Siemens Mobility Gmbh

Deutsche Bahn Ag

Helge Aufderheide

Udhayaraj Sivalingam

Marco Fechtig

Michael Taylor

Phillipp Richter

A method for diagnosing a technical system, an apparatus, and a computer program product are provided for carrying out a main component analysis of predefined values for n variables for describing a normal state of the technical system, where n≥2, and at least one main component of the n variables is ascertained. The at least one main component is predefined for describing the normal state of the technical system. Deviations of values for the n variables for describing a current state of the technical system are ascertained from the at least one predefined main component for describing the normal state, in order to infer a fault. A data carrier is also provided.

Diagnosis of technical systems

A method for energy-optimized operation of a rail vehicle fleet. The fleet includes n rail vehicles, each with a state-influencing system for influencing a vehicle state to generate and/or consume electrical energy and a computer unit trained by machine learning. For every i of 1 to n during operation of the rail vehicle fleet an action to be applied to the state-influencing system of the i-th rail vehicle is selected by the computer unit of the i-th rail vehicle while taking into account at least one target criterion for the i-th rail vehicle and according to vehicle, location, and/or route-related status parameters. The action, when applied to the state-influencing system of the i-th rail vehicle, contributes to the optimization of an electrical total energy balance of the state-influencing systems of the rail vehicle fleet, and the selected action is applied to the state-influencing system of the i-th rail vehicle.

Energy optimisation during operation of a rail vehicle fleet

A method analyzes conditions of technical components in view of a rarity and/or an abnormality of a condition. To provide a reliable analysis and thus a safely operating system the method includes: a) describing conditions of the technical components in a behavioral input space that is spanned by state variables, which are characteristic for the technical components, b) analyzing a condition of one technical component in respect to other conditions of this technical component in the behavioral input space, whereby a rarity of this condition of the technical component is detectable, and c) analyzing the condition of the technical component also in respect to analyses of conditions of further technical components in the behavioral input space. Whereby an abnormality of the condition of the technical component is detectable.

Method for analyzing conditions of technical components

A method for generating an image of a route network that is travelled through by a rail vehicle. The image is generated with the use of activities that are recorded by the rail vehicle as it travels through the route network and sorted in an activity sequence. In order to provide an improved method, patterns in the activity sequence are identified with use of a pattern detection method and the image of the route network is generated with the use of the identified patterns.

Method for generating an image of a route network, use of the method, computer program, and computer-readable storage medium

A method and a computer program product monitor infrastructure facilities of a route network for vehicles. The vehicles generate messages about a respective operating state, which messages are transmitted with a time and a specification of location which represent the occurrence of a signaled operating state, to a land-based evaluation device. The messages received are stored in a database and evaluated. The messages of a predefined time period relating to a predefined operating state are read out from the database. Limited areas with frequent occurrence of the predefined operating state are determined by means of a predefined algorithm. The infrastructure facilities in the areas with the frequent occurrence of the predefined operating state as a possible cause of the predefined operating state of the vehicles are identified, and information about the infrastructure facilities which are detected as a possible cause of the predefined operating state of the vehicles are output.

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Munich, Germany

Helge Aufderheide