Affiliation:
1. Computer Architecture and Microelectronics Group, Federal University of Pampa, Alegrete 97546-550, Brazil
Abstract
Machine failure in modern industry leads to lost production and reduced competitiveness. Maintenance costs represent between 15% and 60% of the manufacturing cost of the final product, and in heavy industry, these costs can be as high as 50% of the total production cost. Predictive maintenance is an efficient technique to avoid unexpected maintenance stops during production in industry. Vibration measurement is the main non-invasive method for locating and predicting faults in rotating machine components. This paper reviews the techniques and tools used to collect and analyze vibration data, as well as the methods used to interpret and diagnose faults in rotating machinery. The main steps of this technique are discussed, including data acquisition, data transmission, signal processing, and fault detection. Predictive maintenance through vibration analysis is a key strategy for cost reduction and a mandatory application in modern industry.
Funder
Brazilian research agency Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul
Subject
General Earth and Planetary Sciences
Cited by
16 articles.
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