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Aero-engine main bearing residual life prediction method based on digital twinning

An aero-engine and life prediction technology, which is applied in the fields of electrical digital data processing, special data processing applications, biological neural network models, etc. , to achieve the effect of preventing major flight accidents and ensuring work safety

Active Publication Date: 2019-12-03
XI AN JIAOTONG UNIV
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Problems solved by technology

[0005] In order to solve the above problems, the present invention provides a method for predicting the remaining life of main bearings of aero-engines based on digital twins, which solves the problem that the model in the existing methods for predicting the remaining life of main bearings of aero-engines is only applicable to a single working condition, and insufficient consideration is given to changes in working conditions. The problem of inaccurate remaining life prediction results

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  • Aero-engine main bearing residual life prediction method based on digital twinning
  • Aero-engine main bearing residual life prediction method based on digital twinning
  • Aero-engine main bearing residual life prediction method based on digital twinning

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[0048] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0049] refer to figure 1 and figure 2 , the method for predicting the remaining life of an aero-engine main bearing based on digital twins proposed by the present invention includes the following steps:

[0050] S1, using multiple restricted Boltzmann machine stacks to construct a deep neural network, and training the deep neural network through data samples, so that the deep neural network can detect the deep damage hidden in the vibration signal of the main bearing of the aeroengine The feature is extracted; the data sample comes from real experimental data, and the data points include vibration response, deep damage feature and aeroengine main bearing life; the deep damage feature includes but not limited to damage area and damage depth;

[0051] S2, use the deep neural network obtained in S1 to extract the deep damage features, and con...

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Abstract

The invention provides an aero-engine main bearing residual life prediction method based on digital twinning. The method comprises: firstly, using a plurality of restricted Boltzmann machines and a regression algorithm to construct a main bearing health monitoring model; comparing the main bearing actual measurement vibration signals with main bearing health state information extracted from the digital twinning model, adjusting and correcting the digital twinning model by utilizing a comparison result, and finally predicting the residual life of the main bearing by utilizing the updated digital twinning model. According to the aero-engine main bearing residual life prediction method based on digital twinning, a digital twinning technology is introduced into the field of main bearing residual life prediction, so that a main bearing digital twinning model applied to the method can be updated in real time along with the change of the working condition of the main bearing of the aero-engine, and a more accurate residual life prediction result can be obtained.

Description

technical field [0001] The invention belongs to the field of mechanical life prediction, in particular to a method for predicting the remaining life of an aero-engine main bearing based on digital twins. Background technique [0002] As one of the important parts in contemporary mechanical equipment, bearings play the role of supporting, reducing friction coefficient, and ensuring rotation accuracy. Aeroengine main bearings have been subjected to extreme conditions such as high temperature, high pressure, and poor lubrication conditions for a long time during the working process. The level of design, manufacture, monitoring, diagnosis, and prediction will directly affect the performance of the aeroengine. The existing aero-engine main bearing remaining life prediction technology is not mature, so in order to ensure the safety of aero-engine operation, the main bearing is often replaced when it is not close to the upper limit of life, resulting in serious waste. Moreover, th...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/50G06N3/04
CPCG06N3/045Y02T90/00
Inventor 曹宏瑞苏帅鸣付洋乔百杰陈雪峰
Owner XI AN JIAOTONG UNIV
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