Blunt-nosed aircraft embedded air data system fault detection method and device

Abstract

The present invention discloses a method and device for detecting faults in an embedded atmospheric data system of a blunt-nosed aircraft. The detection method utilizes a modified parity detection method to obtain data from multiple pressure sensors at the aircraft's head. The angle of attack is based on data from a vertical pressure sensor, and a characteristic three-point combination method is selected to construct a first parity equation. A floating threshold is set according to the modified formula, and by determining whether the first parity equation is within the floating threshold, it is determined whether there is a fault in the pressure sensor in the characteristic three-point combination method. If a fault exists, the specific faulty pressure sensor is determined by intersecting the failed combinations, and the faulty pressure sensor is isolated. The sideslip angle is based on data from a horizontal pressure sensor. The process is consistent with the above, and it can be determined whether all pressure sensors are faulty, thereby ensuring that all raw pressure data used to calculate atmospheric parameters are accurate.

Description

Technical Field

[0001] The present invention relates to the field of atmospheric data system fault detection, and in particular to a method and device for detecting faults in an embedded atmospheric data system of a blunt-nosed aircraft. Background Art

[0002] The embedded air data system uses a pressure sensor installed on the aircraft's nose instead of an external probe. Because embedded air data modules are prone to failures such as pressure sensor leaks and surface material ablation in harsh flight environments, autonomous diagnosis of the collected air data is required.

[0003] Currently, many embedded air data systems use even-odd equations for fault detection. These equations are derived from the three-point method. Because the three-point method requires only three pressure taps to calculate atmospheric parameters, and the relatively large nose of an aircraft allows for seven to nine pressure taps, the number of taps available for selection is significantly increased, significantly reducing the overall air data system's failure rate.

[0004] The currently available parity detection method only uses a simple judgment threshold of ±N to determine whether there is a fault. However, considering that the overall shape of any aircraft in engineering practice cannot be a standard blunt-headed body, the rear shape of the aircraft will cause unpredictable interference with the pressure collected by its ball head, causing failures in the fault detection process of the atmospheric data system. Summary of the Invention

[0005] In order to solve the above problems, the present invention provides a method for accurately determining whether there is a fault in the atmospheric parameters collected by the embedded atmospheric data system of a blunt-nosed aircraft.

[0006] In order to achieve the above object, the present invention provides a method for detecting a fault in an embedded air data system of a blunt-nosed aircraft, comprising the following steps:

[0007] Acquiring data from a plurality of pressure sensors on the head of the aircraft; wherein the plurality of pressure sensors are distributed in a cross shape;

[0008] Based on the data of the vertical pressure sensor, a characteristic hole position combination is selected to construct the first parity equation;

[0009] determining whether there is a fault in the vertical pressure sensor according to a relationship between the first parity equation and the floating threshold;

[0010] Based on the data of the horizontal pressure sensor, a characteristic hole position combination is selected to construct the second parity equation;

[0011] determining whether there is a fault in the horizontal pressure sensor according to a relationship between the second parity equation and the floating threshold;

[0012] If a fault condition exists, the faulty pressure sensor is determined by intersecting the failed combinations;

[0013] Isolate the faulty pressure sensor, determine the angle of attack based on the data from the effective pressure sensor in the vertical direction, and determine the sideslip angle based on the data from the effective pressure sensor in the horizontal direction.

[0014] As a preferred technical solution, in the above detection method, taking the vertical pressure sensor as an example, the selection of the pressure hole combination is classified according to the characteristics of the experimental results, further including:

[0015] Different angles, wind speeds, and combinations all have an impact on the value of the odd-even equation. Using a simple, unified threshold to determine the value of the odd-even equation can lead to overly sensitive or slow fault detection processes.

