A Fusion Diagnosis Method for Gas Path Faults of Aeroengines Based on Statistical Distribution Characteristics

An aero-engine, statistical distribution technology, applied in the direction of calculation, design optimization/simulation, special data processing application, etc., can solve the problem of limited fault diagnosis accuracy in engine data, achieve credible diagnosis results, improve accuracy and reliability The effect of improving reliability and reliability

Active Publication Date: 2022-04-12
AERO ENGINE ACAD OF CHINA
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Problems solved by technology

The engine is affected by the volume effect, metal heat transfer and measurement noise, and the parameters themselves have certain fluctuations. Most current diagnosis methods do not consider the fluctuation of the measurement parameters, resulting in limited accuracy of fault diagnosis in real engine data.

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  • A Fusion Diagnosis Method for Gas Path Faults of Aeroengines Based on Statistical Distribution Characteristics
  • A Fusion Diagnosis Method for Gas Path Faults of Aeroengines Based on Statistical Distribution Characteristics
  • A Fusion Diagnosis Method for Gas Path Faults of Aeroengines Based on Statistical Distribution Characteristics

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[0058] The present disclosure will be further described in detail below with reference to the drawings and embodiments. It can be understood that the specific implementation manners described here are only used to explain relevant content, rather than to limit the present disclosure. It should also be noted that, for ease of description, only parts related to the present disclosure are shown in the drawings.

[0059] It should be noted that, in the case of no conflict, the implementation modes and the features in the implementation modes in the present disclosure can be combined with each other. The present disclosure will be described in detail below with reference to the drawings and embodiments.

[0060] The current engine gas path fault diagnosis mainly includes fault diagnosis methods based on models, fault diagnosis methods based on measurement parameter deviation thresholds, and fault diagnosis methods based on artificial intelligence. Model-based diagnosis is highly ...

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Abstract

The present disclosure provides an aeroengine gas path fault fusion diagnosis method based on statistical distribution characteristics, constructs a matching diagnosis module based on parameter deviation statistical characteristics, and uses the weighted D‑S evidence theory based on fault sensitivity to fuse the diagnosis results , to reduce or even eliminate the adverse effects of engine volume effect, metal heat transfer, and measurement noise and offset on engine fault diagnosis, and improve the accuracy and reliability of engine fault diagnosis; To obtain the reliability of different measurement parameters, so as to assign different weight coefficients to the fault diagnosis results of the statistical distribution characteristics of different measurement parameters during the fusion process, so as to improve the reliability of diagnosis.

Description

technical field [0001] The present disclosure relates to the technical field of aero-engine fault diagnosis and health management, in particular to an aero-engine air path fault fusion diagnosis method based on statistical distribution characteristics. Background technique [0002] Aeroengine is a large complex electromechanical system integrating machine, electricity, hydraulic, gas and various high-tech. The structure of the engine is complex and the processing and installation requirements of the components are high. The working environment is very severe. The temperature in front of the turbine can reach up to 2000K, and the rotor speed exceeds 10000rpm. During use, tasks such as takeoff, climb, and cruise are often performed. , long-term high centrifugal load, pneumatic load, high temperature and atmospheric temperature difference load, and alternating load of vibration, etc., will inevitably fail. In order to ensure the safe and reliable operation of the engine, it is...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20G06F30/15G06F16/215G06F17/16
CPCG06F30/20G06F30/15G06F16/215G06F17/16Y02T90/00
Inventor 范满意孔祥兴张瑞杨博闻李洋洋梁宁宁
Owner AERO ENGINE ACAD OF CHINA
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