Wear rate–state interactions within a multi-component system: a study of a gearbox-accelerated life testing platform. (August 2018)

• Record Type: Journal Article
• Authors: Assaf, Roy; Do, Phuc; Nefti-Meziani, Samia; Scarf, Philip
• Other Names: Emmanouilidis Christos guest-editor.; Iung Benoit guest-editor.; Macchi Marco guest-editor.; Peres Francois guest-editor.
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 232:Number 4(2018:Aug.)
• Page Start: 425
• Page End: 434
• Publication Date: 2018-08
• Subjects: Degradation modelling -- degradation dependence -- rate–state interaction -- multi-component system -- condition monitoring -- gearbox; Reliability (Engineering) -- Mathematical models -- Periodiclals; Risk assessment -- Mathematical models -- Periodicals; Engineering design -- Mathematical models -- Periodicals; 620.00452
• DOI: 10.1177/1748006X18764061
• Languages: English
• ISSNs: 1748-006X

Abstract

The degradation process of complex multi-component systems is highly stochastic in nature. A major side effect of this complexity is that components of such systems may have unexpected reduced life and faults and failures that decrease the reliability of multi-component systems in industrial environments. In this work, we provide maintenance practitioners with an explanation of the nature of some of these unpredictable events, namely, the degradation interactions that take place between components. We begin by presenting a general wear model where the degradation process of a component may be dependent on the operating conditions, the component's own state and the state of the other components. We then present our methodology for extracting accurate health indicators from multi-component systems by means of a time–frequency domain analysis. Finally, we present a multi-component system degradation analysis of experimental data generated by a gearbox-accelerated life testing platform. In doing so, we demonstrate the importance of modelling the interactions between the system components by showing their effect on component lifetime reduction.