Study of Friction and Transfer Layer Formation in Copper-Steel Tribo-System: Role of Surface Texture and Roughness Parameters

In the present investigation, experiments were conducted on a tribological couple-copper pin against steel plate-using an inclined pin-on-plate sliding tester to understand the role of surface texture and roughness parameters of the plate on the coefficient friction and transfer layer formation. Two surface characteristics of the steel plates-roughness and texture-were varied in the tests. It was observed that the transfer layer formation and the coefficient of friction along with its two components, namely, the adhesion and plowing, are controlled by the surface texture of the plate. The plowing component of friction was highest for the surface texture that promotes plane strain conditions while it was lowest for the texture that favors plane stress conditions at the interface. Dimensionless quantifiable roughness parameters were formulated to describe the degree of plowing and hence the plane strain/stress type deformations taking place at the asperity level.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters II. Numerical performance

A very general and numerically quite robust algorithm has been proposed by Sastry and Gauvrit (1980) for system identification. The present paper takes it up and examines its performance on a real test example. The example considered is the lateral dynamics of an aircraft. This is used as a vehicle for demonstrating the performance of various aspects of the algorithm in several possible modes.

Non-Abelian monopoles break color. II. Field theory and quantum mechanics

Many grand unified theories (GUT's) predict non-Abelian monopoles which are sources of non-Abelian (and Abelian) magnetic flux. In the preceding paper, we discussed in detail the topological obstructions to the global implementation of the action of the "unbroken symmetry group" H on a classical test particle in the field of such a monopole. In this paper, the existence of similar topological obstructions to the definition of H action on the fields in such a monopole sector, as well as on the states of a quantum-mechanical test particle in the presence of such fields, are shown in detail. Some subgroups of H which can be globally realized as groups of automorphisms are identified. We also discuss the application of our analysis to the SU(5) GUT and show in particular that the non-Abelian monopoles of that theory break color and electroweak symmetries.

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.

A study of geotechnical properties of Cochin Marine Clays

Most of the Greater Cochin area, which is undergoing rapid industrialisation, consists of extremely soft marine clay calling for expensive deep foundations. This paper presents a study on the physical properties and engeering characteristics of Cochin marine clays. These marine clays are characterised by high Atterberg limits and natural water contents. They are moderately sensitive with liquidity indices ranging over 0.46 to 0.87.The grain size distribution shows almost equal fractions of clay and silt size with sand content varying around 20%. Use of a dispersing agent in carrying out grain size distribution test plays an important role. The fabric of these clays had been identified as flocculant. The pore water has low salinity which results in marginal changes in properties on washing.Consolidation test results showed a preconsolidation pressure of up to about 0.5 kg/cm2 with high compression indices. Compression index vs liquid limit yielded a correlation comparable to that of published data. The undisturbed samples have a much larger coefficient of secondary consolidation as a result of flocculant fabric. These clays have very low undrained shear strength.

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 vector measure for the intelligence of a question-answering (Q-A) system

The problem of quantification of intelligence of humans, and of intelligent systems, has been a challenging and controversial topic. IQ tests have been traditionally used to quantify human intelligence based on results of test designed by psychologists. It is in general very difficult to quantify intelligence. In this paper the authors consider a simple question-answering (Q-A) system and use this to quantify intelligence. The authors quantify intelligence as a vector with three components. The components consist of a measure of knowledge in asking questions, effectiveness of questions asked, and correctness of deduction. The authors formalize these parameters and have conducted experiments on humans to measure these parameters

