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This book offers a single-resource reference on different analysis strategies of the ball mill acoustics. One of the major problems in the mining industry is the raw material wastage. The biggest challenge faced by the researchers is to install sensors to acquire meaningful data during the crushing operation due to huge dust and the presence of grinding media. The book aims to propose an intelligent system to predict the particle size distribution of the raw material in the closed-loop mill operation and stop the mill automatically by receiving the desired particle size ranges. The simulated results are validated with the experimental results, obtained from an instrumented lab-based ball mill. The acoustics of the running ball mill is considered as the key parameter which is a state of art in this field. This book will be useful for Researchers who work in the field of Digital signal processing.
List of contents
1.Introduction and Preliminaries.- 2.Ball Mill Acoustics and Analysis.- 3.Particle Size Analysis and Predictive Grinding.- 4.State Prediction of a Running Ball Mill.- 5.Residence Time Calculation of the Grinding Materials using Genetic Algorithm.- 6.Real-time System Design to Predict the States of a Ball Mill.- 7.System Validation.- 8.Conclusion and Future Scope.
About the author
Dr. Jaya Sil is Professor of Computer Science & Technology, Indian Institute of Engineering Science and Technology, Shibpur, with specialization in Image Processing and Artificial Intelligence. She earned her Ph.D. in the year 1996 in Engineering from Jadavpur University, where her research focused on Artificial Intelligence and Soft Computing techniques. Dr. Sil has published many research papers in leading academic journals and Conference Proceedings. She authored two books published by Springer, titled as “A Metaheuristic Approach to Protein Algorithms and Insights from Fitness Landscape Analysis,” in 2018 and “Intrusion Detection: A Data Mining Approach,” in 2017. She has guided more than 20 doctoral students. She has received academic honors, including the INSA Senior Scientist Fellowship, Wraclaw University of Technology, Poland, INSA, for her contributions to the field.
Dr. Sonali Sen is Associate Professor of Computer Science at St. Xavier’s College (Autonomous) Kolkata with specialization in Machine Learning, Signal Processing, Bioinformatics, VLSI and Security. She earned her Ph.D. in the year 2022 in Computer Science from Maulana Abul Kalam Azad University of Technology, Kolkata, West Bengal. Her research was focused on Audio Signal Processing and Soft Computing. Dr. Sen has published more than 15 research papers in International Journals and Conferences. She has completed one Minor Project sponsored by UGC. She has also worked as the reviewer and program committee member in several conferences and seminars. She is the life Member of IETE, CSI and ACM.
Dr. Arup Kumar Bhaumik is Professor in Computer Sc. & Engineering and Director of Camellia Institute of Engineering and Technology, Budbud, By Pass(N), BURDWAN—713403, West Bengal, did his Bachelors (B. Tech.) & M.Tech. in Computer Science and Engineering in 1990 and in 1992 respectively from University of Calcutta. He was awarded with Ph.D. in Computer Engineering from Bengal Engineering and Science University, Shibpur (now IIEST) in 2005. In his R&D endeavour, he worked for automation of mining machinery to control those without human intervention and takes keen interest in the study of Control Systems, Artificial Intelligent Systems, Neural Network, Fuzzy Systems, Hybrid Intelligent Systems and also having specialization in Image Processing, Cryptography & Cyber Security, IOT, Data Structure, Database Management System, Compiler Design and Computer Architecture.
Summary
This book offers a single-resource reference on different analysis strategies of the ball mill acoustics. One of the major problems in the mining industry is the raw material wastage. The biggest challenge faced by the researchers is to install sensors to acquire meaningful data during the crushing operation due to huge dust and the presence of grinding media. The book aims to propose an intelligent system to predict the particle size distribution of the raw material in the closed-loop mill operation and stop the mill automatically by receiving the desired particle size ranges. The simulated results are validated with the experimental results, obtained from an instrumented lab-based ball mill. The acoustics of the running ball mill is considered as the key parameter which is a state of art in this field. This book will be useful for Researchers who work in the field of Digital signal processing.
