A fault prediction method based on aviation power supply

Abstract

The present application relates to the technical field of aviation power supply fault prediction, and relates to a fault prediction method based on aviation power supply.The method comprises the following steps: S1, obtaining a flight route, and performing height and temperature analysis along the route; S2, obtaining configuration data and historical voltage data of the aviation power supply, and dividing a flight area according to the height, temperature and configuration data; the present application greatly improves the accuracy of aviation power supply fault prediction through multi-dimensional data fusion and dynamic correction, not only obtains height and temperature basic data of the flight route, but also integrates configuration data, historical voltage data and aircraft parameters of the aviation power supply, thereby providing comprehensive data support for prediction, and at the same time, in the area division link, a differentiated height and temperature tolerance range is set in combination with the power supply stability parameter, so as to ensure that the divided flight area is highly matched with the actual working environment of the power supply.

Description

Technical Field

[0001] This invention relates to the field of aviation power supply failure prediction technology, and more specifically, to a failure prediction method based on aviation power supplies. Background Technology

[0002] In the field of aerospace engineering, aviation power supply is a core component of the aircraft power supply system. Its stable operation directly determines the reliability of the flight control system, avionics equipment and passenger life support system, and is a key link to ensure safe take-off and landing and smooth flight.

[0003] Currently, power supply fault diagnosis relies on monitoring key parameters such as power supply voltage and current, combined with historical fault data, to identify potential power supply fault risks. However, during flight, sudden changes in altitude and temperature fluctuations have a coupled impact on power supply voltage, affecting the aircraft's stability. If existing technologies use uniform parameter thresholds or static models, they cannot adapt to the environmental characteristics of different flight areas, easily leading to a disconnect between prediction results and actual operating conditions, resulting in misjudgment or missed faults, and failing to accurately guarantee the power supply stability during aircraft flight. Therefore, a fault prediction method based on aviation power supplies is proposed. Summary of the Invention

[0004] The purpose of this invention is to provide a fault prediction method based on aviation power supplies to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, a fault prediction method based on aviation power supplies is provided, comprising the following steps:

[0006] S1. Obtain the flight path and perform altitude and temperature analysis along the path;

[0007] S2. Obtain the configuration data and historical voltage data of the aviation power supply, divide the flight area according to the altitude, temperature and configuration data, and analyze the probability of extreme weather in the flight area in combination with the flight time, and add extreme weather labels to the flight area.

[0008] S3. Combine historical voltage data with flight area, altitude, and temperature, and establish a flight simulation model by combining flight route and aircraft parameters. Input the screened voltage data into the flight simulation model, and the flight simulation model outputs the predicted voltage data of the flight area.

[0009] S4. For the same altitude and temperature conditions within the flight area, set basic deviation data by combining predicted voltage data and historical voltage data, and adjust the basic deviation data of the flight area based on the configuration data and work records of the aviation power supply.

[0010] S5. Select the target altitude and temperature within the flight area, set the risk voltage data under the corresponding conditions for the flight area based on the configuration data, and then compare the predicted voltage data with the adjusted basic deviation data and the risk voltage data. If it is not within the range of the risk voltage data, proceed to S6.

[0011] S6. Set impact deviation data for extreme weather, add impact deviation data to flight areas with extreme weather labels and compare again, and predict the risk of aviation power failure based on the comparison results.

[0012] As a further improvement to this technical solution, S1 obtains the fixed flight route of the aircraft, divides the fixed flight route into outbound route and return route, and then determines the flight route in the outbound route and return route according to the flight requirements.

[0013] As a further improvement to this technical solution, S1 performs altitude and temperature analysis based on the determined flight route, prioritizing the analysis from the airport where the aircraft takes off until the aircraft lands at another airport, analyzing the altitude and temperature of all flight positions during the flight process.

[0014] As a further improvement to this technical solution, step S2 is as follows:

[0015] S2.1 Obtain the configuration data and historical voltage data of the aircraft power supply;

[0016] S2.2 Divide the flight route into multiple flight areas based on differences in altitude, temperature, and configuration data.

[0017] Configuration data shows that the higher the stability of the aviation power supply, the greater the allowable range for altitude and temperature differences.

[0018] S2.3 Obtain the flight time of the aircraft corresponding to the aviation power source, and analyze the probability of extreme weather occurrence in the flight area based on the flight time and the meteorological network. Obtain the extreme weather list of the flight area and the probability of occurrence of the extreme weather, and then add extreme weather tags to the flight areas with the extreme weather list.

[0019] As a further improvement to this technical solution, step S2.3 also includes the following steps:

[0020] S2.3.1 Set a retention threshold for extreme weather events;

[0021] S2.3.2. Compare the extreme weather occurrence probability in the extreme weather list of the flight area with the storage threshold. In the comparison results, only extreme weather with an occurrence probability greater than the storage threshold is retained in the extreme weather list.

[0022] As a further improvement to this technical solution, step S3 is as follows:

[0023] S3.1 First, the historical voltage data is divided into regions according to the flight area. Then, the historical voltage data corresponding to the flight area is screened according to altitude and temperature to obtain historical voltage data corresponding to different altitudes and temperatures in the flight area.

[0024] S3.2 Obtain aircraft parameters, then combine aircraft parameters with flight routes to establish a flight simulation model, then input the screened voltage data into the flight simulation model, and use the flight simulation model to simulate the aircraft passing through the flight area in sequence until the flight route is completed.

[0025] S3.3 During the simulation process in S3.2, the aircraft in the flight area is simulated to fly at different temperatures and altitudes, and the voltage data of the aircraft's aviation power supply corresponding to the flight area is recorded. The recorded voltage data is used as the predicted voltage data.

[0026] As a further improvement to this technical solution, step S4 is as follows:

[0027] S4.1 Within the same flight area, select the predicted voltage data and historical voltage data of the aviation power supply under the same altitude and temperature conditions, then analyze the maximum deviation value of the two sets of data, and use the obtained maximum deviation value as the basic deviation data.

[0028] S4.2 Obtain the working record of the aviation power supply, and then adjust the basic deviation data of the flight area according to the configuration data and the working record;

[0029] The more work records there are, the greater the impact on the adjustment of basic deviation data;

[0030] The higher the stability of the configuration data, the smaller the impact on the adjustment of the basic deviation data.

[0031] As a further improvement to this technical solution, step S6 is as follows:

[0032] S6.1 Set corresponding impact deviation data for different extreme weather conditions, and then select the maximum impact deviation data from the extreme weather list of the flight area in the extreme weather label;

[0033] S6.2, Add the data with the largest impact deviation to S5.2 for a second comparison;

[0034] When the predicted voltage data, combined with the basic deviation data and the maximum impact deviation data, falls within the risk voltage data range, it is determined that the aviation power supply is at risk of failure, and maintenance is recommended.

[0035] If the predicted voltage data, combined with the basic deviation data and the maximum impact deviation data, is not within the risk voltage data range, then the aviation power supply prediction is determined to be fault-free.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0037] 1. In this method for predicting the failure of aviation power supply, the accuracy of aviation power supply failure prediction is greatly improved by multi-dimensional data fusion and dynamic correction. It not only obtains basic data such as altitude and temperature of flight route, but also integrates configuration data, historical voltage data and aircraft parameters of aviation power supply to provide comprehensive data support for prediction. At the same time, in the area division process, differentiated altitude and temperature tolerance ranges are set in combination with power supply stability parameters to ensure that the divided flight area is highly matched with the actual working environment of the power supply.

[0038] 2. In this method for predicting the failure of aviation power supply, a dual risk screening system of "normal environment + extreme environment" is constructed. It not only covers the power supply failure risk under normal flight conditions, but also considers the additional impact of special weather such as thunderstorms and extreme high temperatures on the power supply. This avoids the failure to be detected due to extreme environment, and ensures that potential power supply risks can still be accurately identified under complex flight conditions, providing comprehensive protection for flight safety.

