Avinash Maruti Badadhe

Scopus Publications

Reducing label dependence in vibration-based drill-bit condition monitoring with masked feature pretraining
M. N. Chandan, Avinash Badadhe, Alemu Workie Kebede, Himadri Majumder
Scientific Reports, 2026
Reliable tool condition monitoring (TCM) plays a critical role in precision machining, where progressive wear can lead to dimensional inaccuracies, degraded surface finish, and unplanned downtime. Despite advances in data-driven diagnostics, most machine-learning solutions remain constrained by their reliance on extensive labelled datasets, which poses a major barrier to industrial adoption. To address this limitation, this work introduces a Self-Supervised Masked-Feature Pretraining (SSL-MFP) framework that learns latent vibration representations by reconstructing partially masked time-frequency features, thereby eliminating the need for class labels during the initial learning stage. The pretrained encoder is subsequently fine-tuned using only a small subset of the labelled dataset for downstream drill-wear classification, markedly reducing annotation demands. The framework is evaluated on a fused vibration-feature dataset and benchmarked against established supervised baselines spanning machine-learning and deep-learning architectures. Results indicate that the proposed approach achieves classification accuracy comparable to that of fully supervised models while utilizing significantly fewer labelled samples, demonstrating effective generalization under limited annotation conditions. Furthermore, the learned feature manifold exhibits distinct class separability, evidencing the representational strength of the self-supervised encoder. Overall, the SSL-MFP paradigm provides a data-efficient foundation for TCM, enabling industrial deployment where labelling costs and adaptation are critical challenges.
Optimization of ECDM Process Parameters for Microchannel Fabrication Through Mixed Electrolyte in Borosilicate Glass Using Taguchi-GRA Approach
Akshay Doke, Avinash M. Badadhe, N. S. Mujumdar
Journal of the Institution of Engineers India Series D, 2026
Influence of Alloy Addition on Mechanical Properties of Low Alloy Steel in Powder Metallurgy Gears
Mangesh B. Bankar, Avinash M. Badadhe, Sudarshan C. Palve
Journal of the Institution of Engineers India Series D, 2026
A Comparative Review on Design and Development of Landmine Detection System for Military Applications
Prerana Pisal, Yathartha Jadhav, Rayappa Shrinivas, Mahale Swarupa Shirkar, Smit Waikar, Avinash M. Badadhe
Adaptive Technologies for Sustainable Growth, 2026
Advancement of High Entropy Alloys from Few Decades
Rayappa Shrinivas Mahale, Raj Shyam Mahajan, Avinash M. Badadhe, Ravi Shankar Rai, Shashanka Rajendrachari, Swapnil S. Vyavahare, Amol G. Kamble
Engineering Materials, 2026
High entropy alloys (HEAs) are a new kind of metal materials that have become one of the most exciting topics in materials science over the last few decades. Unlike traditional alloys, which have one main element and few small additions, HEAs are made by mixing five or more elements in equal or near-equal amounts, so no single element is the main one. This special way of making alloys gives HEAs four important effects high entropy, severe lattice distortion, sluggish diffusion, and the cocktail effect which together give them very good and sometimes surprising properties. This chapter gives a full review of how HEAs started, from the early ideas in the 1990s and first real experiments in early 2000s, up to the latest breakthroughs from 2020 to 2025. The main ways of making HEAs, like arc melting, powder metallurgy, and additive manufacturing, are discussed, along with the challenges that still make large-scale production hard. The mechanical properties of HEAs, including their special ability to be both strong and ductile at the same time, are explained. Functional properties like corrosion resistance, oxidation resistance, and magnetic behaviour are also covered, showing why HEAs are useful for extreme environments. The role of computer modeling tools including Density Functional Theory (DFT), CALPHAD, and machine learning is discussed, as these have become very important for finding new HEA compositions without testing every possible mix in the lab. The chapter also looks at where HEAs are already being used, in aerospace, automotive, energy, and biomedical fields, and what challenges still need to be solved, like the high cost of raw materials and lack of standard testing methods. Sustainability and the need for more affordable and environmentally responsible designs are also discussed. Overall, this chapter shows that HEAs have changed the limits of what metals can do, and with continued research and better production methods, they are set to play a leading role in the future of materials science and engineering.
Enhancing PV Efficiency using Direct Cooling with CuO Nanofluid
Nikhil Kondibhau Purwant, Avinash M. Badadhe
Renewable Energy and Sustainable Development, 2025
A Dual-Stream Gated Attention Network for Fault Diagnosis of Drill Bit Using time and Frequency Domain-based Vibration Features
Chandan M. N., Himadri Majumder, Avinash Badadhe
Journal of Vibration Engineering and Technologies, 2025
An Efficient-Secure Patient Authentication Framework Using Wireless Body Sensor Networks in the Healthcare System
Sachin Argade, Swapnil Vyavahare, Vishal Naranje, Avinash Badadhe, Yashwant Chapke, Rayappa Mahale
International Journal of Communication Systems, 2025
