Diagnosis of Intermittent Faults and its dynamics

Abstract

Intermittent faults (IFs) are difficult to diagnose and may cause a great disruption in industrial processes. Most IFs are related to gradual degradation of components or systems. For instance, evolution of connection failures is shown in Fig. 1 (Correcher et al., 2004), (Sorensen et al, 1998). Connection failures are rarely repaired so its behaviour worsens over time. Intermittent faults behave as small noise fluctuations in stage 1 of their development. As the amplitude and duration of the fluctuations increase (stage 2), IFs start to occur. The effects of IFs are severe in stage 3. Therefore, in many instances, the occurrence of IFs in a device is a prelude of permanent failures (PFs). In these cases, if IFs can be detected then appropriate actions could be taken in order to minimise the economic impact. In (Correcher et al., 2004) an IFs diagnosis tool was presented by the authors. This tool was able to diagnose the failure and recovery events in a system with IFs. This paper presents an extension of the work in (Correcher et al., 2004) which includes not only event detection but also fault dynamics detection, defined as the evolution of IFs occurrence over time. Other approaches to IFs diagnosis (Contant et al., 2004), (Jinag et al. 2003), do not consider IF dynamics.