Anomaly Detection for Hydraulic Power Units—A Case Study

Paweł Fic (), Adam Czornik and Piotr Rosikowski
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Paweł Fic: Department of Automatic Control and Robotics, Silesian University of Technology, 44-100 Gliwice, Poland
Adam Czornik: Department of Automatic Control and Robotics, Silesian University of Technology, 44-100 Gliwice, Poland
Piotr Rosikowski: PONAR Wadowice S.A., Św. Jana Pawła II 10, 43-170 Łaziska Górne, Poland

Future Internet, 2023, vol. 15, issue 6, 1-29

Abstract: This article aims to present the real-world implementation of an anomaly detection system of a hydraulic power unit. Implementation involved the Internet of Things approach. A detailed description of the system architecture is provided. The complete path from sensors through PLC and the edge computer to the cloud is presented. Some technical information about hydraulic power units is also given. This article involves the description of several model-at-scale deployment techniques. In addition, the approach to the synthesis of anomaly and novelty detection models was described. Anomaly detection of data acquired from the hydraulic power unit was carried out using two approaches, statistical and black-box, involving the One Class SVM model. The costs of cloud resources and services that were generated in the project are presented. Since the article describes a commercial implementation, the results have been presented as far as the formal and business conditions allow.

Keywords: predictive maintenance; internet of things; hydraulic power units; machine learning; anomaly detection; cloud computing; Microsoft Azure Cloud (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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