Wireless body sensor networks (WBSNs) are increasingly used in healthcare for remote monitoring of patients. Although these systems improve access to medical care, they also face serious challenges related to data security and patient authentication. This study proposes a lightweight and secure authentication framework based on a Three‐Tier Secure Message Authentication Code (TTSMAC) protocol. The framework combines three key techniques: Factorized RSA (FRSA) for efficient key generation, Length Pearson Hashing (LPH) for secure token management, and Dual Secret Key Elliptic Curve Cryptography (DSK‐ECC) for protecting stored data. Experimental results showed that the proposed framework reduces encryption/decryption time, lowers key setup overhead, and achieves higher throughput compared with existing methods. Also, the performance evaluations showed substantial improvements in encryption/decryption times and throughput, demonstrating the framework's suitability for resource‐constrained, battery‐powered wearable sensors. Overall, the framework enhances security, maintains patient data privacy, and ensures reliable authentication for WBSN‐based healthcare applications.
Design and Development of Novel Oxygen Concentrator using Pressure Swing Adsorption Technique
Swapnil Vyavahare, Vishal Naranje, Yashawant Chapke, Ruchira Tare, Avinash Badadhe, Dinesh Washimkar
Journal of the Institution of Engineers India Series C, 2025
Improvement of ride comfort and stability of high-speed rail vehicles with semi-active suspension system
K. Hemanth, T. M. Gurubasavaraju, V. Shamanth, M. Y. Supritha, K. S. Narayanaswamy, Rayappa Mahale, Swapnil Vyavahare, Avinash Badadhe
International Journal of Dynamics and Control, 2025
Machine learning techniques in monitoring and controlling friction stir welding process: a critical review
Bhardwaj Kulkarni, Saurabh Tayde, Yashwant Chapke, Swapnil Vyavahare, Avinash Badadhe
Discover Applied Sciences, 2025
FDM Printed PLA/Coconut Wood Composite: Compression Characteristics and Parametric Optimization
Mahendran Samykano, Rajan Kumaresan, Reji Kumar Rajamony, Muhamad Mat Noor, Kumaran Kadirgama, Devarajan Ramasamy, Wan Sharuzi Wan Harun, Adarsh Kumar Pandey, Avinash Maruti Badadhe, Satesh Namasivayam
Journal of Advanced Research in Micro and Nano Engineering, 2025
Performance Modelling and Simulation of Cobot for Pick and Place Application Using RoboDK
Rachayya R Arakerimath, Aditya H. Badve, Divyani P. Deshmukh, M. N. Chandan, Avinash Badadhe
International Conference on Emerging Technologies in Electronics and Green Energy Iceteg 2025, 2025
Human–machine collaborative additive manufacturing: a systematic review and bibliometric analysis
Swapnil Vyavahare, Vishal Naranje, Avinash Badadhe, Rayappa Mahale, Yashwant Chapke
Robotic Intelligence and Automation, 2025
A Comparative Review on Design and Development of Automation System for Grading of Onion
Rahul Suryawanshi, Jayesh Jagtap, Dnyaneshwari Shegokar, Siddhesh Jaju, Chandan M. N, Avinash M. Badadhe
2025 1st International Conference on Aiml Applications for Engineering and Technology Icaet 2025, 2025
A comprehensive study on the mechanical qualities of FDM 3D printed coconut wood-polylactic acid composite
Rajan Kumaresan, Ngui Wai Keng, Mahendran Samykano, Kumaran Kadirgama, Adarsh Kumar Pandey, Avinash M. Badadhe, Ponnambalam S. G
International Journal of Polymer Analysis and Characterization, 2025
Vision Based Automation System for Onion Grading Using Robotic Arm
Rahul Suryawanshi, Jayesh Jagtap, Dnyaneshwari Shegokar, Siddhesh Jaju, Chandan M.N, Avinash M. Badadhe, Pranav Lad, Eric Fernandes
2025 IEEE 4th International Conference for Advancement in Technology Iconat 2025, 2025
Enhancing the borosilicate glass micromachining by using mixed alkaline electrolytes in the ECDM process
Akshay Doke, Avinash M. Badadhe, Pradeep Dixit
Materials and Manufacturing Processes, 2024
Investigation of bending and compression properties on PLA-brass composite using FDM
S.K. Selvamani, W.K. Ngui, K. Rajan, M. Samykano, Reji Kumar R, Avinash M. Badadhe
Physics and Chemistry of the Earth, 2022
Utilization and Study of Raw Groundnut Shell as a Source of Sound Absorbing Material
Ulhas A. Malawade, Vishvesh V. Malgaonkar, Avinash M. Badadhe, Madhavrao G. Jadhav
Journal of Natural Fibers, 2022
Significance of phase change material and nanofluid in photovoltaic panel cooling technique: SWOC analysis
Nikhil K. Purwant, Avinash M. Badadhe
Materials Today Proceedings, 2021
Evaluation of energy absorbing capacity of crash box filled with honeycomb material
Shivpal S. Wadkar, A. M. Badadhe
Techno Societal 2018 Proceedings of the 2nd International Conference on Advanced Technologies for Societal Applications, 2020
Optimisation of performance and emission parameters of diesel engine using tyre pyrolysis oil
R. N. Pote, R. K. Patil, A. M. Badadhe
Australian Journal of Mechanical Engineering, 2020
Investigation of vibration characteristics of ball bearing defects using dimensional analysis
Abhishek P. Mohite, A. M. Badadhe, R. G. Desavale
Lecture Notes in Mechanical Engineering, 2020
Correlations between tool displacement and surface roughness in a boring process: An experimental study
Avinash M. Badadhe, Suresh Y. Bhave, Laxman G. Navale
International Journal of Manufacturing Technology and Management, 2013
Cutting parameters optimization in boring process by using Taguchi parametric design
International Journal of Applied Engineering Research, 2012

Avinash Maruti Badadhe

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Scopus Publications