A wavelet analysis for identifying simulated anomalies superimposed to real signals

When intense working conditions (e.g. production on continuous shifts) do not permit plant inactivity, conjugating both the continuous request of productivity and the constant demand of high performance, in terms of qualitative standards, becomes one of the most important factor in determining the profit of a business. The aim of this paper is to propose a method based both on wavelet and discriminant analysis for the identification of simulated anomalies superimposed to real signals carried out on mechanical equipment.