New motor development requires high-speed load testing using dynamo equipment to calculate the efficiency of the motor. Abnormal noise and vibration may occur in the test equipment rotating at high speed due to misalignment of the connecting shaft or looseness of the fixation, which may lead to safety accidents. In this study, three single-axis vibration sensors for X, Y, and Z axes were attached on the surface of the test motor to measure the vibration value of vibration. Analog data collected from these sensors was used in classification models for anomaly detection. Since the classification accuracy was around only 93%, commonly used hyperparameter optimization techniques such as Grid search, Random search, and Bayesian Optimization were applied to increase accuracy. In addition, Response Surface Method based on Design of Experiment was also used for hyperparameter optimization. However, it was found that there were limits to improving accuracy with these methods. The reason is that the sampling data from an analog signal does not reflect the patterns hidden in the signal. Therefore, in order to find pattern information of the sampling data, we obtained descriptive statistics such as mean, variance, skewness, kurtosis, and percentiles of the analog data, and applied them to the classification models. Classification models using descriptive statistics showed excellent performance improvement. The developed model can be used as a monitoring system that detects abnormal conditions of the motor test.

Failure diagnoses on large diesel engine are commonly detected when a deviation or fluctuation in its temperature, pressure, vibration or noise set parameter limits arises. These parameters can be easily monitored and can provide information of the engine’s present state depending on external environment and operating conditions. On the other hand, long term monitoring and condition management can be interfaced into the engine’s existing operating system. The approach is seen to keep track of monitored machines’ status using resonance and vibration amplitude. In particular, these signals will be able to identify complex vibration characteristic pertaining to such as engine torque output and support mounts. In this paper, a basic research for large diesel engine diagnosis was carried-out. The failure diagnosis collects and monitors the vibration state time history by using various vibration signals with reference to ISO 13373-1. Further, this monitoring system in the field of large diesel engines has not been applied practically and the results of this study are presented herein.

The market for Game is gradually expanding every year, but most of games are disappearing. For this Reason, User have chosen games based on external factors, and users have been not able to choose customized games for users. Thus, This study aim to provide customized game contents to users among 6 content (logic, space, word, nature, body, music) by making a immersion evaluation model using the Csikszentmihalyi’s theory of flow and Gardner's theory of multiple intelligence. First, it is assumed that the definition of immersion can be obtained as an arousal which is an axis of the emotion criterion. Then, after learning the arousal classification model based on the head micro-vibration as emotion signal, the immersion evaluation system is verified through the evaluation with the multi-intelligence theory. As a result, the user can be informed of what contents are most immersed in the content, and allow to choose the game suitable for himself.

High speed railway bridges should be strictly maintained due to its social importance. However, There are many problems to execute loading test for precision safety diagnosis. A numerical experiment with a numerical model which is updated for reflecting characteristics of an existing bridge can be useful for high speed railway bridge maintenance. Moreover, more efficient maintenance can be possible if only ambient vibration is needed for numerical model updating process. In this study, a numerical model updating process is introduced in which only ambient vibration is enough to execute the process. Also, the usability of updated numerical model is verified by comparing measured and analyzed acceleration.