Movable yro life predicting method based on gray mode

Through a gray model-based method, using wavelet transform and performance parameter extrapolation method, the life trend term of the dynamically controlled gyroscope is extracted, which solves the problem of gyroscope life assessment in the existing technology and realizes the optimization of the gyroscope under the conditions of small batch and high cost. Reliable life predictions simplify the evaluation process and reduce resource consumption.

CN1587989AInactive Publication Date: 2005-03-02SHANGHAI JIAOTONG UNIV

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SHANGHAI JIAOTONG UNIV
Filing Date
2004-07-15
Publication Date
2005-03-02
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

It is difficult to effectively evaluate and predict the life of aerospace electromechanical components such as gyroscopes with existing technology, especially in the case of small batches and high costs. The traditional accelerated life test method has difficulties in funding, time and sample quantity, and the reliability of conventional life It is difficult for the evaluation method to introduce pre-test information that expands the reliability parameters of the evaluation.

Method used

A dynamically controlled gyroscope life prediction method based on the gray model is used to find the law of life operation by testing multiple parameters related to life, using wavelet transform to extract trend terms, establishing a gray single-variable first-order model, and combining the performance parameter extrapolation method , perform life prediction, simplifying data processing and model building.

🎯Benefits of technology

It achieves reliable prediction of the life of dynamically controlled gyroscopes under extremely small sample conditions, reduces costs and waste of resources, provides a simple and easy basis for life judgment, and is suitable for life assessment and prediction of other electromechanical components.

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Abstract

The invention relates to a dynamic adjust gyroscope life forecasting method based on gray model. By data collection of vibration effective value, random drift and environmental temperature parameter which are preprocessed using radial neural networks, influence of environmental temperature on vibration effective value and random drift is eliminated and random drift and effective value just related to time are obtained by subtracting drift constant value term, then trend term of vibration effective value and random drift are extracted by using wavelet transformation and gray model are built separately for their trend term. The smaller data in two values of life predicted of dynamic adjust gyroscope unless two predicted values exceeding performance parameter limitation when dynamic adjust gyroscope is considered losing effect. The invention uses performance parameter of life probative period of product to predict its life, showing discipline of performance parameter and life of dynamic adjust gyroscope. It is easy and convenient economical and reliable.
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