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A wide variety of natural and human-made systems consist of a large set ofdynamical units coupled into a complex structure. Breakdown of such systems canhave a dramatic impact, as in the case of neurons in the brain or lines in anelectric grid, to name but a few. Preventing such catastrophic events requiresin particular to be able to detect and locate the source of disturbances asfast as possible. We propose a simple method to identify and locatedisturbances in networks of coupled dynamical agents, relying only on timeseries measurements and on the knowledge of the (possibly Kron-reduced) networkstructure. The strength and the appeal of the present approach lies in itssimplicity paired with the ability to precisely locate disturbances and even todifferentiate between line and node disturbances. If we have access tomeasurement at only a subset of nodes, our method is still able to identify thelocation of the disturbance if the disturbed nodes are measured. If not, wemanage to identify the region of the network where the disturbance occurs.

Locating line and node disturbances in networks of diffusively coupled dynamical agents