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Machine tele-monitoring using machine learning for predicting bearing failures

Neural Networks require thousands of training data sequences. Fetching data at a daily rate is slow. We propose to produce lots of realistic and synthetic data stemming from a purpose built test bench and applying novel signal processing techniques. This enables Mechmine to launch new services.

https://www.aramis.admin.ch/Grunddaten/?ProjectID=40390

Kategorie

Innosuisse

Referenznummer

26177.1 PFIW-IW

Projektstart

01.07.2017

Projektende

01.07.2020

Projektdauer

3 Years

Projektstatus

abgeschlossen

Bereich

ICAI-OST

Neural Networks require thousands of training data sequences. Fetching data at a daily rate is slow. We propose to produce lots of realistic and synthetic data stemming from a purpose built test bench and applying novel signal processing techniques. This enables Mechmine to launch new services.

https://www.aramis.admin.ch/Grunddaten/?ProjectID=40390

Personen

Prof. Dr.

Guido Schuster

Projektverantwortlich
Zum Detail

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