Smart Predictive Maintenance Device for Critical In-Service Motors

Abstract

The paper proposed an innovative predictive maintenance system, designated to monitor and diagnose critical electrical equipment (generally large power electric motors) within industrial electrical installations. A smart and minimally invasive system is designed and developed. Its scope is to evaluate continuously the essential operating parameters (electrical, thermal, and mechanical) of the investigated equipment. It manages to report the deviations of inspected machine operating parameters values from the rated ones. The system also suggests the potential cause of these abnormal variations along with possible means (if the defect is identified in a database, constantly updated with each appearance of a malfunction). The developed maintenance device generates an operating report of the analyzed equipment, in which the values of power quality and energy indicators are computed and interpreted. Additionally, real-time remote transmission of analyzed data is facilitated, making them accessible from any location. The proposed maintenance system is a low-cost device that is easy to install and use in comparison with similar existing devices and equipment. The designed maintenance system was tested on dedicated to low-voltage equipment up to 100 kW.

Keywords

• electric critical equipment
• induction motors
• predictive maintenance
• power quality
• experimental device