Estimation of geometric properties of three-component signals for system monitoring. (December 2017)

• Record Type: Journal Article
• Authors: Granjon, Pierre; Phua, Gailene Shih Lyn
• Is Part Of: Mechanical systems and signal processing. Volume 97(2017)
• Page Start: 95
• Page End: 111
• Publication Date: 2017-12
• Subjects: Three-component signals -- Geometric properties -- Frenet-Serret frame -- Bearing faults -- Voltage dips -- Condition monitoring; Structural dynamics -- Periodicals; Vibration -- Periodicals; Constructions -- Dynamique -- Périodiques; Vibration -- Périodiques; Structural dynamics; Vibration; Periodicals; 621
• DOI: 10.1016/j.ymssp.2017.04.002
• Languages: English
• ISSNs: 0888-3270

Abstract

Highlights: Condition monitoring method based on geometric properties of three-component signals. Theoretical study of the geometric properties of three-component sinusoidal signals. Efficient algorithm to estimate geometric properties of three-component signals. Experimental validation using three-axis vibrations for bearing faults monitoring. Experimental validation using three-phase voltages for voltage dips monitoring. Abstract: Most methods for condition monitoring are based on the analysis and characterization of physical quantities that are three-dimensional in nature. Plotted in a three-dimensional Euclidian space as a function of time, such quantities follow a trajectory whose geometric characteristics are representative of the state of the monitored system. Usual condition monitoring techniques often study the measured quantities component by component, without taking into account their three-dimensional nature and the geometric properties of their trajectory. A significant part of the information is thus ignored. This article details a method dedicated to the analysis and processing of three-component quantities, capable of highlighting the special geometric features of such data and providing complementary information for condition monitoring. The proposed method is applied to two experimental cases: bearing fault monitoring in rotating machines, and voltage dips monitoring in three-phase power networks. In this two cases, the obtained results are promising and show that the estimated geometric indicators lead to complementary information that can be useful for condition monitoring.