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A Bayesian Inference-Based Dynamic Threshold Calculation Method for Helicopter Moving Parts

A dynamic threshold and component technology, applied in inference methods, special data processing applications, geometric CAD, etc., can solve the problem of low dynamic threshold accuracy, and achieve the effect of improving calculation accuracy

Active Publication Date: 2022-07-26
NANCHANG HANGKONG UNIVERSITY
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Problems solved by technology

[0005] The purpose of the present invention is to provide a method for calculating the dynamic threshold of helicopter moving parts based on Bayesian reasoning, aiming to solve the problem that the accuracy of the dynamic threshold calculated by the prior art is not high for different types of fault data

Method used

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  • A Bayesian Inference-Based Dynamic Threshold Calculation Method for Helicopter Moving Parts
  • A Bayesian Inference-Based Dynamic Threshold Calculation Method for Helicopter Moving Parts
  • A Bayesian Inference-Based Dynamic Threshold Calculation Method for Helicopter Moving Parts

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Embodiment Construction

[0033] The present invention adopts such as figure 1 The shown work flow chart of the dynamic threshold calculation method of helicopter moving parts based on Bayesian reasoning realizes the calculation of dynamic threshold, and the specific implementation steps are as follows:

[0034] 1) Data preprocessing

[0035] (1.1) Collect normal data, inner ring fault data, outer ring fault data, and ball fault data.

[0036] In the embodiment of the present invention, the experimental data is normal and faulty data collected by means of fault implantation.

[0037] (1.2) Using the data preprocessing method to preprocess all the data collected in step (1.1), filter out the noise in the data, and obtain the denoised data.

[0038] The data preprocessing method is a singular value decomposition method, a wavelet denoising method, a wavelet packet denoising method, a sliding smoothing method, a basic morphological filtering method or a difference morphological filtering method.

[003...

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Abstract

The invention discloses a dynamic threshold calculation method for helicopter moving parts based on Bayesian reasoning. The method comprises the steps of: 1) data preprocessing, filtering out noise in the data; 2) feature extraction, extracting normal data and fault data respectively 3) Dynamic threshold calculation, using Bayesian inference method to calculate the dynamic threshold of normal data and fault data. The advantages of the present invention are: in the feature extraction method, four methods are respectively used to extract the inner ring characteristic frequency energy, the outer ring characteristic frequency energy extraction, the ball characteristic frequency energy extraction and the M6A extraction, to carry out the characteristics of the normal data and different types of fault data. Extraction can effectively reflect the vibration characteristics of normal and fault data; in the dynamic threshold calculation, the Bayesian inference method is used, which not only considers the probability density of normal data, but also considers the probability density of different types of fault data, which improves dynamic performance. The calculation accuracy of the threshold.

Description

technical field [0001] The invention relates to the field of helicopter health monitoring and fault diagnosis, in particular to a method for calculating dynamic thresholds of helicopter moving parts based on Bayesian reasoning. Background technique [0002] Compared with fixed-wing aircraft, helicopters can take off and land vertically, have better maneuverability, quick response capabilities and are not limited by terrain and landforms, and can be widely used in civil and military fields. [0003] With the more and more extensive application of helicopters, its safety has been paid more and more attention by people. Helicopter health and usage monitoring system (HUMS) is an important technology and system to ensure the safe operation of helicopters in today's world. In order to reduce accidents, real-time monitoring of the working status of key parts of helicopters, especially moving parts, is an important part of HUMS. In HUMS, fault implantation tests are often used in ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/15G06N5/04
CPCG06N5/04G06F30/00Y02T90/00
Inventor 熊邦书丛雷李新民雷鸰
Owner NANCHANG HANGKONG UNIVERSITY
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