On-line fault diagnosis method, system and equipment for undercarriage and medium

Abstract

The invention discloses an on-line fault diagnosis method, an on-line fault diagnosis system, on-line fault diagnosis equipment and a medium for an undercarriage, and relates to the technical field of fault data monitoring. And acquiring historical fuselage vertical acceleration of a corresponding vibration response case from the vibration response case data according to the vertical landing speed of the aircraft, performing fault detection according to the time domain index data, the frequency domain index data and the historical fuselage vertical acceleration, and outputting a fault level diagnosis result based on similarity analysis. Fault diagnosis of the undercarriage system is realized by factually analyzing the flight state and fuselage dynamic response of the aircraft in the takeoff and landing processes of the aircraft, and faults can be diagnosed more accurately by analyzing the dynamic response of the undercarriage system in the landing process of the aircraft in real time. Meanwhile, the problems that the undercarriage maintenance depends on a manual and the system maintenance labor cost is high are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault data monitoring, and in particular to a landing gear online fault diagnosis method, system, equipment and medium. Background Art

[0002] The health of the landing gear system directly determines aircraft landing safety. Currently, landing gear system fault diagnosis primarily relies on scheduled inspections and maintenance based on collected maintenance manuals. This involves manual testing based on the maintenance manual. Faults not listed in the manual cannot be monitored, and manual fault monitoring cannot reveal the cause of the fault. Fault diagnosis can only be determined by comparing the manual with the instructions. This health management approach suffers from limitations such as high reliance on the manual and maintenance personnel's experience, lack of predictive power, high labor costs, and lengthy maintenance times. The landing gear online fault diagnosis system primarily monitors and diagnoses landing gear system health by analyzing data collected by sensors installed on the aircraft. However, many aircraft landing gear systems lack sensors for monitoring landing gear status. The drilling and slotting required to install additional sensors can compromise the safety of the landing gear structure, making it difficult to meet airworthiness certification requirements. Summary of the Invention

[0003] The technical problem addressed by this invention is the inaccurate monitoring accuracy of existing monitoring methods, which prevent real-time monitoring. The goal is to provide a landing gear online fault diagnosis method, system, device, and medium. This method analyzes the aircraft's flight state and the dynamic response of the fuselage during takeoff and landing to diagnose landing gear system faults. By analyzing the dynamic response of the landing gear system during landing in real time, faults can be diagnosed more accurately. This method also addresses the manual-dependent maintenance and high labor costs associated with system overhaul, thereby enabling efficient fault prediction and health management.

[0004] The present invention is achieved through the following technical solutions: A first aspect of the present invention provides a landing gear online fault diagnosis method, comprising the following specific steps: Real-time acquisition of the aircraft's vertical landing speed and fuselage vertical acceleration when the wheels touch the ground during landing; Obtain historical landing data and build a database of vibration response cases; Obtaining a historical fuselage vertical acceleration corresponding to a vibration response case from a vibration response case database according to the vertical landing speed of the aircraft; Perform time domain analysis and frequency domain analysis on the vertical acceleration of the fuselage collected in real time to obtain time domain index data and frequency domain index data; Combine time domain index data, frequency domain index data and historical fuselage vertical acceleration to perform fault detection and obtain time domain detection results and frequency domain detection results; Performing similarity analysis on the time domain detection results and the frequency domain detection results to obtain similarity analysis results; According to the similarity analysis result, a fault level diagnosis result is output.

[0005] Furthermore, fault detection is performed by combining time domain indicator data and historical fuselage vertical acceleration, specifically including: Compare the aircraft's vertical landing speed with the corresponding vibration response case data to determine whether it is the normal fuselage vertical acceleration; If so, the vertical acceleration of the fuselage in the vibration response case database under normal conditions and the fuselage acceleration signal collected in real time by the sensor are obtained; Periodically calculating the root mean square value of the fuselage acceleration signal to obtain the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions and the root mean square value of the fuselage acceleration signal collected in real time by the sensor; The root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions is compared with the root mean square value of the fuselage acceleration signal collected by the sensor in real time. The presence of a landing gear fault and the type of fault are determined based on the root mean square value.

[0006] Furthermore, judging whether a fault exists based on the root mean square value specifically includes: determining whether a root mean square value deviation of landing acceleration within a first set time exceeds a set threshold; If the deviation exceeds the set threshold, the fault type is determined to be a damping fault; determining whether a root mean square value deviation of the landing acceleration within a second set time exceeds a set threshold; If the deviation exceeds the set threshold, the fault type is determined to be a stiffness fault; If the RMS deviation does not exceed the set threshold, it is determined that the landing gear has no fault.

[0007] Furthermore, the frequency domain index data and historical fuselage vertical acceleration are combined to perform fault detection, including: Obtaining the vertical acceleration of the fuselage in a vibration response case database under normal conditions, and calculating the vertical vibration duration of the fuselage of the vertical acceleration in the vibration response case database; Obtaining the vertical acceleration of the fuselage collected by the sensor in real time, and calculating the duration of the vertical vibration of the fuselage based on the vertical acceleration of the fuselage collected by the sensor in real time; The vertical vibration duration of the fuselage vertical acceleration in the vibration response case database is compared with the vertical vibration duration of the fuselage vertical acceleration collected by the sensor in real time. If the ratio exceeds the set threshold, it is determined that abnormal vibration exists in the aircraft fuselage.

[0008] Furthermore, the similarity analysis of the time domain detection results and the frequency domain detection results specifically includes: Calculating the similarity between the time domain index data and the vibration response case corresponding to the vertical landing speed of the aircraft collected in real time to obtain the time domain similarity; Calculating the similarity between the frequency domain index data and the historical fuselage vertical acceleration of the corresponding vibration response case obtained from the vibration response case database according to the vertical landing speed of the aircraft to obtain the frequency domain similarity; The fault level is determined by combining the time domain similarity, frequency domain similarity, fault type and abnormal vibration judgment results of the fuselage.

[0009] A second aspect of the present invention provides a landing gear online fault diagnosis system, comprising: Aircraft landing status monitoring unit, used to collect real-time vertical landing speed of the aircraft when the wheels touch the ground during landing; The fuselage response acquisition unit is used to collect the vertical acceleration of the aircraft fuselage in real time; a fault type determination unit configured to obtain historical landing data and construct a vibration response case database; obtain vibration response case data corresponding to the aircraft's vertical landing speed and the fuselage's vertical acceleration from the fuselage vibration response database; perform time domain analysis and frequency domain analysis on the fuselage's vertical acceleration to obtain time domain index data and frequency domain index data; perform fault detection based on the time domain index data, the frequency domain index data, and the vibration response case data corresponding to the aircraft's vertical landing speed and the fuselage's vertical acceleration to obtain time domain detection results and frequency domain detection results; and perform similarity analysis on the time domain detection results and the frequency domain detection results to obtain a similarity analysis result. The fault level judgment unit outputs a fault level diagnosis result according to the similarity analysis result.

[0010] Furthermore, the aircraft landing status monitoring unit includes a gyroscope sensor, the fault type judgment unit includes an acceleration sensor, and the gyroscope sensor and the acceleration sensor are both arranged on the landing gear.

[0011] Furthermore, the fault type determination unit includes: a time domain analysis unit, configured to perform time domain analysis on the fuselage vertical acceleration collected in real time, including obtaining the fuselage vertical acceleration in a vibration response case database under normal conditions and the fuselage acceleration signal collected in real time by the sensor, periodically calculating the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions and the root mean square value of the fuselage acceleration signal collected in real time by the sensor, comparing the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions with the root mean square value of the fuselage acceleration signal collected in real time by the sensor, and determining whether there is a landing gear fault and the type of fault based on the root mean square value; The frequency domain analysis unit is used to perform frequency domain analysis on the fuselage vertical acceleration collected in real time, including obtaining the fuselage vertical acceleration in a vibration response case database under normal conditions and the fuselage vertical acceleration collected in real time by the sensor, and obtaining a judgment result on abnormal aircraft fuselage vibration based on the calculated fuselage vertical vibration duration of the fuselage vertical acceleration in the vibration response case database and the calculated fuselage vertical vibration duration of the fuselage vertical acceleration collected in real time by the sensor.

[0012] A similarity analysis unit is configured to calculate the similarity between the time-domain index data and a vibration response case corresponding to the aircraft's vertical landing speed collected in real time, and to calculate the similarity between the frequency-domain index data and a historical fuselage vertical acceleration corresponding to a vibration response case obtained from a vibration response case database based on the aircraft's vertical landing speed.

[0013] A third aspect of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for online fault diagnosis of a landing gear is implemented.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a landing gear online fault diagnosis method.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: By analyzing the aircraft's flight status and the dynamic response of the fuselage during takeoff and landing, the system can diagnose landing gear system faults. By analyzing the dynamic response of the landing gear system during landing in real time, faults can be diagnosed more accurately, solving the problem of manual reliance on landing gear maintenance and high labor costs for system maintenance. The landing gear fault diagnosis system is installed inside the aircraft fuselage and can be installed in the cockpit or cabin floor. It does not need to be installed on the landing gear structure and will not damage the landing gear structure, so as to pass the aircraft airworthiness certification. The landing gear online fault diagnosis system based on aircraft fuselage response can realize landing gear fault diagnosis without affecting the landing gear structure, which can save labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for use in the examples. It should be understood that the following drawings only illustrate certain embodiments of the present invention and should not be considered as limiting the scope. A person of ordinary skill in the art can also derive other relevant drawings based on these drawings without inventive effort. In the drawings: Figure 1is the diagnostic method in an embodiment of the present invention; Figure 2 A diagnostic system in an embodiment of the present invention; Figure 3 A fault type determination unit in an embodiment of the present invention; Figure 4 The vertical acceleration of the fuselage in the vibration response case database under normal conditions and the fuselage acceleration signal collected by the sensor in an embodiment of the present invention; Figure 5 The first time domain data of the vertical acceleration of the fuselage and the fuselage acceleration signal collected by the sensor in the vibration response case database under normal conditions in the embodiment of the present invention; Figure 6 The second time domain data of the vertical acceleration of the fuselage and the fuselage acceleration signal collected by the sensor in the vibration response case database under normal conditions in the embodiment of the present invention; Figure 7 It is the vertical acceleration of the fuselage in the vibration response case database under normal conditions in an embodiment of the present invention and the frequency domain data of the fuselage acceleration signal collected by the sensor. DETAILED DESCRIPTION

[0017] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with examples and drawings. The exemplary embodiments of the present invention and their descriptions are only used to explain the present invention and are not intended to limit the present invention.

[0018] Prognostics and Health Management (PHM) is widely used in various fields, primarily in the field of aviation engines, particularly in intelligent aircraft monitoring systems. It covers several functions, including aircraft system condition monitoring, health assessment, fault prediction, and maintenance planning. Through condition-based maintenance (CBM), PHM systems record and analyze the health data of electronic systems to achieve system health management. With technological advancements, PHM systems will become more intelligent and automated, enabling more accurate fault prediction, reducing unplanned downtime, and improving equipment reliability and efficiency. Existing PHM systems have the following problems: Currently, landing gear fault diagnosis relies primarily on maintenance manuals and manual experience, resulting in high labor costs, an inability to detect faults not included in the manual, and a reliance on experience for fault diagnosis accuracy; pressure gauges can only monitor the air pressure of oil-gas shock absorbers, but cannot monitor internal structures that also affect shock absorber performance. Therefore, based on the above technical issues, this embodiment further improves existing prognostic and health management methods, resulting in the following specific implementation details: As a possible implementation method, based on the following issues: A. Nose landing gear fault diagnosis mainly relies on maintenance manuals and manual experience, which has high labor costs, cannot detect faults not included in the manual, and the accuracy of fault diagnosis depends on experience; B. Currently, most aircraft, especially general aviation aircraft, have no online fault diagnosis problems on their landing gear. This embodiment provides a landing gear online fault diagnosis method, such as Figure 1 As shown, the following specific steps are included: Collect the aircraft's vertical landing speed and fuselage vertical acceleration when the wheels touch the ground during landing; Obtain historical landing data and build a database of vibration response cases; Obtaining the historical fuselage vertical acceleration of the corresponding vibration response case from the vibration response case data according to the vertical landing speed of the aircraft; Obtain the aircraft vertical landing speed from the vibration response case database to obtain the corresponding historical fuselage vertical acceleration; Perform time domain analysis and frequency domain analysis on the collected vertical acceleration of the fuselage to obtain time domain index data and frequency domain index data; Combine time domain index data, frequency domain index data and historical fuselage vertical acceleration to perform fault detection and obtain time domain detection results and frequency domain detection results; Performing similarity analysis on the time domain detection results and the frequency domain detection results to obtain similarity analysis results; According to the similarity analysis results, the fault level diagnosis results are output.

[0019] In some possible implementations, fault detection is performed by combining time-domain indicator data and historical fuselage vertical acceleration, specifically including: Compare the aircraft's vertical landing speed with the corresponding vibration response case data to determine whether it is the normal fuselage vertical acceleration; If so, the vertical acceleration of the fuselage in the vibration response case database under normal conditions and the fuselage acceleration signal collected by the sensor are obtained; Periodically calculating the root mean square value of the fuselage acceleration signal to obtain the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions and the root mean square value of the fuselage acceleration signal collected by the sensor; The root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions is compared with the root mean square value of the fuselage acceleration signal collected by the sensor. The presence of a landing gear fault and the type of fault are determined based on the root mean square value.

[0020] In some possible implementations, determining whether a fault exists based on the RMS value specifically includes: determining whether a root mean square value deviation of landing acceleration within a first set time exceeds a set threshold; If the deviation exceeds the set threshold, the fault type is determined to be a damping fault; determining whether a root mean square value deviation of the landing acceleration within a second set time exceeds a set threshold; If the deviation exceeds the set threshold, the fault type is determined to be a stiffness fault; If the RMS deviation does not exceed the set threshold, it is determined that the landing gear has no fault.

[0021] In some possible implementations, fault detection is performed by combining frequency domain indicator data and historical fuselage vertical acceleration, specifically including: Obtaining the vertical acceleration of the fuselage in a vibration response case database under normal conditions, and calculating the vertical vibration duration of the fuselage of the vertical acceleration in the vibration response case database; Obtaining the vertical acceleration of the fuselage collected by the sensor, and calculating the duration of the vertical vibration of the fuselage based on the vertical acceleration of the fuselage collected by the sensor; The vertical vibration duration of the fuselage vertical acceleration in the vibration response case database is compared with the vertical vibration duration of the fuselage vertical acceleration collected by the sensor. If the ratio exceeds the set threshold, it is determined that abnormal vibration exists in the aircraft fuselage.

[0022] In some possible implementations, performing similarity analysis on the time domain detection results and the frequency domain detection results specifically includes: Calculate the similarity between the time domain index data and the vibration response case corresponding to the collected aircraft vertical landing speed to obtain the time domain similarity; Calculate the similarity between the frequency domain index data and the historical fuselage vertical acceleration of the corresponding vibration response case obtained from the vibration response case data according to the vertical landing speed of the aircraft to obtain the frequency domain similarity; The fault level is determined by combining the time domain similarity, frequency domain similarity, fault type and abnormal vibration judgment results of the fuselage.

[0023] As a possible implementation, Figure 2 As shown, this embodiment provides a landing gear online fault diagnosis system, including: Aircraft landing status monitoring unit, used to collect the aircraft's vertical landing speed when the wheels touch the ground during landing; The fuselage response acquisition unit is used to collect the vertical acceleration of the aircraft fuselage; a fault type determination unit configured to obtain historical landing data and construct a vibration response case database; obtain vibration response case data corresponding to the aircraft's vertical landing speed and the fuselage's vertical acceleration from the fuselage vibration response database; perform time domain analysis and frequency domain analysis on the fuselage's vertical acceleration to obtain time domain index data and frequency domain index data; perform fault detection based on the time domain index data, frequency domain index data, and the vibration response case data corresponding to the aircraft's vertical landing speed and the fuselage's vertical acceleration to obtain time domain detection results and frequency domain detection results; and perform similarity analysis on the time domain detection results and the frequency domain detection results to obtain similarity analysis results. The fault level judgment unit outputs a fault level diagnosis result based on the similarity analysis result.

[0024] In some possible implementations, such as Figure 3 As shown, the aircraft landing status monitoring unit includes a gyroscope sensor, which is used to collect the aircraft's vertical landing speed in real time when the wheels are touching the ground during actual aircraft operation. The fault type determination unit includes an acceleration sensor, which is used to collect vertical acceleration information of the aircraft fuselage in real time during actual aircraft operation. Both the gyroscope sensor and the acceleration sensor are installed on the landing gear.

[0025] In some possible implementations, the fault type determination unit includes: The time domain analysis unit is used to perform time domain analysis on the collected fuselage vertical acceleration, including obtaining the fuselage vertical acceleration in the vibration response case database under normal conditions and the fuselage acceleration signal collected by the sensor, periodically calculating the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions and the root mean square value of the fuselage acceleration signal collected by the sensor, comparing the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions with the root mean square value of the fuselage acceleration signal collected by the sensor, and determining whether there is a fault in the landing gear and the type of the fault based on the root mean square value.

[0026] The frequency domain analysis unit is used to perform frequency domain analysis on the collected fuselage vertical acceleration, including obtaining the fuselage vertical acceleration in the vibration response case database under normal conditions and the fuselage vertical acceleration collected by the sensor, and obtaining a judgment result on abnormal aircraft fuselage vibration based on the calculated fuselage vertical vibration duration of the fuselage vertical acceleration in the vibration response case database and the calculated fuselage vertical vibration duration of the fuselage vertical acceleration collected by the sensor.

[0027] The similarity analysis unit is used to calculate the similarity between the time-domain index data and the vibration response case corresponding to the collected aircraft vertical landing speed, and to calculate the similarity between the frequency-domain index data and the historical fuselage vertical acceleration of the corresponding vibration response case obtained from the vibration response case data based on the aircraft vertical landing speed.

[0028] In the system provided in this embodiment, 1. The hardware system composition does not require changes to the existing aircraft structure or drilling holes, making it easier to communicate for airworthiness certification; 2. The sensor system only collects the vertical landing speed of the aircraft and the vertical acceleration of the fuselage, and has a simple structure; 3. Software system with simple algorithm and high accuracy.

[0029] As a possible implementation, this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, a landing gear online fault diagnosis method is implemented.

[0030] As a possible implementation, this embodiment provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, a landing gear online fault diagnosis method is implemented.

[0031] As a possible implementation, this example provides a landing gear fault diagnosis system for a certain type of general aviation aircraft. The system consists of sensors, a data collector, a storage unit, and a power supply unit. The sensors include gyroscopes and vibration accelerometers. The sensors are mounted on the cockpit floor, as close to the floor centerline as possible. The sampling frequency of the gyroscopes and vibration accelerometers is 1000 Hz per second.

[0032] The normal situation in the case library and the vertical acceleration signal of the fuselage measured by the sensor are as follows Figure 4 As shown in the figure, the aircraft flight status acquisition system collects real-time flight status data, including aircraft descent speed and fuselage vertical vibration acceleration. The acquisition system indicates that the aircraft's descent speed before landing was 1 m / s. Based on the assumption that the aircraft's landing vertical descent speed is 1 m / s, the fuselage vertical acceleration signal for a vertical descent speed of 1 m / s is selected from the typical response case library.

