An effective data reduction model for machine emergency state detection from big data tree topology structures - Iaremko, Iaroslav; Senkerik, Roman; Jasek, Roman; Lukastik, Petr (Zielona Góra: Uniwersytet Zielonogórski)
This work presents an original model for detecting machine tool anomalies and emergency states through operation data processing. The paper is focused on an elastic hierarchical system for effective data reduction and classification, which encompasses several modules. Firstly, principal component analysis (PCA) is used to perform data reduction of many input signals from big data tree topology structures into two signals representing all of them. Then the technique for segmentation of operating machine data based on dynamic time distortion and hierarchical clustering is used to calculate signal accident characteristics using classifiers such as the maximum level change, a signal trend, the variance of residuals, and others.
Keywords: OPC UA; OPC tree; PCA; big data analysis; data reduction; machine tool; anomaly detection; emergency states