Ajay Chhokra, Saqib Hasan, Abhishek Dubey, Nagabhushan Mahadevan, Gabor Karsai
Proceedings of the 8th International Conference on Cyber-Physical Systems, ICCPS 2017, Pittsburgh, Pennsylvania, USA, April 18-20, 2017 2017
Reliable operation of cyber-physical systems like power transmission networks requires rapid fault diagnosis and prognosis. Existing approaches often miss system-level effects introduced by control algorithms and communication delays. This work is innovative because it integrates temporal causal reasoning with structured formalism to predict fault propagation across complex distributed systems.
This work presents temporal causal diagrams (TCDs) for diagnosing and prognosing faults in cyber-physical energy systems. The approach uses behavior-augmented temporal failure propagation graphs to identify system-level effects and design robust diagnostic and prognostic strategies. The methodology combines temporal causal reasoning with TCD formalism for power transmission systems.
The paper demonstrates TCD-based diagnosis and prognosis for IEEE 14-bus power systems, enabling identification of cascading faults and system reconfiguration actions to arrest blackout progression. The methodology provides actionable insights for designing fault-tolerant control strategies.
@inproceedings{Chhokra2017a,
author = {Chhokra, Ajay and Hasan, Saqib and Dubey, Abhishek and Mahadevan, Nagabhushan and Karsai, Gabor},
booktitle = {Proceedings of the 8th International Conference on Cyber-Physical Systems, {ICCPS} 2017, Pittsburgh, Pennsylvania, USA, April 18-20, 2017},
title = {Diagnostics and prognostics using temporal causal models for cyber physical energy systems},
year = {2017},
pages = {87},
abstract = {Reliable operation of cyber-physical systems such as power transmission and distribution systems is crtiical for the seamless functioning of a vibrant economy. These systems consist of tightly coupled physical (energy sources, transmission and distribution lines, and loads) and computational components (protection devices, energy management systems, etc.). The protection devices such as distance relays help in preventing failure propagation by isolating faulty physical components. However, these devices rely on hard thresholds and local information, often ignoring system-level effects introduced by the distributed control algorithms. This leads to scenarios wherein a local mitigation in a subsytem could trigger a larger fault cascade, possibly resulting in a blackout.Efficient models and tools that curtail such systematic failures by performing fault diagnosis and prognosis are therefore necessary.},
bibsource = {dblp computer science bibliography, https://dblp.org},
biburl = {https://dblp.org/rec/bib/conf/iccps/ChhokraHDMK17},
category = {poster},
contribution = {lead},
doi = {10.1145/3055004.3064843},
file = {:Chhokra2017a-Diagnostics_and_prognostics_using_temporal_causal_models_for_cyber_physical_energy_systems.pdf:PDF},
keywords = {temporal causal diagrams, fault diagnosis, fault prognosis, cyber-physical systems, power transmission, system reliability},
project = {cps-reliability},
tag = {platform,power},
timestamp = {Wed, 16 Oct 2019 14:14:57 +0200},
url = {https://doi.org/10.1145/3055004.3064843}
}