Intelligent System Design for Stator Windings Faults Diagnosis: Suitable for Maintenance Work

• 作者: Gleison F. V. Amaral Lane M. Rabelo Baccarini Valceres Vieira R. E. Silva Vinícius S. Avelar
• 来源期刊: 软件工程与应用(英文)
• 学科: 医学
• 关键词: FAULT Diagnosis Support VECTOR MACHINES Maintenance WORK Software Tool WINDING SHORT-CIRCUIT
• 年，卷（期）: 2013,（10）
• 页码范围: 526-532
• 页数: 7页
• 分类号: R73

摘要

The short circuit is a severe fault that occurs in the stator windings. Therefore, it is very important to diagnose this type of failure in its beginning before it causes unscheduled stop and the machine loss. In this context, the Support Vector Machine (SVM) is a tool of considerable importance for standard classification. From some training data, it can diagnose whether or not there is a short circuit beginning, and which is important for predictive maintenance. This work proposes a technique for early detection of a short circuit between the turns aiming at its implementation in a real plant. The paper shows simulation and experimental results, and validates the proposed technique.