High Velocity Oxy-Fuel (HVOF) spray techniques can produce high performance alloy and cermet coatings for applications that require wear resistant surfaces. In HVOF spraying heat is produced by burning mixtures of oxygen and fuel, mainly hydrogen, kerosene, propane, propylene, natural gas or acetylene. In these processes, the particle velocity and temperature determine the resultant coating properties and in many cases enables a better understanding of the process. The aim of this study is to investigate influences of different oxygen/fuel ratios on velocity and temperature of flying particles as well as properties of the HVOF thermal sprayed WC-CoCr coatings. In this work the feedstock powders were thermally sprayed by two different variants of the high velocity oxy-fuel process, in which the fuels were hydrogen and kerosene. Particle parameters were recorded just prior to impact on the substrate using in-flight particle diagnostic tool Accuraspray-g3®. Detailed correlation of particle parameters and the coating properties is evaluated in order to deduce particle parameter ranges providing coatings with optimum properties.

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Industrial applications involving mobile systems can benefit from the use of wireless technology. However, wireless communication has not been widely accepted on the factory floor due to its difficulty in achieving the timely and reliable transmission of messages\ud over error-prone wireless channels. This paper presents an autonomous guided vehicle (AGV) path tracking wireless control system where an accurate delay estimation scheme is shown to be the key for successful operation. The control architecture consists\ud on an AGV connected through a wireless network to a controller. To mitigate the negative effects that varying time delays in data transfer have in the networked control\ud loop, the controller performs two tasks at each loop operation. First, it uses a Kalman filter to produce an optimal delay estimate considering a simple stochastic model of the wireless delay dynamics. Second, each delay estimate is employed to infer the real AGV position which permits to compute the appropriate control commands. Results show that the proposed technique provides more efficient and effective operation for path\ud tracking control compared to similar previously proposed solutions.Peer ReviewedPostprint (published version

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