Research of insulation condition monitoring and fault diagnosing method of motor of mine main ventilator

Abstract

The paper analyzed causes of insulation aging status and insulation failure and its evolution process of motor of mine main ventilator, introduced an online insulation condition monitoring and fault diagnosing system of motor of mine main ventilator. In order to solve problems which will lead to signal ambiguity in insulation status failure diagnosing process, it proposed insulation fault diagnosing method of motor based on fuzzy theory and D-S evidence theory combining with existing database of fault diagnostic information. The method uses fuzzy theory to calculate membership function values of fault information, and uses combination rules of the D-S evidence theory to realize information fusion and processing to determine types of insulation fault of the system according to corresponding diagnostic criteria. The instance analysis of the system verifies feasibility and validity of the method.

Keywords

• mine main ventilator
• insulation condition
• fault diagnosing
• d-s evidence theory
• fuzzy theory