Siemens Aktiengesellschaft

Igor Kogan

Andreas Jurisch

Silvio Becher

Cezary Dzienis

Florian Büttner

Felix Buggenthin

Matthias Kereit

Josep Soler Garrido

Sigurd Spieckermann

Klaus Böhme

Ji Chen

Andrej Görbing

Abhishek Agarwal

Oliver Lindner

Stefan Flemming

Christian Kern

Christian Liedtke

Anjana AR

Florian BÜTTNER

A method for avoiding function disablements of intelligent electronic units IEDs that are connected in a local network which has at least two timing units. One of the timing units assumes an active grandmaster role as a synchronization source while the other timing units remain in their slave state and synchronize with the timing unit in the grandmaster role. When one of the timing units changes from the slave state to the grandmaster role, a pre-synchronization message is used to notify all IEDs in the local network whether and, if applicable, with which previous grandmaster timing unit the present grandmaster timing unit was synchronized. This avoids a disablement of the function of the IEDs that generate or process data streams whose samples have been acquired in sync with the previous grandmaster timing unit.

Method for avoiding function disablements for intelligent electronic units

A method identifies a location of a fault on a faulty line of an electrical power supply network having a plurality of lines, a plurality of inner nodes, and at least three outer nodes. The outer nodes each bound a line and are provided with measurement devices which are used to measure high-frequency current and/or voltage signals. To locate faults, one of the outer nodes is selected as the starting node for the search for the fault location. Starting from the starting node, paths to the other outer nodes are determined, and that those paths on which the fault location could be located are selected. A line on which the fault location could be located, in principle, is identified for each of the selected paths using the respective times at which the traveling waves arrive, and a potential fault location is determined for the respectively identified line.

Method and device for identifying the location of a fault on a line of an electrical power supply network

Provided is an in-field apparatus and method for automatic localization of a fault having occurred at power transmission lines of a power supply system, the in-field apparatus includes a preprocessing unit configured to process measured voltage and/or current raw time series data of the power transmission lines to provide a normalized raw data and/or feature representation of the measured raw time series data, and an artificial intelligence module configured to predict an optimal evaluation time used for evaluation of the measured voltage and/or current raw time series data to localize the fault based on the normalized raw data and/or feature representation.

Method and apparatus for automatic localization of a fault

A method for deployment of a machine learning model (MLM) on a target field device is disclosed herein. The method includes automatically generating a set of source code files based on the machine learning model, wherein the set of source code files is configured to execute the machine learning model according to predetermined capabilities of the target field device; transforming the generated source code files into a model binary using a tool chain specific to the target field device; and deploying the model binary in a memory of the target field device.

Method for development and execution of a machine learning model on a field device

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Berlin, Germany

Igor Kogan