强流脉冲电子束辐照诱发多晶纯铝中的空位缺陷簇结构

利用强流脉冲电子束（HCPEB）技术对多晶纯铝样品进行辐照,采用透射电子显微镜详细分析了辐照诱发的空位簇缺陷.HCPEP辐照后,在辐照表层内形成了大量的四方形空位胞,其间包含位错圈和堆垛层错四面体（SFT）等类型的空位簇缺陷.1次辐照后,空位胞内产生空位型位错圈,5次辐照则主要产生SFT;10次辐照后,空位胞内产生的空位簇缺陷主要是位错圈,局部区域也观察到了SFT缺陷,在产生SFT的附近区域具有很低的位错密度或者几乎无位错出现.HCPEB辐照产生的瞬间加热和冷却诱发了幅值极大且应变速率极高的应力,这一因素 关键词： 强流脉冲电子束 多晶纯铝 空位簇缺陷 堆垛层错四面体     

基于迭代学习的离散切换系统故障估计

针对一类具有任意切换序列的离散切换系统的故障估计问题,提出了一种新的故障估计算法.该算法利用引入的虚拟故障信号构建出故障估计器,并利用残差信号通过迭代学习方法对引入的虚拟故障进行逐次修正.使虚拟故障随着迭代次数的增加逐渐逼近实际故障.利用压缩映射方法严格证明了算法在各个子区间上的收敛性,给出了算法的收敛条件.理论分析表明,所提算法能够在有限区间上精确估计出切换系统发生的不同类型故障.最后通过仿真实验进一步验证了所提算法的有效性.     

基于径向基神经网络的航空发动机气路故障诊断

基于径向基神经网络对民用高涵道比航空发动机风扇、增压级、高压压气机、高压涡轮、低压涡轮5大气路部件的效率降低故障进行诊断。采用Gasturb进行故障训练样本和测试样本库的生成,诊断结果显示,采用径向基神经网络进行航空发动机气路故障诊断的计算时间短、精度较高,不仅能定性的定位故障部位,而且在大多数情况下可以定量的给出该部件的性能衰退程度。某些情况下诊断结果与测试样本不尽一致,但都是方程的合理解,这是因为航空发动机的数学模型是一个多解的复杂方程,一个总性能的衰减对应着多组部件性能衰退的组合。随噪声幅值加大,诊断精度变差,同时研究发现诊断精度受噪声影响的敏感系数在不同的噪声幅值水平下是不同的。     

超导故障限流器的数学模型研究

文中总结了几种超导故障限流器的模型。在数学模型的基础上 ,阐述了超导材料的温升、失超传播速度和临界电流密度对超导故障限流器性能的影响     

Extrapolation for Aeroengine Gas Path Faults with SVM Bases on Genetic Algorithm

Mining aeroengine operational data and developing fault diagnosis models for aeroengines are to avoid running aeroengines under undesired conditions. Because of the complexity of working environment and faults of aeroengines, it is unavoidable that the monitored parameters vary widely and possess larger noise levels. This paper reports the extrapolation of a diagnosis model for 20 gas path faults of a double-spool turbofan civil aeroengine. By applying support vector machine (SVM) algorithm together with genetic algorithm (GA), the fault diagnosis model is obtained from the training set that was based on the deviations of the monitored parameters superimposed with the noise level of 10%. The SVM model (C = 24.7034; γ = 179.835) was extrapolated for the samples whose noise levels were larger than 10%. The accuracies of extrapolation for samples with the noise levels of 20% and 30% are 97% and 94%, respectively. Compared with the models reported on the same faults, the extrapolation results of the GASVM model are accurate.     

飞航装备测试性设计分析及故障诊断实施策略工程应用研究

飞航装备的测试性设计分析及故障诊断研究对提高武器装备的测试性水平,提升装备的战备完好性和战时利用率,拓展可持续的作战能力具有重要作用;通过从国内外测试性发展现状入手展开分析,经对一般测试性设计分析流程的深入研究,从工程实用的角度提出了适用于飞航装备的测试性设计与分析的方法,其中包括探讨了测试性建模的工具和一般建模流程,梳理了测试性建模数据准备素材类型和具体内容,分析了测试性建模的具体步骤以及基于测试性模型的分析方法,最后基于所建立测试性模型探讨了基于D矩阵的故障隔离和诊断模式,对后续飞航武器装备型号中的测试性设计分析及故障诊断工作具有重要意义。     

Low-Pass Filtering Empirical Wavelet Transform Machine Learning Based Fault Diagnosis for Combined Fault of Wind Turbines

Fault diagnosis of wind turbines is of great importance to reduce operating and maintenance costs of wind farms. At present, most wind turbine fault diagnosis methods are focused on single faults, and the methods for combined faults usually depend on inefficient manual analysis. Filling the gap, this paper proposes a low-pass filtering empirical wavelet transform (LPFEWT) machine learning based fault diagnosis method for combined fault of wind turbines, which can identify the fault type of wind turbines simply and efficiently without human experience and with low computation costs. In this method, low-pass filtering empirical wavelet transform is proposed to extract fault features from vibration signals, LPFEWT energies are selected to be the inputs of the fault diagnosis model, a grey wolf optimizer hyperparameter tuned support vector machine (SVM) is employed for fault diagnosis. The method is verified on a wind turbine test rig that can simulate shaft misalignment and broken gear tooth faulty conditions. Compared with other models, the proposed model has superiority for this classification problem.     

A New Universal Domain Adaptive Method for Diagnosing Unknown Bearing Faults

The domain adaptation problem in transfer learning has received extensive attention in recent years. The existing transfer model for solving domain alignment always assumes that the label space is completely shared between domains. However, this assumption is untrue in the actual industry and limits the application scope of the transfer model. Therefore, a universal domain method is proposed, which not only effectively reduces the problem of network failure caused by unknown fault types in the target domain but also breaks the premise of sharing the label space. The proposed framework takes into account the discrepancy of the fault features shown by different fault types and forms the feature center for fault diagnosis by extracting the features of samples of each fault type. Three optimization functions are added to solve the negative transfer problem when the model solves samples of unknown fault types. This study verifies the performance advantages of the framework for variable speed through experiments of multiple datasets. It can be seen from the experimental results that the proposed method has better fault diagnosis performance than related transfer methods for solving unknown mechanical faults.     

Studying edge effects near rectangular mine workings weakened by a crack

Edge effects in a rock mass near a system of periodic mine workings crossed by a crack (fold fault) are considered. The stress state near the mine workings is determined by solving an elastic problem using the piecewise-homogeneous medium model. The original differential problem is reduced to a discrete problem based on the concept of a base scheme. Methods are proposed to solve the discrete problem, and the issue of optimizing the numerical analysis is discussed. The stress distribution around mine workings is analyzed. The stress isolines that represent the boundaries of edge effect zones and indicate their maximum decay length are plotted __________ Translated from Prikladnaya Mekhanika, Vol. 44, No. 1, pp. 74–78, January 2008.     

电动机故障诊断专家系统研究

通过对电动机故障分析，主要研究了产生式电动机故障诊断专家系统的总体结构，知识获取，知识库建立及推理机制。