[0039] 3. In this fault prediction method based on aviation power supply, a dual deviation correction mechanism is introduced. First, the basic deviation is determined based on the predicted voltage and historical voltage data under the same altitude and temperature conditions. Then, the basic deviation is dynamically adjusted by combining the power supply operation record and configuration stability, which effectively eliminates the inherent error between the prediction model and the actual situation. In addition, the flight simulation model simulates the flight state at different altitudes and temperatures, making the predicted voltage data more consistent with the actual working state of the power supply, providing an accurate benchmark reference for fault judgment. Attached Figure Description

[0040] Figure 1 This is an overall flowchart of the fault prediction method based on aviation power supply of the present invention;

[0041] Figure 2 This is a flowchart illustrating the process of acquiring configuration data and historical voltage data of an aviation power supply according to the present invention.

[0042] Figure 3 This is a flowchart illustrating the process of obtaining historical voltage data for different altitudes and temperatures in a flight area according to the present invention.

[0043] Figure 4 This is a flowchart illustrating the process of obtaining the maximum deviation between predicted voltage data and historical voltage data according to the present invention.

[0044] Figure 5 This is a flowchart illustrating the process of setting risk voltage data for flight areas based on configuration data according to the present invention.

[0045] Figure 6 This is a flowchart illustrating the process of setting corresponding impact deviation data for different extreme weather conditions in this invention. Detailed Implementation

[0046] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0047] Please see Figure 1 - Figure 6 As shown, the purpose of this embodiment is to provide a fault prediction method based on aviation power supplies, including the following steps:

[0048] S1. Obtain the flight route and perform altitude and temperature analysis along the route; clarify the specific flight route and obtain basic altitude and temperature data for the entire route to provide an environmental benchmark for subsequent area division and power analysis, ensuring that the area division matches the actual flight environment;

[0049] S1 obtains the fixed flight routes of the aircraft, divides the fixed flight routes into outbound routes and return routes, and then determines the flight route from the outbound and return routes according to the flight requirements.

[0050] Obtain the fixed flight route information of the flight from the relevant management system or database of the airline. Clearly divide the obtained fixed flight routes into two types: outbound routes and return routes. Based on specific flight needs, such as flight scheduling and passenger travel needs, determine the actual flight route to be executed by the flight from the divided outbound and return routes.

[0051] S1 performs altitude and temperature analysis based on the determined flight route, prioritizing the analysis from the airport where the aircraft takes off until the aircraft lands at another airport, recording the altitude and temperature at all flight positions throughout the flight process.

[0052] For the established flight route, altitude and temperature analysis are conducted. The analysis process starts from the airport where the aircraft takes off and continues along the flight route, analyzing the altitude and temperature at all flight locations until the aircraft lands at another airport, thereby gaining a comprehensive understanding of the altitude and temperature conditions at each location along the flight route.

[0053] S2. Obtain the configuration data and historical voltage data of the aviation power supply, divide the flight area according to altitude, temperature and configuration data, and analyze the probability of extreme weather occurrence in the flight area in combination with flight time, and add extreme weather labels to the flight area; by combining historical data with simulation, obtain voltage prediction values ​​that fit the actual flight scenario, and provide a benchmark reference for fault diagnosis.

[0054] The steps for S2 are as follows:

[0055] S2.1 Obtain the configuration data (including parameters reflecting its stability) and historical voltage data of the aircraft power supply;

[0056] S2.2 Divide the flight route into multiple flight areas based on differences in altitude, temperature, and configuration data.

[0057] Configuration data shows that the higher the stability of the aviation power supply, the greater the allowable range for altitude and temperature differences.

[0058] Based on the stability of the aviation power configuration data, different tolerance ranges for altitude and temperature differences are set. The higher the stability, the larger the allowable range of altitude and temperature differences (i.e., the more tolerant the conditions). Then, according to the rules, all flight positions on the flight route are screened and classified. Continuous positions that meet the same set of altitude and temperature difference conditions are divided into a flight area, ultimately forming multiple independent flight areas.

[0059] S2.3 Obtain the flight time of the aircraft corresponding to the aviation power source, and analyze the probability of extreme weather occurrence in the flight area based on the flight time and the meteorological network. Obtain the extreme weather list of the flight area and the probability of occurrence of each extreme weather event. Then, add extreme weather tags to the flight areas with the extreme weather list. The specific steps are as follows:

[0060] The specific flight times of the aircraft corresponding to the aviation power source are obtained from the flight scheduling system, including departure time, estimated time of passage through each flight area, and landing time. Based on the obtained flight times and combined with historical and real-time meteorological data provided by the meteorological network, the extreme weather that may occur in each flight area within the corresponding time period is analyzed to determine the types of extreme weather that may occur in each flight area (such as thunderstorms, strong winds, extreme high temperatures, etc.) and the probability of occurrence of each type of extreme weather. Then, an extreme weather list containing extreme weather types and their corresponding probabilities is compiled for each flight area. For flight areas with extreme weather lists, extreme weather tags are added to indicate that the area may be affected by extreme weather.

