: identifying a time period of a deceleration stage from runway taxiing stage data after landing; s5: defining a gear value interval, and identifying an automatic deceleration gear in a time period of a deceleration stage. The method is based on QAR data of the airplane, divides flight stages through flight parameters, defines manual brake intervention time and traversal starting time points, improves the stability of the algorithm, sets a setting mode of a gear value interval, and improves gear identification precision, so the method is suitable for being popularized in the field in a large amount.
Description
Technical Field
The invention relates to the field of simulated flight, in particular to an identification method for an aircraft landing automatic deceleration gear based on QAR parameter feature extraction.
Background
In recent years, the data of accidents actually rushing out of the runway are few, so on the basis of the QAR data, researchers often focus attention on the navigation sections with greater risks of rushing out of the runway although the accidents actually rushing out of the runway do not occur, so as to achieve the purpose of early warning.
In the EOFDM (european operators flight data monitoring) forum in 2012, experts have proposed a risk area-based risk assessment model for a runway-rushing out, which considers that the risk of the airplane rushing out of the runway is mainly determined by the position of the airplane on the runway when landing and the landing ground speed of the airplane, and assumes that the airplane performs deceleration movement at a fixed deceleration rate (acceleration) until stopping after landing, and measures the risk of the runway-rushing out by using the calculated stopping position of the airplane.
The deceleration rate of an aircraft after landing is related to a number of factors, among which the automatic deceleration gear selection of the aircraft is of greater influence. In the automatic deceleration stage, the aircraft usually has a relatively constant deceleration rate, but the QAR data does not include parameters of the automatic deceleration gear, so a method for identifying the aircraft gear according to the QAR data of the aircraft is urgently needed to be researched.
Disclosure of Invention
In view of this, the present invention aims to provide an aircraft landing automatic deceleration gear identification method based on QAR parameter feature extraction, which divides the flight phase by flight parameters, defines the intervention time of artificial brake and the traversal start time point, improves the stability of the algorithm, sets a setting mode of a gear value range, and improves the gear identification precision.
The purpose of the invention is realized by the following technical scheme:
an airplane landing automatic deceleration gear identification method based on QAR parameter feature extraction specifically comprises the following steps: s1: extracting QAR parameters required by identifying the automatic deceleration gear;
s2: carrying out data cleaning on the extracted QAR parameters;
s3: extracting stage data of runway sliding after landing based on S2;
s4: identifying a time period of a deceleration stage from runway taxiing stage data after landing;
s5: defining a gear value interval, and identifying an automatic deceleration gear in a time period of a deceleration stage.
Further, S1 specifically is:
s11: decoding and analyzing QAR parameters in the civil aircraft to obtain a CSV file;
s12: extracting parameter data required by automatic gear identification in the landing stage, wherein the parameter data comprise ground speed change rate, a speed reduction pedal position, engine rotating speed, longitudinal acceleration, airspeed, ground speed, vertical speed, a flap state, a slat state, a landing gear state, altitude and a pitch angle.
Further, the S3 specifically is:
s31: dividing flight phases according to values of flight parameters;
s32: in the landing phase data, the landing time point of the aircraft is identified by the landing gear state parameters.
Further, the S4 specifically is:
s41: recognizing intervention opportunity t of artificial brake according to position parameters of speed reduction pedal mbk ；
S42: starting from the first 2 time points of the landing time point, searching a time point t when the engine speed ratio reaches 85% -95% of the maximum speed ratio for the first time start ；
S43: from t start At the beginning, find the first time point t when the deceleration rate is stable stable ；
S44: judging t mbk ＞t stable If yes, ending, otherwise entering S45;
s45: from the point of time t stable Beginning to traverse each time point t stable+i Where i =1,2,3 \ 8230; \8230until a first unstable rate time is encountered, this time is marked t end ；
S46: marker [ t stable ，t end ]A deceleration stage, and calculating the average value of the deceleration rate of the time period as an automatic deceleration rate;
s47: let time point t end+1 ＝t start Judging whether the next deceleration stage exists, if so, repeating S43-S46, and if not, entering S48;
s48: all deceleration phases are output.
