A novel laser coating-texturing (LCT) technique was proposed to achieve appropriate surface topographies and frictional
behaviour. The LCT process was realized by applying laser pulses at very high repetition rates to produce innumerable
micro-craters with the required shape profile on the surface of the workpiece. Moreover, surface alloying of the dimples
was carried out by melting submicron WC-Ni alloy powder on the substrates. Morphology and microstructures of the
texturing layers were characterized using optical microscopy (OM), scanning electron microscopy (SEM), and X-ray
diffraction (XRD). Mechanical properties of the textured samples were evaluated by abrasive resistance tests and
microhardness measurement. Experimental results show that good fusion bonding between the texturing layers and the
substrate has been formed, and the texturing layers is mainly composed of dense and hard fine-grained structures. The
abrasive wear resistance of the laser coating textured surface was 5 times higher than that of the substrates. The average
surface microhardness values were as high as 850HV.
KEYWORDS: Actuators, Neural networks, Fourier transforms, Single point diamond turning, Servomechanisms, Systems modeling, Data modeling, Control systems, Calibration, Optics manufacturing
In recent years, interests have been growing for fast tool servo (FTS) systems to increase the capability of existing single-point diamond turning machines. Although piezoelectric actuator is the most universal base of FTS system due to its high stiffness, accuracy and bandwidth, nonlinearity in piezoceramics limits both the static and dynamic performance of piezoelectric-actuated control systems evidently. To compensate the nonlinear hysteresis behavior of piezoelectric actuators, a hybrid model coupled with Preisach model and feedforward neural network (FNN) has been described. Since the training of FNN does not require a special calibration sequence, it is possible for on-line identification and real-time implementation with general operating data of a specific piezoelectric actuator. To describe the rate dependent behavior of piezoelectric actuators, a hybrid dynamic model was developed to predict the response of piezoelectric actuators in a wider range of input frequency. Experimental results show that a maximal error of less than 3% was accomplished by this dynamic model.
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