FOQA monitoring false alarm suppression method

Abstract

The invention provides an FOQA monitoring false alarm suppression method. The method comprises the following steps: (1) calculating takeoff and landing moments; (2) calculating an average taxiing direction during takeoff and landing; (3) calculating the transverse movement distance per second before takeoff and after landing by using a differential method; (4) summing up the transverse movement distances per second to obtain the transverse distance relative to the runway at each moment; and (5) suppressing the false alarm in the FOQA by using the transverse movement distance. According to the method, the QAR data is used for calculating the transverse distance of the aircraft relative to the runway during takeoff and landing, the problem that in traditional FOQA alarm logic, a ground operation item is prone to false alarm due to boundary condition setting, airport requirements and other factors is effectively solved, and FOQA monitoring and other flight data analysis work are powerfully supported.

Description

Technical Field

[0001] The invention relates to the field of flight data analysis, and in particular to a method for suppressing false alarms in FOQA monitoring. Background Art

[0002] Flight Quality Assessment (FOQA) is internationally recognized as one of the important means to ensure flight safety and has been widely recognized by the world's civil aviation industry. The Convention on International Civil Aviation stipulates that operators of aircraft with a maximum certified takeoff mass exceeding 27,000 kg should formulate and implement a flight quality assessment program as part of their safety management system. It is also recommended that operators of aircraft with a certified takeoff mass exceeding 20,000 kg should formulate and implement a flight quality assessment program.

[0004] The value of flight quality monitoring is to identify safety hazards such as substandard operations, defective procedures, degradation of aircraft performance, and imperfect air traffic control systems as early as possible by monitoring flight parameter overlimits, and to provide data and information support for the formulation and implementation of improvement measures. However, in the process of flight quality monitoring, due to problems with the data itself and irrational settings of monitoring thresholds and logic, false alarms have always troubled monitoring personnel, especially alarms related to ground operations, which have always been the hardest hit area for false alarms.

[0005] Taking the FOQA monitoring items of a certain airline as an example, it includes ground operation items such as "ground straight taxi speed is too high" and "ground turning speed is too high". Because the existing program cannot accurately determine whether the aircraft is on the runway, that is, its position relative to the runway, the aircraft is very likely to trigger the "ground straight taxi speed is too high" alarm during the takeoff phase. When landing, since the tower often requires pilots to leave the runway as soon as possible, it is also easy to trigger false alarms of ground operation items. Therefore, in summary, when performing FOQA work, certain alarm items triggered by the aircraft on the airport runway need to be conditionally suppressed, and the suppression segment and the non-suppression segment are such as Figure 2 shown. Summary of the invention

[0006] The purpose of the present invention is to provide a method for calculating the lateral distance of an aircraft from a runway when the aircraft is on the ground, in order to solve the problem that false alarms are prone to occur in existing ground monitoring items.

[0007] The object of the present invention is achieved through the following technical solutions:

[0008] A FOQA monitoring false alarm suppression method, the method comprising the steps of:

[0009] (1) Calculate take-off and landing times;

[0010] (2) Calculate the average roll direction during takeoff and landing;

[0011] (3) Use the differential method to calculate the lateral movement distance per second before takeoff and after landing;

[0012] (4) Sum up the lateral movement distance per second to obtain the lateral distance relative to the runway at each moment;

[0013] (5) Use the lateral movement distance to suppress false alarms in FOQA.

[0014] As a further technical solution, the specific content of step (1) is as follows:

[0015] (1.1) Obtain landing gear wheel load signal data;

[0016] (1.2) Calculate the first moment when the landing gear wheel load signal changes from loaded to unloaded, which is taken as the take-off point of the aircraft;

[0017] (1.3) Calculate the last moment when the landing gear wheel load signal changes from no load to load, which is taken as the landing point of the aircraft.

