Civil aircraft ice accumulation diagnosis method, system, device and storage medium

Abstract

The application provides a civil aircraft icing diagnosis method, system, equipment and storage medium, and the method comprises the following steps: obtaining the total temperature of the aircraft according to the environmental temperature, air density, flight speed and environmental pressure; obtaining the aircraft icing index by combining the SFIP algorithm with the total temperature of the aircraft; and judging the icing degree of the aircraft according to the icing index. The total temperature of the aircraft is obtained by the environmental temperature, air density, flight speed and environmental pressure, the aircraft icing index is obtained by combining the SFIP algorithm with the total temperature of the aircraft, and the aircraft power warming effect is considered, which helps to improve the accuracy of the icing diagnosis and prediction algorithm, and is obviously helpful for the accurate planning and safety protection of the flight task. The situation of icing air report is reduced, thereby reducing the waste of airspace resources and improving the test flight progress and efficiency of the aircraft.

Description

Technical Field

[0001] This document relates to the field of aircraft icing diagnostic technology, and in particular to a method, system, device and storage medium for icing diagnostics of civil aircraft. Background Technology

[0002] When an aircraft operates in clouds rich in supercooled water droplets, these droplets adhere to the fuselage surface and condense into ice in certain areas, severely affecting its aerodynamic characteristics. This leads to increased drag, decreased lift, and reduced controllability of the horizontal and vertical stabilizers. In severe cases, it can cause loss of control and result in a flight accident. Since flight records began, nearly 200 serious safety incidents caused by aircraft icing have occurred on domestic and international flights. Between 1999 and 2000, 92% of icing-related accidents were caused by in-flight icing. Accurate in-flight icing prediction is one of the most effective measures to reduce aircraft encounters with icing.

[0003] Aircraft icing prediction is a crucial component of aircraft icing research. The mainstream method for predicting icing events is to combine numerical weather prediction models with icing diagnostic algorithms. Currently, the International Civil Aviation Organization (ICAO) recommended Ic algorithm is commonly used in China. Other common international icing prediction algorithms include RAOB, CIP, and FIP.

[0004] Currently known parameters affecting aircraft icing include ambient temperature, humidity, cloud top temperature, atmospheric vertical velocity, and aircraft airspeed. However, the Ic icing index algorithm used domestically only considers the influence of atmospheric temperature and relative humidity, neglecting the impact of other meteorological factors and aircraft parameters. The fuzzy logic-based FIP algorithm is one of the forecasting algorithms currently used by the US National Oceanic and Atmospheric Administration (NOAA). In 2019, Morcrette, through a study of over 10,000 icing reports, reported a simplified icing forecasting algorithm that comprehensively considers atmospheric influence factors. However, this type of algorithm does not yet consider the impact of aircraft parameters on the diagnosis of aircraft icing potential. Compared to other aircraft, civil aircraft fly at high speeds, high cruising altitudes, and long ranges, making them more susceptible to engine overheating. Commonly used icing forecasting algorithms often result in numerous false alarms during operational use. Furthermore, during civil aircraft test flights, flight safety often necessitates avoiding any potential icing airspace; false alarms of icing weather lead to a significant waste of airspace resources, impacting test flight progress and efficiency. Summary of the Invention

[0005] This invention aims to solve the above-mentioned problems by providing a method, system, device and storage medium for diagnosing icing on civil aircraft.

[0006] This invention provides a method for diagnosing icing on civil aircraft, comprising:

[0007] S1. Obtain the total temperature of the aircraft based on ambient temperature, air density, flight speed, and ambient pressure.

[0008] S2. Obtain the aircraft icing index based on the total aircraft temperature and the SFIP algorithm.

[0009] S3. Determine the degree of icing on the aircraft based on the icing index.

[0010] This invention provides a civil aircraft icing diagnostic system, comprising:

[0011] The aircraft total temperature acquisition module is used to acquire the aircraft's total temperature based on ambient temperature, air density, flight speed, and ambient pressure.

[0012] The icing index acquisition module is used to obtain the aircraft icing index based on the aircraft total temperature and the SFIP algorithm.

[0013] The aircraft icing diagnostic module is used to determine the degree of icing on an aircraft based on the icing index.

