Tire-related crashes account for a large proportion of all types of car accidents. The causes of tire-related accidents are inappropriate tire temperature, pressure, and wear. Although temperature and pressure can be monitored easily with TPMS, there exists no system to monitor tire wear regularly. This paper proposes a system that can estimate tire wear using a 3-axis accelerometer attached to the tread inside the tire. This system utilizes axial acceleration, extracts feature from data acquired with the accelerometer and estimates tire wear by feature classification using machine learning. In particular, the proposed tire wear estimation method is designed to estimate tread depth in four types (7, 5.6, 4.2, and 1.4 mm) at speeds of 40, 50, and 60 kmph. Based on the data obtained during several runs on a test track, it has been found that this system can estimate the tread depth with reasonable accuracy.

In the existing machine tool field, the focus was on the displacement of the feed system from the viewpoint of the motion of the machine tool. The displacement of the tool or spindle of a machine tool is useful for developing various functions. In this study, using the acceleration data of the spindle, we proposed an algorithm that tracked the displacement of the spindle with respect to the pseudo-step waveform motion. In order to solve the bandwidth problem of the pseudo-step waveform, the displacement data measured by the motor encoder of the feed system was used. In addition, in order to solve the drift problem due to double integration, a new drift removal filter was proposed and a displacement estimation algorithm was implemented. In order to examine the performance and possibility of the proposed spindle displacement estimation algorithm, it was applied to a gantry-type engraver and its excellent performance was confirmed compared to other algorithms.

In this study, the disturbance torque that maintains the gimbal at a specific angle during the centrifugal acceleration test was analyzed. Newton"s Second Law for Rotation was applied, to calculate the disturbance torque. A Theoretic solution for calculating the disturbance torque was derived, by separating the horizontal/vertical components of the moment of inertia. The Theoretic solution was verified, by numerical analysis (RecurDyn) of the simplified Gimbal model. To include the effect of acceleration, the distance between the central axis of the gimbal and the accelerated test equipment was applied as 0 and L (non-Zero). As a result of the analysis, it was found that the main disturbance torque is not related to acceleration, but to self-centrifugal force caused by rotation. A centrifugal acceleration test was conducted, to verify the operational performance of gimbal. The disturbance torque was calculated, by measuring the torque used to operate the gimbal"s motor. The result was compared with the disturbance torque, calculated by the Theoretic solution of the gimbal. The error between the result of test and Theoretic solution of torque was less than 4.5%.

In this study we investigated Kalman filter-based attitude estimation algorithms, considering external acceleration and bias effects in several different scenarios. Towards these goals, gyro biases were first estimated, or calibrated, in all three applied algorithms. Whereas external acceleration effects were not considered in the first algorithm, external acceleration effects were compensated for in the second and third algorithms, using the Kalman filter’s residual and acceleration model. Low, intermediate, and high external acceleration scenarios were then implemented in our test-bed. Three different rotational frequencies (0.3, 3, and 6 ㎐) for roll and pitch rotations were applied. Performance of each estimation algorithm was analyzed using slopes, y-intercepts, and standard deviations obtained from the linear regression. Our results confirm that attitude estimation errors are linearly proportional to the magnitude of the applied external acceleration. Perhaps most importantly, our results show the second algorithm may be used to provide relatively uniform and accurate estimation performance for low- and high-frequency motions.

In this study, a numerical analysis on the impact response of HHA (High Hardness Armor Plate) sequences under a 7.62 mm projectile impact was performed to obtain the fundamental design data for a combat-vehicle platform. Recently, the ballistic-protection levels for combat vehicles have increased, and ballistic-protection designs should now be able to deflect multi-hit projectiles. To study the ballistic-impact characteristics, armor-plate sequences of one or two layers with a gap of 0 mm to 2 mm between the front and rear plate were defined under the same weight and thickness. For the certification of the reliability of the numerical model, ballistic tests and an analysis of the single plate under the 7.62 mm projectile impact were performed and analyzed. On the basis of a valid numerical model, a numerical analysis was performed and analyzed. Lastly, it was proved that the performances of the two-layer sequence with the 2 mm gap regarding the impact-response acceleration, deflection efficiency, and penetration depth are the highest.