P. Krishnakumar

According to our database, P. Krishnakumar authored at least 6 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

An Explainable AI Framework for Predictive Tool Condition Monitoring in High-Speed Machining of Ti-6Al-4V: Interpretable Intelligence.

George Varghese, P. Krishnakumar, K. I. Ramachandran

IEEE Access, 2026

2024

EXACFS - A CIL Method to mitigate Catastrophic Forgetting.

S. Balasubramanian, M. Sai Subramaniam, Sai Sriram Talasu, P. Krishnakumar, M. Pranav Phanindra Sai, Ravi Mukkamala, Darshan Gera

CoRR, 2024

Machine Learning Approach for Predicting the Solid Particle Lubricant Contamination in a Spherical Roller Bearing.

K. Rameshkumar, Kaviarasu Nataraj, P. Krishnakumar, M. Saimurugan

IEEE Access, 2024

2022

Establishing Statistical Correlation Between Sensor Signature Features and Lubricant Solid Particle Contamination in a Spur Gearbox.

K. Rameshkumar, R. Sriram, M. Saimurugan, P. Krishnakumar

IEEE Access, 2022

2018

Acoustic Emission-Based Tool Condition Classification in a Precision High-Speed Machining of Titanium Alloy: A Machine Learning Approach.

P. Krishnakumar, K. Rameshkumar, K. I. Ramachandran

Int. J. Comput. Intell. Appl., 2018

Machine learning based tool condition classification using acoustic emission and vibration data in high speed milling process using wavelet features.

P. Krishnakumar, K. Rameshkumar, K. I. Ramachandran

Intell. Decis. Technol., 2018