[0014] This invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps described in the civil aircraft icing diagnosis method.

[0015] This invention provides a computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps described in the civil aircraft icing diagnosis method.

[0016] This invention obtains the aircraft's total temperature by measuring ambient temperature, air density, flight speed, and ambient pressure. Based on this total temperature and the SFIP algorithm, the aircraft icing index is calculated. Considering the aircraft's dynamic heating effect helps improve the accuracy of icing diagnosis and prediction algorithms, and also significantly aids in accurate flight mission planning and safety protection. This reduces the occurrence of icing-related false alarms, thereby reducing airspace resource waste and improving aircraft test flight progress and efficiency. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1This is a flowchart of a method for diagnosing icing on civil aircraft according to an embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of ice accumulation diagnosis using a conventional ice accumulation algorithm according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of the icing diagnosis method for civil aircraft according to an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of a civil aircraft icing diagnostic system according to an embodiment of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0023] Method Implementation Examples

[0024] This invention provides a method for diagnosing icing on civil aircraft. Figure 1 This is a flowchart of a civil aircraft icing diagnosis method according to an embodiment of the present invention. The civil aircraft icing diagnosis method according to an embodiment of the present invention specifically includes:

[0025] S1. Obtain the aircraft's total temperature based on ambient temperature, air density, flight speed, and ambient pressure; Step S1 specifically includes:

[0026] The total temperature of the aircraft is obtained according to formulas 1-4.

[0027] Pd = 1 / 2 × ρ × v 2 Formula 1;

[0028] Ma = (5 × ((Pd / Ps+1)(r-1) / r-1))0.5 (Formula 2)

[0029] IAS / TAS=1+(r-1) / 2×Ma 2 Formula 3;

[0030] IAS = TAS × (1 + 0.2 × 5 × (ρ × v) 2 / 2 / Ps+1) 2 / 7 -1))-273.15 Formula 4;

[0031] Where IAS is the total temperature of the aircraft, TAS is the ambient temperature, ρ is the air density, v is the flight speed, Ps is the ambient pressure, Pd is the dynamic pressure, Ma is the Mach number, and r is the air adiabatic index, which is taken as 1.4 here.

[0032] S2. Obtain the aircraft icing index based on the total aircraft temperature and the SFIP algorithm.

[0033] In this embodiment of the invention, the SFIP algorithm is used as an algorithm for icing potential diagnosis and prediction to calculate the icing index.

[0034]

[0035] M T M RH M M CLW Let represent the membership functions for temperature, relative humidity, vertical velocity, and cloud water content, respectively. The temperature membership function is as follows:

[0036]

[0037] The membership function for relative humidity is as follows:

[0038]

[0039] The vertical velocity membership function is as follows:

[0040]

[0041] The membership function for the liquid water content in clouds is as follows:

[0042]

[0043] a, b, and c represent the weighting coefficients assigned to each membership function, which are 0.2, 0.45, and 0.35, respectively. Ambient temperature, relative humidity, vertical velocity, and cloud water content are all derived from atmospheric reanalysis data of global climate from the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF). Ambient temperature was used to calculate the above temperature membership functions, and the SFIP icing potential value was calculated and defined as SFIP0.

[0044] In this embodiment of the invention, the total aircraft temperature is obtained according to Formula 4, and the above-mentioned ambient temperature variable is replaced with the total aircraft temperature for calculating the icing index, which is defined as SFIP1.

[0045] IAS = TAS × (1 + 0.2 × 5 × (ρ × v) 2 / 2 / Ps+1) 2 / 7 -1))-273.15 Formula 4;

[0046] Due to aerodynamic heating, aircraft surface temperatures are often higher than ambient temperatures. This prevents icing when supercooled water at higher temperatures collides with the aircraft surface. Icing only occurs when the total temperature satisfies the temperature membership function. Therefore, replacing static temperature with total aircraft temperature aims to reduce the probability of false alarms due to icing.

[0047] S3. Determine the degree of icing on the aircraft based on the icing index. Step S3 specifically includes:

[0048] If SFIP1=0, then the aircraft will not accumulate ice.

[0049] If SFIP1>0 and SFIP1<=0.3, then the aircraft has slight icing.

[0050] If SFIP1 > 0.3 and SFIP1 <= 0.7, then the aircraft has moderate icing.

