Fault detection for rolling element bearing using an enhanced morphological-hat product filtering method

Abstract

A novel morphological filter (MF), named enhanced morphological-hat product filtering (EMHPF) is proposed for bearing fault detection. Within this method, a new morphological-hat product operation (MHPO) is firstly proposed based on two morphological-hat operators that are previously reported. Subsequently, an efficient evaluation index called fault feature ratio (FFR) is applied to select adaptively the length of structuring element (SE) for improving the precision of bearing fault diagnosis. The simulation and experimental results on rolling bearing fault illustrate that the proposed EMHPF method is capable of enhancing fault detection of rolling bearing, and its feature extraction capability is superior to that of some existing morphological filter methods.