Artificial Intelligence in Automation

PrognoseBrain: Entwicklung eines Systems zur Nutzung lernender, korrelativ und prognostisch interpretierender Algorithmen für das Condition Monitoring im produzierenden Mittelstand

Prof. Dr. rer. nat. Oliver Niggemann , Prof. Dr.-Ing. Jürgen Jasperneite
01.02.2014 bis 31.07.2015

The aim of the project PrognoseBrain is to develop a condition monitoring system, with that the breakdown of systems can be avoided. This CMS provides the ability of faults prognosis, which enables the predective maintenances and reduces the breakdown risks of systems. In this project, a learning, correlative and prognostic interpretive algorithms for condition monitoring will be generalized and implemented with a slim hardware, which can be quickly and cost effectively used by small Enterprises.

The development of these promissing technologies requires the solution of the following problems:

  1. Handling of big data in real time.
  2. Universal applicability.
  3. Central Analysis of plants conditions in distributed systems.
This project is promoted by:
Bundesministerium für Wirtschaft und Energie (BMWi)
Sponsors: AiF Projekt GmbH
Funding Code: KF2448216KM3
Funding Lines: Zentrales Innovationsprogram Mittelstand (ZIM)
Stakeholders / Contacts: Dr.-Ing. Peng Li
Employees: Dr.-Ing. Peng Li
Dr.-Ing. Peng Li¹, Dr.-Ing. Peng Li, Jens Eickmeyer, Prof. Dr. rer. nat. Oliver Niggemann, Prof. Dr. rer. nat. Oliver Niggemann²
Data Driven Condition Monitoring of Wind Power Plants Using Cluster Analysis
In: 2015 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC 2015), Sep 2015
¹ First Authors
² Last authors
Promoted by
AiF Projekt GmbH