| In fault detection and assessment, a comprehensive understanding and investigation of advanced signal processing methods is required. The empirical mode decomposition (EMD) method is an adaptive time-frequency domain signal processing method that is completely driven by the data itself. The cubic spline interpolation method has been used to approximate the local mean in the sifting process of EMD, where problems of undershooting and overshooting have been identified.; This study explores approaches to improving the approximation of the local mean to obtain better EMD performance. In this thesis, the modified monotone piecewise Hermite interpolation (MMPHI) method is applied for envelope-mean approximation, because it demonstrates advantages over the cubic spline method. A type of direct approximation of the local mean, i.e. the windowed local mean approach, is also investigated and its merit in identifying impulses is demonstrated. Performance of MMPHI and the windowed local mean approach are also demonstrated when these are used to analyze experimental data obtained from a gearbox. |
