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In this paper, we have proposed a Condition-based Maintenance technique for vehicle tire pressure monitoring utilizing univariate statistical analysis. Statistical techniques are very powerful for predicting the future states based on current and previous states of the system or subsystem. Two important statistical techniques ARAR and Holt-Winters have been studied for their robustness to the predictions of such data set. This paper also performs comparative simulation studies to prove the usefulness of both the algorithms based on the data available from wireless sensor nodes. These sensors are directly mounted on tires externally and report the current air pressure to control unit. The control unit performs tire pressure prognosis using univariate statistical technique.

Weld Joints are widely used in automotive and aerospace industry. The main issue in the weld joints is the quality inspection to detect the disconnection in the welded area. In this paper, Shearographic technique with dynamic excitation is introduced to test the weld joints. In the experiments, the coupons are of 4 very thin layers of metal sheets welded together. The goal is to find out if there are any disconnections between the layers. They are clamped and then excited by a PZT actuator from behind. A real time digital Shearographic system with a self-refreshed reference image technology has been developed to display the measuring result, i.e. shearogram. A big range of driving frequencies is scanned to find the proper frequency and amplitude that can help to identify the disconnections. The results show that when the driving frequency reaches the resonance frequency, there will be big amplitude and thus a fringe pattern becomes visible on the coupon surface.