Synthesis and Degradation of Sorbitol-Based Polymers

A new class of biodegradable copolyesters was synthesized by the catalyst-free melt condensation of sorbitol with citric acid, tartaric acid, and sebacic acid. The resulting polymers were designated as poly(sorbitol citric sebacate) p(SCS)] and poly(sorbitol tartaric sebacate) p(STS)]. The synthesized polymers were characterized by Fourier transform infrared spectroscopy, H-1-NMR spectroscopy, and differential scanning calorimetry analysis. Porous spongelike scaffolds were prepared with a salt-leaching technique and characterized with scanning electron microscopy. Tensile testing of the p(SCS) and p(STS) polymers showed that they exhibited a wide range of mechanical properties. The Young's modulus and tensile strengths of the polymers ranged from 1.06 +/- 0.12 to 462.65 +/- 34.21 MPa and from 0.45 +/- 0.04 to 20.32 +/- 2.54 MPa, respectively. In vitro degradation studies were performed on disc-shaped polymer samples. The half-life of the polymers ranged from 0.54 to 38.52 days. The percentage hydration of the polymers was in the range 9.36 +/- 1.26 to 78.25 +/- 1.91, with sol contents of 2-14%. At any given polymer composition, the Young's modulus and tensile strength of p(SCS) was higher than that of p(STS), whereas the degradation rates of p(SCS) was lower than that of p(STS). This was attributed to the structural difference between the citric and tartaric monomers and to the degree of crosslinking. (C) 2011 Wiley Periodicals, Inc. J Appl Polym Sci 121: 2861-2869, 2011

Tribological response of soft materials sliding against hard surface textures at various numbers of cycles

In the present investigation, various kinds of textures were attained on the steel surfaces. Roughness of the textures was varied using different grits of emery papers or polishing powders. Pins made of pure Al, Al-4Mg alloy and pure Mg were then slid against prepared steel plate surfaces at various numbers of cycles using an inclined pin-on-plate sliding tester. Tests were conducted at a sliding velocity of 2mms(-1) in ambient conditions under both dry and lubricated conditions. Normal loads were increased up to 110N during the tests. The morphologies of the worn surfaces of the pins and the formation of transfer layer on the counter surfaces were observed using a scanning electron microscope. Surface roughness parameters of the plate were measured using an optical profilometer. In the experiments, it was observed that the coefficient of friction and formation of a transfer layer (under dry and lubricated conditions) only depended on surface texture during the first few sliding cycles. The steady-state variation in the coefficient of friction under both dry and lubrication conditions was attributed to the self-organisation of texture of the surfaces at the interface during sliding. Copyright (C) 2012 John Wiley & Sons, Ltd.

Recognition of Kannada characters extracted from scene images

In this paper, we describe a method for feature extraction and classification of characters manually isolated from scene or natural images. Characters in a scene image may be affected by low resolution, uneven illumination or occlusion. We propose a novel method to perform binarization on gray scale images by minimizing energy functional. Discrete Cosine Transform and Angular Radial Transform are used to extract the features from characters after normalization for scale and translation. We have evaluated our method on the complete test set of Chars74k dataset for English and Kannada scripts consisting of handwritten and synthesized characters, as well as characters extracted from camera captured images. We utilize only synthesized and handwritten characters from this dataset as training set. Nearest neighbor classification is used in our experiments.

Factors influencing stick-slip motion: effect of hardness, crystal structure and surface texture

In the present investigation, efforts were made to study the different frictional responses of materials with varying crystal structure and hardness during sliding against a relatively harder material of different surface textures and roughness. In the experiments, pins were made of pure metals and alloys with significantly different hardness values. Pure metals were selected based on different class of crystal structures, such as face centered cubic (FCC), body centered cubic (BCC), body centered tetragonal (BCT) and hexagonal close packed (HCP) structures. The surface textures with varying roughness were generated on the counterpart plate which was made of H-11 die steel. The experiments were conducted under dry and lubricated conditions using an inclined pin-on-plate sliding tester for various normal loads at ambient environment. In the experiments, it was found that the coefficient of friction is controlled by the surface texture of the harder mating surfaces. Further, two kinds of frictional response, namely steady-state and stick-slip, were observed during sliding. More specifically, stead-state frictional response was observed for the FCC metals, alloys and materials with higher hardness. Stick-slip frictional response was observed for the metals which have limited number of slip systems such as BCT and HCP. In addition, the stick-slip frictional response was dependent on the normal load, lubrication, hardness and surface texture of the counterpart material. However, for a given kind of surface texture, the roughness of the surface affects neither the average coefficient of friction nor the amplitude of stick-slip oscillation significantly.

