Nonlinear impact monitoring: 2-dimensional sampling

Monitoring Nonlinear Profiles Using Wavelets

In many manufacturing processes, the quality of a product is characterized by a non-linear relationship between a dependent variable and one or more independent variables. Using nonlinear regression for monitoring nonlinear profiles have been proposed in the literature of profile monitoring which is faced with two problems 1) the distribution of regression coefficients in small samples is unkno...

An Adaptive Sampling Strategy for Online High-Dimensional Process Monitoring

2-Dimensional Inelastic Impact Osciallator

We present an investigation of a two-dimensional inelastic impact oscillator representing a friction force microscope. This paper includes the equations of motion, an analysis of the Jacobi matrix, and the fundamental domain. By applying periodic orbit theory to these and then calculating the diffusion, we find a possible link between nanotribology and everyday kinetic friction. Included is a s...

monitoring nonlinear profiles using wavelets

in many manufacturing processes, the quality of a product is characterized by a non-linear relationship between a dependent variable and one or more independent variables. using nonlinear regression for monitoring nonlinear profiles have been proposed in the literature of profile monitoring which is faced with two problems 1) the distribution of regression coefficients in small samples is unkno...

Monitoring Depth of Anesthesia by Nonlinear Correlation Measures

Background: Monitoring the depth of anesthesia (DOA) takes an important role for anesthetists in order avoiding undesirable reactions such as intraoperative awareness, prolonged recovery and increased risk of postoperative complications.The Central Nervous System (CNS) is the main target of anesthetic drugs, hence EEG signal processing during anesthesia is helpful for monitoring DOA. In order t...