Condition Monitoring for Heliostat Fields Using Artificial Intelligence

Steinberg, Dominik (2024) Condition Monitoring for Heliostat Fields Using Artificial Intelligence. EU Solaris 1st Doctoral Colloquium (18th Sollab Doctoral Colloquium), 2024-07-03 - 2024-07-05, Odeillo, Frankreich.

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Item URL in elib:

https://elib.dlr.de/208225/

Document Type:

Conference or Workshop Item (Speech)

Title:

Condition Monitoring for Heliostat Fields Using Artificial Intelligence

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Steinberg, Dominik	UNSPECIFIED	https://orcid.org/0009-0000-1114-4526	UNSPECIFIED

Date:

2024

Refereed publication:

Open Access:

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

Condition Monitoring, Predictive Maintenance, Heliostat, Heliostat fields, Artificial Intelligence, Machine Learning, Data Analysis, Ageing effects, Fault detection, Central receiver, Solar power tower, CSP

Event Title:

EU Solaris 1st Doctoral Colloquium (18th Sollab Doctoral Colloquium)

Event Location:

Odeillo, Frankreich

Event Type:

international Conference

Event Start Date:

3 July 2024

Event End Date:

5 July 2024

HGF - Research field:

Energy

HGF - Program:

Materials and Technologies for the Energy Transition

HGF - Program Themes:

High-Temperature Thermal Technologies

DLR - Research area:

Energy

DLR - Program:

E SW - Solar and Wind Energy

DLR - Research theme (Project):

E - Condition Monitoring

Location:

Jülich

Institutes and Institutions:

Institute of Solar Research > Qualification

Deposited By:

Steinberg, Dominik

Deposited On:

11 Nov 2024 10:33

Last Modified:

11 Nov 2024 10:33

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