Application of Morphology Filtering Method in the De-nosing of Wheel Out-of-roundness Signals

Abstract

：Wheel defects, such as pitting, generally occur on the tread of railway vehicle wheels. The measured wheel out-of-roundness (OOR) signals usually contain interference signals induced by pitting or other defects. The dimension of pitting is less than wheel-rail contact patch. The morphology filtering method is used to de-noise the wheel OOR signals. The influence of structure element's dimension and shape of morphology filter on the de-nosing of wheel OOR signals is investigated. A new de-nosing method combining morphology filtering with cubic spline smoothing is proposed to overcome the shortcoming of morphology filter. The results of wheel OOR signals processed using the new and ordinary methods are compared. Moreover, the influence of wheel OOR on wheel-rail dynamic interaction is also investigated by using wheel OOR signals from different de-nosing methods. The results indicate that the morphology filter with triangular structure element, of which the amplitude and width are 1 mm and 4 mm, respectively, combined with cubic spline smoothing is more suitable in the de-nosing of wheel OOR signals. The results of this method applied to process wheel OOR signals show that the signal-noise ratio of the processed signal is much higher than the ordinary method and can keep the main characteristics of the original signal.

A morphological filtering-based strain data processing method for biaxial fatigue testing of wind turbine blades

“…The morphological filters are built from rectangular structure elements, linear structure elements, disk structure elements and cosine structure elements, respectively. And measured by calculating two criteria, 22 signal-to-noise ratio (SNR) and filtering error ( E ), where the larger the signal-to-noise ratio and the smaller the filtering error, the better the filtering effect, which are defined as:…”