Method for judging steady state of flight parameter data

Abstract

The invention belongs to the technical field of flight parameter data processing, and particularly provides a method for judging the steady state of flight parameter data, which comprises the following steps: extracting flight parameter point location data to generate a parameter list; calculating and combining time intervals meeting preconditions; screening parameter points of the main parameters in the merging time interval; two stable time intervals are obtained through comparison of adjacent point thresholds and comparison of interval time thresholds; and taking the intersection of the two intervals to obtain a final steady-state time interval. According to the method, the sample size is reduced through precondition screening, the data processing efficiency is improved, irrelevant data is filtered, the judgment credibility is improved, and the method can be used for deducing pilot operation habits, judging the sensitivity of finished products / structural parts and predicting system faults and is suitable for flight parameter data steady-state analysis of various airplanes.

Description

Technical Field

[0001] This invention belongs to the field of flight parameter data processing technology, specifically relating to a method for determining the steady state of flight parameter data. Background Technology

[0002] During aircraft flight, some finished products or structural components maintain a stable state for extended periods, including remaining stable or steadily rising / falling, such as the throttle position and control surface angles during cruise. The states of these finished products / structural components are recorded by sensors and entered into flight parameter data files. Analyzing the dynamic changes in continuous flight parameter data is of great significance, as it can be used to infer pilot operating habits, assess the sensitivity of relevant finished products / structural components, and predict system malfunctions.

[0003] With the development of technologies such as aerial refueling, the duration of single flight missions is constantly increasing, resulting in a significant increase in the size of flight parameter data files and the amount of point data recorded in these files, leading to a decrease in the efficiency of flight parameter data analysis. Therefore, there is an urgent need for a method to quickly determine the steady state of continuous flight parameter data in order to efficiently assess the working status of relevant finished products / structural components and achieve the goal of fault prediction. Summary of the Invention

[0004] Purpose of the invention: This invention provides a method for determining the steady state of flight parameter data, which solves the problem of low analysis efficiency caused by the increase in the amount of existing flight parameter data, improves data processing efficiency and the reliability of steady state determination results. This method has been applied to the development of the health management module of the CB aircraft autonomous support information system and has been delivered to the field for use by the military.

[0005] Technical solution: To achieve the above-mentioned objective, the present invention proposes a method for determining the steady state of flight parameter data, comprising the following steps: Step S1: Extract all flight parameter point data information from the original flight parameter data file to interpret the required parameters, and generate a series of original parameter lists; define the required parameters as: parameter A, parameter B, parameter C, ... parameter M; Step S2: Set one or more preconditions and calculate the time interval of the preconditions; Step S3: Merge the time interval sets of parameters B, C...M generated in step S2 to obtain the merged precondition time intervals; Step S4: Filter the points of parameter A that are located in each time sub-interval of the time interval of the precondition obtained in step S3, and obtain a series of parameter point subsets of parameter A. Step S5: Traverse the parameter point subset generated in step S4. Starting from the first point, calculate the absolute value of the difference between the parameter values ​​of every two adjacent points and compare it with a predefined first threshold. If it is less than or equal to the first threshold, continue to compare the next two adjacent points. If it is greater than the first threshold, generate a stable interval end time value, and then set the time of the next point as the start time value of the next stable interval. Find the next stable time interval in the same way, and finally gather them into a stable time interval T1. Step S6: Iterate through the parameter point subset generated in step S4 again. Starting from the first point, find the point with a time difference of t seconds, calculate the absolute value of the parameter difference between the two points, and compare it with the predefined second threshold. If it is less than or equal to the second threshold, continue to compare whether the absolute value of the parameter difference between the next two adjacent points exceeds the second threshold. If it is greater than the second threshold, generate a stable state time interval, and then set the time of the next point as the start time value of the next stable interval. Find the next stable time interval in the same way, and finally gather them into a stable time interval T2. Step S7: Merge the stable time intervals generated in steps S5 and S6 by taking their intersection to obtain the final steady-state time interval.

[0006] Furthermore, in step S1, each point of all parameters includes the recording time and parameter value.

[0007] Furthermore, in step S2, the prerequisite is: for a specific flight state, find the set of time intervals that satisfy that flight state.

[0008] Further, in step S2, the calculation process is as follows: assuming parameter A is the main parameter, the set of time intervals that satisfy the set preconditions in parameters B, C...M are calculated in sequence.

