Stuck-at fault

About: Stuck-at fault is a research topic. Over the lifetime, 9707 publications have been published within this topic receiving 160254 citations.

A methodology for functional level testing of microprocessors

Abstract: The task of fault detection in microprocessors is very difficult because of their complexity. In this paper we present a general model for microprocessors in terms of their control and data processing sections, which includes features o f a large variety of available microprocessors. We then develop a fault model on a functional level which takes into account a large number of failures, including faults in instruction decoding, control commands, data transfer mechanisms, data s torage facilities, and the arithmetic and logic u nit. The basic requirement of a test procedure for a microprocessor is that it be able to check for proper execution of every instruction using o ther potentially faulty i nstructions. A set of test procedures is presented; this set is proved to be capable of detecting all faults in the fault model.

Fault classification and fault signature production for rolling element bearings in electric machines

Abstract: Most condition monitoring techniques for rolling element bearings are designed to detect the four characteristic fault frequencies. This has lead to the common practice of categorizing bearing faults according to fault location (i.e., inner race, outer race, ball, or cage fault). While the ability to detect the four characteristic fault frequencies is necessary, this approach neglects another important class of faults that arise in many industrial settings. This research introduces the notion of categorizing bearing faults as either single-point defects or generalized roughness. These classes separate bearing faults according to the types of fault signatures that are produced rather than by the physical location of the fault. Specifically, single-point defects produce the four predictable characteristic fault frequencies while faults categorized as generalized roughness produce unpredictable broadband changes in the machine vibration and stator current. Experimental results are provided from bearings failed in situ via a shaft current. These results illustrate the unpredictable and broadband nature of the effects produced by generalized roughness bearing faults. This issue is significant because a successful bearing condition monitoring scheme must be able to reliably detect both classes of faults.

System and methods for fault path testing through automated error injection

Abstract: The system and methods described herein relate to testing and verifying the fault tolerance in fault tolerant systems. Fault logic integrated into a fault tolerant system permits automated testing of fault paths in system firmware and hardware dedicated to handling fault scenarios. Advantages of the disclosed system and methods include the ability to inject errors without the need to modify system firmware or hardware. Errors can be injected in a controlled manner and asynchronously to normal system firmware execution which permits improved coverage of firmware error paths. The automated error injection capability disclosed is applicable in both the development and production of fault tolerant systems.

Gas Path Fault Diagnosis of a Turbofan Engine From Transient Data Using Artificial Neural Networks

Abstract: Transient and steady state data may contain the same essential fault information but some faults have been shown to be more easily detectable from transient data because the transient records provide significant diagnostic content especially as the fault effects are magnified under transient. Various traditional and conventional techniques such as fault trees, fault matrixes, gas path analysis and its variants have been applied to gas path fault diagnosis of gas turbines. Recently, artificial intelligence techniques such as artificial neural networks (ANN) as well as optimization techniques such as genetic algorithm (GA) are being explored for fault diagnosis activities. In this paper, a novel approach to gas path fault diagnosis is proposed. The method involves the use of ANN with engine transient data. A set of nested neural networks designed to estimate independent parameter (efficiencies and flow capacities) changes due to faults within single or multiple components of a turbofan engine are presented. The approach involves classification and approximation type networks. Measurements from the engine are first assessed by a trained network and if a fault is diagnosed, are then classified into two groups — those originating from sensor faults and those from component faults, by another trained network. Other trained networks continue the fault isolation process and finally the magnitude of the fault(s) is quantified. A computer simulation of the process shows that results from a batched process of these networks can be obtained in less than three seconds. Four of the gas path components — intermediate pressure compressor (IPC), high pressure compressor (HPC), high pressure turbine (HPT) and low pressure turbine (LPT) — and measurements from eight sensors are considered. Sensor noise and bias are also considered in this analysis. The comparison of fault signatures from a steady state and transient process show that diagnosis with transient data can improve the accuracy of gas turbine fault diagnosis.Copyright © 2003 by ASME

The Boolean Difference and Multiple Fault Analysis

Abstract: The Boolean difference is a well-known mathematical concept which has found significant application in the single fault analysis of combinational logic circuits. One of the primary attributes of the Boolean difference in such situations is its completeness. In this paper we extend the Boolean difference concept to cover multiple fault situations. Expressions are developed which give all possible input patterns that can be applied to combinational logic circuits to demonstrate the presence or absence of a specified multiple fault of the stuck-type class. Such expressions are useful in situations where at most, say, p simultaneous faults need be considered, as well as situations where any multiple fault can exist. In addition the expressions developed are also shown to complete some existing single fault analysis concepts.