Predictive Maintenance of Electric Motors Using Supervised Learning Models: A Comparative Analysis
Predictive maintenance is a key strategy for ensuring the reliability and efficiency of industrial systems. This study investigates the use of supervised learning models to diagnose the condition of electric motors, categorizing them as "Healthy," "Needs Preventive Maintenance (PM)," or "Broken." Key features of motor operation were employed to train various machine learning algorithms, including Naive Bayes, Support Vector Machines (SVM), Regression models, Random Forest, k-Nearest Neighbors (k-NN), and Gradient Boosting techniques. The performance of these models was evaluated to identify the most effective classifier for predicting motor health. Results showed notable differences in accuracy among the models, with one emerging as the best-performing solution. This study underscores the practicality of using supervised learning for electric motor diagnostics, providing a foundation for efficient maintenance scheduling and minimizing unplanned downtimes in industrial applications.
Code (0)
등록된 구현이 없습니다.
Tasks
SchedulingSimilar Papers 제목 키워드 기반
A Workbench for Testing and Simulation Faults in Three-phase Electric Motors with Intelligent Electronic Device and Microcontrolled System
Electric motors can be damaged or operate improperly from a possible set of failures. Such failures are related to high or very low voltage and current levels, phase loss or blocked rotor. Therefore, it is important to p…
Intelligent Electric Power Steering: Artificial Intelligence Integration Enhances Vehicle Safety and Performance
Electric Power Steering (EPS) systems utilize electric motors to aid users in steering their vehicles, which provide additional precise control and reduced energy consumption compared to traditional hydraulic systems. EP…
Global Attention-based Encoder-Decoder LSTM Model for Temperature Prediction of Permanent Magnet Synchronous Motors
Temperature monitoring is critical for electrical motors to determine if device protection measures should be executed. However, the complexity of the internal structure of Permanent Magnet Synchronous Motors (PMSM) make…
DecoderSupervised load identification of 18 fixed-speed motors based on their turn-on transient current
Several studies have already shown that the transient current can be successfully used to identify electric loads. However, most of the proposed methods were validated using only a handful of loads whose electric propert…
Fault Analysis And Predictive Maintenance Of Induction Motor Using Machine Learning
Induction motors are one of the most crucial electrical equipment and are extensively used in industries in a wide range of applications. This paper presents a machine learning model for the fault detection and classific…
Fault Detection