Further, the method for judging the stability of the deceleration rate is as follows:
from this time point, the deceleration rate values at 2 time points are taken forward, the deceleration rate values at 3 time points are taken backward, and 6 values of the deceleration rate at this time point are added to form an array [ a ] t-2 ,a t-1 ,a t ,a t+1 ,a t+2 ,a t+3 ]Calculating the standard deviation sigma (t) of the array, and considering that the deceleration rate is stable when the standard deviation sigma (t) is less than or equal to theta, otherwise, the deceleration rate is unstable;
where θ is the stability threshold parameter, θ ∈ (0, 0.2].
Further, S5 specifically is:
s51: comparing the interval lengths of all the deceleration stages, extracting the longest interval length and the corresponding deceleration stage, and defining the deceleration stage as a main deceleration stage;
s52: extracting the automatic deceleration rate of the main deceleration stage, judging which gear value interval the automatic deceleration rate falls in, and outputting the automatic deceleration gear corresponding to the gear value interval;
and if the automatic deceleration rate does not fall in any gear value interval, judging that the interval length of the automatic deceleration rate from the end point value of which gear value interval is the smallest, and outputting the automatic deceleration gear of the gear value interval.
Further, the setting mode of the gear value range is as follows:
collecting QAR data of all airplanes of the same model of the same airport, and respectively calculating automatic deceleration rates according to the method provided by S46, wherein the distribution of the automatic deceleration rates is concentrated in a first area and a second area, an obvious discontinuous section exists between the first area and the second area, the first area corresponds to an automatic deceleration low gear, and the second area corresponds to an automatic deceleration middle gear;
calculating the mean value mu of the automatic deceleration rate of the automatic deceleration low gear 1 Sum variance σ 1 Will [ mu ] of 1 -3σ 1 ，μ 1 +3σ 1 ]The gear value interval is used as the gear value interval of the automatic deceleration low gear;
calculating the mean value mu of the automatic deceleration rate of the gears in the automatic deceleration 2 Sum variance σ 2 Will [ mu ] of 2 -3σ 2 ，μ 2 +3σ 2 ]And the gear value interval is used as the gear value interval of the automatic deceleration middle gear.
The invention has the beneficial effects that:
the method is based on QAR data of the airplane, divides flight stages through flight parameters, defines manual brake intervention time and traversal starting time points, improves the stability of the algorithm, sets a setting mode of a gear value interval, and improves gear identification precision, so the method is suitable for being popularized in the field in a large amount.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof.
Drawings
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings, in which:
FIG. 1 is a graph of landing speed versus landing distance;
FIG. 2 is a schematic diagram of the method S4;
fig. 3 is a schematic diagram of a deceleration rate value interval source, wherein the abscissa is the deceleration rate and the ordinate is the flight segment data volume.
Detailed Description
Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be understood that the preferred embodiments are only for illustrating the present invention, and are not intended to limit the scope of the present invention.
The runway rushing-out risk assessment model based on the risk area considers that the risk of the airplane rushing out of the runway is mainly determined by the position of the airplane on the runway and the landing ground speed of the airplane when the airplane lands, and assumes that the airplane does deceleration movement until stopping according to a fixed deceleration rate after landing. Specifically, the model firstly draws a two-dimensional grid graph, a runway is arranged on the grid graph, a runway head corresponds to a grid origin, an abscissa represents the remaining runway distance of the aircraft in a certain flight section at the landing moment, and an ordinate represents the ground speed at the landing moment.
After the grid map is provided, the position and the ground speed of the aircraft in each flight segment at the grounding moment can be extracted based on the QAR data of the flight segment, and the flight segment is used as a data point markInto the grid graph, as indicated by the prismatic marks in FIG. 1. On the basis, starting from the origin, a curve with constant acceleration (assumed to be a) is drawn, the abscissa of the curve is distance, and the ordinate is speed (according to the formula v) 2 =2 aS), it is clear that this curve is a quadratic curve of distance versus speed, aS shown by the curve in fig. 1. The physical meaning of this curve is: if the landing point corresponding to a certain flight segment is positioned on the curve, the airplane decelerates according to the deceleration rate corresponding to the curve, and the airplane can just stop at the head of the runway when the speed is reduced to zero. If a landing point of a certain flight segment is located above the curve, the flight segment cannot stop at the runway head when the flight segment decelerates by adopting the deceleration rate corresponding to the curve, and an accident of rushing out of the runway can occur. Thus, the upper part of the curve represents the area where there is a risk of running out of the runway, the lower part of the curve is the safe area, and the distance of the sample point from the curve reflects the magnitude of the risk of running out of the runway, obviously the smaller the distance, the greater the risk. In the above research, a fixed deceleration rate is assumed, and the deceleration rate generally has a small difference under the same deceleration gear, but the original QAR has no automatic deceleration gear parameter and needs to be extracted later.
Therefore, based on the above theory, the present embodiment provides a method for identifying an aircraft landing automatic deceleration gear based on QAR parameter feature extraction, and the method specifically includes:
s1: extracting QAR parameters required by identifying the automatic deceleration gear;
s11: the QAR parameters in the civil aircraft are decoded and analyzed to obtain a CSV file, each CSV file comprises a plurality of lines, each line corresponds to one data acquisition time (unit: second), namely the ith line represents the flight parameters of the ith second in the QAR recording process. Each row corresponds to a plurality of QAR acquisition parameters, the acquisition frequency of most parameters is 1Hz (sampling 1 time per second), the acquisition frequency of part of parameters is higher than 1Hz (maximum 8 Hz), the parameters appear in the same row for multiple times, the sampling frequency of part of parameters is 1 time (minimum 0.5 Hz) in multiple seconds, and the parameters appear 1 time every other rows.
S12: parameter data required by identification of a deceleration gear of the airplane in a landing stage are extracted, and the parameter data are not limited to parameters such as ground speed change rate, deceleration pedal position, engine rotating speed, longitudinal acceleration, airspeed, ground speed, vertical speed, flap state, slat state, undercarriage state, altitude and pitch angle.
S2: the extracted QAR parameters are subjected to data cleaning, and the original QAR data has obvious abnormal conditions such as partial data field dislocation or information loss due to factors such as decoding dislocation or acquisition error and the like. And (4) identifying, deleting, deducing and completing the abnormal data by combining all parameter data of the aircraft state in a period of time near the time point of the abnormal data.
Abnormal data identification range: the CSV files are incomplete, and the whole process from take-off to landing is omitted; the CSV file is flight training data with the same departure place and destination; decoding the parameter dislocation of the outputted CSV file, namely displaying the data of the parameter 2 on a certain row in the column of the parameter 1; the parameter value exceeds the theoretical value range; and the parameter value is subjected to unreasonable jump and the like.
And (3) deleting operation: for the above-mentioned CSV file format abnormal condition, discarding as invalid data; and for the CSV file, the format is correct, only the data with even abnormal parameter values are used, only the abnormal data in the CSV file are deleted, and then the completion is deduced by combining other parameters.
And (3) a method for deducing completion: generally, taking a front-back average value of continuous numerical parameters such as speed, longitude and latitude, height and the like; for discrete state parameters such as flap state and slat state, the values are typically filled in.
S3: extracting stage data of runway sliding after landing based on S2;
s31: the method comprises the steps of dividing flight stages according to values of flight parameters, wherein the flight stages comprise a takeoff stage, a stable flight stage and a landing stage, the flight parameters comprise engine rotating speed, longitudinal acceleration, airspeed, ground speed, vertical speed, flap state, slat state, altitude and pitch angle, and the flight stages are identified according to the sequence of time points and the properties of the flight parameters.
S32: in the landing phase data, the landing time point of the aircraft is identified by air-to-ground electric gate switching. The method comprises the following specific steps: the landing gear state parameter in the QAR data is identified by an air-to-ground electric door sensor change, where the air-to-ground electric door transition uses the landing gear state parameter.