[0009] Furthermore, in step S3, the conditions that need to be satisfied simultaneously are taken as the intersection, and the conditions that need to be satisfied at any one are taken as the union.

[0010] Furthermore, in step S2, the prerequisite is to find the set of time intervals that satisfy a specific flight state, and parameter A is the main parameter.

[0011] Furthermore, in step S3, the rules for merging are: conditions that need to be satisfied simultaneously are taken as the intersection, and conditions that need to be satisfied at any point are taken as the union.

[0012] Further, in step S5, the first threshold is set to 0.2% of the range of parameter A.

[0013] Further, in step S6, the second threshold is set to 0.5% of the range of parameter A.

[0014] Furthermore, in step S6, the value of t ranges from 30 to 60 seconds.

[0015] Furthermore, parameter A can be either the throttle position parameter or the aircraft control surface angle parameter.

[0016] Technical Effects: This invention significantly reduces the number of samples required for subsequent traversal by setting preconditions and filtering the subset of parameter points for the main parameter A, greatly reducing subsequent processing time and significantly improving the efficiency of flight parameter data processing. By filtering out data points that do not meet the preconditions, interference from irrelevant data is eliminated, improving the reliability of the final steady-state determination results of the flight parameter data. The method proposed in this invention is adaptable to the steady-state determination requirements under different flight states, and the preconditions and thresholds can be flexibly adjusted, making it widely applicable. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the process for determining the steady state of flight parameter data according to the present invention. Detailed Implementation

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below with reference to the accompanying drawings or specific implementation examples. It should be noted that some (but not all) of the disclosed examples are shown in the drawings. In fact, many different examples can be described, and these examples should not be construed as limited to the examples set forth herein. Rather, these examples are described to better demonstrate the positive effects of the present invention, and all aspects not detailed herein are considered to be well-known or conventional techniques in the art.

[0019] See appendix Figure 1 The method for determining the steady state of flight parameter data proposed in this invention can be executed in a computer program. The specific implementation steps are as follows: Step 1. Extract all flight parameter point data information from the original flight parameter data file for the parameters required for interpretation (parameter A, parameter B, parameter C, ... parameter M), and generate a series of original parameter lists.

[0020] Step 2. Calculate the time interval of the prerequisites based on one or more prerequisites.

[0021] Step 3. Merge the multiple precondition intervals generated in Step 2 (take the intersection of conditions that need to be met simultaneously, and the union of conditions that need to be met at any one time) to obtain the merged precondition time interval.

[0022] Step 4. Filter the points that are located in each time sub-interval of the time interval of the precondition obtained in Step 3, and obtain a set of data points for parameter A.

[0023] Step 5. Traverse the parameter point subset generated in Step 4. Starting from the first point, calculate the absolute value of the difference between the parameter values ​​of every two adjacent points and compare it with a predefined threshold. If it is less than or equal to the threshold, continue to compare the next two adjacent points; if it is greater than the threshold, generate a stable interval end time value, and then set the time of the next point as the start time value of the next stable interval. Find the next stable time interval in the same way, and finally gather them into a stable time interval.

[0024] Step 6. Iterate through the parameter point subset generated in Step 4 again. Starting from the first point, find the point with a time difference of t seconds, calculate the absolute value of the parameter difference between the two points, and compare it with a predefined threshold. If it is less than or equal to the threshold, continue to compare whether the absolute value of the parameter difference between the next two adjacent points exceeds the threshold. If it is greater than the threshold, generate a stable state time interval, and then set the time of the next point as the start time value of the next stable interval. Find the next stable time interval in the same way, and finally gather them into a stable time interval.

[0025] Step 7. Merge the time intervals generated in Step 5 and Step 6 by taking their intersection to obtain the final steady-state time interval.

[0026] The implementation process of this invention is described in detail below: 1. Extract all flight parameter point data information for the parameters required for interpretation (parameter A, parameter B, parameter C, ... parameter M) from the original flight parameter data file, generate a series of original parameter lists ListA (Point1, Point2, Point3, ... Pointn), ListB (Point1, Point2, Point3, ... Pointn) ... ListM (Point1, Point2, Point3, ... Pointn) and store them in the system cache. Parameter A is the parameter for determining the steady-state interval in the implementation case. Each point (Point) of all parameters includes the recording time and parameter value.