[0016] Taking the data of three pressure sensors in the vertical direction as a group, seven groups of feature combinations are selected to construct the first parity equation; the seven groups of feature data include the data of the central pressure sensor and the two pressure sensors closest to the central pressure sensor, and the value of the parity equation of this combination changes the least; the data of the central pressure sensor and any two pressure sensors above or below the upper central pressure sensor, the value of the parity equation of this combination is not 0 when the angle is 0°, but there is a certain offset upward or downward respectively; without the data of the central pressure sensor, the value of the parity equation of this type of combination has the largest slope as the angle changes.

[0017] As a preferred technical solution, in the above detection method, determining whether there is a fault in the vertical pressure sensor according to the first parity equation further includes:

[0018] determining whether a result of the first parity equation is within an error range;

[0019] If yes, it means that the pressure sensor group is normal, otherwise it means that the pressure sensor group is faulty.

[0020] As a preferred technical solution, in the above detection method, the error range is changed to a floating threshold K = C1 + C2 × β + C3 × Ma + C4 × β 2 +C5×β×Ma+C6×Ma 2 ±100, where C1-C6 are the calibration coefficients for odd and even detection values, obtained based on actual pressure measurement data from wind tunnel experiments. Different aircraft should use different calibration systems.

[0021] As a preferred technical solution, in the above detection method, based on the data of the horizontal pressure sensor, a feature combination method is selected to construct a second parity equation, further comprising:

[0022] Taking the data of three pressure sensors in the horizontal direction as a group, seven groups of feature combinations are selected to construct the second parity equation; the seven groups of feature data include the data of the central pressure sensor and the two pressure sensors closest to the central pressure sensor, and the value of the parity equation of this combination changes minimally; the data of the central pressure sensor and any two pressure sensors above or below the upper central pressure sensor, the value of the parity equation of this combination is not 0 when the angle is 0°, but there is a certain offset upward or downward respectively; without the data of the central pressure sensor, the value of the parity equation of this type of combination has the largest slope as the angle changes.

[0023] As a preferred technical solution, in the above detection method, determining whether there is a fault in the horizontal pressure sensor according to the second parity equation further includes:

[0024] determining whether a result of the second parity equation is within an error range;

[0025] If it is, it means that the pressure sensor group is not faulty, otherwise it means that the pressure sensor group is faulty. As a preferred technical solution, in the above measurement method, the error range is changed to a floating threshold value K = C1 + C2 × α + C3 × Ma + C4 × α 2 +C5×α×Ma+C6×Ma 2 ±100, where C1-C6 are the calibration coefficients for odd and even detection values, obtained based on actual pressure measurement data from wind tunnel experiments. Different aircraft should use different calibration systems.

[0026] As a preferred technical solution, before determining the sideslip angle based on data from a pressure sensor effective in the horizontal direction, the method further includes:

[0027] The isolated pressure sensor is monitored in real time within a period of time. If the isolated data is judged to be normal through the parity diagnosis equation within the monitoring time, the calculation is recalculated. Otherwise, the faulty pressure sensor is completely isolated.

[0028] The beneficial effects of this method over the prior art are as follows: based on the classical three-point method principle, this measurement method targets blunt-nosed leading-edge high-speed aircraft, selects seven characteristic hole position combinations from a total of 35 different three-hole combinations for seven pressure measuring hole positions in each vertical or horizontal direction through wind tunnel experiments, and uses the floating threshold value obtained from the experimental results to determine the value of the parity equation to eliminate faulty pressure sensors, thereby ensuring that all pressure acquisition data are accurate.

[0029] On the other hand, the present invention also provides a device for detecting a fault in an embedded air data system of a blunt-nosed aircraft, comprising:

[0030] An acquisition unit, configured to acquire data from a plurality of pressure sensors on the aircraft head; wherein the plurality of pressure sensors are distributed in a cross shape;

[0031] A first constructing unit is configured to construct a first parity equation by selecting a feature combination method based on data from a vertical pressure sensor;

[0032] a first determining unit, configured to determine whether there is a fault in the vertical pressure sensor according to the first parity equation;

[0033] A second construction unit is configured to select a feature combination method to construct a second parity equation based on data from the horizontal pressure sensor;