[0033] Perform time domain analysis on the vertical acceleration of the fuselage under normal conditions of the case library sensor and the fuselage acceleration signal collected by the sensor, and calculate the root mean square value of the fuselage acceleration signal, which is calculated every 0.5s. The calculation results are as follows: Figure 5 and Figure 6 As shown in the figure, the calculation results show that the difference between the two accelerations at 0.5s is small, while the difference between the two accelerations after 0.5s is large. Therefore, it can be determined that there is a stiffness fault in the current landing gear system. like Figure 7As shown in the figure, frequency domain analysis is performed on the data of the normal conditions of the two case libraries and the vertical vibration acceleration signals of the fuselage collected by the sensor. The frequency domain analysis includes calculating the vibration peak values ​​(peak value, peak time) of the normal conditions of the case library and the signals collected by the sensor. The waveform diagram formed by the calculation results shows that under the condition of a vertical landing speed of 1m / s, the vertical vibration duration of the fuselage is 1.348s under the normal conditions in the case library, while the duration of the fuselage vibration measured by the sensor is 3.025s.

[0034] The time domain analysis results, frequency domain analysis results, and vibration signals of the sensor collected signals were used to search for the case with the highest similarity in the case library. It was finally determined that the case was a landing gear shock absorber air pressure failure and the shock absorber air pressure increased by 20%.

[0035] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A landing gear online fault diagnosis method, characterized in that: The specific steps include: Real-time acquisition of the aircraft's vertical landing speed and fuselage vertical acceleration when the wheels touch the ground during landing; Obtain historical landing data and build a database of vibration response cases; Obtaining a historical fuselage vertical acceleration corresponding to a vibration response case from a vibration response case database according to the vertical landing speed of the aircraft; Perform time domain analysis and frequency domain analysis on the vertical acceleration of the fuselage collected in real time to obtain time domain index data and frequency domain index data; Combine time domain index data, frequency domain index data and historical fuselage vertical acceleration to perform fault detection and obtain time domain detection results and frequency domain detection results; Performing similarity analysis on the time domain detection results and the frequency domain detection results to obtain similarity analysis results; According to the similarity analysis result, a fault level diagnosis result is output.

2. The landing gear online fault diagnosis method according to claim 1, characterized in that: Combine time-domain indicator data and historical fuselage vertical acceleration to perform fault detection, including: Compare the aircraft's vertical landing speed with the corresponding vibration response case data to determine whether it is the normal fuselage vertical acceleration; If so, the vertical acceleration of the fuselage in the vibration response case database under normal conditions and the fuselage acceleration signal collected in real time by the sensor are obtained; Periodically calculating the root mean square value of the fuselage acceleration signal to obtain the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions and the root mean square value of the fuselage acceleration signal collected in real time by the sensor; The root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions is compared with the root mean square value of the fuselage acceleration signal collected by the sensor in real time. The presence of a landing gear fault and the type of fault are determined based on the root mean square value.

3. The landing gear online fault diagnosis method according to claim 2, characterized in that: The determining whether a fault exists based on the RMS value specifically includes: determining whether a root mean square value deviation of landing acceleration within a first set time exceeds a set threshold; If the deviation exceeds the set threshold, the fault type is determined to be a damping fault; determining whether a root mean square value deviation of the landing acceleration within a second set time exceeds a set threshold; If the deviation exceeds the set threshold, the fault type is determined to be a stiffness fault; If the RMS deviation does not exceed the set threshold, it is determined that the landing gear has no fault.

4. The landing gear online fault diagnosis method according to claim 2, characterized in that: Fault detection is performed by combining frequency domain indicator data and historical fuselage vertical acceleration, including: Obtaining the vertical acceleration of the fuselage in a vibration response case database under normal conditions, and calculating the vertical vibration duration of the fuselage of the vertical acceleration in the vibration response case database; Obtaining the vertical acceleration of the fuselage collected by the sensor in real time, and calculating the duration of the vertical vibration of the fuselage based on the vertical acceleration of the fuselage collected by the sensor in real time; The vertical vibration duration of the fuselage vertical acceleration in the vibration response case database is compared with the vertical vibration duration of the fuselage vertical acceleration collected by the sensor in real time. If the ratio exceeds the set threshold, it is determined that abnormal vibration exists in the aircraft fuselage.

