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Big Machinery Data Preprocessing Methodology for Data-Driven Models in Prognostics and Health Management
2021
Sensors
Sensor monitoring networks and advances in big data analytics have guided the reliability engineering landscape to a new era of big machinery data. Low-cost sensors, along with the evolution of the internet of things and industry 4.0, have resulted in rich databases that can be analyzed through prognostics and health management (PHM) frameworks. Several data-driven models (DDMs) have been proposed and applied for diagnostics and prognostics purposes in complex systems. However, many of these
doi:10.3390/s21206841
pmid:34696058
pmcid:PMC8537368
fatcat:njw2vqnskbev5cpb2kooedonyy