Citation

Alqaraleh, Doaa Ahmad and Hajjaj, Sami Salama Hussen and Baharuddin, Mohd Zafri and Aridi, Mohd Radzi and Moorthy, Usha and Easwaramoorthy, Sathishkumar Veerappampalayam (2026) Multisensor Condition Monitoring Dataset from a Sulzer Industrial Centrifuge at Arab Potash Company: A One-Year Time Series for Predictive Maintenance Research. Scientific Data, 13 (1421). ISSN 2052-4463

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Abstract

This paper presents a publicly accessible industrial condition monitoring dataset collected from a Sulzer centrifuge at the Arab Potash Company (APC) in Jordan. The twelve-month dataset (September 2022–August 2023) was acquired using an ABB 800xA distributed control system (DCS) sampling four sensor channels: torque (% of nominal load), vibration velocity (mm/s RMS), and dual bearing temperatures (°C, solid and liquid ends) at one-minute intervals (≈0.0167 Hz), yielding approximately 525,600 observations per channel. The preprocessing pipeline included timestamp synchronisation, duplicate removal, and linear interpolation for short gaps; records exceeding DCS alarm thresholds (vibration ≥12 mm/s, torque ≥85%, temperature ≥85 °C) were retained and labelled as candidate anomalies rather than deleted, to preserve event realism. The dataset is internally consistent, plant-specific, and suitable for exploratory benchmarking in industrial AI, digital twin development, and prognostics and health management (PHM) research.

Item Type:	Article
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD2321-4730.9 Industry > HD2329 Industrialization
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	29 Oct 2026 02:33
Last Modified:	29 Oct 2026 02:33
URII:	http://shdl.mmu.edu.my/id/eprint/16976

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