[0034] a second determining unit, configured to determine whether there is a fault in the horizontal pressure sensor according to the second parity equation;

[0035] a third determining unit configured to determine a faulty pressure sensor by intersecting combinations of failures;

[0036] The fourth determining unit is configured to determine an angle of attack based on data from a pressure sensor effective in a vertical direction and to determine a sideslip angle based on data from a pressure sensor effective in a horizontal direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a flow chart of an aircraft fault detection method provided by one embodiment of the present invention;

[0038] Figure 2 is a distribution diagram of pressure sensors in one embodiment of the present invention;

[0039] Figure 3 This is a schematic diagram of the aircraft head selected in the experimental characteristic hole position combination method in one embodiment of the present invention;

[0040] Figure 4 It is a linear graph showing the value changes of the even-odd equation of the experimental characteristic hole position combination in one embodiment of the present invention.

[0041] Figure 5 This is a structural diagram of an aircraft fault detection device provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0043] Reference Figure 1 This embodiment provides a method for detecting a fault in an embedded air data system of a blunt-nosed aircraft, comprising the following steps:

[0044] S10: Acquire data from a plurality of pressure sensors on the aircraft head, wherein the plurality of pressure sensors are distributed in a cross shape;

[0045] Specifically, in this embodiment, the distribution of pressure sensors is as follows: Figure 2 As shown, they are arranged in a cross shape. In order to facilitate the subsequent explanation, all pressure sensors are numbered in sequence. The specific numbers are as follows Figure 2 shown.

[0046] S20: Based on the data of the vertical pressure sensor, a feature combination method is selected to construct a first parity equation;

[0047] Specifically, according to the three-point method, the pressure (P i 、P j 、P k ) and the incoming incident angle (θ i ,θ j ,θ k ) is shown in the following formula:

[0048]

[0049] The incident angle is related to the incoming flow's angle of attack α, the sideslip angle β, the pressure sensor's circumferential angle φ, and the cone angle λ. The specific formula is as follows:

[0050] cosθ=cosαcosβcosλ+sinβsinφsinλ+sinαcosβcosφsinλ

[0051] From this we can derive the even-odd equation:

[0052]

[0053] Since the angle of attack is mainly the change of the vertical pressure gradient, the feature combination method is selected based on the vertical pressure sensors (pressure sensor position numbers 4, 3, 2, 1, 8, 9, and 10) to construct the odd-even equation.

[0054] Theoretically, there are 35 combinations of pressure sensors, but according to experimental results, Figure 3 As shown, the solutions to the odd-even equations exhibit significant linear variations between combinations with varying angles of attack, and some combinations exhibit similar linear slopes and intercepts. To ensure the simplicity and efficiency of the redundant algorithm, while satisfying redundancy requirements, we extracted the solution data with significant variations in linear slope and intercept based on experimental results as characteristic combinations. These characteristic combinations are 321, 328, 318, 218, 219, 289, and 189. These seven characteristic combinations can be divided into three categories: the combination closest to the center hole (218); combinations located slightly above or below the center (321, 219, 318, and 189); and combinations without a center hole (328 and 289).

[0055] S30: Determine whether there is a fault in the vertical pressure sensor according to the first parity equation;

[0056] Specifically, theoretically, if the result of the left side of formula (2) is 0, it means that the three selected pressure sensors are not faulty and the obtained atmospheric parameters are correct. If the result is not 0, it means that a pressure sensor is faulty and the atmospheric parameters need to be recalculated without the faulty pressure sensor.

[0057] However, in actual situations, the solution on the left side of the parity equation is affected by changes in the aircraft's shape and the collected pressure fluctuations, and it is impossible for it to be constantly zero. Therefore, it is necessary to set a fluctuation range for the solution result. If the solution result is within this range, the pressure sensor is considered to be fault-free; if it is outside this range, it is considered to be faulty.