S4: identifying time periods of all deceleration phases from runway glide phase data after landing, as shown in fig. 2;
s41: recognizing intervention opportunity t of artificial brake according to position parameters of speed reduction pedal mbk When the parameter value of the speed reducing pedal is particularly small, the condition that automatic speed reducing release cannot be triggered exists, so that the intervention time of manual braking is defined as that the parameter value of any speed reducing pedal is more than or equal to 4;
s42: starting from the first two time points of the landing time point, searching a time point t when the engine rotating speed ratio reaches 85% -95% of the maximum rotating speed ratio for the first time start In order to improve the stability of the algorithm, t is selected by the embodiment start The time point when the maximum rotation speed ratio is 90% is reached for the first time;
s43: from t start At the beginning, find the first time point t when the deceleration rate is stable stable The method for judging the stability of the deceleration rate comprises the following steps: from this time point, the deceleration values at 2 time points are taken forward, the deceleration values at 3 time points are taken backward, and 6 values of the deceleration values at the time points are added to form an array [ a ] t-2 ,a t-1 ,a t ,a t+1 ,a t+2 ,a t+3 ]Calculating the standard deviation sigma (t) of the array, and considering that the deceleration rate is stable when the standard deviation sigma (t) is less than or equal to theta, otherwise, the deceleration rate is unstable;
where θ is the stability threshold parameter, θ ∈ (0, 0.2], and θ =0.15 is selected in this embodiment.
S44: determine t mbk ＞t stable If the deceleration rate is stable, the method is ended, namely whether the manual brake is intervened before the deceleration rate is stable, if yes, the manual brake is intervened, namely, the automatic brake of the airplane is automatically disconnected after the manual brake is intervened, and the method has the beneficial effect of improving the calculation efficiency when the automatic brake of the airplane is ended, otherwise, the method enters S45;
s45: from the point of time t stable Begin to go backEach time point t stable+i Where i =1,2,3 \8230 \8230untila first time point of instability of the deceleration rate is encountered, this time point is marked as t end ；
S46: marker [ t stable ，t end ]The deceleration stage is a deceleration stage, and the average value of the deceleration rate of all time points in the time period is calculated and used as the automatic deceleration rate;
s47: let a time point t end+1 ＝t start ，t end+1 T as described for S45 end Judging whether the next deceleration stage exists or not by adopting a method for judging the stability of the deceleration rate at the next time point, if so, repeating S43-S46, and if not, entering S48;
s48: all deceleration phases are output.
S5: defining a gear value interval, and identifying an automatic deceleration gear in a time period of a deceleration stage.
S51: comparing the interval lengths of all the deceleration stages, extracting the longest interval length and the corresponding deceleration stage, and defining the deceleration stage as a main deceleration stage;
s52: extracting the automatic deceleration rate of the main deceleration stage, judging which gear value interval the automatic deceleration rate falls in, and outputting the automatic deceleration gear corresponding to the gear value interval;
and if the automatic deceleration rate does not fall in any gear value interval, judging that the interval length of the automatic deceleration rate from the endpoint value of which gear value interval is the minimum, and outputting the automatic deceleration gear of the gear value interval.
The setting mode of the gear value range is as follows:
collecting QAR data of all airplanes of the same model of the same airport, as shown in FIG. 3, respectively calculating automatic deceleration rates according to the method proposed by S46, wherein the distribution of the automatic deceleration rates is concentrated in a first area and a second area, and an obvious discontinuous section exists between the first area and the second area, the first area corresponds to an automatic deceleration low gear, and the second area corresponds to an automatic deceleration middle gear;
calculating the mean value mu of the automatic deceleration rate of the automatic deceleration low gear 1 Sum variance σ 1 Will [ mu ] of 1 -3σ 1 ，μ 1 +3σ 1 ]The gear value interval is used as the gear value interval of the automatic deceleration low gear;
calculating the mean value mu of the automatic deceleration rate of the gears in the automatic deceleration 2 Sum variance σ 2 Will [ mu ] of 2 -3σ 2 ，μ 2 +3σ 2 ]And the gear value interval is used as the gear value interval of the automatic deceleration middle gear.
In a normal distribution population, 99.74% of the data are contained in this interval. And calculating the deviation of the mean value and the variance of the sample from the overall mean value and the variance, wherein the larger the sample size, the smaller the deviation.
Finally, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that various changes and modifications may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (5)
1. An aircraft landing automatic deceleration gear identification method based on QAR parameter feature extraction is characterized in that: the method specifically comprises the following steps: s1: extracting QAR parameters required by identifying the automatic deceleration gear;
s2: carrying out data cleaning on the extracted QAR parameters;
s3: extracting stage data of runway sliding after landing based on S2;
s4: identifying a time period of a deceleration stage in runway taxiing stage data after landing, wherein the step S4 specifically comprises:
s41: recognizing intervention time t of artificial brake according to position parameters of speed reducing pedal mbk ；
S42: starting from the first 2 time points of the landing time point, searching a time point t when the engine speed ratio reaches 85% -95% of the maximum speed ratio for the first time start ；
S43: from t start At the beginning, find the first time point t when the deceleration rate is stable stable ；
S44: judging t mbk ＞t stable If yes, ending, otherwise entering S45;
s45: from the point of time t stable Beginning to traverse each time point t stable+i Where i =1,2,3 \ 8230; \8230until a first unstable rate time is encountered, this time is marked t end ；
S46: marker [ t stable ，t end ]A deceleration stage, and calculating the average value of the deceleration rate of the time period as an automatic deceleration rate;
s47: let time point t end+1 ＝t start Judging whether the next deceleration stage exists, if so, repeating S43-S46,
if not, entering S48;
s48: outputting all deceleration stages;
s5: defining a gear value interval, and identifying an automatic deceleration gear in a time period of a deceleration stage, wherein S5 specifically comprises:
s51: comparing the interval lengths of all the deceleration stages, extracting the longest interval length and the corresponding deceleration stage, and defining the deceleration stage as a main deceleration stage;
s52: extracting the automatic deceleration rate of the main deceleration stage, judging which gear value interval the automatic deceleration rate falls in,
and outputting an automatic deceleration gear corresponding to the gear value range;
and if the automatic deceleration rate does not fall in any gear value interval, judging that the interval length of the automatic deceleration rate from the endpoint value of which gear value interval is the minimum, and outputting the automatic deceleration gear of the gear value interval.
2. The method for identifying the landing automatic deceleration gear of the airplane based on the QAR parameter feature extraction as claimed in claim 1, wherein: the S1 specifically comprises the following steps:
s11: decoding and analyzing QAR parameters in the civil aircraft to obtain a CSV file;
s12: and extracting parameter data required by the airplane to identify the landing automatic deceleration gear.
3. The method for identifying an aircraft landing automatic deceleration gear based on QAR parameter feature extraction as claimed in claim 1, wherein: the S3 specifically comprises the following steps:
s31: dividing flight stages according to values of flight parameters, wherein the flight parameters comprise engine rotating speed, longitudinal acceleration, airspeed, ground speed, vertical speed, flap state, slat state, altitude and pitch angle;
s32: in the landing phase data, the landing time point of the aircraft is identified by air-to-ground electric gate switching.
4. The method for identifying an aircraft landing automatic deceleration gear based on QAR parameter feature extraction as claimed in claim 1, wherein: the method for judging the stability of the deceleration rate comprises the following steps:
from this time point, the deceleration values at 2 time points are taken forward, the deceleration values at 3 time points are taken backward, and 6 values of the deceleration values at the time points are added to form an array [ a ] t-2 ,a t-1 ,a t ,a t+1 ,a t+2 ,a t+3 ]Calculating the standard deviation sigma (t) of the array, and considering that the deceleration rate is stable when the standard deviation sigma (t) is less than or equal to theta, otherwise, the deceleration rate is unstable;
where θ is a stability threshold parameter, θ ∈ (0, 0.2).
5. The method for identifying an aircraft landing automatic deceleration gear based on QAR parameter feature extraction as claimed in claim 1, wherein: the gear value interval is set in the following mode:
collecting QAR data of all airplanes of the same model of the same airport, and respectively calculating automatic deceleration rates according to the method provided by S46, wherein the distribution of the automatic deceleration rates is concentrated in a first area and a second area, an obvious discontinuous section exists between the first area and the second area, the first area corresponds to an automatic deceleration low gear, and the second area corresponds to an automatic deceleration middle gear;
automatic calculation of automatic deceleration low gearMean value of deceleration rate mu 1 Sum variance σ 1 Will [ mu ] be 1 -3σ 1 ，μ 1 +3σ 1 ]The gear value interval is used as the gear value interval of the automatic deceleration low gear;
calculating the mean value mu of the automatic deceleration rate of the gears in the automatic deceleration 2 Sum variance σ 2 Will [ mu ] be 2 -3σ 2 ，μ 2 +3σ 2 ]And the gear value interval is used as the gear value interval of the automatic deceleration middle gear.
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