[0061] S2.3 also includes the following steps:

[0062] S2.3.1. Based on aviation safety standards and flight requirements, set a retention threshold for extreme weather, which is the minimum probability standard for determining whether extreme weather needs to be retained.

[0063] S2.3.2. Compare the extreme weather occurrence probability in the extreme weather list of the flight area with the storage threshold. In the comparison results, only extreme weather with an occurrence probability greater than the storage threshold is retained in the extreme weather list.

[0064] S3. Combine historical voltage data with flight area, altitude, and temperature, and establish a flight simulation model by combining flight route and aircraft parameters. Input the screened voltage data into the flight simulation model, and the flight simulation model outputs the predicted voltage data of the flight area. Using historical data and simulation model, predict the power supply voltage of each flight area at a specific altitude and temperature to obtain the basic prediction value. By combining historical data with simulation, obtain the voltage prediction value that fits the actual flight scenario, and provide a benchmark reference for fault diagnosis.

[0065] The steps for S3 are as follows:

[0066] S3.1 First, the historical voltage data is divided into regions according to the flight area. Then, the historical voltage data corresponding to the flight area is screened according to altitude and temperature to obtain historical voltage data corresponding to different altitudes and temperatures in the flight area.

[0067] S3.2 Obtain aircraft parameters (various parameters, such as aircraft type, load, engine performance, etc.), then combine the aircraft parameters with the flight route to establish a flight simulation model, then input the screened voltage data into the flight simulation model, and simulate the aircraft passing through the flight area in sequence through the flight simulation model until the flight route is completed;

[0068] S3.3. During the simulation in S3.2, the aircraft in the flight area is simulated to fly at different temperatures and altitudes, and the voltage data of the aircraft's aviation power supply corresponding to the flight area is recorded. The recorded voltage data is used as the predicted voltage data, as shown in the following formula:

[0069] ;

[0070] Among them, U y (z, t, A, L) k Let be the predicted voltage data for the k-th flight area, z be the flight altitude, t be the ambient temperature, A be the set of aircraft parameters, and L be the ambient temperature. k Let k be the route characteristic parameter of the k-th flight area. s (z, A) is the height-load coupling loss coefficient, U l (z, t) represents the historical voltage data after screening, ΔU w(t, A) is the temperature-load compensation voltage, ΔU q (L) k ) represents the regional characteristic correction voltage, and ε represents the model error term, reflecting random disturbances (such as power supply instantaneous fluctuations and sensor errors) that are not covered by the above factors.

[0071] ;

[0072] Where α is a constant loss coefficient, determined by the power supply hardware characteristics. For height-standardized items, such as the standardized value of 10,000 meters for height is 1. For load standardization, A2 represents the predicted total load of the avionics system during flight. 20 The baseline load for the avionics system (the total design rated load of the avionics system for this aircraft type under standard cruise conditions, extracted from the aircraft technical manual or avionics system design documents).

[0073] ;

[0074] Where β is a temperature coefficient constant, t0 is the reference temperature, and the greater the deviation of temperature t from the reference temperature, the lower the engine power. The larger, For the engine power normalization term, A1 is the expected engine output power during predicted flight, A 10 The engine's reference operating power (the design rated power of this aircraft under standard operating conditions, extracted from the aircraft technical manual or the equipment parameter library provided by the manufacturer) is used. Higher engine power results in a greater heat dissipation load within the cabin and more unstable operating temperature of the power supply environment. This standardized term quantifies the amplification effect of engine power on temperature. (t-t0) represents the temperature deviation term, ΔU. w Used to compensate for this deviation;

[0075] ;

[0076] Where γ is a region coefficient constant, v k Let L be the expected flight speed of the k-th region, and L be the length of the region. k The longer the flight speed v k The slower (the longer the time spent in the area). This is a standardized term for the area length; for example, the standardized value for a 500-meter area is 5. This is a flight speed correction term, where v0 is the baseline flight speed (extracted from the aircraft technical manual). If the expected flight speed v k If the speed is below the baseline flight speed v0, the coefficient is greater than 1, which means that the power source stays in the area for a longer time and the cumulative effect of the environment on the voltage is more significant.