[0051] If SFIP1 > 0.7, the aircraft has severe icing.

[0052] The following example verifies the scientific validity and accuracy of the aircraft icing diagnosis method that incorporates the aircraft's aerodynamic heating effect. A case of severe aircraft icing is cited below to review the icing weather using the method of this invention, in order to illustrate the advantages of the icing potential algorithm that incorporates the aircraft's dynamic heating effect.

[0053] At 16:00 on January 20, 2022, according to the crew report, severe icing occurred near Xi'an, with the flight altitude at approximately 11,000 Ft (3,300 m) and the flight speed at approximately 103 m / s (230 knots). The aircraft's icing potential was calculated using ERA5 data, covering the latitude and longitude of 34.25°N 109°E.

[0054] Figure 1 As shown, using the original icing potential algorithm, the height layer of severe icing in this case is between 800hPa and 640hPa (1600-3500m). The potential height layer of icing is relatively wide, making it impossible to accurately determine the actual icing height layer.

[0055] Figure 2 As shown, using the icing potential algorithm of this invention, the high-probability icing altitude layer for this icing weather event is located around 630 hPa (3200 m). Around this altitude, the probability of icing decreases linearly. According to the crew report, the actual icing altitude occurred at approximately 3200 m. This indicates that the aircraft's dynamic heating effect is one of the important factors affecting aircraft icing. Considering the aircraft's dynamic heating effect helps improve the accuracy of icing diagnosis and forecasting algorithms, and also significantly contributes to accurate flight mission planning and safety protection.

[0056] By employing the embodiments of the present invention, the following beneficial effects are achieved:

[0057] Considering the thermal effect of aircraft power helps improve the accuracy of icing diagnosis and forecasting algorithms. It also significantly helps in the accurate planning and safety protection of flight missions, reduces the waste of airspace resources caused by air reports of icing weather, and improves the progress and efficiency of flight tests.

[0058] System Implementation Examples

[0059] This invention provides a diagnostic system for icing on civil aircraft. Figure 2 This is a flowchart of a civil aircraft icing diagnostic system according to an embodiment of the present invention. The civil aircraft icing diagnostic system according to an embodiment of the present invention specifically includes:

[0060] The aircraft total temperature acquisition module 40 is used to acquire the aircraft total temperature based on ambient temperature, air density, flight speed and ambient pressure.

[0061] The icing index acquisition module 41 is used to obtain the aircraft icing index based on the total aircraft temperature and the SFIP algorithm.

[0062] The aircraft icing diagnostic module 42 is used to determine the degree of icing on the aircraft based on the icing index.

[0063] The aircraft total temperature acquisition module 40 is specifically used for:

[0064] The total temperature of the aircraft is obtained according to formulas 1-4.

[0065] Pd = 1 / 2 × ρ × v 2 Formula 1;

[0066] Ma = (5 × ((Pd / Ps+1)(r-1) / r-1))0.5 (Formula 2)

[0067] IAS / TAS=1+(r-1) / 2×Ma 2 Formula 3;

[0068] IAS = TAS × (1 + 0.2 × 5 × (ρ × v) 2 / 2 / Ps+1) 2 / 7 -1))-273.15 Formula 4;

[0069] Where IAS is the total temperature of the aircraft, TAS is the ambient temperature, ρ is the air density, v is the flight speed, Ps is the ambient pressure, Pd is the dynamic pressure, Ma is the Mach number, and r is the air adiabatic index, which is taken as 1.4 here.

[0070] The ice accumulation index acquisition module 41 is specifically used for:

[0071] Formula 5;

[0072] M RH M M CLW represents the membership functions of relative humidity, vertical velocity, and cloud liquid water content, respectively, and SFIP0 is the icing index.

[0073] The aircraft icing diagnostic module 42 is specifically used for:

[0074] If SFIP1=0, then the aircraft will not accumulate ice.

[0075] If SFIP1>0 and SFIP1<=0.3, then the aircraft has slight icing.

[0076] If SFIP1 > 0.3 and SFIP1 <= 0.7, then the aircraft has moderate icing.

[0077] If SFIP1 > 0.7, the aircraft has severe icing.

