Recent Advances in Condition Monitoring : Select Proceedings of NCCM 2024 (Lecture Notes in Mechanical Engineering)

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Recent Advances in Condition Monitoring : Select Proceedings of NCCM 2024 (Lecture Notes in Mechanical Engineering)

Andhare, Atul (EDT)/ Ganesh Kumar, PVS (EDT)

ウェブストア価格 ¥61,245（本体¥55,678）
Springer Nature Switzerland AG（2025/08発売）
外貨定価 US$ 299.99
ポイント 556pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 327 p.
言語 ENG
商品コード 9789819657902

Full Description

This book presents select peer-reviewed proceedings of the National Conference on Condition Monitoring (NCCM 2024), organized by Visvesvaraya National Institute of Technology Nagpur in collaboration with the Condition Monitoring Society of India. It showcases the latest research and advancements in the field of condition monitoring and predictive maintenance. Various topics covered in this book include vibration monitoring, thermography, wear debris analysis, and other critical techniques employed in industry for condition monitoring. The book also emphasizes the implementation of advanced strategies for equipment reliability and the optimization of maintenance practices. This compilation is of significant value to researchers, professionals, and academicians working in the field of condition monitoring and predictive maintenance, offering insights into the most recent trends and developments shaping the industry.

Identification of Wear Particles obtained through Gearbox using Convolution Neural Network.- Fault detection of gearbox using sound intensity and sound pressure mapping.- Fault detection of gearbox using vibration and noise analysis.- Fault Detection of Industrial Air Blower Using Vibration Signal Analysis.- Structural Optimization of Diesel Genset Bracket Using FEA.- Optimizing Coal Mill downtime by early detection of Main Reducer Gearbox Foundation Deterioration.- Power Loss Prediction in Solar PV Modules Using Image Processing and Machine Learning.- Fault Initiation Identification in a Run to Fail Scenario of Bearing.- Qualitative and Quantitative Analysis of Accumulated Dust on Solar PV Modules.- Integrating Machine Learning With Empirical Mode Decomposition For Multiple Fault Diagnosis In Rotating Machinery.- Intelligent Fault Detection in Wind Turbine using Spectral Estimation Methods.- Optimisation of Sensors for Comprehensive Vibration Condition Monitoring at Large Sites.- Intelligent Oil Analysis: Predicting Maintenance Needs.- Detection Of Abnormality In Hydrostatic Lubrication System Through Average Shaft Centre Line Plot At Sinter Plant Waste Gas Fan.- Detection and monitoring of crack in a Grinding Mill Shell-A Case Study.- Minimal Redundancy Maximal Relevance (MRMR) Based Feature Ranking for Efficient Automated Fault Diagnosis of Rolling Element Bearing.