Myshkin / Markova On-line Condition Monitoring in Industrial Lubrication and Tribology

1. Auflage 2018
ISBN: 978-3-319-61134-1
Verlag: Springer Nature Switzerland
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 8, 241 Seiten

Reihe: Applied Condition Monitoring

This book offers readers a concise yet comprehensive introduction to a set of diagnostic methods for on-line condition monitoring of lubricated tribosystems used in industry. It covers the latest trends in on-line tribodiagnostics, an important and rapidly developing area of tribology. The book also reports on new tools as they have been developed and applied by the authors. A special emphasis is given to the physical fundamentals of opto-magnetic detectors, ferro-analyzers and analyzers of metal particles in lubricated tribosystems, as well as fluorescence methods for real-time oil monitoring in compressors, hydraulic systems and electrical transformers. Further, the book discusses other important issues such as the monitoring of water content in oil, and presents techniques for measuring soot content in oil in diesel engine oils. Lastly, it describes the modular intelligent (SMART) diagnostic system for vehicles. Mainly intended for researchers, industrial and automotive engineers developing cost-effective techniques and sensors for the on-line monitoring of lubricating oil, the book also offers a valuable source of information for students and project managers in the manufacturing, energy, oil and gas, and automotive industry.

Autoren/Hrsg.

Myshkin, Nikolai K.

Markova, Liubou V.

Inhaltsverzeichnis

1;Preface;6
2;Contents;8
3;Nomenclature;10
4;Introduction;18
5;1 Methods and Instruments for Condition Monitoring of Lubricants;21
5.1;1.1 Introduction;21
5.2;1.2 Laboratory Methods of Oil Monitoring;22
5.3;1.3 Methods and Means for Real-Time Monitoring Lubricant Performance;23
5.4;1.4 Fluorescence Methods and Tools for Real-Time Oil Oxidation Monitoring;32
5.5;1.5 Fluorescence Emission Ratio Technique and Sensor for On-Board Application;37
5.5.1;1.5.1 Application of the Fluorescent Sensor for Hydraulic Oil Condition Monitoring;41
5.5.2;1.5.2 Application of Fluorescence Emission Ratio Technique for Transformer Oil Monitoring;42
5.6;1.6 Conclusions;47
5.7;References;48
6;2 Oil Viscosity Monitoring;50
6.1;2.1 Introduction;50
6.2;2.2 Oil Viscosity Characterization;50
6.3;2.3 Laboratory Measurements of Viscosity;52
6.4;2.4 Methods of On-Line Viscosity Monitoring;54
6.5;2.5 Viscosity Sensor Based on Magneto-Elasticity;63
6.5.1;2.5.1 Magnetoelastic Viscometry Technique;63
6.5.2;2.5.2 Magnetoelastic Viscometer;67
6.5.3;2.5.3 Experimental Results;71
6.6;2.6 Conclusions;76
6.7;References;77
7;3 Monitoring of Water Content in Oil;79
7.1;3.1 Introduction;79
7.2;3.2 Forms of Water in Oil;80
7.3;3.3 Water Content Characteristics;82
7.4;3.4 Laboratory Methods for Measuring Water Content in Oil;84
7.5;3.5 Methods and Devices for Real-Time Monitoring of Water Content in Oil;87
7.6;3.6 Conclusions;97
7.7;References;98
8;4 Control of Soot Concentration in Oil;100
8.1;4.1 Introduction;100
8.2;4.2 Up-to-Date Requirements to Monitoring of Diesel Oil;101
8.3;4.3 Laboratory Methods of Monitoring Soot Content in Oil and Its Properties;103
8.4;4.4 Portable and Built-in Devices for Monitoring Soot in Oil;105
8.5;4.5 Fiber–Optic Sensors of Soot Content in Diesel Oil;112
8.6;4.6 Conclusions;144
8.7;References;144
9;5 Wear Prediction for Tribosystems Based on Debris Analysis;147
9.1;5.1 Introduction;147
9.2;5.2 Laboratory Diagnostics Basing on Wear Debris Analysis;158
9.3;5.3 Portable Means for Machine Condition Monitoring;164
9.4;5.4 Techniques and Devices for Wear Diagnostics in Real-Time;169
9.5;5.5 Development of Tribodiagnostic Devices;183
9.5.1;5.5.1 On-line Opto-Magnetic Detector;183
9.5.2;5.5.2 Optical Ferroanalyzer;198
9.5.3;5.5.3 Inductive Wear Particle Counter;205
9.6;5.6 Conclusions;212
9.7;References;212
10;6 Trends in On-line Tribodiagnostics;218
10.1;6.1 Introduction;218
10.2;6.2 Modular Systems;218
10.3;6.3 Intelligent (SMART) System;228
10.4;6.4 Artificial Intelligence Methods of Data Processing;229
10.5;6.5 Conclusions;236
10.6;References;237
11;Conclusions;239