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Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Proceedings of the Fourth International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, CMMNO'2014, Lyon, France December 15-17

  • Conference proceedings
  • © 2016

Overview

Editors:
  1. Fakher Chaari

    1. National School of Engineers of Sfa, Sfax, Tunisia

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  2. Radoslaw Zimroz

    1. Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław University of Technology Institute of Mining Engineering, Wroclaw, Poland

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  3. Walter Bartelmus

    1. Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław Univ of Technology Inst of Mining Engineering, Wroclaw, Poland

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  4. Mohamed Haddar

    1. Mechanical Engineering Department, National School of Engineers of Sfa, Sfax, Tunisia

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  • Reports on the latest research trends and advanced solutions for machine condition monitoring
  • Includes both theory and case studies
  • Offers a hands-on reference guide to signal-processing techniques, data mining and condition monitoring of machines under non-stationary conditions
  • Includes supplementary material: sn.pub/extras

Part of the book series: Applied Condition Monitoring (ACM, volume 4)

Included in the following conference series:

Conference proceedings info: CMMNO 2014.

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Table of contents (37 papers)

  1. Data Mining

    1. On Optimal Threshold Selection for Condition Monitoring

      • Ðani Juričić, Nada Kocare, Pavle Boškoski
      Pages 237-249

    2. Diagnostic Features Modeling for Decision Boundaries Calculation for Maintenance of Gearboxes Used in Belt Conveyor System

      • Paweł K. Stefaniak, Agnieszka Wyłomańska, Radoslaw Zimroz, Walter Bartelmus, Monika Hardygóra
      Pages 251-263

    3. Vertical Axis Wind Turbine States Classification by an ART-2 Neural Network with a Stereographic Projection as a Signal Normalization

      • Tomasz Barszcz, Andrzej Bielecki, Marzena Bielecka, Mateusz Wójcik, Mirosław Włuka
      Pages 265-275

    4. Electric Motor Bearing Diagnosis Based on Vibration Signal Analysis and Artificial Neural Networks Optimized by the Genetic Algorithm

      • Fenineche Hocine, Felkaoui Ahmed
      Pages 277-289

    5. Gear Fault Diagnosis Based on Angular Measurements and Support Vector Machines in Normal and Nonstationary Conditions

      • Semchedine Fedala, Didier Rémond, Rabah Zegadi, Ahmed Felkaoui
      Pages 291-308

    6. Diversity Measures in Classifier Ensembles Used for Rotating Machinery Fault Diagnosis

      • Wojciech Jamrozik
      Pages 309-319

    7. Diagnostics of Slow Rotating Bearings Using a Novel DAI Based on Acoustic Emission

      • Sylvester A. Aye, P. Stephan Heyns, Coenie J. H. Thiart
      Pages 321-333

    8. Development of Expert System Shell for Coal Mining Industry

      • Piotr Przystałka, Wojciech Moczulski, Anna Timofiejczuk, Mateusz Kalisch, Marek Sikora
      Pages 335-348

  2. Condition Monitoring Techniques

    1. Front Matter

      Pages 349-349
      Download chapter PDF

    2. Analysis of a Planetary Gearbox Under Non-stationary Operating Conditions: Numerical and Experimental Results

      • Cristián Molina Vicuña, Fakher Chaari
      Pages 351-362

    3. Model-Based Estimation of Elevator Rail Friction Forces

      • Ekaitz Esteban, Oscar Salgado, Aitzol Iturrospe, Inge Isasa
      Pages 363-374

    4. Modelling and Simulation of Gear Systems Dynamics for Supporting Condition Monitoring Using Mathematica

      • Walter Bartelmus, Juliusz Grabski
      Pages 375-384

    5. Wind Turbine Generator Bearing Fault Diagnosis Using Amplitude and Phase Demodulation Techniques for Small Speed Variations

      • Ehsan Mollasalehi, Qiao Sun, David Wood
      Pages 385-397

    6. Diagnostics of a Defective Bearing Within a Planetary Gearbox with Vibration and Acoustic Emission

      • Faris Elasha, Matthew Greaves, David Mba
      Pages 399-412

    7. Methodology for the Estimation of the Fatigue Life of Rolling Element Bearings in Non-stationary Conditions

      • Urko Leturiondo, Oscar Salgado, Diego Galar, Madhav Mishra
      Pages 413-423

    8. Adaptive Vibration Diagnostic Technique for Bearings Condition Monitoring of Complicated Machines

      • Alexey Mironov, Pavel Doronkin, Alexander Priklonsky
      Pages 425-438

    9. Study on Rotating Machine Vibration Behavior Using Measured Vibro-Acoustic Signals

      • Akilu Yunusa-Kaltungo, Jyoti K. Sinha, Adrian D. Nembhard
      Pages 439-446

    10. A Probabilistic Approach to the Crack Identification in a Beam-like Structure Using Monitored Mode Shapes and Their Curvature Data with Uncertainty

      • Sergey Shevtsov, Igor Zhilyaev, Paul Oganesyan, Vladimir Akopyan
      Pages 447-461

    11. Condition Monitoring of Aircraft Engine Rotor System with Stiffness Anisotropy of Rotor Supports. Comparative Analysis of Accelerometers Mounting Schemes

      • S. V. Semenov, M. Sh. Nikhamkin, N. A. Sazhenkov, I. V. Semenova
      Pages 463-471

    12. Operational Safety of Steel-Cord Conveyor Belts Under Non-stationary Loadings

      • Ryszard Blazej, Leszek Jurdziak, Witold Kawalec
      Pages 473-481
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  1. Advances in Condition Monitoring of Machinery in Non-Stationary Operations

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About this book

The book provides readers with a snapshot of recent research and technological trends in the field of condition monitoring of machinery working under a broad range of operating conditions. Each chapter, accepted after a rigorous peer-review process, reports on an original piece of work presented and discussed at the 4th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO 2014, held on December 15-16, 2014, in Lyon, France. The contributions have been grouped into three different sections according to the main subfield (signal processing, data mining or condition monitoring techniques) they are related to. The book includes both theoretical developments as well as a number of industrial case studies, in different areas including, but not limited to: noise and vibration; vibro-acoustic diagnosis; signal processing techniques; diagnostic data analysis; instantaneous speed identification; monitoring and diagnostic systems; and dynamic and fault modeling. This book not only provides a valuable resource for both academics and professionals in the field of condition monitoring, it also aims at facilitating communication and collaboration between the two groups.

Editors and Affiliations

  • National School of Engineers of Sfa, Sfax, Tunisia

    Fakher Chaari

  • Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław University of Technology Institute of Mining Engineering, Wroclaw, Poland

    Radoslaw Zimroz

  • Diagnostics and Vibro-Acoustics Science Laboratory, Wrocław Univ of Technology Inst of Mining Engineering, Wroclaw, Poland

    Walter Bartelmus

  • Mechanical Engineering Department, National School of Engineers of Sfa, Sfax, Tunisia

    Mohamed Haddar

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