What question did this study set out to answer?

The aim is to enhance predictive maintenance for ball screw feed drives by detecting electrical imbalances and faults.

Machine learning based electrical imbalance detection of ball screw feed drive in machine tools

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Randomized trial demonstrates fault detection and imbalance classification in machine tools, suggesting improvements in maintenance efficiency.

The aim is to enhance predictive maintenance for ball screw feed drives by detecting electrical imbalances and faults.
Proposed a low-cost framework utilizing three-phase motor current signals.
Employed supervised machine learning methods for binary fault detection and multiclass imbalance severity classification.
Extracted time domain features from current signals and trained a Support Vector Machine classifier.
SVM achieved 94% accuracy in detecting severe faults and 78% accuracy for multiclass severity classification.
Analysis showed effectiveness for motor impedance up to 41%.
SVM outperformed Random Forest and CNN models in accuracy and computational efficiency.

Hussain et al. (2026) studied this question.

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Bookmark

View Full Paper

Ask AI

Bookmark

Authors

Randomized trial demonstrates fault detection and imbalance classification in machine tools, suggesting improvements in maintenance efficiency.

The aim is to enhance predictive maintenance for ball screw feed drives by detecting electrical imbalances and faults.
Proposed a low-cost framework utilizing three-phase motor current signals.
Employed supervised machine learning methods for binary fault detection and multiclass imbalance severity classification.
Extracted time domain features from current signals and trained a Support Vector Machine classifier.
SVM achieved 94% accuracy in detecting severe faults and 78% accuracy for multiclass severity classification.
Analysis showed effectiveness for motor impedance up to 41%.
SVM outperformed Random Forest and CNN models in accuracy and computational efficiency.

Hussain et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark