关联维数在往复压缩机气阀故障诊断中的应用

针对传统方法难以有效进行往复压缩机气阀故障诊断的现状,提出了应用关联维数对往复压缩机气阀故障进行诊断的方法。通过对气阀常见故障类型的诊断,表明关联维数可以有效地分析出往复压缩机气阀的常见故障。     

Short beam three point bend tests in syntactic foams. Part I: Microscopic characterization of the failure zones

Scanning Electron Microscopic (SEM) studies were carried out on the failure surface of syntactic foam material tested in a short beam three point bend test (SBT) by employing 21 × 15 × 3 mm³ dimension bearing specimens. The syntactic foams were fabricated using glass microballoons in epoxy binder. The failure of the tensile, compression, and shear dominated regions were studied by SEM at different magnifications. The tensile region had characteristic features, such as partial debonding of the microballoons from the matrix and cracking of glass microballoons, apart from matrix cracking and some river pattern features. The compression side was characterized by crushing and collapsing of microballoons, resulting in accumulation of debris with no apparent river pattern for matrix‐rich regions. The midway positions of the SBT failed surface comprised of deformation bands in the matrix and occasional debonding of microballoons. The morphology recorded in the tensile and compression regions corroborated well with the results obtained on these foam samples in those specimens that were subjected to pure uniaxial tension and compression, respectively. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 673–679, 2005     

Intelligent fault diagnosis for rolling bearings based on graph shift regularization with directed graphs

Graph shift regularization is a new and effective graph-based semi-supervised classification method, but its performance is closely related to the representation graphs. Since directed graphs can convey more information about the relationship between vertices than undirected graphs, an intelligent method called graph shift regularization with directed graphs (GSR-D) is presented for fault diagnosis of rolling bearings. For greatly improving the diagnosis performance of GSR-D, a directed and weighted k-nearest neighbor graph is first constructed by treating each sample (i.e., each vibration signal segment) as a vertex, in which the similarity between samples is measured by cosine distance instead of the commonly used Euclidean distance, and the edge weights are also defined by cosine distance instead of the commonly used heat kernel. Then, the labels of samples are considered as the graph signals indexed by the vertices of the representation graph. Finally, the states of unlabeled samples are predicted by finding a graph signal that has minimal total variation and satisfies the constraint given by labeled samples as much as possible. Experimental results indicate that GSR-D is better and more stable than the standard convolutional neural network and support vector machine in rolling bearing fault diagnosis, and GSR-D only has two tuning parameters with certain robustness.     

巨厚砂岩顶板“三带”范围的数值模拟与界定

为定量划分采空区上覆巨厚砂岩顶板的"三带"范围,根据数值模拟的应力与位移结果,提出"三带"的界定准则:将上覆岩层中主应力都为拉应力的区域定为冒落带;将只有一个主应力为拉应力的岩层高度定为裂隙带的上限。采用FLAC3D软件对开采过程中的顶板运动规律进行了数值模拟,模拟结果与实际观测结果一致。表明此界定准则可为地质条件相似矿区的顶板"三带"分布提供借鉴。     

Fault diagnosis of internal combustion engines using visual dot patterns of acoustic and vibration signals

An investigation of the fault diagnosis technique in internal combustion engines based on the visual dot pattern of acoustic and vibration signals is presented in this paper. Acoustic emissions and vibration signals are well known as being able to be used for monitoring the conditions of rotating machineries. Most of the conventional methods for fault diagnosis using acoustic and vibration signals are primarily based on observing the amplitude differences in the time or frequency domain. Unfortunately, the signals caused by damaged elements, such as those buried in broadband background noise or from smearing problems arising in practical applications, particularly at low revolution, are not always available. In the present study, a visual dot pattern technique is proposed to identify the acoustic emission and vibration signals for fault diagnosis in an internal combustion engine and drive axle shaft. Experiments are carried out to evaluate the proposed system for fault diagnosis under various fault conditions. The experimental results indicate that the proposed technique is effective in the fault diagnosis of an internal combustion engine and drive axle shaft.     

Bearing failure detection using matching pursuit

In this paper, a new approach to the detection of localized defects of rolling element bearings is proposed. It employs matching pursuit with time–frequency atoms to analyze bearing vibration and extract vibration signatures. In particular, this approach utilizes not only the temporal and spectral but also the scale characteristics of the vibration generated due to the presence of a defect for the detection. This leads to a high signal-to-noise ratio and facilitates considerably the detection at the early stage of failure development. Experimental results show that the proposed approach is sensitive and reliable and works better than continuous wavelet transform and envelope detection.     

基于容积效率的液压齿轮泵状态监测与故障诊断

阐述了容积效率作为特征信息进行液压齿轮泵状态监测与故障诊断的原理,分析了液压齿轮泵中流量信号以及容积效率与齿轮泵工况之间的关系,指出了容积效率是状态信息的丰富载体,讨论了利用容积效率进行液压齿轮泵状态监测与故障诊断的可行性及方法.