Repository Copy of: CNN Based Ensemble Approach for Malfunction Detection from Machine Sounds

Key Points

• To explore a CNN-based ensemble method for detecting malfunctions from audio signals of machinery.
• Developed a convolutional neural network (CNN) model to analyze machine sounds.
• Utilized ensemble techniques to improve detection accuracy.
• Evaluated model performance on sound datasets.
• Achieved improved accuracy in malfunction detection compared to traditional methods.
• Demonstrated effectiveness of ensemble strategies in enhancing detection rates.
• Showed potential applicability for real-time monitoring of machinery.