Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

A Design for Testability of Undetectable Crosspoint Faults in Programmable Logic Arrays

In this paper, the validity of'single fault assumption in deriving diagnostic test sets is examined with respect to crosspoint faults in programmable logic arrays (PLA's). The control input procedure developed here can be used to convert PLA's having undetectable crosspoint faults to crosspoint-irredundant PLA's for testing purposes. All crosspoints will be testable in crosspoint-irredundant PLA's. The control inputs are used as extra variables during testing. They are maintained at logic I during normal operation. A useful heuristic for obtaining a near-minimal number of control inputs is suggested. Expressions for calculating bounds on the number of control inputs have also been obtained.

An on-line algorithm for the location of cross point faults in programmable logic arrays

An on-line algorithm is developed for the location of single cross point faults in a PLA (FPLA). The main feature of the algorithm is the determination of a fault set corresponding to the response obtained for a failed test. For the apparently small number of faults in this set, all other tests are generated and a fault table is formed. Subsequently, an adaptive procedure is used to diagnose the fault. Functional equivalence test is carried out to determine the actual fault class if the adaptive testing results in a set of faults with identical tests. The large amount of computation time and storage required in the determination, a priori, of all the fault equivalence classes or in the construction of a fault dictionary are not needed here. A brief study of functional equivalence among the cross point faults is also made.

An On-Line Algorithm for the Location of Cross Point Faults in Programmable Logic Arrays

An on-line algorithm is developed for the location of single cross point faults in a PLA (FPLA). The main feature of the valgorithm is the determination of a fault set corresponding to the response obtained for a failed test. For the apparently small number of faults in this set, all other tests are generated and a fault table is formed. Subsequently, an adaptive procedure is used to diagnose the fault. Functional equivalence test is carried out to determine the actual fault class if the adaptive testing results in a set of faults with identical tests. The large amount of computation time and storage required in the determination, a priori, of all the fault equivalence classes or in the construction of a fault dictionary are not needed here. A brief study of functional equivalence among the cross point faults is also made.

Stream power criterion and design of sand bed channels at incipient motion

The critical stream power criterion may be used to describe the incipient motion of cohesionless particles of plane sediment beds. The governing equation relating ``critical stream power'' to ``shear Reynolds number'' is developed by using the present experimental data as well as the data from several other sources. Simultaneously, a resistance equation, relating the ``particle Reynolds number'' to the``shear Reynolds number'' is developed for plane sediment beds in wide channels with little or no transport. By making use of these relations, a procedure is developed to design plane sediment beds such that any two of the four design variables, including particle size, energy/friction slope, flow depth, and discharge per unit width in the channel should be known to predict the remaining two variables. Finally, a straightforward design procedure using design tables/design curves and analytical methods is presented to solve six possible design problems.

An incipient 310 helix in Piv-Pro-Pro-Ala-NHMe as a model for peptide folding

The molecular mechanism of helix nucleation in peptides and proteins is not yet understood and the question of whether sharp turns in the polypeptide backbone serve as nuclei for protein folding has evoked controversy1,2. A recent study of the conformation of a tetrapeptide containing the stereochemically constrained residue alpha-aminoisobutyric acid, both in solution and the solid state, yielded a structure consisting of two consecutive beta-turns, leading to an incipient 310 helical conformation3,4. This led us to speculate that specific tri- and tetra-peptide sequences may indeed provide a helical twist to the amino-terminal segment of helical regions in proteins and provide a nucleation site for further propagation. The transformation from a 310 helical structure to an alpha-helix should be facile and requires only small changes in the phi and psi conformational angles and a rearrangement of the hydrogen bonding pattern5. If such a mechanism is involved then it should be possible to isolate an incipient 310 helical conformation in a tripeptide amide or tetrapeptide sequence, based purely on the driving force derived from short-range interactions. We have synthesised and studied the model peptide pivaloyl-Pro-Pro-Ala-NHMe (compound I) and provide here spectroscopic evidence for a 310 helical conformation in compound I.

