Fault detection system using machine learning on geothermal power plant

Zulkarnain, Isti Surjandari, Resha Rafizqi Bramasta, Enrico Laoh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Geothermal power plants are a renewable clean energy source with great potential that Indonesia has. The manual fault detection system at the critical machine is one of the problems in the operation of geothermal power plants in Indonesia. Vulnerable errors in determining engine conditions and delays in knowing alerts are two major problems that arise. The application of machine learning algorithms in making fault detection models has been used in various industries and objects. This research is the application of machine learning algorithms to create fault detection classification models on critical engines of geothermal power plants. The algorithm used is the basic classifier and ensemble classifier to compare which algorithms produce the best classification indicators of classifications. This research can provide insight into the geothermal power plant industry in Indonesia to overcome existing fault detection system by utilizing sensor data using machine learning algorithm.

Original languageEnglish
Title of host publication2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728119410
DOIs
Publication statusPublished - Jul 2019
Event16th International Conference on Service Systems and Service Management, ICSSSM 2019 - Shenzhen, China
Duration: 13 Jul 201915 Jul 2019

Publication series

Name2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019

Conference

Conference16th International Conference on Service Systems and Service Management, ICSSSM 2019
CountryChina
CityShenzhen
Period13/07/1915/07/19

Keywords

  • Classification Model
  • Fault Detection
  • Geothermal Power Plant
  • Machine Learning

Fingerprint Dive into the research topics of 'Fault detection system using machine learning on geothermal power plant'. Together they form a unique fingerprint.

  • Cite this

    Zulkarnain, Surjandari, I., Bramasta, R. R., & Laoh, E. (2019). Fault detection system using machine learning on geothermal power plant. In 2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019 [8887710] (2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSSSM.2019.8887710