密封式继电器贮存寿命预测方法的研究

发布时间：2018-03-16 21:00

本文选题：密封式继电器　切入点：贮存寿命　出处：《河北工业大学》2015年硕士论文　论文类型：学位论文

【摘要】：密封式继电器是一种常用的低压电器元件,密封性良好,能够承受高温、低温、辐射、振动等各种恶劣环境,广泛用于飞机、卫星、火箭、导弹等及其相关配套设备中,更是航天继电器的首选。随着我国航天事业的迅速发展,对继电器的可靠性有了更高的要求,应运而生的是寿命试验和寿命评估的新技术和新理论。密封式继电器作为航天继电器使用时长期处于贮存状态,贮存可靠性和工作可靠性同等重要,为保证其寿命剖面各阶段始终保持在备用激活状态,对继电器贮存寿命进行准确预测有非常实际的意义。论文首先介绍了课题的研究背景及国内外发展现状,阐述了可靠性寿命加速试验原理及分类,并对密封式继电器贮存退化参数进行了小波阈值去噪处理。围绕着密封式继电器贮存寿命预测这一核心,本课题研究综合环境应力对密封式继电器贮存寿命的影响,建立了两种继电器贮存退化参数预测模型。模型一为基于遗传算法优化BP神经网络的密封式继电器贮存退化参数预测模型,模型二基于主元分析和RBF神经网络建立了继电器的贮存退化参数预测模型。文中对多种算法进行了介绍,并比较了算法的优劣,对其存在的一些缺点进行了改进。基于MATLAB进行模型的搭建及仿真,分析预测结果,对各模型方法进行误差评价,通过继电器的退化模型预测常温下继电器的贮存寿命。
[Abstract]:Sealing relay is a kind of commonly used low-voltage electrical components, it has good sealing ability, and can withstand various bad environments such as high temperature, low temperature, radiation, vibration and so on. It is widely used in aircraft, satellite, rocket, missile and other related equipments. It is the first choice of space relay. With the rapid development of China's aerospace industry, the reliability of the relay has higher requirements. The new technology and theory of life test and life evaluation have emerged as the times require. The sealed relay is in the storage state for a long time when it is used as a spaceflight relay, so the storage reliability and the working reliability are equally important. In order to keep its life profile in the state of standby activation, it is very practical to predict the storage life of relay accurately. Firstly, this paper introduces the research background of the subject and the present situation of development at home and abroad. This paper describes the principle and classification of accelerated reliability life test, and carries out wavelet threshold de-noising for storage degradation parameters of sealed relays, which is centered on the prediction of storage life of sealed relays. In this paper, the effect of comprehensive environmental stress on the storage life of sealed relays is studied. Two kinds of relay storage degradation parameter prediction models are established. The first model is a sealed relay storage degradation parameter prediction model based on genetic algorithm optimization BP neural network. In the second model, based on principal component analysis and RBF neural network, the prediction model of relay storage degradation parameters is established. In this paper, several algorithms are introduced, and the advantages and disadvantages of the algorithms are compared. Based on MATLAB, the model is built and simulated, the prediction results are analyzed, the error of each model method is evaluated, and the storage life of relay at room temperature is predicted by the degradation model of relay.
【学位授予单位】：河北工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM58

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