Name: RAFAEL MARIANO CHAGAS
Publication date: 10/09/2024
Examining board:
Name |
Role |
|---|---|
| HELDER ROBERTO DE OLIVEIRA ROCHA | Examinador Interno |
| LUCAS FRIZERA ENCARNACAO | Examinador Interno |
| SILVANGELA LILIAN DA SILVA LIMA BARCELOS | Examinador Externo |
| THAÍS PEDRUZZI DO NASCIMENTO | Examinador Interno |
| WALBERMARK MARQUES DOS SANTOS | Presidente |
Summary: Electric current signature analysis (ESA) has been widely used as a solution for projects to improve operational reliability in industries, since there are many studies that prove its effectiveness. ESA is a set of techniques capable of detecting failures by reading electrical signals collected remotely. According to BONALDI et al (2007), among the techniques that make up ESA, the MCSA (Motor Current Signature Analysis) technique is the most widely used technique in the industrial sector and stands out for its comprehensiveness and simplicity, since it only requires the analysis of the machine's current spectrum signal to detect abnormal conditions. In the search for better industrial development, the study of techniques that improve equipment availability is of utmost importance. Within this context, this dissertation aims to study the applicability of using this technique to improve the reliability of a roller table, where 264 electric motors are installed in series and driven by a frequency inverter. The drive by frequency inverter can pollute the MCSA response and therefore this problem will also be discussed. The results presented in this dissertation show that the fault detection technique works, even with all the practical realities encountered in the actual implementation of equipment.