[0077] S4. For the same altitude and temperature conditions within the flight area, set basic deviation data by combining predicted voltage data and historical voltage data. At the same time, adjust the basic deviation data of the flight area based on the configuration data and work records of the aviation power supply. Determine the deviation benchmark between the predicted voltage and the historical voltage, and correct the deviation by combining the power supply's own status to improve the prediction accuracy. Through deviation correction, eliminate the inherent error between the prediction model and the actual situation, and make the predicted value closer to the actual working state of the power supply.

[0078] The steps for S4 are as follows:

[0079] S4.1 Within the same flight area, filter out the predicted voltage data and historical voltage data of the aviation power supply under the same altitude and temperature conditions (ensure that the environmental conditions of the two sets of data are completely consistent to avoid inaccurate deviation analysis due to differences in altitude or temperature). Then, perform maximum deviation value analysis on the two sets of data. For the filtered data, calculate the difference (i.e., deviation value) between each set of predicted voltage data and the corresponding historical voltage data. Record all the calculated deviation values ​​to form a set of deviation values. Find the value with the largest absolute value and determine the maximum deviation value as the basic deviation data of the flight area under the current altitude and temperature conditions.

[0080] S4.2 Obtain the working records of the aviation power supply (including cumulative working time, past maintenance times, load change records, etc.), and then adjust the basic deviation data of the flight area based on the configuration data (such as rated power, voltage fluctuation range, anti-interference capability, etc.) and the working records;

[0081] The more work records there are (such as longer cumulative work hours and more detailed maintenance records), the greater the impact on the adjustment of basic deviation data;

[0082] The higher the stability of the configuration data (e.g., the smaller the voltage fluctuation range and the stronger the anti-interference capability), the smaller the impact on the adjustment of the basic deviation data, as shown in the following formula:

[0083] ;

[0084] Among them, D tz For the adjusted baseline deviation data, D jc The baseline deviation data before adjustment, m gz The work record influence coefficient, determined by industry experience or historical data fitting, is used to quantify the impact of work records on the adjustment range. W represents the work record weight; the more work records there are, the closer the weight is to 1. wd The stability impact coefficient is determined by the power supply hardware characteristics and is used to quantify the impact of configuration stability on the adjustment range. S is the configuration stability weight, and the configuration data shows that the higher the stability, the closer it is to 1.

[0085] S5. Select the target altitude and temperature within the flight area, set the risk voltage data under the corresponding conditions for the flight area based on the configuration data, and then compare the predicted voltage data with the adjusted basic deviation data and the risk voltage data. If it is not within the risk voltage data range, proceed to S6. Based on the predicted voltage and the corrected deviation data, compare it with the risk threshold to preliminarily determine the fault risk in the absence of extreme weather, complete the fault screening under normal conditions, and quickly identify high-risk situations.

[0086] The steps for S5 are as follows:

[0087] S5.1 Select the flight altitude and temperature for each flight area based on the flight time and flight route;

[0088] By combining the specific flight time of the flight (such as departure time, estimated time of passing through each area, and landing time) and the divided flight route, we analyze the typical environmental conditions of each flight area when the flight passes through it, and select the most likely flight altitude and temperature for each flight area during this flight to ensure that the selected parameters fit the actual flight scenario.

[0089] At the same time, risk voltage data is set for the flight area based on the configuration data;

[0090] Based on the configuration data of the aviation power supply (including the rated voltage of the power supply, the voltage fluctuation range under rated load, the limit operating voltage threshold, etc.), and combined with the environmental characteristics of different flight areas (such as the potential impact of altitude and temperature on power supply performance), corresponding risk voltage data (i.e. the voltage range in which the power supply is at risk of failure) are set for each flight area.

