A smart and intuitive machine condition monitoring in the Industry 4.0 scenario. (October 2018)

• Record Type: Journal Article
• Authors: Dinardo, G.; Fabbiano, L.; Vacca, G.
• Is Part Of: Measurement. Volume 126(2018)
• Page Start: 1
• Page End: 12
• Publication Date: 2018-10
• Subjects: Internet of Things -- Decision making -- Machine condition monitoring -- Signal analysis and processing -- Vibration acceleration measurements -- Laser Doppler Vibrometry; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2018.05.041
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: In the smart industry philosophy, continuous monitoring of the machinery condition is crucial to follow up the decision-making strategy. In this context, the purpose of the paper is to elaborate a simple procedure aimed at rotating machine condition monitoring and prognosis. The general assessment of the machine operating condition goodness is indeed crucial for a smart and efficient industrial processes running. Any incipient defect manifests itself in an alteration of the component vibratory status. The proposed procedure is based on the continuous monitoring of the energetic features of the vibration signals acquired from the equipment under analysis. The considered parameter is the vibration velocity RMS value. It is representative of the amount of the fatigue stress affecting the machine. By means of a continuous monitoring of such energetic features, the user is able to plan the maintenance of the equipment, prior to impeding failures. The case study provided in this paper, can illustrate how the data from a monitored process can lead to the machine system self-awareness and, eventually, self-maintenance. Such an approach allows for a self-assessment of health and degradation status of the machine system, in the framework of the Industry 4.0 scenario, one of the pillars of the Smart City.