5. The landing gear online fault diagnosis method according to claim 4, characterized in that: The similarity analysis of the time domain detection results and the frequency domain detection results specifically includes: Calculating the similarity between the time domain index data and the vibration response case corresponding to the vertical landing speed of the aircraft collected in real time to obtain the time domain similarity; Calculating the similarity between the frequency domain index data and the historical fuselage vertical acceleration of the corresponding vibration response case obtained from the vibration response case database according to the vertical landing speed of the aircraft to obtain the frequency domain similarity; The fault level is determined by combining the time domain similarity, frequency domain similarity, fault type and abnormal vibration judgment results of the fuselage.

6. A landing gear online fault diagnosis system, characterized in that: include: Aircraft landing status monitoring unit, used to collect real-time vertical landing speed of the aircraft when the wheels touch the ground during landing; The fuselage response acquisition unit is used to collect the vertical acceleration of the aircraft fuselage in real time; Fault type judgment unit, used to obtain historical landing data and build a vibration response case database; Obtain vibration response case data corresponding to the aircraft vertical landing speed and fuselage vertical acceleration from the fuselage vibration response database; Performing time domain analysis and frequency domain analysis on the vertical acceleration of the fuselage to obtain time domain index data and frequency domain index data; performing fault detection by combining the time domain index data, the frequency domain index data, and vibration response case data corresponding to the vertical landing speed of the aircraft and the vertical acceleration of the fuselage to obtain time domain detection results and frequency domain detection results; performing similarity analysis on the time domain detection results and the frequency domain detection results to obtain a similarity analysis result; The fault level judgment unit outputs a fault level diagnosis result according to the similarity analysis result.

7. The landing gear online fault diagnosis system according to claim 6, characterized in that: The aircraft landing status monitoring unit includes a gyroscope sensor, and the fault type judgment unit includes an acceleration sensor. Both the gyroscope sensor and the acceleration sensor are arranged on the landing gear.

8. The landing gear online fault diagnosis system according to claim 7, characterized in that: The fault type judgment unit includes: a time domain analysis unit, configured to perform time domain analysis on the fuselage vertical acceleration collected in real time, including obtaining the fuselage vertical acceleration in a vibration response case database under normal conditions and the fuselage acceleration signal collected in real time by the sensor, periodically calculating the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions and the root mean square value of the fuselage acceleration signal collected in real time by the sensor, comparing the root mean square value of the fuselage vertical acceleration in the vibration response case database under normal conditions with the root mean square value of the fuselage acceleration signal collected in real time by the sensor, and determining whether there is a landing gear fault and the type of fault based on the root mean square value; a frequency domain analysis unit configured to perform frequency domain analysis on the fuselage vertical acceleration collected in real time, including obtaining the fuselage vertical acceleration in a vibration response case database under normal conditions and the fuselage vertical acceleration collected in real time by the sensor, and obtaining a result of determining abnormal vibration of the aircraft fuselage based on a calculated duration of fuselage vertical vibration from the fuselage vertical acceleration in the vibration response case database and a calculated duration of fuselage vertical vibration from the fuselage vertical acceleration collected in real time by the sensor; A similarity analysis unit is configured to calculate the similarity between the time-domain index data and a vibration response case corresponding to the aircraft's vertical landing speed collected in real time, and to calculate the similarity between the frequency-domain index data and a historical fuselage vertical acceleration corresponding to a vibration response case obtained from a vibration response case database based on the aircraft's vertical landing speed.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the landing gear online fault diagnosis method according to any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the landing gear online fault diagnosis method according to any one of claims 1 to 5 is implemented.

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