基于BP神经网络的复杂电子设备实时故障诊断专家系统

以某型通信设备为例,介绍了如何将BP神经网络和传统的专家系统结合在一起,构成实时的故障诊断系统,从而避免传统的专家系统存在的一些问题,更好地解决故障诊断的问题.     

脉冲末修弹落点预测导引方法研究

在分析剩余射程影响因素的基础上,以弹道特征参数弹道高y及速度矢量分量Vx和Vy为解释变量,以回归分析方法为数学工具,建立脉冲末修弹剩余射程预测模型。以目标点与弹丸预测落点之间的差值为广义弹道偏差,结合数值仿真,对落点预测导引进行深入研究,验证了回归分析模型的可行性。     

基于排放和模糊神经网络模型的柴油机故障诊断方法

根据排放检测数据规律,定义并提取特征参数,建立了规则与模糊神经网络有机结合的柴油机故障诊断模型及其对应的特征知识库,确立了模型的“可塑性”学习路线,并以单缸失火故障为例,进行了模型诊断实例研究。结果表明：运用该方法进行柴油机的故障诊断,结果准确,识别速度快,诊断效率高。     

数据挖掘故障诊断专家系统

为了及时准确地对防空导弹飞行试验故障进行诊断,克服传统专家系统获取专家知识的瓶颈,立足于防空导弹飞行试验历史数据,利用数据挖掘的方法获得飞行试验故障模式判定决策树,进而得出导弹故障判定规则,形成故障诊断专家知识库,构建防空导弹故障诊断专家系统.这使数据挖掘和专家系统两者的优点得到充分发挥.     

考虑腐蚀因素的船体结构寿命预测方法

为建立考虑腐蚀因素的船体结构寿命预测方法,在分析现有常用的船体结构腐蚀损伤时变模型的基础上,根据舰船维修保障实际情况建立了考虑腐蚀防护系统作用时间和维修时间等因素的腐蚀时变模型。根据相关规范选择了船体结构腐蚀寿命标准,并建立了一种计算船体结构腐蚀寿命的方法。该方法建立了船体结构腐蚀寿命与腐蚀防护系统作用时间和修理时间等因素之间的量化关系,可以用于预测均匀腐蚀条件下船体结构寿命,也可以反过来指导腐蚀防护系统设计指标的选择和船体结构维修策略的确定。     

Storage life prediction under pre-strained thermally-accelerated aging of HTPB coating using the change of crosslinking density

In order to predict the storage life of a certain type of HTPB (hydroyl-terminated polybutadiene) coating at 25 C and analyze the influence of pre-strain on the storage life, the accelerated aging tests of HTPB coating at 40 C, 50 C, 60 C, 70 C with the pre-strain of 0%, 3%, 6%, 9%, respectively were carried out. The variation regularity of the change of crosslinking density was analyzed and the aging model of HTPB coating under pre-strained thermally-accelerated aging was proposed. The storage life of HTPB coating at 25 C was estimated by using the Berthelot equation as the end point of the aging life with a 30% decrease in maximum elongation. The results showed that the change of crosslinking density of HTPB coating increased with the increase of aging temperature and aging time, and decreased with the in-crease of pre-strain. Under 0% pre-strain, the relationship between the change of crosslinking density of HTPB coating and the aging time can be described by the logarithmic model with the confidence probability greater than 99%.The stress relaxation phenomenon existed under 3%, 6% and 9% pre-strained aging. The aging model considering chemical aging and pre-strain was established with the confidence probability greater than 90%. The storage life of HTPB coating was 15.2935 years at 25 C under 0% pre-strain, which was reduced by 13.9007%, 75.6949% and 89.7859% under 3%, 6% and 9% pre-strain, respectively. The existence of pre-strain has a serious impact on the storage life of HTPB coating, therefore, the pre-strain should be avoided as much as possible during the actual storage.     

未来30年太空安全发展趋势及影响

“太空安全战略”专题编者按 组稿专家：杨乐平（国防科技大学空天科学学院教授、博士生导师） 近年来,以美国重建太空司令部与天军独立为标志,国际太空领域战略竞争与军事对抗日益加剧,太空前所未有地应用于军事与安全,太空安全也受到了前所未有的挑战。为了解未来太空安全发展和主要国家太空安全战略动向,深化太空安全战略研究,《国防科技》编辑部于2021年6月启动“太空安全战略”专题征文活动,国内相关学者积极投稿,经专家遴选,本期发表入选稿件6篇。来稿内容涵盖未来30年太空安全发展预测、美国太空安全最新发展、俄罗斯太空安全政策、欧盟太空安全政策、日本太空安全战略以及印度太空力量发展等主题,较为全面地反映了当前国际太空安全领域的最新发展与战略动向。从长远看,随着地球以外人类活动的增加、太空新经济蓬勃发展和太空创造财富规模不断扩大,水平大幅提升,太空将超越陆、海、空成为国家安全最重要的领域。从这个意义上讲,太空安全战略研究学术价值与影响较大,值得高度关注。     

基于时域平均的齿轮故障诊断

提出了信号时域平均处理的新算法,解决了周期截断误差对平均结果的影响,并对测取的齿轮箱齿轮故障振动信号进行了处理。实验结果表明:该方法在齿轮故障信号的处理中能够消除背景噪声的影响,取得比较理想的效果。     

Transient analysis of Markov models of fault‐tolerant systems with deferred repair using split regenerative randomization

The (standard) randomization method is an attractive alternative for the transient analysis of continuous time Markov models. The main advantages of the method are numerical stability, well‐controlled computation error, and ability to specify the computation error in advance. However, the fact that the method can be computationally very expensive limits its applicability. In this paper, we develop a new method called split regenerative randomization, which, having the same good properties as standard randomization, can be significantly more efficient. The method covers reliability‐like models with a particular but quite general structure and requires the selection of a subset of states and a regenerative state satisfying some conditions. For a class of continuous time Markov models, model class C₂, including typical failure/repair reliability‐like models with exponential failure and repair time distributions and deferred repair, natural selections are available for both the subset of states and the regenerative state and, for those natural selections, theoretical results are available assessing the efficiency of the method in terms of “visible” model characteristics. Those results can be used to anticipate when the method can be expected to be competitive. We illustrate the application of the method using a large class C₂ model and show that for models in that class the method can indeed be significantly more efficient than previously available randomization‐based methods. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006     

基于退化速率跟踪粒子滤波的剩余使用寿命预测框架

毋庸置疑,剩余使用寿命预测对于设备的健康管理越来越重要。近年来粒子滤波方法被越来越多地应用到设备寿命预测技术当中,这是因为粒子滤波方法能更好的解决非线性非高斯系统滤波问题,而且能够获得不确定度信息。但该方法的预测性能却过度依赖于预测模型,并且对于模型参数的初始分布也比较敏感,这在一定程度上限制了粒子滤波预测方法的进一步发展。本文针对基本粒子滤波预测方法的不足,提出了一种基于退化速率跟踪粒子滤波的通用预测框架,以历史观测数据的退化速率统计规律作为指导来跟踪目标数据的退化速率,实现对粒子滤波预测方法的简化。并将该方法用于轴承和锂离子电池的剩余使用寿命预测,验证了方法的有效性。