SELF-ORGANIZATION AND FRICTION DURING SLIDING

In self-organized sliding processes, the surfaces align to each other during sliding. This alignment leads to a more ordered contact state and significantly influences the frictional behavior. To understand the self-organization sliding processes, experiments were conducted on a pin-on-plate reciprocating sliding tester for various numbers of cycles. In the experiments, soft magnesium pins were slid against hard steel plates of various surface textures (undirectional, 8-ground, and random). Experimental results showed that the transfer layer formation on the steel plates increased with increasing number of cycles for all surfaces textures under both dry and lubricated conditions. The friction also increased with the number of cycles under dry conditions for all of the textures studied. During lubricated conditions, the friction decreased for unidirectional and 8-ground surfaces and increased for random surfaces with the number of cycles. Furthermore, the friction and transfer layer formation depend on the surface textures under both dry and lubricated conditions during the first few sliding cycles. Later on, it is less dependent of surface textures. The variation in the coefficient of friction under both dry and lubrication conditions were attributed to the self-organization process that occurred during repeated sliding.

STUDENT'S-t MIXTURE MODEL BASED MULTI-INSTRUMENT RECOGNITION IN POLYPHONIC MUSIC

We address the problem of multi-instrument recognition in polyphonic music signals. Individual instruments are modeled within a stochastic framework using Student's-t Mixture Models (tMMs). We impose a mixture of these instrument models on the polyphonic signal model. No a priori knowledge is assumed about the number of instruments in the polyphony. The mixture weights are estimated in a latent variable framework from the polyphonic data using an Expectation Maximization (EM) algorithm, derived for the proposed approach. The weights are shown to indicate instrument activity. The output of the algorithm is an Instrument Activity Graph (IAG), using which, it is possible to find out the instruments that are active at a given time. An average F-ratio of 0 : 7 5 is obtained for polyphonies containing 2-5 instruments, on a experimental test set of 8 instruments: clarinet, flute, guitar, harp, mandolin, piano, trombone and violin.

Bayesian Accelerated Life Testing under Competing Weibull Causes of Failure

Consider a J-component series system which is put on Accelerated Life Test (ALT) involving K stress variables. First, a general formulation of ALT is provided for log-location-scale family of distributions. A general stress translation function of location parameter of the component log-lifetime distribution is proposed which can accommodate standard ones like Arrhenius, power-rule, log-linear model, etc., as special cases. Later, the component lives are assumed to be independent Weibull random variables with a common shape parameter. A full Bayesian methodology is then developed by letting only the scale parameters of the Weibull component lives depend on the stress variables through the general stress translation function. Priors on all the parameters, namely the stress coefficients and the Weibull shape parameter, are assumed to be log-concave and independent of each other. This assumption is to facilitate Gibbs sampling from the joint posterior. The samples thus generated from the joint posterior is then used to obtain the Bayesian point and interval estimates of the system reliability at usage condition.

Bayesian Accelerated Life Testing under Competing Weibull Causes of Failure

Consider a J-component series system which is put on Accelerated Life Test (ALT) involving K stress variables. First, a general formulation of ALT is provided for log-location-scale family of distributions. A general stress translation function of location parameter of the component log-lifetime distribution is proposed which can accommodate standard ones like Arrhenius, power-rule, log-linear model, etc., as special cases. Later, the component lives are assumed to be independent Weibull random variables with a common shape parameter. A full Bayesian methodology is then developed by letting only the scale parameters of the Weibull component lives depend on the stress variables through the general stress translation function. Priors on all the parameters, namely the stress coefficients and the Weibull shape parameter, are assumed to be log-concave and independent of each other. This assumption is to facilitate Gibbs sampling from the joint posterior. The samples thus generated from the joint posterior is then used to obtain the Bayesian point and interval estimates of the system reliability at usage condition.