Limited data driving long-life part residual life prediction method

A technology of data-driven and forecasting methods, which is applied in the cross-field of engineering application and information science, and can solve the problems that multi-parameter forecasting models cannot independently select the optimal parameter combination, large amount of data, and poor nonlinear data processing capabilities.

Active Publication Date: 2016-12-07
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

This method fully considers the characteristics of high reliability and high cost of long-life components, and solves the problems that traditional prediction models cannot respond for a long time, requires a large amount of data, and has poor nonlinear data processing capabilit

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  • Limited data driving long-life part residual life prediction method
  • Limited data driving long-life part residual life prediction method
  • Limited data driving long-life part residual life prediction method

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Embodiment Construction

[0021] Below in conjunction with accompanying drawing, the present invention will be further described.

[0022] The overall process of the present invention is as figure 1 shown. The sub-module processes it contains are as follows: figure 2 , image 3 , Figure 4 as well as Figure 5 As shown, the following will describe in detail in conjunction with each flow chart.

[0023] The present invention utilizes the limited monitoring data of long-life parts to analyze the remaining life, adopts wavelet-envelope analysis to preprocess the original data, reduces the noise in the original data, and uses the two-parameter residual to correct the autoregressive gray long-term prediction model for long-life parts. Preprocess the data for modeling prediction, and map the independent selection of parameters to the optimal two-parameter independent selection of the prediction model in the coalition formation process in the cooperative game, and map the failure modes in the FMEA syste...

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Abstract

The invention discloses a limited data driving long-life part residual life prediction method comprising the following steps: using a wavelet-envelope to analyze and preprocess long life part history monitoring data, thus reducing data noises; building a multiparameter residual error correction autoregression gray long-term prediction model for the preprocessed data; using combined cooperate gaming to map autonomous selection optimal parameters; mapping a failure mode and a failure mode in an influence analysis system as reliability evaluation indexes of the prediction model, and thus real time evaluating prediction result reliability. The advantages are that the cooperate gaming and the residual error correction autoregression gray long-term prediction model are organically combined, thus fully utilizing long life part limited monitoring data, and solving a series of problems in the prior art that a conventional prediction method cannot respond in long time, is large in data amount demand, multiparameter selection depends on expert knowledge, and the prediction reliability cannot be evaluated in real time; the novel method can improve long-life part residual life prediction result reliability and accuracy under the limited data background; the method is suitable for residual life prediction of the highly reliable long life part with limited data and high test cost; the novel method has universality.

Description

technical field [0001] The invention relates to a method for predicting the remaining life of long-life components driven by limited data, which is a data-driven life prediction method for high-reliability and high-cost long-life components, and belongs to the cross field of engineering application and information science. Background technique [0002] With the discovery of new materials and the development of manufacturing technology, the reliability of equipment components in the field of engineering applications (such as spacecraft inertial navigation components, electronic equipment components, telemetry sensors, etc.) is getting higher and higher, and the working life is getting longer and longer. , ranging from a few years to decades. The high manufacturing cost and high reliability of these long-lived components have brought great challenges to the study of their final service life and the determination of maintenance time nodes. How to obtain the remaining life of l...

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Application Information

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IPC IPC(8): G06F11/34G06F17/18
CPCG06F11/3447G06F17/11G06F17/18
Inventor 皮德常代成龙
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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