Research on the influence of engine rotational speed to the vibration penetration into the driver via feet – multidimensional analysis

The manuscript provides a discussion on the studies and analysis of influence of engine rotational speed to the vibration penetration into the driver via feet. For the driving safety and comfort it is very important what kind and values of vibration are transferred to car body. The motor-engine was chosen as the vibration source. The paper presents some results of investigation on influence of idle gear rotational speed of engine to the vibration registered at place for driver feet. Changes of the values of the influence of vibration on human were presented as RMS and Awmax distribution or proposed estimator of spectrum Tabs(FFT). The changes of the vibration signals and its spectrums were observed in orthogonal 3 axes. The complementary analysis was conducted as time-frequency distribution of the vibration. The experiments were conducted on the car vehicle which was placed on the special test racks. It allows to lessen the road roughens impact on the suspension and the car body

A hybrid prognostics approach to estimate the residual useful life of a planetary gearbox with a local defect

A hybrid prognostics approach for the monioring of a planetary gearbox with the local defect is presented. This hybrid method can predict the remaining useful life (RUL) of planetary gearbox with a fatigue crack. The method consists of a dynamical model for simulation data generation, a statistical algorithm for feature selection and weighting, and a modified grey model for RUL prediction. Experimental studies are conducted to validate and demonstrate the feasibility of the proposed method for RUL prediction of a cracked sun gear in planetary gearbox. And the validation has a promising result

Decomposition of the symptom observation matrix and grey forecasting in vibration condition monitoring of machines

With the tools of modern metrology we can measure almost all variables in the phenomenon field of a working machine, and many of the measured quantities can be symptoms of machine conditions. On this basis, we can form a symptom observation matrix (SOM) intended for condition monitoring and wear trend (fault) identification. On the other hand, we know that contemporary complex machines may have many modes of failure, called faults. The paper presents a method of the extraction of the information about faults from the symptom observation matrix by means of singular value decomposition (SVD), in the form of generalized fault symptoms. As the readings of the symptoms can be unstable, the moving average of the SOM is applied with success. An attempt to assess the diagnostic contribution of a primary symptom is made, and also an approach to assess the symptom limit value and to connect the SVD methodology with neural nets is considered. Finally, a condition forecasting problem is discussed and an application of grey system theory (GST) to symptom prognosis is presented. These possibilities are illustrated by processing data taken directly from the machine vibration condition monitoring area