Today, real-time fault detection and predictive maintenance based on sensor data are actively introduced in various areas such as manufacturing, aircraft, power system monitoring. Many faults motors or rotating machinery like industrial robots, aircraft engines, wind turbines can be diagnosed by analyzing signal vibration noise. In this study, to detect failures data, preprocessing was performe...

In this paper we introduce DeepNCM, a Nearest Class Mean classification method enhanced to directly learn highly non-linear deep (visual) representations of the data. To overcome the computational expensive process of recomputing the class means after every update of the representation, we opt for approximating the class means with an online estimate. Moreover, to allow the class means to follo...

One-class Bayes learning such as one-class Naïve Bayes and one-class Bayesian Network employs Bayes learning to build a classifier on the positive class only for discriminating the positive class and the negative class. It has been applied to anomaly detection for identifying abnormal behaviors that deviate from normal behaviors. Because one-class Bayes classifiers can produce probability score...

We use a geometric digraph family called class cover catch digraphs (CCCDs) to tackle the class imbalance problem in statistical classification. CCCDs provide graph theoretic solutions to the class cover problem and have been employed in classification. We assess the classification performance of CCCD classifiers by extensive Monte Carlo simulations, comparing them with other classifiers common...