[0078] By employing the embodiments of the present invention, the following beneficial effects are achieved:

[0079] Considering the thermal effect of aircraft power helps improve the accuracy of icing diagnosis and forecasting algorithms. It also significantly helps in the accurate planning and safety protection of flight missions, reduces the waste of airspace resources caused by air reports of icing weather, and improves the progress and efficiency of flight tests.

[0080] Device Example 1

[0081] This invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the steps of the method embodiments described above.

[0082] Device Example 2

[0083] A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the method embodiments described above.

[0084] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for diagnosing icing on civil aircraft, characterized in that, include: S1. Obtain the total temperature of the aircraft based on ambient temperature, air density, flight speed, and ambient pressure. S2. Obtain the aircraft icing index based on the total aircraft temperature and the SFIP algorithm. S3. Determine the degree of icing on the aircraft based on the icing index; Step S1 specifically includes: The total temperature of the aircraft is obtained according to formulas 1-4. Pd = 1 / 2 × ρ × v 2 Official 1; Ma = (5 × ((Pd / Ps+1)(r-1) / r-1))0.5 (Formula 2) IAS / TAS=1+(r-1) / 2×Ma 2 Formula 3; IAS = TAS × (1 + 0.2 × 5 × (ρ × v) 2 / 2 / Ps+1) 2 / 7 -1))-273.15 Formula 4; Where IAS is the total temperature of the aircraft, TAS is the ambient temperature, ρ is the air density, v is the flight speed, Ps is the ambient pressure, Pd is the dynamic pressure, Ma is the Mach number, and r is the air adiabatic index, which is taken as 1.4 here.

2. The method according to claim 1, characterized in that, Step S2 specifically includes: Official 5; M RH M M CLW represents the membership functions for relative humidity, vertical velocity, and cloud water content, respectively, and SFIP1 is the icing index.

3. The method according to claim 2, characterized in that, Step S3 specifically includes: If SFIP1=0, then the aircraft will not accumulate ice. If SFIP1>0 and SFIP1<=0.3, then the aircraft has slight icing. If SFIP1 > 0.3 and SFIP1 <= 0.7, then the aircraft has moderate icing. If SFIP1 > 0.7, the aircraft has severe icing.

4. A diagnostic system for icing on a civil aircraft, characterized in that, include: The aircraft total temperature acquisition module is used to acquire the aircraft's total temperature based on ambient temperature, air density, flight speed, and ambient pressure. The icing index acquisition module is used to obtain the aircraft icing index based on the total aircraft temperature and the SFIP algorithm. The aircraft icing diagnostic module is used to determine the degree of icing on the aircraft based on the icing index. The aircraft total temperature acquisition module is specifically used for: The total temperature of the aircraft is obtained according to formulas 1-4. Pd = 1 / 2 × ρ × v 2 Official 1; Ma = (5 × ((Pd / Ps+1)(r-1) / r-1))0.5 (Formula 2) IAS / TAS=1+(r-1) / 2×Ma 2 Formula 3; IAS = TAS × (1 + 0.2 × 5 × (ρ × v) 2 / 2 / Ps+1) 2 / 7 -1))-273.15 Formula 4; Where IAS is the total temperature of the aircraft, TAS is the ambient temperature, ρ is the air density, v is the flight speed, Ps is the ambient pressure, Pd is the dynamic pressure, Ma is the Mach number, and r is the air adiabatic index, which is taken as 1.4 here.

5. The system according to claim 4, characterized in that, The ice accumulation index acquisition module is specifically used for: Official 5; M RH M M CLW represents the membership functions for relative humidity, vertical velocity, and cloud water content, respectively, and SFIP1 is the icing index.

6. The system according to claim 5, characterized in that, The aircraft icing diagnostic module is specifically used for: If SFIP1=0, then the aircraft will not accumulate ice. If SFIP1>0 and SFIP1<=0.3, then the aircraft has slight icing. If SFIP1 > 0.3 and SFIP1 <= 0.7, then the aircraft has moderate icing. If SFIP1 > 0.7, the aircraft has severe icing.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it performs the steps described in any one of the civil aircraft icing diagnosis methods as claimed in claims 1 to 3.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps described in any one of the civil aircraft icing diagnosis methods as claimed in claims 1 to 3.

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