Contact state analysis using NFIS and SOM

TL;DR

This paper explores the use of NFIS and SOM neural networks to detect contact states in a block system, comparing their effectiveness and accuracy in contact distribution detection.

Contribution

It introduces a novel application of NFIS and SOM for contact state detection and compares their performance on a simple block system.

Findings

NFIS and SOM are applicable for contact state detection.

Different accuracy levels observed between NFIS and SOM.

The methods effectively analyze contact distribution evolution.

Abstract

This paper reports application of neuro- fuzzy inference system (NFIS) and self organizing feature map neural networks (SOM) on detection of contact state in a block system. In this manner, on a simple system, the evolution of contact states, by parallelization of DDA, has been investigated. So, a comparison between NFIS and SOM results has been presented. The results show applicability of the proposed methods, by different accuracy, on detection of contact's distribution.