Test Generation for Crosstalk-Induced Faults: Framework and Computational Results

Due to technology scaling and increasing clock frequency, problems due to noise effects lead to an increase in design/debugging efforts and a decrease in circuit performance. This paper addresses the problem of efficiently and accurately generating two-vector tests for crosstalk induced effects, such as pulses, signal speedup and slowdown, in digital combinational circuits. These noise effects can propagate through a circuit and create a logic error in a latch or at a primary output. We have developed a mixed-signal test generator, called XGEN, that incorporates classical static values as well as dynamic signals such as transitions and pulses, and timing information such as signal arrival times, rise/fall times, and gate delay. In this paper we first discuss the general framework of the test generation algorithm followed by computational results. Comparison of results with SPICE simulations confirms the accuracy of this approach.     

直流励磁机电刷打火的常见原因及对策

主要介绍了中铝公司山西分公司自备热电厂6台发电机组的励磁机电刷打火的常见原因的分析和处理方法。     

铸件浸渗系统脱液机故障树的建立和分析

利用FTA方法对脱液机的各种故障进行系统分析,建立了脱液机的故障树,并对故障树进行定性分析.找出了影响脱液机可靠性的主要因素,提出了提高脱液机可靠性的相应措施.     

中频变频器UFV故障探析

本文对中频变频器的UFV故障进行了系统试验和原因分析，并对UFV故障的关键因素进行了详细探析。     

模拟电路的模块级故障诊断

本文以多端口元件或子网络为基本单元，提出了一种模块级故障诊断方案，这种方案的故障模型更符合电路的实际情况，因而具有更广泛的实际意义，文中首先推导了模块故障诊断议程，并对模块故障可测性问题进行了一般性讨论。然后，给出了模块故障可测的几个拓扑条件，并通过定义广义独立通路使这些拓扑条件适用于一般的非互易网络。     

Measurement selection for parametric IC fault diagnosis

This article presents experimental results which show feedforward neural networks are well-suited for analog IC fault diagnosis. Boundary band data (BBD) measurement selection is used to reduce the computational overhead of the FFN training phase. We compare the diagnostic accuracy between traditional statistical classifiers and feedforward neural networks trained with various measurement selection criteria. The feedforward networks consistently perform as well as or better than the other classifiers in term of accuracy. Training using BBD consistently reduces the FFN training efforts without degrading the performance. Experimental results suggest that feedforward networks provide a cost efficient method for IC fault diagnosis in a large scale production testing environment.This work is supported by NSF-IUC CDADIC, Project 90-1.     

基于故障树与灰关联分析的鱼雷故障诊断

将灰色关联度与故障树联合运用于鱼雷故障诊断,为鱼雷的故障诊断提供了一种新途径。在鱼雷动力系统故障树诊断模式识别中,运用灰色系统理论中的灰关联分析,通过进行关联度计算及排序,对各种故障模式发生的可能性大小作出了判断,从而为处理故障的轻重缓急、控制故障的发生以及改进系统的可靠性提供了理论依据。实例诊断表明,这种方法是有效可行的,并且诊断结果可靠。     

应用地应力模拟技术研究断块区剩余油分布

应力场数值模拟不仅能够重塑出不同阶段地应力场，而且还可以定量一半定量地预测破裂的发生、裂缝的方向和密度，进一步探讨时间和空间上油气运移的规律，为油田勘探、开发提供必要的依据。本文以大庆萨北开发区北二西断层区为研究对象，通过应力场数值模拟研究了流体运移势场与剩余油分布的关系、流体运移与构造应力的关系、裂缝形成与剩余油分布的关系，确定了剩余油分布的有利区域，为油田注采系统的设计、部署和油田开发及措施调整提供了依据。     

Application of the blind source separation method to feature extraction of machine sound signals

As the result of vibration emission in air, a machine sound signal carries important information about the working condition of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods .