Felkaoui / Chaari / Haddar Rotating Machinery and Signal Processing

Proceedings of the First Workshop on Signal Processing Applied to Rotating Machinery Diagnostics, SIGPROMD'2017, April 09-11, 2017, Setif, Algeria
1. Auflage 2019
ISBN: 978-3-319-96181-1
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 12, 142 Seiten

Reihe: Applied Condition Monitoring

This book provides readers with a timely snapshot of the potential offered by and challenges posed by signal processing methods in the field of machine diagnostics and condition monitoring. It gathers contributions to the first Workshop on Signal Processing Applied to Rotating Machinery Diagnostics, held in Setif, Algeria, on April 9-10, 2017, and organized by the Applied Precision Mechanics Laboratory (LMPA) at the Institute of Precision Mechanics, University of Setif, Algeria and the Laboratory of Mechanics, Modeling and Manufacturing (LA2MP) at the National School of Engineers of Sfax. The respective chapters highlight research conducted by the two laboratories on the following main topics: noise and vibration in machines; condition monitoring in non-stationary operations; vibro-acoustic diagnosis of machinery; signal processing and pattern recognition methods; monitoring and diagnostic systems; and dynamic modeling and fault detection.

Autoren/Hrsg.

Felkaoui, Ahmed

Chaari, Fakher

Haddar, Mohamed

Inhaltsverzeichnis

1;Preface;6
2;Contents;8
3;Feature Selection Scheme Based on Pareto Method for Gearbox Fault Diagnosis;10
3.1;Abstract;10
3.2;1 Introduction;10
3.3;2 Support Vector Machines (SVMs);13
3.4;3 Vibration Data and Feature Extraction;13
3.4.1;3.1 The CH46 Gearbox;13
3.4.2;3.2 Features Extraction;15
3.5;4 Feature Selection;17
3.5.1;4.1 Pareto Based Feature Selection Method;17
3.5.2;4.2 Selection Criterions;18
3.6;5 Results and Discussion;19
3.7;6 Conclusion;22
3.8;References;22
4;Intelligent Gear Fault Diagnosis in Normal and Non-stationary Conditions Based on Instantaneous Angular Speed, Differential Evolution and Multi-class Support Vector Machine;25
4.1;Abstract;25
4.2;1 Introduction;26
4.3;2 Measuring Principle;27
4.4;3 Test Bench and Experimental Protocol;28
4.5;4 Experimental Part;30
4.5.1;4.1 Feature Extraction;31
4.5.1.1;4.1.1 Signal Analysis (Angular Features Extraction);31
4.5.1.2;4.1.2 Spectral Analysis (Spectra Features Extraction);32
4.5.1.3;4.1.2 Spectral Analysis (Spectra Features Extraction);32
4.5.2;4.2 Feature Vector;34
4.5.3;4.3 Feature Selection by DEFS Algorithm;35
4.5.4;4.4 Classification Procedure;36
4.5.4.1;4.4.1 Support Vector Machine Theory;36
4.5.4.2;4.4.2 Multiclass SVM;38
4.6;5 Classification Results and Discussions;38
4.7;6 Conclusion;40
4.8;Acknowledgments;40
4.9;References;41
5;Effect of Input Data on the Neural Networks Performance Applied in Bearing Fault Diagnosis;43
5.1;Abstract;43
5.2;1 Introduction;43
5.3;2 Background;44
5.3.1;2.1 Rolling Element Bearings;44
5.3.2;2.2 Bearing Fault Diagnosis Technique;45
5.3.3;2.3 Multi-Layer Perceptron (MLP);45
5.4;3 Materials and Methods;46
5.4.1;3.1 Data Acquisition;46
5.4.2;3.2 Preprocessing of Vibration Signals;48
5.4.2.1;3.2.1 Time Domain Indicators;48
5.4.2.2;3.2.2 Frequencies Domain Indicators;48
5.4.3;3.3 Constitution of the Patterns Vector (Networks Input);48
5.4.4;3.4 Choice of the Classes (Networks Output);48
5.4.5;3.5 Data Standardization;49
5.4.6;3.6 The Network Configuration;49
5.5;4 Results and Discussion;49
5.6;5 Conclusion;51
5.7;Acknowledgment;51
5.8;References;51
6;Bearing Diagnostics Using Time-Frequency Filtering and EEMD;53
6.1;Abstract;53
6.2;1 Introduction;53
6.3;2 Time-Frequency Filtering (TFF);54
6.4;3 EMD and EEMD Algorithms;55
6.5;4 Simulation;56
6.6;5 Application to Experimental Data;59
6.7;6 Conclusion;64
6.8;References;64
7;The Time-Frequency Filtering (TFF) Method Used in Early Detection of Gear Faults in Variable Load and Dimensions Defect;65
7.1;Abstract;65
7.2;1 Introduction;65
7.3;2 Time-Frequency Filtering (TFF);67
7.4;3 EMD and EEMD Algorithms;68
7.4.1;3.1 EMD Algorithm;68
7.4.2;3.2 EEMD Algorithm;69
7.5;4 Application;70
7.6;5 Conclusion;75
7.7;References;75
8;Comparison Between Hidden Markov Models and Artificial Neural Networks in the Classification of Bearing Defects;77
8.1;Abstract;77
8.2;1 Introduction;77
8.3;2 Related Works;78
8.4;3 Apparatus and Experimentation;80
8.5;4 Data Analysis and Features Extraction;81
8.6;5 Building Data Sets;82
8.7;6 Application of Hidden Markov Models and Artificial Neural Networks in the Classification of Bearing Defects;83
8.7.1;6.1 Theoretical Background;83
8.7.1.1;6.1.1 HMM;83
8.7.1.2;6.1.2 ANN;83
8.7.2;6.2 Application;83
8.7.2.1;6.2.1 HMM;83
8.7.2.2;6.2.2 ANN;84
8.8;7 Comparison Between HMM and ANN Based Classifiers;84
8.9;8 Conclusion;85
8.10;Acknowledgements;85
8.11;References;85
9;On-line Adaptive Scaling Parameter in Active Disturbance Rejection Controller;88
9.1;Abstract;88
9.2;1 Introduction;88
9.3;2 Description of the System and Road Input;89
9.4;3 Controller Design;90
9.5;4 “?” On-Line Adaptation;90
9.6;5 Results of Simulation;92
9.7;6 Conclusion;94
9.8;References;95
10;Modal Analysis of the Clutch Single Spur Gear Stage System with Eccentricity Defect;96
10.1;Abstract;96
10.2;1 Introduction;96
10.3;2 Numerical Model;97
10.3.1;2.1 Combined Clutch-Transmission Model;97
10.3.2;2.2 Equation of Motions;98
10.3.3;2.3 Modeling of Eccentricity Defect on the Gear System;99
10.4;3 Results and Discussion;99
10.5;4 Conclusion;103
10.6;References;103
11;Estimation of Road Disturbance for a Non Linear Half Car Model Using the Independent Component Analysis;105
11.1;Abstract;105
11.2;1 Introduction;105
11.3;2 Half Car Model;106
11.4;3 Description of the Applied Algorithm: ICA;109
11.5;4 Numerical Results;110
11.6;5 Conclusion;111
11.7;References;111
12;Transfer Path Analysis of Planetary Gear with Mechanical Power Recirculation;113
12.1;Abstract;113
12.2;1 Introduction;113
12.3;2 Description of the Test Bench;114
12.4;3 Numerical Results;116
12.4.1;3.1 Calculation of the Direct Transmissibility Matrix;116
12.4.2;3.2 Operational Response Decomposition;118
12.4.3;3.3 Experimental Setup;118
12.4.4;3.4 Experimental Results;119
12.4.4.1;3.4.1 Global and Direct Transmissibilities;119
12.4.4.2;3.4.2 Operational Response Reconstruction in the Stationary Conditions;121
12.5;4 Conclusion;123
12.6;Acknowledgements;123
12.7;References;123
13;Modeling the Transmission Path Effect in a Planetary Gearbox;125
13.1;Abstract;125
13.2;1 Introduction;125
13.3;2 Origin of the Modulation Phenomenon;126
13.4;3 Mathematical Formulation of the Transmission Path;127
13.5;4 Numerical Simulation;128
13.5.1;4.1 Impact of Each Planet on the Resultant Vibration;129
13.5.2;4.2 Analysis of Numerical Results;129
13.6;5 Conclusion;131
13.7;Acknowledgements;131
13.8;References;131
14;Dynamic Behavior of Spur Gearbox with Elastic Coupling in the Presence of Eccentricity Defect Under Acyclism Regime;132
14.1;Abstract;132
14.2;1 Introduction;132
14.3;2 Dynamic Model;133
14.3.1;2.1 Acyclism Modeling;134
14.3.2;2.2 Eccentricity Modeling;135
14.4;3 Equation of Motion;137
14.5;4 Numerical Results;137
14.6;5 Conclusion;140
14.7;References;141
15;Author Index;142