Turbine disk probability failure physical life predicting method based on Bayes information update

Abstract

The invention relates to a turbine disk probability failure physical life predicting method based on Bayes information update, which comprises the following steps that 1, failure physical information of a turbine disk is determined in a reliability analyzing method based on physics of failure according to the structural characteristics of the aircraft engine turbine disk; 2, the failure physical information of the aircraft engine turbine disk obtained in step 1 and the existing failure information obtained by maintenance data statistics are analyzed in an FTA (failure tree analysis) / FMECA (failure mode, effects & criticality analysis) method to obtain the main failure mode and the failure position of the turbine disk, and uncertain factors and inaccurate data of the turbine disk facing whole life cycle are collected and cleared up; and 3, a failure physical life predicting model of the aircraft engine turbine disk is established according to the main failure mode and the failure position of the turbine disk obtained in step 2. The method disclosed by the invention has the beneficial effects that the design cycle of the aircraft engine turbine disk can be obviously shortened, the development cost is reduced, and the life reliability of the aircraft engine turbine disk can be obviously improved.

Description

technical field [0001] The invention belongs to the field of reliability design and life prediction of mechanical products, in particular to a new method for reliability design and life prediction of aero-engine wheels. Background technique [0002] The aeroengine is the power device of the aircraft, which provides flight thrust and is known as the "heart" of the aircraft. Aeroengines are sophisticated and complex high-tech products. A large number of components work in a very harsh environment and bear the workload of high temperature, high pressure and high speed. With the development of the aviation industry, the requirements for the performance of aero-engines have been continuously improved, and the thrust-to-weight ratio has continued to increase, which has led to an increase in the temperature and speed before the turbine of the aero-engine, resulting in more complex thermal loads and cycles of the components of the aero-engine, especially the turbine rotor components...

AI Technical Summary

Problems solved by technology

The existing deterministic fatigue life prediction methods are developing towards the uncertain fatigue life prediction based on probability and statistics, and the traditional statistical method based on the large-sample progressive learning theory is not suitable for the rare characteristics of aero-engine turbine disk test samples

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