[0027] 2. Calculate the time intervals for one or more preconditions. For example, if one of the preconditions is "during flight", and ListB (Point1, Point2, Point3, ..., Pointn) is a list of wheel-mounted switch signal parameter data, the implementation process requires calculating the time interval TimeIntervalB when the wheel-mounted signal is equal to 0 (in the air); and in the same way, calculate the time intervals TimeIntervalC, ..., TimeIntervalM for the preconditions of other parameters.

[0028] 3. Merge the multiple precondition intervals TimeIntervalB, TimeIntervalC, … TimeIntervalM generated in step 2 (take the intersection for conditions that need to be satisfied simultaneously, and take the union for conditions that need to be satisfied by any one), to obtain the merged precondition time interval TimeIntervalTotal, which contains the following series of time sub-intervals (TimeBegin1, TimeEnd1), (TimeBegin2, TimeEnd2), (TimeBegin3, TimeEnd3), … (TimeBeginn, TimeEndn). Here, TimeBegin is the start time point, and TimeEnd is the end time point, combined into a time interval that meets the preconditions.

[0029] 4. Screen the points of parameter A that are located in each time sub-interval of the precondition time interval TimeIntervalTotal obtained in step 3, to obtain a set of data points of parameter A. For example, the subset of parameter points located in the first sub-interval (TimeBegin1, TimeEnd1) is ListA1 (Point1, Point2, Point3, …… Pointn), and the subset of parameter points located in the second sub-interval (TimeBegin2, TimeEnd2) is ListA2 (Point1, Point2, Point3, …… Pointn).

[0030] 5. Traverse the subset of parameter points ListA1 (Point1, Point2, Point3, …… Pointn) generated in step 4. Starting from the first point Point1, record its moment as the start time value tcBegin of the stable interval. Then calculate the absolute value of the difference |Pointk - Pointk+1| between the parameter values of every two adjacent points (Pointk and Pointk+1, where 1 <= k < n), and compare it with the predefined threshold λ1 (the threshold λ1 is generally set to 0.2% of the parameter value range). If |Pointk - Pointk+1| <= λ1, continue to compare whether the absolute value of the parameter value difference between the next two adjacent points Pointk+1 and Pointk+2 exceeds the threshold λ1; if |Pointk - Pointk+1| > λ1, set the moment of point Pointk as the end time value tcEnd of the stable interval, to obtain a stable state time interval (tcBegin, tcEnd). Then set the moment of the next point Pointk+1 as the start time value of the next stable interval, and find the next stable time interval in the same way. Finally, aggregate them into a stable time interval TimeInterval5.

[0031] 6. Iterate through the parameter point set ListA1(Point1, Point2, Point3, ..., Point...) generated in step 4 again. n Starting from the first point Point1, find the point with a time difference of t seconds (t is set manually, usually 30-60 seconds). If the sampling time interval of parameter A is s, then the difference between the index of the point with time difference t and the starting point Point1 is the integer (t / s), let's assume it's M. Record the point Point. M+1 The time is the start time of the stable interval, tcBegin. Then, calculate the absolute value of the difference between the parameter values ​​at the two points, |Point1-Point1. M+1 | is compared with a predefined threshold λ2 (the threshold λ2 is generally set to 0.5% of the parameter range). If |Point1-Point M+1 If |<=λ2, continue comparing the next two adjacent points Point2 and Point... M+2 Does the absolute value of the parameter difference exceed the threshold λ1? If |Point2-Point M+2 |>λ2, Set Point M+1 The time is set to the end of the stable interval, tcEnd, to obtain a stable state time interval (tcBegin, tcEnd), and then the next point, Point... M+2 The time is set as the start time value of the next stable interval, and the next stable time interval is found in the same way, eventually merging into a stable time interval TimeInterval6.

[0032] 7. Merge the time intervals TimeInterval5 and TimeInterval6 generated in steps 5 and 6. Both conditions must be met simultaneously, so perform intersection processing to obtain the final steady-state time interval TimeInterval5_6.

