Diagnosis of Higher-Order Discrete-Event Systems

Abstract

Preventing major events, like the India blackout in 2012 or the Fukushima nuclear disaster in 2011, is vital for the safety of society. Automated diagnosis may play an important role in this prevention. However, a gap still exists between the complexity of systems such these and the effectiveness of state-of-the-art diagnosis techniques. The contribution of this paper is twofold: the definition of a novel class of discrete-event systems (DESs), called higherorder DESs (HDESs), and the formalization of a relevant diagnosis technique. HDESs are structured hierarchically in several cohabiting subsystems, accommodated at different abstraction levels, each one living its own life, as happens in living beings. The communication between subsystems at different levels relies on complex events, occurring when specific patterns of transitions are matched. Diagnosis of HDESs is scalable, context-sensitive, and in a way intelligent. IntroductionIn the last decades, automated diagnosis of complex systems has become increasingly important for the safety of society. It suffices to consider two recent fateful events: the 2012 India blackout, and the 2011 Fukushima Daiichi nuclear disaster. history, occurring as two separate events (on 30 and 31 July), which affected over 620 million people (half of India's population), and spread across 22 states, with an estimated 32 gigawatts of generating capacity being taken offline.Among other consequences, the outage caused chaos in rush hours, as passenger trains were shut down and traffic signals were non-operational. Several hospitals reported interruptions in health services. Hundreds of miners were trapped underground due to failures in lifts. Water treatment points were shut down for hours and millions of people were not able to draw water from wells powered by electric pumps. responsible for the blackout was the loss of a 400V transmission line caused by misbehavior of the protection system [1]. The committee also provided several recommendations to prevent further blackouts, including an audit of the protection system. Also some technology sources and the United States Agency for International Development (USAID) proposed that another widespread outage could be prevented by an integrated network of microgrids and distributed generation connected seamlessly with the main grid via a superior smart grid technology which includes automated fault detection, islanding and self-healing of the network.

Diagnosis of Deep Discrete-Event Systems

“…Each DDES adopted for the experiments represents a power transmission system consisting of several contiguous protected lines. The schema of a protected line is a variant of that outlined in Figure 10; in this variant, the protection apparatus at either end of the line includes two breakers and (only) one sensor, the same as in the paper by Lamperti and Zhao (2013a). Each leaf AU in the DDES hierarchy represents a protection apparatus, hence it includes three ACs.…”

Diagnosis of Complex Active Systems with Uncertain Temporal Observations

“…To this end, the notion of context-sensitive diagnosis was first introduced in [14] and then extended in [18], for active systems that are organized within abstraction hierarchies, so that candidate diagnoses can be generated at different abstraction levels. Active systems have been equipped with behavior stratification [16,17], where different networks of components are accommodated within a hierarchy. This resembles emergent behavior that arises from the vertical interaction of a network with superior levels based on pattern events.…”