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Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Proceedings of the 6th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations, CMMNO’2018, 20-22 June 2018, Santander, Spain

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Alfonso Fernandez Del Rincon

    1. Department of Structural and Mechanical Engineering, Faculty of Industrial and Telecommunications Engineering, University of Cantabria, Santander, Spain

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  2. Fernando Viadero Rueda

    1. Department of Structural and Mechanical Engineering, Faculty of Industrial and Telecommunications Engineering, University of Cantabria, Santander, Spain

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  3. Fakher Chaari

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

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  4. Radoslaw Zimroz

    1. Institute of Mining Engineering, Wroclaw University of Technology, Wrocław, Poland

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  5. Mohamed Haddar

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

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  • Reports on the latest research and industrial case studies
  • Describes advanced signal processing methods for the analysis of non-stationary processes
  • Covers a wide range of models, including dynamic, neural networks and probabilistic models

Part of the book series: Applied Condition Monitoring (ACM, volume 15)

Included in the following conference series:

Conference proceedings info: CMMNO 2018.

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Table of contents (42 papers)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Condition Monitoring in Non-Stationary Operations

    1. Front Matter

      Pages 1-1
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    2. Extraction of Weak Bearing Fault Signatures from Non-stationary Signals Using Parallel Wavelet Denoising

      • Dustin Helm, Markus Timusk
      Pages 3-10

    3. Non-stationary Operating Conditions of Rotating Machines: Assumptions and Their Consequences

      • Emna Sghaier, Adeline Bourdon, Didier Remond, Jean-Luc Dion, Nicolas Peyret
      Pages 11-19

    4. Neighbor Retrieval Visualizer for Monitoring Lifting Cranes

      • Paul Honeine, Samira Mouzoun, Mario Eltabach
      Pages 20-29

    5. Influence of the Non-linear Hertzian Stiffness on the Dynamic Behavior of Planetary Gear During Run up Condition

      • Ayoub Mbarek, Ahmed Hammami, Alfonso Fernández del Rincón, Fakher Chaari, Miguel Iglesias, Fernando Viadero Rueda et al.
      Pages 30-38

    6. High Resolution Drilling-Induced Temperature Mapping of CFRP Laminates Using a Fully Distributed Optical Fiber Sensor

      • Pingyu Zhu, Yongjing Li, Yetian Wang, Marcelo A. Soto
      Pages 39-43

    7. Normalization Process Based on Kernel Ridge Regression Applied on Wind Turbine IAS Monitoring

      • Hugo Andre, Flavien Allemand, Ilyes Khelf, Adeline Bourdon, Didier Remond
      Pages 44-53

    8. The Automatic Method of Technical Condition Change Detection for LHD Machines - Engine Coolant Temperature Analysis

      • Paweł Stefaniak, Paweł Śliwiński, Paula Poczynek, Agnieszka Wyłomańska, Radosław Zimroz
      Pages 54-63

  3. Monitoring and Diagnostic Systems

    1. Front Matter

      Pages 65-65
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    2. Convolutional Neural Networks for Fault Diagnosis Using Rotating Speed Normalized Vibration

      • Dongdong Wei, KeSheng Wang, Stephan Heyns, Ming J. Zuo
      Pages 67-76

    3. Model-Based State Estimation for the Diagnosis of Multiple Faults in Non-linear Electro-Mechanical Systems

      • Mikel Gonzalez, Oscar Salgado, Jan Croes, Bert Pluymers, Wim Desmet
      Pages 77-89

    4. Estimating the Rotational Synchronous Component from Instantaneous Angular Speed Signals in Variable Speed Conditions

      • Guillaume Bruand, Florent Chatelain, Pierre Granjon, Nadine Martin, Christophe Duret, Hervé Lénon
      Pages 90-100

    5. A Fleet-Wide Approach for Condition Monitoring of Similar Machines Using Time-Series Clustering

      • Kilian Hendrickx, Wannes Meert, Bram Cornelis, Karl Janssens, Konstantinos Gryllias, Jesse Davis
      Pages 101-110

    6. Remaining Useful Life Prediction of Rolling Element Bearings Based on Unscented Kalman Filter

      • Junyu Qi, Alexadre Mauricio, Mathieu Sarrazin, Karl Janssens, Konstantinos Gryllias
      Pages 111-121

    7. Centrifugal Pump Condition Monitoring and Diagnosis Using Frequency Domain Analysis

      • Maamar Ali Saud ALTobi, Geraint Bevan, Peter Wallace, David Harrison, K. P. Ramachandran
      Pages 122-131

    8. Analysis of Autogram Performance for Rolling Element Bearing Diagnosis by Using Different Data Sets

      • Ali Moshrefzadeh, Alessandro Fasana, Luigi Garibaldi
      Pages 132-141

    9. Fault Detection of Wind Turbine Planetary Epicyclic Gears Using Adaptive Empirical Wavelet Decomposition Based Hybrid Features

      • R. Uma Maheswari, R. Umamaheswari
      Pages 142-150

    10. Long Term Temperature Data Analysis for Damage Detection in Electric Motor Bearings with Density Modeling and Bhattacharyya Distance

      • Wiesław Migdał, Jacek Wodecki, Maciej Wuczyński, Paweł Stefaniak, Agnieszka Wyłomańska, Radosław Zimroz
      Pages 151-159

    11. Diesel Engine Condition Monitoring Due to Different Operation Areas

      • Suzana Lampreia, José Requeijo, Vitor Lobo
      Pages 160-168
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Other volumes

  1. Advances in Condition Monitoring of Machinery in Non-Stationary Operations

Keywords

About this book

This book is aimed at researchers, industry professionals and students interested in the broad ranges of disciplines related to condition monitoring of machinery working in non-stationary conditions. Each chapter, accepted after a rigorous peer-review process, reports on a selected, original piece of work presented and discussed at the International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO’2018, held on June 20 – 22, 2018, in Santander, Spain. The book describes both theoretical developments and a number of industrial case studies, which cover different topics, such as: noise and vibrations in machinery, conditioning monitoring in non-stationary operations, vibro-acoustic diagnosis of machinery, signal processing, application of pattern recognition and data mining, monitoring and diagnostic systems, faults detection, dynamics of structures and machinery, and mechatronic machinery diagnostics.

Editors and Affiliations

  • Department of Structural and Mechanical Engineering, Faculty of Industrial and Telecommunications Engineering, University of Cantabria, Santander, Spain

    Alfonso Fernandez Del Rincon, Fernando Viadero Rueda

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

    Fakher Chaari

  • Institute of Mining Engineering, Wroclaw University of Technology, Wrocław, Poland

    Radoslaw Zimroz

  • National School of Engineers of Sfax, Sfax, Tunisia

    Mohamed Haddar

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