A comparative study of non-parametric spectral estimators for application in machine vibration analysis

Abstract The vibration of a machine carries important information about the health of its internal components; this information, if properly extracted, can be extremely useful in the detection of developing faults within the machine. One of the most effective methods to extract this information is the computation of the vibration power spectrum, but since the statistical properties of the vibration signal are generally unknown, the power spectrum has to be estimated from the available finite-length data. A number of methods have been proposed for vibration spectral estimation, each presenting advantages and disadvantages. In each specific application, it is often necessary to evaluate and choose the optimum spectral estimation method. This paper presents an analysis of four widely accepted non-parametric spectral estimation methods: Periodogram, Blackman-Tukey, Welch, and Nuttall-Carter. It compares them based on their mean, variance, resolution, and computational requirements. It is found that all methods, except the Periodogram, can achieve the same mean, variance, and resolution but differ in leakage suppression and computational complexity. The Welch method has the best leakage suppression and the Nuttall-Carter method has the lowest computational burden in most cases.