Machine Diagnostics and Vibration Analysis

Dear Colleagues,

The main scope of this special issue, in machine diagnostics and vibration analysis, is to gather state-of-the-art of the research adding latest scientific advancements in the field. The presented papers are expected to make demonstrable original contributions to scientific world.

The difficulties, usually, are the failures that initiate unplanned machinery stops. In this context, it is necessary to predict possible failures to anticipate them and to be able to plan a predictive machine maintenance, “just before it fails”.  The benefices of a proper condition monitoring are: Increasing lifespan of machinery, maximizing production output, and lowering maintenance cost.  

Some of the most promising approaches for the continuous advancement of machine diagnosis and vibration analysis are: Next-generation active vibration control systems, machinery diagnostics and prognostics using intelligent analysis, signal processing in machine health monitoring, vibration-based condition monitoring, modal and operational mode analysis, neural networks analysis, and machine learning.

Finally, vibration analysis for machine diagnosis based on machine learning has become one of the most efficient tool, with high accuracy, precision automated learning, robustness, and the capacity to handle complex data are some of the attributes.

Prof. Dr. Grover Zurita Villarroel
Prof. Dr. Örjan Johansson
Guest Editors

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