Abstract: The invention concerns a method for generating a fault indication signal in the event of a fault in an electric power supply network being monitored through a neural network arrangement. In order to rapidly generate fault indication signals capable of distinguishing between permanent metal contact short-circuits and short circuits due to arcing, a neural network (26) is used for each phase of the power supply network being monitored. Each neural network (26) is taught, while being coached through simulated voltages (U.sub.R (t)) of each phase during short-circuits caused by metal contact and arcing, so that the output signal (S) assumes a pre-defined value (0.8) for arcing and another pre-defined value (0.1) for a metal contact short-circuit. At the same time, the sequentially sampled normalized values (U.sub.Rn1 (t) through U.sub.Rn20 (t)) of the respective phase voltages (R.sub.

Abstract: A method of generating a protection-triggering signal using a triggering device of a selective-protective arrangement for an electrical power network to be monitored. In order to produce a protection-triggering signal in a relatively short time after the occurrence of a fault in the power network, a triggering device is provided in which a neural network is associated with each phase conductor in the power network. Successively sampled normalized values of the current in the power network are applied at the same time to the various neurons in the input layer of each neural network and a subsequently sampled normalized value (comparison value) of the current compared with the signal from the output neuron. If the normalized comparison value exceeds the output from the output neuron, a protection-triggering signal is generated.

Abstract: A process for generating a direction signal indicating the direction of a short-circuit current in a power transmission line to be monitored. To reliably produce a direction signal even in the event of a short-circuit occurring in the proximity of the control point, each derived current and voltage signal (J.sub.R (t)) is separately sampled and normalized to obtain different normalized sample values (J.sub.Rn). Taking the triggering reference values (S.sub.n) into account, difference values (.DELTA.i.sub.R (t), .DELTA.i.sub.R (t-1), .DELTA.i.sub.R (t-2), .DELTA.i.sub.R (t-3)) are formed. The difference values (.DELTA.i.sub.R (t), .DELTA.i.sub.R (t-1), .DELTA.i.sub.R (t-2), .DELTA.i.sub.R (t-3)) of a series (S.sub.iR) are supplied to different input neurons of a suitably trained neural network successively and simultaneously with the difference values corresponding to the same times of the other series (S.sub.iS, S.sub.iT, S.sub.uR, S.sub.uT).