This study investigates advanced diagnostic techniques for predicting bearing faults in industrial turbogenerators using Artificial Neural Networks (ANNs) and Support Vector Regression (SVR). Real-world data were collected from a 58 MW steam-driven turbogenerator over a two-year period, including vibration and rotation...
Soumaya Zaroual, Erroumayssae Sabani, H. Mastouri et al.· Engineer· 0 citations
This paper presents the design and development of a laboratory-scale 3D printing platform intended for research on sustainable construction materials. The growing interest in low-carbon and locally available materials, including clay, geopolymers, recycled aggregates, and bio-based composites, has increased the need fo...
Proactive detection of faults in turbine bearings is key to ensuring system reliability in industrial systems. This work introduces the use of Moving Average (MA) and Exponentially Weighted Moving Average (EWMA) control charts for diagnosing bearing faults in the context of predictive maintenance. Unlike other statisti...
Ali Khouilid, Erroumayssae Sabani, H. Mastouri et al.· Engineer· 0 citations
Monitoring the health of bearings in industrial rotating machines is a major challenge for ensuring the reliability and continuous operation of installations. Conventional fault detection methods, based on multivariate control charts such as Hotelling’s T2, multivariate exponentially weighted moving average, or multiva...
Erroumayssae Sabani, E. Loualid, H. Mastouri et al.· Engineer· 0 citations
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