[0058] According to actual wind tunnel test data, the left-hand side solution of the odd-even equation is affected by the aircraft shape, resulting in significant differences in the solution results under different wind speeds, angles of attack, and sideslip angles. Therefore, it is necessary to set the fluctuation range of the odd-even equation solution based on the wind tunnel test data of different aircraft shapes. The floating threshold K = C1 + C2 × α + C3 × Ma + C4 × α 2 +C5×α×Ma+C6×Ma 2 ±100, where C1-C6 are the calibration coefficients for odd and even detection values, obtained based on actual pressure measurement data from wind tunnel experiments. Different aircraft should use different calibration systems. (i.e. Figure 3 The linear slope and intercept of each line segment in the equation).

[0059] S40: Based on the data of the horizontal pressure sensor, a feature combination method is selected to construct a second parity equation;

[0060] Specifically, the principle is the same as in step S20, and the data of the three pressure sensors in the horizontal direction are taken as a group, and seven groups of feature combinations are selected to construct the second parity equation; the seven groups of feature data include the data of the central pressure sensor and the two pressure sensors closest to the central pressure sensor (1, 5, 11), the data of the central pressure sensor and any two pressure sensors on the left or right side of the upper central pressure sensor (12, 11, 1; 11, 1, 6; 1, 5, 6; 6, 1, 12), and the data of no central pressure sensor (12, 11, 5; 11, 6, 7).

[0061] S50: Determine whether there is a fault in the horizontal pressure sensor according to the second parity equation;

[0062] It should be understood that the specific determination method and principle are the same as those of step S30, and therefore will not be repeated here.

[0063] S60: If a fault condition exists, the faulty pressure sensor is determined by intersecting the failed combinations;

[0064] Specifically, if there is a pressure sensor failure, the failed combinations in the seven pressure sensor combinations are intersected to determine the position of the faulty pressure sensor.

[0065] In another embodiment, in order to further improve the accuracy of the measurement, the isolated pressure sensor position is monitored in real time within a certain time T. If the isolated data is judged to be normal through the parity diagnostic equation within the monitoring time T, the abnormal data is considered to be a system measurement fluctuation and recalculation is performed.

[0066] S70: Isolate the faulty pressure sensor, determine the angle of attack based on the data from the effective pressure sensor in the vertical direction, and determine the sideslip angle based on the data from the effective pressure sensor in the horizontal direction.

[0067] Specifically, the angle of attack data is obtained by using the combination of the fault-free hole positions among the 7 vertical pressure sensor position combinations and taking the average value; similarly, the sideslip angle data is obtained by using the combination of the fault-free hole positions among the 7 horizontal pressure sensor position combinations and taking the average value.

[0068] This measurement method is based on the principle of the classic three-point method. It corrects the odd-even equations of high-speed aircraft with blunt leading edges to eliminate faulty pressure sensors, thereby ensuring that all data used to calculate the aircraft's angle of attack and sideslip angle are accurate, effectively eliminating the impact of pressure fluctuations.

[0069] Reference Figure 5 This embodiment further provides a device for detecting a fault in an embedded air data system of a blunt-nosed aircraft, comprising:

[0070] The acquisition unit 100 is used to acquire data from multiple pressure sensors at the head of the aircraft; wherein the multiple pressure sensors are distributed in a cross shape; it should be noted here that since the specific acquisition method and process have been explained in detail in step S10 of the above-mentioned method for measuring the angle of attack and sideslip angle of the aircraft, they will not be repeated here.

[0071] The first construction unit 200 is used to select a feature combination method to construct a first parity equation based on the data of the vertical pressure sensor; it should be noted here that since the specific construction method and process have been explained in detail in step S20 of the above-mentioned aircraft angle of attack and sideslip angle measurement method, they will not be repeated here.

[0072] The first determination unit 300 is used to determine whether there is a fault in the vertical pressure sensor based on the first parity equation; it should be noted that since the specific determination method and process have been explained in detail in step S30 of the above-mentioned aircraft angle of attack and sideslip angle measurement method, they will not be repeated here.

