Diagnosis of Rolling Bearing Failure Using Jerk Sensor (1st Report, Characteristics of Vibration Signal by Jerk Sensor at Low Speed Rotation)

New Damped-Jerk trajectory for vibration reduction

This paper derives a jerk-shaped profile to address the vibration reduction of underdamped flexible dynamics of motion system. The jerk-limited profile is a widespread smooth command pattern used by modern motion systems. The ability of the jerk-limited profile to cancel the residual vibration of an undamped flexible mode is clearly explained using an equivalent continuous filter representation...

Dissociated jerk-limited trajectory applied to time-varying vibration reduction

Jerk-limited trajectories are a widespread solution for the trajectory planning of industrial machinestools or robots. It is known that jerk limitation can reduce vibrations and in some cases can totally suppress residual vibration induced by a lightly damped stationary mode. However, for systems with time-varying mode, which is classically the case for configuration dependent mode or load mass...

Hypogenetic chaotic jerk flows

Vibration Sensor-Based Bearing Fault Diagnosis Using Ellipsoid-ARTMAP and Differential Evolution Algorithms

Effective fault classification of rolling element bearings provides an important basis for ensuring safe operation of rotating machinery. In this paper, a novel vibration sensor-based fault diagnosis method using an Ellipsoid-ARTMAP network (EAM) and a differential evolution (DE) algorithm is proposed. The original features are firstly extracted from vibration signals based on wavelet packet de...

Some simple chaotic jerk functions

One of the most remarkable recent developments in classical physics has been the realization that simple nonlinear deterministic equations can have unpredictable ~chaotic! long-term solutions. Chaos is now thought to be rather common in nature, and the study of nonlinear dynamics has brought new excitement to one of the oldest fields of science. The widespread availability of inexpensive person...