Graphical User Interface Aided Online Fault Diagnosis of Electric Motor - DC motor case study

Abstract

This paper contains graphical user interface (GUI) aided online fault diagnosis for DC motor. The aim of the research is to prevent system faults. Online fault diagnosis has been studied. Design of fault diagnosis has two main levels: Level 1 comprises a traditional control loop; Level 2 contains knowledge based fault diagnosis. Fault diagnosis technique contains feature extraction module, feature cluster module and fault decision module. Wavelet analysis has been used for the feature extraction module. For the feature cluster module, fuzzy cluster has been applied. Faults effects are examined on the system using statistical analysis. In this study Fault Diagnosis technique obtains fault detection, identification and halting the system. In the meantime graphical user interface (GUI) is opened when fault is detected. GUI shows the measurement value, fault time and fault type. This property gives some information about the system to the personnel. As seen from the simulation results, faults can be detected and identified as soon as fault appears. In summary, if the system has a fault diagnosis structure, system dangerous situations can be avoided.

Keywords

• wavelet analysis
• fuzzy logic control
• fault diagnosis
• graphical user interface