Nanostructured, biocompatible, TiC/Ti Supersonic Cold Gas Sprayed coatings were deposited onto a Ti6Al4V alloy and their microstructure, wear resistance and hardness were investigated. The starting nanostructured powder, containing a varied mixture of Ti and TiC particles, was produced by high energy ball milling. Scanning and transmission electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction were used for structural and chemical analyses of powder particles and coatings. Coatings, 250-350 μm thick, preserving the nanostructure and chemical powder composition, with low porosity and relatively high hardness (~850 HV), were obtained. These nanostructured TiC/Ti coatings exhibited better tribological properties than commonly used biomedical benchmark materials, due to an appropriate balance of hard and soft nano-phases.
Communication noise is classified as one of the pollutions for the current environment. Experimental techniques to measure tire-pavement noise generation from asphalt pavements in the laboratory have been limited. A series of experiments were conducted on six different asphalt mixtures to determine if Purdue University’s Tire-Pavement Test Apparatus (TPTA) could be used to overcome these limitations. The procedure produced samples with low tire-pavement noise; however, the air void contents of the samples were higher than designed. Despite these difficulties, the sample preparation technique and the TPTA testing protocol were shown to offer an effective approach for quick laboratory assessment of tire-pavement noise characteristics of hot mix asphalt pavements at a substantially reduced cost compared to field testing.
The paper deals with the application of the feed-forward and cascade-forward neural networks to mechanical state variable estimation of the drive system with elastic coupling. The learning procedure of neural estimators is described and the influence of the input vector size and neural network structure to the accuracy of state variable estimation is investigated. The quality of state estimation by neural estimators of different types is tested and compared. The simple optimisation procedure is proposed. Optimised neural estimators of the torsional torque and the load machine speed are tested in the open-loop and closed-loop control structure of the drive system with elastic joint, with additional feedbacks from the shaft torque and the difference between the motor and the load speeds. It is shown that torsional vibrations of the two-mass system are damped effectively using the closed-loop control structure with additional feedbacks obtained from the developed neural estimators. The simulation results are confirmed by laboratory experiments.
The paper deals with the application of the extended Kalman filters in the control structure of a two-mass drive system. In the first step only linear extended Kalman filter was used for the estimation of mechanical state variables of the drive including load torque value. The estimation algorithm showed good robustness to mechanical parameters variations. For the system with some parameters changing in the wide range, simultaneous estimation of the state variables and chosen system parameters is required. For this reason the non-linear extended Kalman filter, which estimates simultaneously state variables and mechanical parameters of the two-mass drive system, was developed. Parameters of covariance matrices of used Kalman filters were set using the genetic algorithm. Both proposed estimators were investigated in simulation and experimental tests, in the open-loop operation and in the state-feedback control system of the two-mass system.
The paper presents research results of multilayer systems composed of alternate Cu/Ni layers. The layers thickness obtained by the galvanic treatment was determined by using the transmission electron microscopy and X-ray diffraction method in the grazing incidence diffraction geometry. The surface morphology was observed using scanning electron microscope with EDS microanalysis. Observation of the surface topography of systems using the atomic force microscope was also carried out.