Natural gas transmission infrastructure is a large-scale complex system often exhibiting a considerable operating states not only due to natural, slow and normal process changes related to aging but also to a dynamic interaction with multiple agents overall having different functional parameters, an irregular demand trend adjusted by the hour, and sometimes affected by external conditions as severe climate periods.

As traditional fault detection relies in alarm management system and operator’s expertise, it is paramount to deploy a strategy being able to update its underlying structure and effectively adapting to such process shifts. This feature would allow operators and engineers to have a better framework to address the online data being gathered in dynamic on transient conditions.

This paper presents an extended analysis on WARP technique to address the abnormal condition management activities of multiple-state processes deployed in critical natural gas transmission infrastructure. Special emphasis is made on the updating activity to incorporate effectively the operating shifts exhibited by a new operating condition implemented on a fault detection strategy. This analysis broadens the authors’ original algorithm scope to include multi-state systems in addition to process drifting behavior.

The strategy is assessed under two different scenarios rendering a major shift in process’ operating conditions related to natural gas transmission systems: A transition between low and high natural gas demand to support hydroelectric generation matrix on severe tropical conditions. Performance evaluation of fault detection algorithm is carried out based on false alarm rate, detection time and misdetection rate estimated around the model update.

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