[0033] Implementation Case 1: In this implementation case, based on the design concept proposed by the technical solution and implementation method of the present invention, the method for determining the steady state of flight parameter data includes the following implementation steps: Step 1: Parameter Extraction: Extract the parameters required for interpretation from the original flight parameter data file, including main parameter A (throttle position parameter), parameter B (wheel switch signal parameter), and parameter C (engine speed parameter), and generate original parameter lists ListA, ListB, and ListC. Each point in each list contains the recording time and the corresponding parameter value, and the list is stored in the system cache.

[0034] Step 2, Calculation of Precondition Time Interval: Set the precondition to "Aircraft in flight and engine speed stable". For parameter B (wheel switch signal), calculate the time interval TimeIntervalB when the wheel switch signal is equal to 0 (in the air); for parameter C (engine speed parameter), calculate the time interval TimeIntervalC when the engine speed is within the preset stable range [90% rated speed, 110% rated speed].

[0035] Step 3: Merging time intervals: Since the two preconditions must be met simultaneously, the intersection of TimeIntervalB and TimeIntervalC is processed to obtain the merged precondition time interval TimeIntervalTotal, which contains time sub-intervals (TimeBegin1, TimeEnd1) and (TimeBegin2, TimeEnd2).

[0036] Step 4: Parameter point filtering: Filter the parameter points in ListA that are located within (TimeBegin1, TimeEnd1) and (TimeBegin2, TimeEnd2) to obtain parameter point subsets ListA1 and ListA2.

[0037] Step 5, Threshold comparison of adjacent points: Traverse ListA1, starting from Point1, record its time as tcBegin, calculate the absolute value of the difference between the parameter values ​​of two adjacent points |Pointk-Pointk+1|, and set the first threshold λ1 to 0.2% of the throttle position parameter value range; if |Pointk-Pointk+1|≤λ1, continue to compare the next set of adjacent points; if |Pointk-Pointk+1|>λ1, set the time of Pointk as tcEnd, and obtain the stable interval (tcBegin, tcEnd). Subsequent steps are repeated in this way to obtain the stable time interval TimeInterval5.

[0038] Step 6, Interval Time Threshold Comparison: t is set to 30 seconds, the sampling time interval of parameter A is s=1 second, and the subscript difference corresponding to the time difference t is 30 (30 / 1 rounded down); starting from Point1, find Point31 (1+30), calculate |Point1-Point31|, and set the second threshold λ2 to 0.5% of the throttle position parameter value range; if |Point1-Point31|≤λ2, continue to compare the absolute value of the difference between Point2 and Point32; if it is greater than λ2, set the time of Point31 as tcEnd to obtain the stable interval, and summarize to obtain the stable time interval TimeInterval6.

[0039] Step 7: Determine the steady-state interval: Take the intersection of TimeInterval5 and TimeInterval6 to obtain the final steady-state time interval TimeInterval5_6 for the throttle position parameters.

[0040] Implementation Case Two: This invention also provides another implementation case, specifically implementing the method for determining the steady state of flight parameter data as follows: Step A1, Parameter Extraction: Extract the main parameter A (aircraft control surface angle parameter), parameter B (flight altitude parameter), and parameter D (flight speed parameter) from the original flight parameter data file, and generate the original parameter lists ListA, ListB, and ListD. Each Point contains the recorded time and parameter value and is cached.

[0041] Step A2, Calculation of Precondition Time Interval: Set the precondition as "flight altitude within the cruising altitude range or flight speed stable". The precondition for parameter B is a flight altitude of 10,000-12,000 meters, and the calculated time interval TimeIntervalB is obtained; the precondition for parameter D is a flight speed fluctuation ≤5km / h, and the calculated time interval TimeIntervalD is obtained.

[0042] Step A3: Merging Time Intervals: If either of the two preconditions is met, perform a union operation on TimeIntervalB and TimeIntervalD to obtain the merged precondition time interval TimeIntervalTotal', which includes sub-intervals such as (TimeBegin3, TimeEnd3) and (TimeBegin4, TimeEnd4).

[0043] Step A4: Parameter point filtering: Filter the parameter points in ListA that fall within each sub-interval of TimeIntervalTotal to obtain parameter point subsets such as ListA3 and ListA4.

[0044] Step A5, Adjacent point threshold comparison: Traverse ListA3, set the first threshold λ1 to 0.2% of the rudder angle parameter value range, and summarize the stable time interval TimeInterval5' according to the adjacent point comparison logic of Case 1.

[0045] Step A6, Interval Time Threshold Comparison: t is set to 60 seconds, sampling time interval s = 2 seconds, and subscript difference is 30 (rounded down from 60 / 2); the second threshold λ2 is set to 0.5% of the rudder angle parameter value range. According to the interval point comparison logic in Case 1, the stable time interval TimeInterval6' is obtained by summarizing.

[0046] Step A7: Determine the steady-state interval: Take the intersection of TimeInterval5' and TimeInterval6' to obtain the final steady-state time interval TimeInterval5_6' of the aircraft control surface angle parameters.

[0047] The above specific embodiments or examples are only used to explain the technical solutions of the present invention and are not intended to limit the present application. Parts not described in detail are considered to be conventional technical means or common knowledge in the field. It can be understood by those skilled in the art that, based on the design concept of the present application, the technical solutions described in the foregoing embodiments can be adapted or some or all of the technical features can be equivalently replaced. These modifications, equivalent replacements, and adaptive improvements do not depart from the technical essence of the present invention and should all be covered within the protection scope of the present application.

Claims

1. A method for determining steady state of flight parameter data, characterized in that, The method comprises the following steps: Step S1, parameter extraction: extracting all flight parameter point data information of parameters required for interpretation from original flight parameter data files to generate a series of original parameter lists; defining the required parameters as parameter A, parameter B, parameter C, …, and parameter M; Step S2, precondition time interval calculation: setting one or more preconditions, and sequentially calculating time interval sets of parameters B, C, …, and M that meet the set preconditions; Step S3, time interval merging: merging the time interval sets generated in step S2 to obtain a merged precondition time interval; Step S4, parameter point screening: screening points of parameter A located in each time sub-interval of the merged precondition time interval to obtain a series of parameter point sub-sets of parameter A; Step S5, adjacent point threshold comparison: traversing the parameter point sub-set, comparing the absolute value of the parameter value difference of every two adjacent points with a first threshold value, and collecting a stable time interval T1; Step S6, interval time threshold comparison: traversing the parameter point sub-set again, comparing the absolute value of the parameter value difference of two points with a second threshold value, and collecting a stable time interval T2; Step S7, steady state interval determination: taking the intersection of the stable time intervals T1 and T2 to obtain a final steady state time interval.

2. The method of claim 1, wherein, In step S5, the parameter point sub-set generated in step S4 is traversed, the absolute value of the parameter value difference of every two adjacent points is calculated, and the result is compared with the first threshold value defined in advance. If the result is less than or equal to the first threshold value, the next two adjacent points are compared. If the result is greater than the first threshold value, a stable interval end time value is generated, the time of the next point is set as the start time value of the next stable interval, and the next stable time interval is found in the same way. Finally, a stable time interval T1 is collected.

3. The method for determining the steady state of flight parameter data as described in claim 2, characterized in that, In step S5, step S6, the parameter point sub-set generated in step S4 is traversed again, points with a time difference of t seconds are found, the absolute value of the parameter value difference of the two points is calculated, and the result is compared with the second threshold value defined in advance. If the result is less than or equal to the second threshold value, the absolute value of the parameter value difference of the next two adjacent points is compared to see whether it exceeds the second threshold value. If the result is greater than the second threshold value, a stable state time interval is generated, the time of the next point is set as the start time value of the next stable interval, and the next stable time interval is found in the same way. Finally, a stable time interval T2 is collected.

4. The method of claim 1, wherein, In step S1, each point in all parameters includes a recording time and a parameter value.

5. The method of claim 4, wherein, In step S2, the preconditions are for a specific flight state, and the time interval set that meets the flight state is calculated. Parameter A is the main parameter.

6. The method of claim 5, wherein, In step S3, the merging rule is that the conditions that need to be met at the same time are taken as the intersection, and the conditions that need to be met at any time are taken as the union.

7. The method of claim 6, wherein, In step S5, the first threshold value is set as 0.2% of the value domain of parameter A.

8. The method of claim 7, wherein, In step S6, the second threshold value is set as 0.5% of the value domain of parameter A.

9. The method of claim 8, wherein, In step S6, the value of t ranges from 30 to 60 seconds.

10. The method of claim 9, wherein, Parameter A is any one of the throttle lever position parameter and the aircraft rudder angle parameter.

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