Fault tolerant machine learning for nanoscale cognitive radio

We introduce a machine learning-based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanoscale implementation constraints; we do not describe all physical details but believe future physical implementation to be feasible. The system uses analog computation and consists of cyclostationary feature extraction and a radial basis function network for classification. We describe a model for nanoscale faults in the system, and simulate experimental performance and fault tolerance in recognizing WLAN signals, under different levels of noise and computational errors. The system performs well under expected non-ideal manufacturing and operating conditions.     

On the estimation of adequate test set size using fault failure rates

Test set size in terms of the number of test cases is an important consideration when testing software systems. Using too few test cases might result in poor fault detection and using too many might be very expensive and suffer from redundancy. We define the failure rate of a program as the fraction of test cases in an available test pool that result in execution failure on that program. This paper investigates the relationship between failure rates and the number of test cases required to detect the faults. Our experiments based on 11 sets of C programs suggest that an accurate estimation of failure rates of potential fault(s) in a program can provide a reliable estimate of adequate test set size with respect to fault detection and should therefore be one of the factors kept in mind during test set construction. Furthermore, the model proposed herein is fairly robust to incorrect estimations in failure rates and can still provide good predictive quality. Experiments are also performed to observe the relationship between multiple faults present in the same program using the concept of a failure rate. When predicting the effectiveness against a program with multiple faults, results indicate that not knowing the number of faults in the program is not a significant concern, as the predictive quality is typically not affected adversely.     

多级故障诊断系统

介绍了为提高故障诊断的正确率,将一混合故障诊断专家系统中的基于BP神经网络诊断模块、基于自组织神经网络诊断模块和基于小波分析诊断模块设计成多级诊断系统。对多级诊断系统的性能进行了分析,给出了多级诊断系统的拒绝输出策略。     

知识获取技术及其在网络智能故障诊断中的应用

基于遗传算法提出了一种新型的机器学习方法,它利用遗传算法的全局寻优手段,为解决知识获取这一瓶颈问题另辟捷径。论述了该方法的原理及其实现过程,并且给出了网络故障诊断应用实例,证明了它的有效性。     

Identification of statistical patterns in complex systems via symbolic time series analysis

Identification of statistical patterns from observed time series of spatially distributed sensor data is critical for performance monitoring and decision making in human-engineered complex systems, such as electric power generation, petrochemical, and networked transportation. This paper presents an information-theoretic approach to identification of statistical patterns in such systems, where the main objective is to enhance structural integrity and operation reliability. The core concept of pattern identification is built upon the principles of Symbolic Dynamics, Automata Theory, and Information Theory. To this end, a symbolic time series analysis method has been formulated and experimentally validated on a special-purpose test apparatus that is designed for data acquisition and real-time analysis of fatigue damage in polycrystalline alloys.     

基于Internet的空分设备远程监视与故障诊断专家系统的研究

简介了远程监视与故障诊断专家系统在国内空分设备中应用的实际意义，着重分析了大型空分设备远程监视与故障诊断专家系统中远程监视模块和故障诊断模块的开发。     

感应电机转子绕组故障仿真与实验研究

从仿真计算与实验两方面对感应电机转子绕组故障进行研究。首先分析断条数量对电机的影响：讨论了转子断条故障后转子备导条电流以及备段端环电流分布及变化情况，转子断条数量与定子电流中转子绕组故障特征量的关系。转子断条位置对电机影响很大，过去没有引起人们的重视，该文对此进行深入研究，分析电机转子断条位置与故障特征量之间的关系，转子断条位置与转子导条电流、转子端环电流之间的关系，并总结出其规律，指出哪些位置导条进一步断裂的可能性较大。该文还揭示了过去人们试图把故障特征量的大小作为电机转子断条根数多少的判据的局限性，提出了把断条引起电机的不对称性作为电机转子绕组故障程度判据的新的理论。     

基于电压波形分析的十二相整流装置故障诊断

通过对十二相整流装置正常工作和故障运行时，整流元件电压波形的分析，提出了用以判断整流元件工作状态的特征函数，根据由该函数求出的特征值，可以对十二相整流装置的故障（包括复合故障）进行在线诊断，确定故障性质，并能准确定位到具体元件。     

热网监控系统GPRS通讯终端的设计与实现

针对 GPRS 热网监控系统通讯终端常采用"主-从"轮询通信方式单一的缺点,通过优化故障报警上传通信机制,实现了一种"主-从"与"从-主"有机结合的双向通信系统,不仅大大提高了运行速度,还提高了系统的可靠性。通讯终端采用高性能的32位 ARM 处理器,以嵌入式实时操作系统为核心,使用专用的 GPRS 模块 MC39i 实现换热站与调度中心之间的数据通信。阐述了系统的设计思路和终端软、硬件的设计结构,重点介绍了从-主通信方式—故障报警的设计方法。     

The perceived effect of breakdown and repair on the performance of multiprocessor systems

It is argued that classical measures of computer system performance, for example mean response time, are inadequate in the context of fault-tolerant system design. Alternative, perception-based measures are proposed and theorems established describing their properties. Focus is directed upon the homogeneous M/M/m system in which total processor power is constrained by budget and processors are subject to failure and repair. A numerical technique for extracting both classical and perception-based measures from the associated two-dimensional Markov process is offered, along with bounds on time and space required for its execution. It is seen that the perception-based approach to system design can call for twice as many processors as the classical approach.