[0073] The second construction unit 400 is used to select a feature combination method to construct a second parity equation based on the data of the horizontal pressure sensor; it should be noted here that since the specific construction method and process have been explained in detail in step S40 of the above-mentioned aircraft angle of attack and sideslip angle measurement method, they will not be repeated here.

[0074] The second determination unit 500 is used to determine whether there is a fault in the horizontal pressure sensor based on the second parity equation; it should be noted that since the specific determination method and process have been explained in detail in step S50 of the above-mentioned aircraft angle of attack and sideslip angle measurement method, they will not be repeated here.

[0075] The third determination unit 600 is used to determine the faulty pressure sensor by intersecting the failed combinations. It should be noted that the specific determination method and process have been explained in detail in step S60 of the above-mentioned method for measuring the angle of attack and sideslip angle of the aircraft, so they will not be repeated here.

[0076] The fourth determination unit 700 is used to determine the angle of attack based on data from the pressure sensor that is effective in the vertical direction and to determine the sideslip angle based on data from the pressure sensor that is effective in the horizontal direction. It should be noted that the specific determination method and process have been described in detail in step S70 of the above-mentioned method for measuring the angle of attack and sideslip angle of the aircraft, and will not be repeated here.

[0077] In addition, an embodiment of the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium may store a program, which, when executed, includes some or all of the steps of any method for detecting a failure of an embedded atmospheric data system of a blunt-nosed aircraft described in the above method embodiments.

[0078] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0079] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a memory and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, and other media that can store program code.

[0080] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program. The program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0081] The above describes, with reference to the accompanying drawings, an exemplary flowchart of a method for detecting faults in an embedded air data system of a blunt-nosed aircraft according to an embodiment of the present invention. It should be noted that the numerous details included in the above description are merely illustrative of the present invention and are not intended to limit the present invention. In other embodiments of the present invention, the method may include more, fewer, or different steps, and the order, inclusion, functionality, and other relationships between the steps may differ from those described and illustrated.

Claims

1. A method for detecting a fault in an embedded air data system of a blunt-nosed aircraft, characterized in that: include: Obtain data from multiple pressure sensors on the aircraft's head; wherein the plurality of pressure sensors are distributed in a cross shape; Based on the data of the vertical pressure sensor, a feature combination method is selected to construct a first parity equation, and a first specific floating threshold is set; setting the first specific floating threshold includes , where α is the angle of attack of the incoming flow; - is the calibration coefficient for the odd-even detection value, which is obtained based on the actual pressure measurement data of the wind tunnel experiment. Different aircraft flights should use different calibration systems; is the threshold strip width. This range is related to the required resolution accuracy of the aircraft. Here, the fluctuation of the odd and even detection values ​​within the angle of attack resolution accuracy of 0.5° is selected as the strip width. determining whether there is a fault in the vertical pressure sensor according to the first parity equation; Based on the data of the horizontal pressure sensor, a feature combination method is selected to construct a second parity equation, and a second specific floating threshold is set; setting the second specific floating threshold includes , where β is the sideslip angle of the incoming flow; - is the calibration coefficient for the odd-even detection value, which is obtained based on the actual pressure measurement data of the wind tunnel experiment. Different aircraft flights should use different calibration systems; is the threshold strip width. This range is related to the required resolution accuracy of the aircraft. Here, the fluctuation of the odd-even detection value within the sideslip angle resolution accuracy of 0.5° is selected as the strip width. determining whether there is a fault in the horizontal pressure sensor according to the second parity equation; If a fault condition exists, the faulty pressure sensor is determined by intersecting the failed combinations; Isolate the faulty pressure sensor, determine the angle of attack based on the data from the effective pressure sensor in the vertical direction, and determine the sideslip angle based on the data from the effective pressure sensor in the horizontal direction.

2. The detection method according to claim 1, wherein The angle of attack direction is based on the data of the vertical pressure sensor, and the feature combination method is selected to construct the first parity equation, which further includes: Taking the data of three pressure sensors in the vertical direction as a group, seven groups of feature combinations are selected to construct the first parity equation; the seven groups of feature combinations include data from the central pressure sensor and the two pressure sensors closest to the central pressure sensor, data from the central pressure sensor and any two pressure sensors above or below the upper central pressure sensor, and data from no central pressure sensor.

3. The detection method according to claim 2, characterized in that Determining whether there is a fault in the vertical pressure sensor according to the first parity equation further includes: determining whether a result of the first parity equation is within an error range; If yes, it means that the pressure sensor group is normal, otherwise it means that the pressure sensor group is faulty.

4. The detection method according to claim 1, wherein The sideslip angle direction is based on the data of the horizontal pressure sensor, and the feature combination method is selected to construct the second parity equation, which further includes: Taking the data of three pressure sensors in the horizontal direction as a group, seven groups of feature combinations are selected to construct the second parity equation; the seven groups of feature data include data of the central pressure sensor and the two pressure sensors closest to the central pressure sensor, data of the central pressure sensor and any two pressure sensors on the left or right side of the upper central pressure sensor, and data of no central pressure sensor.

5. The detection method according to claim 4, characterized in that Determining whether there is a fault in the horizontal pressure sensor according to the second parity equation further includes: determining whether a result of the second parity equation is within an error range; If yes, it means that the pressure sensor group is normal, otherwise it means that the pressure sensor group is faulty.

6. The detection method according to claim 1, characterized in that Before determining the sideslip angle based on the data of the pressure sensor effective in the horizontal direction, it also includes: The isolated pressure sensor is monitored in real time within a period of time. If the isolated data is judged to be normal through the parity diagnosis equation within the monitoring time, the calculation is recalculated. Otherwise, the faulty pressure sensor is completely isolated.

7. A device for detecting faults in an embedded air data system of a blunt-nosed aircraft, characterized in that: include: An acquisition unit, used to acquire data from multiple pressure sensors on the aircraft head; wherein the plurality of pressure sensors are distributed in a cross shape; The first construction unit is used to select a feature combination method to construct a first parity equation based on the data of the vertical pressure sensor, and set a first specific floating threshold; setting the specific floating threshold includes: , where α is the angle of attack of the incoming flow; - is the calibration coefficient for the odd-even detection value, which is obtained based on the actual pressure measurement data of the wind tunnel experiment. Different aircraft flights should use different calibration systems; is the threshold strip width. This range is related to the required resolution accuracy of the aircraft. Here, the fluctuation of the odd and even detection values ​​within the angle of attack resolution accuracy of 0.5° is selected as the strip width. determining whether there is a fault in the vertical pressure sensor according to the first parity equation; a first determining unit, configured to determine whether there is a fault in the vertical pressure sensor according to the first parity equation; The second construction unit is used to select a feature combination method to construct a second parity equation based on the data of the horizontal pressure sensor, and set a second specific floating threshold; setting the specific floating threshold includes , where β is the sideslip angle of the incoming flow; - is the calibration coefficient for the odd-even detection value, which is obtained based on the actual pressure measurement data of the wind tunnel experiment. Different aircraft flights should use different calibration systems; is the threshold strip width. This range is related to the required resolution accuracy of the aircraft. Here, the fluctuation of the odd-even detection value within the sideslip angle resolution accuracy of 0.5° is selected as the strip width. a second determining unit, configured to determine whether there is a fault in the horizontal pressure sensor according to the second parity equation; a third determining unit, configured to determine a faulty pressure sensor by intersecting combinations of failures; The fourth determining unit is configured to determine an angle of attack based on data from a pressure sensor effective in a vertical direction and to determine a sideslip angle based on data from a pressure sensor effective in a horizontal direction.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for detecting a failure of an embedded air data system of a blunt-nosed aircraft according to any one of claims 1 to 6 are implemented.

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