Influence of inclination angle of plate on friction, stick-slip and transfer layer-A study of magnesium pin sliding against steel plate

In this study, sliding experiments were conducted using pure magnesium pins against steel plates using an inclined pin-on-plate sliding tester. The inclination angle of the plate was varied in the tests and for each inclination angle, the pins were slid both perpendicular and parallel to the unidirectional grinding marks direction under both dry and lubricated conditions. SEM was used to study morphology of the transfer layer formed on the plates. Surface roughness of plates was measured using an optical profilometer. Results showed that the friction, amplitude of stick-slip motion and transfer layer formation significantly depend on both inclination angle and grinding marks direction of the plates. These variations could be attributed to the changes in the level of plowing friction taking place at the asperity level during sliding.

Studies on friction and formation of transfer layer when Al-4Mg alloy pins slid at various numbers of cycles on steel plates of different surface texture

In the present investigation, various kinds of textures, namely, unidirectional, 8-ground, and random were attained on the die surfaces. Roughness of the textures was varied using different grits of emery papers or polishing powders. Then pins made of Al-4Mg alloys were slid against steel plates at various numbers of cycles, namely 1, 2, 6, 10 and 20 under both dry and lubricated conditions using an inclined pin-on-plate sliding tester. 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. It was observed that the coefficient of friction and formation of transfer layer during the first few cycles depend on the die surface textures under both dry and lubricated conditions. It was also observed that under lubricated condition, the coefficient of friction decreases with number of cycles for all kinds of textures. However, under dry condition, it ecreases for unidirectional and 8-ground surfaces while for random surfaces it increases with number of cycles

The effects of sliding velocity and sliding time on nanocrystalline tribolayer development and properties in copper

The growth of the nanocrystalline tribolayer produced in oxygen free high conductivity copper after sliding against 440C stainless steel was studied. Tests were conducted on a pin-on-disk tribometer at sliding velocities of 0.05 and 1.0 m/s and sliding times of 0.1 to 10,000 s. Subsurface deformation and the growth of the tribolayer as a function of time were studied with the use of transmission electron microscopy and ion induced secondary electron microscopy. A continuous nanocrystalline tribolayer was produced after as little as 10 s of sliding at both sliding velocities. The tribolayer produced by sliding at 0.05 m/s continued to grow at sliding times up to 10,000 s and developed texture. Dynamic recrystallization of the tribolayer at a sliding velocity of 1.0 m/s inhibited the growth of a continuous anocrystalline tribolayer.

Molecular dynamics simulations of sliding in an Fe-Cu tribopair system

Experimental evidence suggests that high strain rates, stresses, strains and temperatures are experienced near sliding interfaces. The associated microstructural changes are due to several dynamic an interacting phenomena. 3D non-equilibrium molecular dynamics (MD) simulations of sliding were conducted with the aim of understanding the dynamic processes taking place in crystalline tribopairs, with a focus on plastic deformation and microstructural evolution. Embedded atom potentials were employed for simulating sliding of an Fe-Cu tribopair. Sliding velocity, crystal orientation and presence of lattice defects were some of the variables in these simulations. Extensive plastic deformation involving dislocation and twin activity, dynamic recrystallization, amorphization and/or nanocrystallization, mechanical mixing and material transfer were observed. Mechanical mixing in the vicinity of the sliding interface was observed even in the Fe-Cu system, which would cluster under equilibrium conditions, hinting at the ballistic nature of the process. Flow localization was observed at high velocities implying the possible role of adiabatic heating. The presence of preexisting defects (such as dislocations and interfaces) played a pivotal role in determining friction and microstructural evolution. The study also shed light on the relationship between adhesion and plastic deformation, and friction. Comparisons with experiments suggest that such simulations can indeed provide valuable insights that are difficult to obtain from experiments.

Reverse Channel Training For Reciprocal Mimo Systems With Spatial Multiplexing

This paper investigates the problem of designing reverse channel training sequences for a TDD-MIMO spatial-multiplexing system. Assuming perfect channel state information at the receiver and spatial multiplexing at the transmitter with equal power allocation to them dominant modes of the estimated channel, the pilot is designed to ensure an stimate of the channel which improves the forward link capacity. Using perturbation techniques, a lower bound on the forward link capacity is derived with respect to which the training sequence is optimized. Thus, the reverse channel training sequence makes use of the channel knowledge at the receiver. The performance of orthogonal training sequence with MMSE estimation at the transmitter and the proposed training sequence are compared. Simulation results show a significant improvement in performance.

Analysis-By-Synthesis Based Switched Transform Domain Split Vq Using Gaussian Mixture Model

Using analysis-by-synthesis (AbS) approach, we develop a soft decision based switched vector quantization (VQ) method for high quality and low complexity coding of wideband speech line spectral frequency (LSF) parameters. For each switching region, a low complexity transform domain split VQ (TrSVQ) is designed. The overall rate-distortion (R/D) performance optimality of new switched quantizer is addressed in the Gaussian mixture model (GMM) based parametric framework. In the AbS approach, the reduction of quantization complexity is achieved through the use of nearest neighbor (NN) TrSVQs and splitting the transform domain vector into higher number of subvectors. Compared to the current LSF quantization methods, the new method is shown to provide competitive or better trade-off between R/D performance and complexity.

Compressive Sensing For Sparsely Excited Speech Signals

Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived from the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra.

Sampling disturbances of soft sensitive clays

Sampling disturbance is unavoidable and hence the laboratory testing most often is on partially disturbed samples. This paper deals with the development of a simple method to assess degree of sample disturbance from the prediction of yield stress due to cementation and comparison of yield stress in compression of partially disturbed sample with reference to a predicted compression path of the clay devoid of any mechanical disturbance. The method uses simple parameters which are normally determined in routine investigations.

MULTI-INSTRUMENT DETECTION IN POLYPHONIC MUSIC USING GAUSSIAN MIXTURE BASED FACTORIAL HMM

We formulate the problem of detecting the constituent instruments in a polyphonic music piece as a joint decoding problem. From monophonic data, parametric Gaussian Mixture Hidden Markov Models (GM-HMM) are obtained for each instrument. We propose a method to use the above models in a factorial framework, termed as Factorial GM-HMM (F-GM-HMM). The states are jointly inferred to explain the evolution of each instrument in the mixture observation sequence. The dependencies are decoupled using variational inference technique. We show that the joint time evolution of all instruments' states can be captured using F-GM-HMM. We compare performance of proposed method with that of Student's-t mixture model (tMM) and GM-HMM in an existing latent variable framework. Experiments on two to five polyphony with 8 instrument models trained on the RWC dataset, tested on RWC and TRIOS datasets show that F-GM-HMM gives an advantage over the other considered models in segments containing co-occurring instruments.