[0091] S5.2. Extract the corresponding predicted voltage data based on the selected flight altitude and temperature of the flight area. Compare the predicted voltage data with the adjusted baseline deviation data from S4.2 and the risk voltage data. The steps are as follows:

[0092] Based on the selected flight altitude and temperature for each flight area, the predicted voltage data corresponding to those altitude and temperature conditions is extracted from the predicted voltage data previously generated by the flight simulation model. This ensures that the data accurately matches the regional environmental parameters. Then, the extracted predicted voltage data is combined with the adjusted baseline deviation data to obtain a comprehensive voltage reference value (i.e., the actual voltage prediction range after considering deviation correction). Finally, the comprehensive voltage reference value is compared with the risk voltage data set for that flight area. The comparison results are as follows:

[0093] When the predicted voltage data combined with the basic deviation data (combined into a comprehensive voltage reference value) falls within the risk voltage data range, it is determined that the aircraft power supply is at risk of failure, and maintenance is recommended.

[0094] If the predicted voltage data combined with the basic deviation data (combined into a comprehensive voltage reference value) is not within the risk voltage data range, then proceed to S6 for a secondary comparison under the influence of extreme weather conditions.

[0095] S6. For extreme weather conditions, set impact deviation data, add impact deviation data to flight areas tagged with extreme weather for further comparison, and predict aviation power supply failure risks based on the comparison results. Introducing the impact of extreme weather on power supplies provides secondary verification of failure risks, covers potential hazards under special environments, supplements the additional impact of extreme environments on power supplies, avoids omissions due to special weather conditions, and improves the comprehensiveness of predictions.

[0096] The steps for S6 are as follows:

[0097] S6.1 Set corresponding impact deviation data for different extreme weather conditions, and then select the maximum impact deviation data from the extreme weather list of the flight area in the extreme weather label;

[0098] Based on the impact of different types of extreme weather (such as thunderstorms, extreme high temperatures, strong crosswinds, icing, etc.) on aviation power supply voltage, and combined with historical fault data and power supply performance test results, corresponding impact deviation data (i.e. the maximum fluctuation value that may cause the power supply voltage to deviate from the normal range under this weather condition) are set for each type of extreme weather. For example, thunderstorm weather may cause voltage fluctuations of ±3V, and extreme high temperatures may cause voltage fluctuations of ±2.5V.

[0099] S6.2, Add the data with the largest impact deviation to S5.2 for a second comparison;

[0100] The comparison method is the same as the comparison method in S5.2 above, except that the maximum influence deviation value is added on the basis of S5.2;

[0101] When the predicted voltage data, combined with the basic deviation data and the maximum impact deviation data, falls within the risk voltage data range, it is determined that the aircraft power supply is at risk of failure, and maintenance of the aircraft power supply is recommended.

[0102] If the predicted voltage data, combined with the basic deviation data and the maximum impact deviation data, is not within the risk voltage data range, then the aircraft power supply prediction is deemed fault-free and the flight mission can be performed normally.

[0103] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A fault prediction method based on aviation power supply, characterized in that: Includes the following steps: S1. Obtain the flight path and perform altitude and temperature analysis along the path; S2. Obtain the configuration data and historical voltage data of the aviation power supply, divide the flight area according to the altitude, temperature and configuration data, and analyze the probability of extreme weather in the flight area in combination with the flight time, and add extreme weather labels to the flight area. S3. Combine historical voltage data with flight area, altitude, and temperature, and establish a flight simulation model by combining flight route and aircraft parameters. Input the screened voltage data into the flight simulation model, and the flight simulation model outputs the predicted voltage data of the flight area. S4. For the same altitude and temperature conditions within the flight area, set basic deviation data by combining predicted voltage data and historical voltage data, and adjust the basic deviation data of the flight area based on the configuration data and work records of the aviation power supply. The steps for S5 are as follows: S5.1 Select the flight altitude and temperature for each flight area based on the flight time and flight route, and set the risk voltage data for the flight area based on the configuration data. S5.2 Extract the corresponding predicted voltage data based on the selected flight altitude and temperature of the flight area, and compare the predicted voltage data with the adjusted basic deviation data and risk voltage data. If the predicted voltage data combined with the adjusted baseline deviation data falls within the risk voltage range, the aircraft power supply is deemed to be at risk of failure, and maintenance is recommended. If the predicted voltage data combined with the adjusted baseline deviation data is not within the risk voltage data range, then proceed to S6 for a second comparison. S6. Set impact deviation data for extreme weather, add impact deviation data to flight areas with extreme weather labels and compare again, and predict the risk of aviation power failure based on the comparison results.

