Master Thesis

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Design and implementation of a data acquisition system for multi fault diagnosis analysis in induction motors
(German Mongolian Institute for Resouce and Technology, 2024-05-20) Tuvshin Gankhuyag; Ariunbolor Purvee; Turbat Shagdar
This Master's thesis focuses on the design of a data acquisition system for detecting motor faults early and implementing smart maintenance strategies. Understanding and diagnosing faults in induction motors is critical for maintaining the reliability and efficiency of industrial operations. The thesis aims to design a data acquisition system for early detection of motor faults. By developing a novel data acquisition system and comparing its performance with existing systems, this research aims to provide valuable insights and practical solutions to enhance motor fault diagnosis, ultimately improving operational reliability and reducing downtime in industrial settings. The study begins by introducing the main research topic, discussing its broader context and significance, and emphasizing the need for a reliable data acquisition system for multi-fault diagnosis in induction motors, particularly squirrel cage motors widely used across various industries.