The studies on micro-structural defects in deformed composite matrix of Al-Si-Mg and SiC

Detailed Fourier line shape analysis has been performed on three different compositions of the composite matrix of Al-Si-Mg and SiC. The alloy composition in wt% is Al-7%Si, 0.35%Mg, 0.14%Fe and traces of copper and titanium (similar to 0.01%) with SiC varying from 0 to 30wt% in three steps i.e., 0, 10 and 30wt%. The line shift analysis has been performed by considering 111, 200, 220, 311 and 222 reflections after estimating their relative shift. Peak asymmetry analysis has been performed considering neighbouring 111 and 200 reflections and Fourier line shape analysis has been performed after considering the multiple orders 111 and 222, 200 and 400 reflections. Combining all these three analyses it has been found that the deformation stacking faults both intrinsic alpha' and extrinsic alpha " are absent in this alloy system whereas the deformation twin beta has been found to be positive and increases with the increase of SiC concentration. So, like other Al-base alloys this ternary alloy also shows high stacking fault energy, and the addition of SiC introduces deformation twin which increases with its concentration in the deformed lattices.

A fault-tolerant distributed deadlock detection algorithm

In this paper, we propose a new fault-tolerant distributed deadlock detection algorithm which can handle loss of any resource release message. It is based on a token-based distributed mutual exclusion algorithm. We have evaluated and compared the performance of the proposed algorithm with two other algorithms which belong to two different classes, using simulation studies. The proposed algorithm is found to be efficient in terms of average number of messages per wait and average deadlock duration compared to the other two algorithms in all situations, and has comparable or better performance in terms of other parameters.

Performance issues of distance relays for shunt FACTS compensated transmission lines

In this paper, the performance of distance relays when applied to transmission system equipped with shunt FACTS device, Static Synchronous Compensator (STATCOM) is described. The aim of the proposed study is to evaluate the performance of distance relays when STATCOM is incorporated at the mid point of transmission lines for voltage control. A detailed model of STATCOM and its control strategy is presented. The presence of these devices significantly affects apparent impedance seen by the distance relays due to their rapid response to different power system configurations. The distance relay is evaluated for different loading conditions and for different fault locations. The faults are created during various pre-fault loading conditions. The studies are performed on 400KV and 132KV systems and the results are presented. Simulation studies are carried out using transient simulation software, PSCAD/EMTDC.

Data rectification and detection of trend shifts in jet engine path measurements using median filters and fuzzy logic

Filtering methods are explored for removing noise from data while preserving sharp edges that many indicate a trend shift in gas turbine measurements. Linear filters are found to be have problems with removing noise while preserving features in the signal. The nonlinear hybrid median filter is found to accurately reproduce the root signal from noisy data. Simulated faulty data and fault-free gas path measurement data are passed through median filters and health residuals for the data set are created. The health residual is a scalar norm of the gas path measurement deltas and is used to partition the faulty engine from the healthy engine using fuzzy sets. The fuzzy detection system is developed and tested with noisy data and with filtered data. It is found from tests with simulated fault-free and faulty data that fuzzy trend shift detection based on filtered data is very accurate with no false alarms and negligible missed alarms.

Fuzzy logic intelligent system for gas turbine module and system fault isolation

A fuzzy logic intelligent system is developed for gas-turbine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. These four measurements are also called the cockpit parameters and are typically found in almost all older and newer jet engines. The fuzzy logic system uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. It automates the reasoning process of an experienced powerplant engineer. Tests with simulated data show that the fuzzy system isolates faults with an accuracy of 89% with only the four cockpit measurements. However, if additional pressure and temperature probes between the compressors and before the burner, which are often found in newer jet engines, are considered, the fault isolation accuracy rises to as high as 98%. In addition, the additional sensors are useful in keeping the fault isolation system robust as quality of the measured data deteriorates.

