文档介绍：基于组合预测的航空发电机寿命预测研究
摘要
航空发电机是飞行器的关键部件之一,飞行中一旦出现故障就可能导致机毁人亡,造成巨大损失。为保障其飞行安全,及时发现故障,减少事故率,降低损失,需要深入研究航空发电机的寿命预测方法。而由于单一的预测方法往往预测精度低,很难满足实际预测要求。因此,本文提出了一种组合预测方法,结合相关的预测知识,运用加权组合模型,实现了对航空发电机寿命预测。
本文首先论述了灰色理论、支持向量机、灰色神经网络三种预测方法的基本理论,重点研究了灰色神经网络模型以及组合预测模型的建立与预测过程。在深入分析航空发电机性能参数相关性的基础上,结合其工作环境特点及影响因素,设计了一种基于组合预测的航空发电机寿命预测方法,并对航空发电机寿命预测模型的设计思想、框架结构、改进算法等进行了详细论述,完成了基于组合预测的航空发电机寿命预测的设计,并通过试验验证了该组合预测方法的有效性。
该组合预测的方法是基于matlab平台构建与实现的。
关键词:航空发电机;灰色理论;支持向量机;灰色神经网络;组合预测
Aero Generator Life Prediction Based bination Forecast
Abstract
Air generator is one of the ponents of aircraft,flight once malfunction can lead to news,cause great losses. To ensure the flight safety, timely find fault, reduce accidents, reduce loss, require further study aviation generator life prediction method. But because of a single forecasting method often prediction accuracy is low, hard to meet the practical prediction requirements forecasting accuracy. Therefore, this paper puts forward a kind bination forecast method, combining relevant knowledge, using the bination forecast model of air generator life prediction.
This paper discusses the gray theory, support vector machines, the grey forecast method of work, three basic theory, key research gray work model bination forecast model establishment and the prediction process. In the deep analysis of air generator based on the relevance of performance parameters, combining the working environment, the characteristics and the influence factors, and designed a kind bination forecast of air generator based on the prediction method, and the prediction model of air generator design ideas, frame structure, the improved algorithm of detail, completed based bination forecast of air generator life prediction of design, and verifies the effectiveness of the method.
bination forecast method is based on the matlab platform building and implementation.
Keywords: air generator; gray theory; support vector machine; gray work; combination forecast
目录
1 绪论 1