An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems

Power system disturbances are often caused by faults on transmission lines. When faults occur in a power system, the protective relays detect the fault and initiate tripping of appropriate circuit breakers, which isolate the affected part from the rest of the power system. Generally Extra High Voltage (EHV) transmission substations in power systems are connected with multiple transmission lines to neighboring substations. In some cases mal-operation of relays can happen under varying operating conditions, because of inappropriate coordination of relay settings. Due to these actions the power system margins for contingencies are decreasing. Hence, power system protective relaying reliability becomes increasingly important. In this paper an approach is presented using Support Vector Machine (SVM) as an intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. Results on 24-bus equivalent EHV system, part of Indian southern grid, are presented for illustration purpose. This approach is particularly important to avoid mal-operation of relays following a disturbance in the neighboring line connected to the same substation and assuring secure operation of the power systems.

Incipient motion design of sand bed channels affected by bed suction

Seepage through sand bed channels in a downward direction (suction) reduces the stability of particles and initiates the sand movement. Incipient motion of sand bed channel with seepage cannot be designed by using the conventional approach. Metamodeling techniques, which employ a non-linear pattern analysis between input and output parameters and solely based on the experimental observations, can be used to model such phenomena. Traditional approach to find non-dimensional parameters has not been used in the present work. Parameters, which can influence the incipient motion with seepage, have been identified and non-dimensionalized in the present work. Non-dimensional stream power concept has been used to describe the process. By using these non-dimensional parameters; present work describes a radial basis function (RBF) metamodel for prediction of incipient motion condition affected by seepage. The coefficient of determination, R-2 of the model is 0.99. Thus, it can be said that model predicts the phenomena very well. With the help of the metamodel, design curves have been presented for designing the sand bed channel when it is affected by seepage. (C) 2010 Elsevier B.V. All rights reserved.

Incipient straining in severe plastic deformation methods

Knowledge of the plasticity associated with the incipient stage of chip formation is useful toward developing an understanding of the deformation field underlying severe plastic deformation processes. The transition from a transient state of straining to a steady state was investigated in plane strain machining of a model material system-copper. Characterization of the evolution to a steady-state deformation field was made by image correlation, hardness mapping, load analysis, and microstructure characterization. Empirical relationships relating the deformation heterogeneity and the process parameters were found and explained by the corresponding effects on shear plane geometry. The results are potentially useful to facilitate a framework for process design of large strain deformation configurations, wherein transient deformation fields prevail. These implications are considered in the present study to quantify the efficiency of processing methods for bulk ultrafine-grained metals by large strain extrusion machining and equal channel angular pressing.

Temperature-dependent stability of stacking faults in Al, Cu and Ni: first-principles analysis

We present comparative analysis of microscopic mechanisms relevant to plastic deformation of the face-centered cubic (FCC) metals Al, Cu, and Ni, through determination of the temperature-dependent free energies of intrinsic and unstable stacking faults along 1 (1) over bar 0] and 1 (2) over bar 1] on the (1 1 1) plane using first-principles density-functional-theory-based calculations. We show that vibrational contribution results in significant decrease in the free energy of barriers and intrinsic stacking faults (ISFs) of Al, Cu, and Ni with temperature, confirming an important role of thermal fluctuations in the stability of stacking faults (SFs) and deformation at elevated temperatures. In contrast to Al and Ni, the vibrational spectrum of the unstable stacking fault (USF1 (2) over bar 1]) in Cu reveals structural instabilities, indicating that the energy barrier (gamma(usf)) along the (1 1 1)1 (2) over bar 1] slip system in Cu, determined by typical first-principles calculations, is an overestimate, and its commonly used interpretation as the energy release rate needed for dislocation nucleation, as proposed by Rice (1992 J. Mech. Phys. Solids 40 239), should be taken with caution.

Protection of Digital Telecom Exchanges Against Lightning Surges and Earth Faults

Low-power electronic devices used in digital telecom exchanges are vulnerable to surge voltages and currents primarily originating from natural lightning or due to the direct interactions between electric power and telecommunication lines, etc., causing the earth/ground potential rise, neutral potential rise, and faults in the system. The fault currents may flow directly to telecom lines or through the equipment to the customer's premises, causing adequate damage to the equipment and personnel safety. In wireline applications, analog or digital, central office, exchanges, and subscriber sides have to be protected. Decisive protection and protective methods have to be employed for proper functioning of the equipment under overvoltage/overcurrent conditions. Current investigation reports some interesting results obtained on the recently developed high-voltage high-current protection cards used in digital telecom exchanges. The performances of protection cards both for the ring wave and hybrid wave surges are evaluated and presented. The surge generators required for the investigation are developed and fabricated in house as per the relevant telecom standards.