PES College of Engineering

madhusudanack@pesce.ac.in

+91 7338513801

Download CV

Assistant Professor

Ph.D – Condition Monitoring National Institute of Technology Karnataka, Surathkal
M.Tech. – Machine Design BMS College of Engineering, Bengaluru.

Condition Monitoring, Vehicle Dynamics, Mechanical Vibrations and Dynamics, Tribology

Madhusudana, C. K., Budati, S., Gangadhar, N., Kumar, H., and Narendranath, S. (2016). “Fault diagnosis studies of face milling cutter using machine learning approach”. Journal of Low Frequency Noise, Vibration and Active Control, 35(2), 128-138.
Madhusudana, C. K., Kumar, H., and Narendranath, S. (2016). “Condition monitoring of face milling tool using K-star algorithm and histogram features of vibration signal”. Engineering Science and Technology, an International Journal, 19(3), 1543–1551.
Madhusudana C. K., Hemantha Kumar and Narendranath S., (2017). “Face Milling Tool Condition Monitoring using Sound Signal”, International Journal of Systems Assurance Engineering and Management, 8(2), 1643-1653.
Madhusudana, C. K., Gangadhar, N., Hemantha Kumar and Narendranath, S., (2018) “Use of Discrete Wavelet Features and Support Vector Machine for Fault Diagnosis of Face Milling Tool”, Structural Durability and Health Monitoring, an International Journal, 12(2), 111-127.
Ravikumar, K. N., Madhusudana, C. K., Kumar, H., and Gangadharan, K. V. (2022). Classification of gear faults in internal combustion (IC) engine gearbox using discrete wavelet transform features and K star algorithm. Engineering Science and Technology, an International Journal, 30, 101048

Ravikumar K.N., Madhusudana C.K., Kumar H., Gangadharan K.V. (2020) Ball Bearing Fault Diagnosis Based on Vibration Signals of Two Stroke IC Engine Using Continuous Wavelet Transform. In: Dutta S., Inan E., Dwivedy S. (eds) Advances in Rotor Dynamics, Control, and Structural Health Monitoring. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-5693-7_28.