[0018] As a further technical solution, the specific content of step (2) is as follows:

[0019] (2.1) Let the aircraft magnetic heading data be set E, and reorganize the data in E, so that a∈R 360 , R 360 is a ring modulo 360;

[0020] (2.2) Obtain the magnetic heading data subset E from E from several seconds before the take-off point to the take-off time T ={θ1,θ2,…,θ n-1 ,θ n}, where θ n is the magnetic heading at takeoff;

[0021] (2.3) Calculate θ1,θ2,…,θ on the ring n-1 to θ n The difference between aver , and then θ aver With θ n Add together to get the average rolling direction θ at takeoff time 起 ,Right now:

[0022]

[0023] It should be noted that the addition and subtraction are all in the loop R 360 Operations on .

[0024] (2.4) Similarly, obtain a subset of magnetic heading data from the time of landing to several seconds after landing, and use the same algorithm as in (2.3) to calculate the average rolling direction θ at the time of landing 降 .

[0025] As a further technical solution, the specific content of step (3) is as follows:

[0026] (3.1) To find the differential, let the aircraft ground speed at time t after landing be v t , angle θ t , the ground speed at t+1 is v t+1 , angle θ t+1 , the aircraft ground speed and angle from time t to time t+1 are differentiated into n parts, n is a large value (>1000), and the data of the ith differential represents the The data at time t; the i-th ground speed data value v at time t to t+1 ti for:

[0027]

[0028] Similarly, the i-th angle data value from time t to t+1 is:

[0029]

[0030] (3.2) Consider the moving distance as the hypotenuse and the horizontal moving distance as the opposite side. The horizontal movement distance at time is x i , then:

[0031]

[0032] (3.3) The x in the time period from t to t+1 is i Sum and get the horizontal displacement of the aircraft from time t to time t+1

[0033]

[0034] (3.4) Use the same algorithm to calculate the lateral movement distance before takeoff. It is worth noting that the data before takeoff are in reverse order.

[0035] As a further technical solution, the specific content of step (5) is as follows:

[0036] (5.1) Obtain the alarms generated by all ground operation monitoring items in the FOQA monitoring items;

[0037] (5.2) Obtain the runway width according to the airport level;

[0038] (5.3) If the lateral distance between the aircraft and the runway is less than the runway width at the time the alarm is generated, it means that the aircraft is on the runway at that time. It may be a false alarm generated during takeoff or landing, so it is suppressed.

[0039] Compared with the prior art, the present invention uses the loop addition, subtraction and differential algorithm to calculate the lateral distance between the aircraft and the runway, thereby improving the accuracy of FOQA alarm monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a flow chart of FOQA monitoring false alarm suppression of the present invention;

[0041] Figure 2 This is an example diagram of FOQA monitoring;

[0042] Figure 3 Schematic diagram of the geometric principle in the calculation

[0043] Figure 4 This is the calculation result diagram. DETAILED DESCRIPTION

[0044] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] This embodiment takes the data of a certain flight segment of a certain type of aircraft as an example to provide a FOQA monitoring false alarm suppression method, which can be applied to the FOQA alarm monitoring field. The specific process of this method is as follows: Figure 1 As shown, including:

[0046] Step 1: Calculate take-off and landing times: QAR data is automatically downloaded by the WQAR module and stored on the server configured by the airline. It is then decoded into structured data by the flight data analysis software. The specific steps are as follows:

[0047] Step 1.1: Obtain landing gear wheel load signal data. According to the flight data parameter table, the specific name of the landing gear wheel load signal data in the flight data analysis software can be known. Therefore, the landing gear wheel load signal data can be obtained through the data interface.

[0048] Step 1.2: Calculate the first moment when the landing gear wheel load signal changes from loaded to unloaded, as the take-off point of the aircraft: The landing gear wheel load signal indicates whether there is a load on the aircraft landing gear. If there is a load, it means that the aircraft is on the ground, so the first moment when the load changes from loaded to unloaded is the take-off time of the aircraft.

[0049] Step 1.3: Similarly, calculate the last moment when the landing gear wheel load signal changes from no load to load, which is taken as the landing point of the aircraft.