2. The fault prediction method based on aviation power supply according to claim 1, characterized in that: S1 obtains the fixed flight route of the aircraft, divides the fixed flight route into outbound route and return route, and then determines the flight route in the outbound route and return route according to the flight requirements.

3. The fault prediction method based on aviation power supply according to claim 1, characterized in that: S1 performs altitude and temperature analysis based on the determined flight route, prioritizing the analysis from the airport where the aircraft takes off until the aircraft lands at another airport, recording the altitude and temperature at all flight positions during the flight process.

4. The fault prediction method based on aviation power supply according to claim 1, characterized in that: The steps in S2 are as follows: S2.1 Obtain the configuration data and historical voltage data of the aircraft power supply; S2.2 Divide the flight route into multiple flight areas based on differences in altitude, temperature, and configuration data. Configuration data shows that the higher the stability of the aviation power supply, the greater the allowable range for altitude and temperature differences. S2.3 Obtain the flight time of the aircraft corresponding to the aviation power source, and analyze the probability of extreme weather occurrence in the flight area based on the flight time and the meteorological network. Obtain the extreme weather list of the flight area and the probability of occurrence of the extreme weather, and then add extreme weather tags to the flight areas with the extreme weather list.

5. The fault prediction method based on aviation power supply according to claim 4, characterized in that: S2.3 further includes the following steps: S2.3.1 Set a retention threshold for extreme weather events; S2.3.

2. Compare the extreme weather occurrence probability in the extreme weather list of the flight area with the storage threshold. In the comparison results, only extreme weather with an occurrence probability greater than the storage threshold is retained in the extreme weather list.

6. The fault prediction method based on aviation power supply according to claim 1, characterized in that: The steps in S3 are as follows: S3.1 First, the historical voltage data is divided into regions according to the flight area. Then, the historical voltage data corresponding to the flight area is screened according to altitude and temperature to obtain historical voltage data corresponding to different altitudes and temperatures in the flight area. S3.2 Obtain aircraft parameters, then combine aircraft parameters with flight routes to establish a flight simulation model, then input the screened voltage data into the flight simulation model, and use the flight simulation model to simulate the aircraft passing through the flight area in sequence until the flight route is completed. S3.3 During the simulation process in S3.2, the aircraft in the flight area is simulated to fly at different temperatures and altitudes, and the voltage data of the aircraft's aviation power supply corresponding to the flight area is recorded. The recorded voltage data is used as the predicted voltage data.

7. The fault prediction method based on aviation power supply according to claim 1, characterized in that: The steps in S4 are as follows: S4.1 Within the same flight area, select the predicted voltage data and historical voltage data of the aviation power supply under the same altitude and temperature conditions, then analyze the maximum deviation value of the two sets of data, and use the obtained maximum deviation value as the basic deviation data. S4.2 Obtain the working record of the aviation power supply, and then adjust the basic deviation data of the flight area according to the configuration data and the working record; The more work records there are, the greater the impact on the adjustment of basic deviation data; The higher the stability of the configuration data, the smaller the impact on the adjustment of the basic deviation data.

8. The fault prediction method based on aviation power supply according to claim 1, characterized in that: The steps in S6 are as follows: S6.1 Set corresponding impact deviation data for different extreme weather conditions, and then select the maximum impact deviation data from the extreme weather list of the flight area in the extreme weather label; S6.2, Add the data with the largest impact deviation to S5.2 for a second comparison; When the predicted voltage data, combined with the basic deviation data and the maximum impact deviation data, falls within the risk voltage data range, it is determined that the aviation power supply is at risk of failure, and maintenance is recommended. If the predicted voltage data, combined with the basic deviation data and the maximum impact deviation data, is not within the risk voltage data range, then the aviation power supply prediction is determined to be fault-free.

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