Technical note: Coherence analysis of the transfer function for dynamic force identification

Identifying dynamic forces with structural response signals is important when direct measurement is difficult or impossible. The minimized condition number method was introduced to reconstruct the forces with selected spatial distribution of response locations. This paper presents another way to optimize the selection of the response locations. The coherence of transfer function matrix is analyzed and the coherence factor of the transfer function matrix is introduced to optimize the response locations. Numerical simulations of the coherence analysis show that it is effective and requires less computational effort than the condition number method. The validity of the analysis is verified by applying it to the identification of the suspension forces on a vehicle cab.     

用于机械状态监测的振动信号的非平稳建模

以往开发的绝大多数故障诊断算法基于数据的平稳性假设,没有考虑机械某一运转周期内的时间相关细节特征。本文针对特定对象强调了非平稳模型用于信号分析的必要性,讨论了模型的时变,耐不变算法及相应的特征提取、工况判断过程。本文引入正交变换,一方面实现了数据的大规模压缩,另一方面完成了代表正常工况的母体模型的建立;其次,借助于模式识别理论的相似性判据得到对多个特征定量监测的方法。一关于柱塞泵振动监测的实例说明了方法的应用过程。     

深圳某中央空调教学设备系统设计及节能措施

中央空调教学设备系统是作为空调专业的辅助教学工具，其设计不同与一般中央空调的设计，本文就中央空调教学设备系统的设计过程及设计中的节能措施和几个具体问题处理做了具体说明。     

复变函数共轭解析的充要条件

在共轭解析函数定义基础上,讨论指数形式表示的函数共轭解析的充要条件.     

Artificial neural networks and genetic algorithm for bearing fault detection

A study is presented to compare the performance of three types of artificial neural network (ANN), namely, multi layer perceptron (MLP), radial basis function (RBF) network and probabilistic neural network (PNN), for bearing fault detection. Features are extracted from time domain vibration signals, without and with preprocessing, of a rotating machine with normal and defective bearings. The extracted features are used as inputs to all three ANN classifiers: MLP, RBF and PNN for two- class (normal or fault) recognition. Genetic algorithms (GAs) have been used to select the characteristic parameters of the classifiers and the input features. For each trial, the ANNs are trained with a subset of the experimental data for known machine conditions. The ANNs are tested using the remaining set of data. The procedure is illustrated using the experimental vibration data of a rotating machine. The roles of different vibration signals and preprocessing techniques are investigated. The results show the effectiveness of the features and the classifiers in detection of machine condition.     

静电粉尘初等模型与场势分布的研究

通过建立静电粉尘的Ｂｏｌｔｚｍａｎｎ分布初等模型计算静电粉尘的场势分布，讨论了击穿条件下粉尘浓度的经验公式，并通过已发表的实验报告证实了上述结论的有效性。     

适用于亚微米沟道MO SFET的阈值电压解析模型

本文利用本征函数方法,采取一定的边界条件,得到了二维泊松方程的解析解.并由此导得适用于亚微米沟道MOS场效应管阈值电压的解析表达式.本解析模型未引进复杂的几何结构参数及经验参数,适用于不同的衬底反偏电压、漏极电压等条件.这些结果与数值模拟的结果以及有关实验的结果符合得较好,对短沟道MOSFET的设计及性能的了解有实际参考价值.     

A Multi-Net System for the Fault Diagnosis of a Diesel Engine

A multi-net fault diagnosis system designed to provide an early warning of combustion-related faults in a diesel engine is presented. Two faults (a leaking exhaust valve and a leaking fuel injector nozzle) were physically induced (at separate times) in the engine. A pressure transducer was used to sense the in-cylinder pressure changes during engine cycles under both of these conditions, and during normal operation. Data corresponding to these measurements were used to train artificial neural nets to recognise the faults, and to discriminate between them and normal operation. Individually trained nets, some of which were trained on subtasks, were combined to form a multi-net system. The multi-net system is shown to be effective when compared with the performance of the component nets from which it was assembled. The system is also shown to outperform a decision-tree algorithm (C5.0), and a human expert; comparisons which show the complexity of the required discrimination. The results illustrate the improvements in performance that can come about from the effective use of both problem decomposition and redundancy in the construction of multi-net systems.     

Detecting natural crack initiation and growth in slow speed shafts with the Acoustic Emission technology

This paper presents results of an experimental investigation to assess the potential of the Acoustic Emission (AE) technology for detecting natural cracks in operational slow speed shafts. A special purpose built test rig was employed for generating natural degradation on a shaft. It was concluded that AE technology successfully detected natural cracks induced on slow speed shafts.     

Modeling and simulation of the engagement dynamics of a wet friction clutch system subjected to degradation: An application to condition monitoring and prognostics

In this paper, a friction model appropriate for wet friction clutches based on the extension of the Generalized Maxwell Slip (GMS) friction model is integrated to a four-DOF lumped-mass-spring-damper system which represents a typical SAE#2 test setup. Degradation models expressing the evolutions of the friction model parameters are also proposed, where the structure of the degradation models is inspired from experimental results obtained in the earlier work. This way, the engagement dynamics of the clutch system during the useful lifetime can be simulated. It appears that the previously developed pre-and postlockup features extracted from the simulated signals obtained in this study are qualitatively in agreement with the experimental results. Those features show their predictive behaviors that confirm their feasibility to be used for clutch monitoring and prognostics. Furthermore, the models and simulation procedure discussed in this paper can be employed for developing and evaluating prognostics algorithms for wet friction clutch applications.