[0050] Step 2: Calculate the average rolling direction during takeoff and landing. The specific steps are as follows:

[0051] Step 2.1: Reshape the aircraft magnetic heading data to a∈R 360 , R 360 The magnetic heading data records the direction of the aircraft at every moment. Obviously, its data value range is 0° to 360°. However, in actual work, the magnetic heading data of this type of aircraft is expressed in the form of -180° to +180°. At this time, it is necessary to add 180° to the value at each moment to reshape the data into a ring R of modulo 360. 360 .

[0052] Step 2.2: Get a subset of magnetic heading data from a few seconds before takeoff to the moment of takeoff. The magnetic heading data of this aircraft is recorded once per second, and the runway direction of the takeoff airport is 1°. Due to factors such as operation and wind speed, the angle may be slightly offset during takeoff. The data in the subset obtained are: 1.05, 0.63, 1.21, 0.77, 1.02, 0.52, 359.86, 0.63. Among them, 0.63 is the magnetic heading of the aircraft at the moment of takeoff.

[0053] Step 2.3: Subtract on the ring and get the difference between each moment before takeoff and the takeoff time: 0.42, 0, 0.58, 0.14, 0.39, -0.11, -0.76. The mean of the deviation is 0.094. Adding it to 0.63 at the takeoff time, the average direction at the takeoff time is 0.724°, which is slightly different from the actual runway direction of the takeoff airport.

[0054] Step 2.4: Similarly, obtain a subset of magnetic heading data from the time of landing to several seconds after landing, and use the same algorithm in step 2.3 to obtain an average rolling direction of 110.21° during landing, which is slightly different from the actual runway heading of 110°.

[0055] Step 3: Use the differential method to calculate the lateral movement distance per second before takeoff and after landing. Take the example of a certain second when the aircraft leaves the runway and turns to the parking position. The specific steps are as follows:

[0056] Step 3.1: Calculate the differential. According to the acquired ground speed and heading data, the ground speed at this moment is 15 knots, and the ground speed in the next second is 12 knots; the aircraft heading at this moment is 248.38°, and the aircraft heading in the next second is 265.08°. Differentiate the whole process into 1000 parts, and at the moment of the 100th part, the angle is:

[0057] 248.38+(100 / 1000)*(265.08-248.38)=250.05°

[0058] The speed is:

[0059] 15+(100 / 1000)*(12-15)=14.7 knots.

[0060] Step 3.2: Consider the moving distance as the hypotenuse and the lateral moving distance as the opposite side. The lateral moving distance is the moving distance multiplied by the sine of the angle between the aircraft and the runway. The geometric principle is as follows: Figure 3 As shown, the detailed results of the calculation method of the aircraft's lateral movement distance in the 100th infinitesimal element are as follows:

[0061] The difference between the aircraft's orientation and the runway's orientation at landing is: 250.05°-110.21°=139.84°;

[0062] The distance the aircraft moves in this one thousandth of a second is 14.7 knots * 0.5144 * 0.001 = 0.00756168 meters;

[0063] Therefore, the lateral movement distance of the aircraft relative to the runway in this one thousandth of a second is: 0.00756168*sin(139.84 / 180)=0.00487671 meters. Step 3.3: Sum the lateral movement distances in all infinitesimals, and the lateral movement distance of the aircraft in this second is: 7.4773449 meters.

[0064] Step 3.4: Use the same algorithm to calculate the lateral movement distance before takeoff. The movement distance after landing is calculated by accumulating backwards second by second, while the movement distance before takeoff is calculated by accumulating forwards second by second, so the data needs to be calculated in reverse order.

[0065] Step 4: Sum up the lateral movement distance per second to obtain the lateral distance relative to the runway at each moment. In the flight segment data, the distance to the runway data is as follows: Figure 4 shown.

[0066] Step 5: Use the lateral movement distance to suppress false alarms in FOQA. Taking the above segment as an example, the specific steps are as follows:

[0067] Step 5.1: Get the alarms generated by all ground operation monitoring items in the FOQA monitoring items. During the flight segment, an alarm of excessive ground taxiing turn rate was generated.

[0068] Step 5.2: Get the runway width according to the airport grade. This airport is a 4C-grade airport, and the runway width is 55 meters.

[0069] Step 5.3: At the time when the alarm is generated, the lateral distance between the aircraft and the runway is 10.45269 meters, which is less than half the width of the runway. This means that the aircraft is on the runway at this time. After analysis, it is determined that the alarm is generated when the pilot follows the tower's instructions and slides off the runway as soon as possible, so it is suppressed.

[0070] The present invention proposes a calculation method for the key data of the lateral distance between the aircraft and the runway, which can effectively distinguish the position state of the aircraft on the runway and outside the runway, thereby suppressing FOQA false alarms and effectively improving the accuracy of FOQA work.

[0071] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. It should be pointed out that any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A FOQA monitoring false alarm suppression method, characterized in that: The algorithm consists of the steps: (1) Calculate take-off and landing times; (2) Calculate the average roll direction during takeoff and landing; (3) Use the differential method to calculate the lateral movement distance per second before takeoff and after landing; (4) Sum up the lateral movement distance per second to obtain the lateral distance relative to the runway at each moment; (5) Use the lateral movement distance to suppress false alarms in FOQA.

2. A FOQA monitoring false alarm suppression method according to claim 1, characterized in that: The specific steps of calculating the take-off and landing times in step (1) include: (2.1) Obtain landing gear wheel load signal data; (2.2) Calculate the first moment when the landing gear wheel load signal changes from loaded to unloaded, which is taken as the aircraft take-off point; (2.3) Calculate the last moment when the landing gear wheel load signal changes from no load to load, which is taken as the landing point of the aircraft.

3. A FOQA monitoring false alarm suppression method according to claim 1, characterized in that: The specific steps of calculating the average taxiing direction during takeoff and landing in step (2) include: (3.1) Let the aircraft magnetic heading data be set E, and reorganize the data in E, so that a∈R 360 , R 360 is a ring modulo 360; (3.2) Obtain the magnetic heading data subset E from E from several seconds before the take-off point to the take-off time T ={θ1,θ2,…,θ n-1 ,θ n }, where θ n is the magnetic heading at takeoff; (3.3) Compute θ1,θ2,…,θ on the ring n-1 to θ n The difference between aver , and then θ aver With θ n Add together to get the average rolling direction θ at takeoff time 起 ,Right now: It should be noted that the addition and subtraction are all in the loop R 360 Operations on . (3.4) Similarly, obtain a subset of magnetic heading data from the time of landing to several seconds after landing, and use the same algorithm as in 3.3 to calculate the average rolling direction θ at the time of landing. 降 .

4. A FOQA monitoring false alarm suppression method according to claim 1, characterized in that: The specific steps of calculating the lateral movement distance per second before takeoff and after landing by differential method in step (3) include: (4.1) To find the differential, let the aircraft ground speed at time t after landing be v t , angle θ t , the ground speed at t+1 is v t+1 , angle θ t+1 , the aircraft ground speed and angle from time t to time t+1 are differentiated into n parts, n is a large value (>1000), and the data of the ith differential represents the Data at time; the i-th ground speed data value from time t to t+1 for: Similarly, the i-th angle data value from time t to t+1 is: (4.2) Consider the moving distance as the hypotenuse and the horizontal moving distance as the opposite side. The horizontal movement distance at time is x i , then: (4.3) x in the time period from t to t+1 i Sum and get the horizontal displacement of the aircraft from time t to time t+1 (4.4) Use the same algorithm to calculate the lateral movement distance before takeoff. It is worth noting that the data before takeoff are in reverse order.

5. The FOQA monitoring false alarm suppression method according to claim 1, characterized in that: The specific steps of using the lateral movement distance to suppress false alarms in FOQA in step (5) include: (5.1) Obtain the alarms generated by all ground operation monitoring items in the FOQA monitoring items; (5.2) Obtain the runway width according to the airport level; (5.3) If the lateral distance between the aircraft and the runway is less than the runway width at the time the alarm is generated, it means that the aircraft is on the runway at that time. It may be a false alarm generated during takeoff or landing, so it is suppressed.

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