Health monitoring,of a helicopter rotor in forward flight using fuzzy logic

A fuzzy logic system is developed for helicopter rotor system fault isolation. Inputs to the fuzzy logic system are measurement deviations of blade bending and torsion response and vibration from a "good" undamaged helicopter rotor. The rotor system measurements used are flap and lag bending tip deflections, elastic twist deflection at the tip, and three forces and three moments at the rotor hub. The fuzzy logic system uses rules developed from an aeroelastic model of the helicopter rotor with implanted faults to isolate the fault while accounting for uncertainty in the measurements. The faults modeled include moisture absorption, loss of trim mass, damaged lag damper, damaged pitch control system, misadjusted pitch link, and damaged flap. Tests with simulated data show that the fuzzy system isolates rotor system faults with an accuracy of about 90-100%. Furthermore, the fuzzy system is robust and gives excellent results, even when some measurements are not available. A rule-based expert system based on similar rules from the aeroelastic model performs much more poorly than the fuzzy system in the presence of high levels of uncertainty.

Fault-Tolerant Average Execution Time Optimization for General Purpose Multi-Processor System-on Chips

Fault-tolerance is due to the semiconductor technology development important, not only for safety-critical systems but also for general-purpose (non-safety critical) systems. However, instead of guaranteeing that deadlines always are met, it is for general-purpose systems important to minimize the average execution time (AET) while ensuring fault-tolerance. For a given job and a soft (transient) error probability, we define mathematical formulas for AET that includes bus communication overhead for both voting (active replication) and rollback-recovery with checkpointing (RRC). And, for a given multi-processor system-on-chip (MPSoC), we define integer linear programming (ILP) models that minimize AET including bus communication overhead when: (1) selecting the number of checkpoints when using RRC, (2) finding the number of processors and job-to-processor assignment when using voting, and (3) defining fault-tolerance scheme (voting or RRC) per job and defining its usage for each job. Experiments demonstrate significant savings in AET.

Bounds on Defect Level and Fault Coverage in Linear Analog Circuit Testing

Transfer function coefficients (TFC) are widely used to test linear analog circuits for parametric and catastrophic faults. This paper presents closed form expressions for an upper bound on the defect level (DL) and a lower bound on fault coverage (FC) achievable in TFC based test method. The computed bounds have been tested and validated on several benchmark circuits. Further, application of these bounds to scalable RC ladder networks reveal a number of interesting characteristics. The approach adopted here is general and can be extended to find bounds of DL and FC of other parametric test methods for linear and non-linear circuits.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.

Surface effects on stacking fault and twin formation in fcc nanofilms: A first-principles study

The free surface effects on stacking fault and twin formation in fcc metals (Al, Cu, and Ni) were examined by first-principles calculations based on density functional theory (DFT). It is found that the generalized planar fault (GPF) energies of Ni are much larger than bulk Ni with respect to Al and Cu. The discrepancy is attributed to the localized relaxation of Ni nanofilm to accommodate the large expansion of the inter-planar separation induced at the fault plane. The localized relaxation can be coupled to the electronic structure of Ni nanofilms. (C) 2011 Elsevier B.V. All rights reserved.

The June 2010 Nicobar Earthquake: Fault Reactivation on the Subducting Oceanic Plate

The similar to 1300-km-long rupture zone of the 2004 Andaman-Sumatra megathrust earthquake continues to generate a mix of thrust, normal, and strike-slip faulting events. The 12 June 2010 M(w) 7.5 event on the subducting plate is the most recent large earthquake on the Nicobar segment. The left-lateral faulting mechanism of this event is unusual for the outer-rise region, considering the stress transfer processes that follow great underthrusting earthquakes. Another earthquake (M(w) 7.2) with a similar mechanism occurred very close to this event on 24 July 2005. These earthquakes and most of their aftershocks on the subducting plate were generated by left-lateral strike-slip faulting on north-northeast-south-southwest oriented near-vertical faults, in response to north-northwest-south-southeast directed compression. Pre-2004 earthquake faulting mechanisms on the subducting oceanic plate are consistent with this pattern. Post-2004, left-lateral faulting on the subducting oceanic plate clusters between 5 degrees N and 9 degrees N, where the 90 degrees E ridge impinges the trench axis. Our study observes that the subducting plate off the Sumatra and Nicobar segments behaves similarly to a chip of the India-Australia plate, deforming in response to a generally northwest-southeast oriented compression, an aspect that must be factored into the plate deformation models.

Fault-Diagnostic System using Support Vector Machines for Power Transmission Systems

This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.