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Advances in Condition Monitoring of Machinery in Non-Stationary Operations

LNME: ADVS IN CNDTN MNTRNG OF MACH NON-STATIONARY OPS

Engineering

Mathematics & Science

Gt Product Group

Binding Format

Marketing Imprint Name

B2B GT

CL Carton Count

Imprint Name

B2B & B2C

This book presents the processing of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13), which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition. The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to point out the signal content that is related to the state of the monitored component particularly in non-stationary conditions.

POST SECONDARY FOUR YEAR

COLFR

COLJR

COLSO

COLSR

Duration

Duration Unit Of Measure

Transaction Type

Cover Page.
Half Title Page.
Title Page.
Copyright Page.
Preface.
Contents.
1: Keynote Speeches.
2: Dynamical Behavior of Rotating Machinery in Non-Stationary Conditions: Simulation and Experimental Results.
3: Speed Transform, a New Time-Varying Frequency Analysis Technique.
4: Smart: Integrating Human Safety Risk Assessment with Asset Integrity.
5: Rolling Bearing Diagnostics.
6: Incipient Fault Detection in Bearings through the Use of WPT Energy and Neural Networks.
7: Bearing Fault Detection Using Beamforming Technique and Artificial Neural Networks.
8: HOS Analysis of Measured Vibration Data on Rotating Machines with Different Simulated Faults.
9: Signal Complexity and Gaussian Process Models Approach for Bearing Remaining Useful Life Estimation.
10: Estimating Rolling Element Bearing Stiffness under Different Operational Conditions through Modal Analysis.
11: Parametric Analysis Focused on Non-Linear Forces in Oil-Film Journal Bearings.
12: Diagnostic of Rolling Element Bearings with Envelope Analysis in Non-Stationary Conditions.
13: Bearing Fault Identification Using Watershed-Based Thresholding Method.
14: Envelope Cepstrum Based Method for Rolling Bearing Diagnostics.
15: Condition Monitoring of Rotating Machines Using Vibration and Bearing Temperature Measurements.
16: A Comparative Analysis of Detecting Bearing Fault, Using Infrared Thermography, Vibration Analysis and Air-Borne Sound.
17: Monitoring Lathe Tool&#x0027;s Wear Condition by Acoustic Emission Technology.
18: Modelling of Dynamics and Fault in Gear Systems.
19: Joint Power-Speed Representation of Vibration Features. Application to Wind Turbine Planetary Gearbox.
20: Parallel Autoregressive Modeling as a Tool for Diagnosing Localized Gear Tooth Faults.
21: Modulation Sidebands of Planetary Gear Set.
22: A Novel Method of Gearbox Health Vibration Monitoring Using Empirical Mode Decomposition.
23: Artificial Immune Systems for Data Classification in Planetary Gearboxes Condition Monitoring.
24: Gearbox Condition Monitoring Procedures.
25: Vibration Monitoring of Winch Epicyclic Gearboxes Using Cyclostationarity and Autoregressive Signal Model.
26: Gear Parameter Identification in Wind Turbines Using Diagnostic Analysis of Gearbox Vibration Signals.
27: Phase Monitoring by esprit with Sliding Window and Hilbert Transform for Early Detection of Gear Cracks.
28: Signal Processing for Machine Condition Monitoring.
29: Performance of Time Domain Indicators for Gear Tooth Root Crack Detection and Their Noise-Sensitivity.
30: Cepstral Removal of Periodic Spectral Components from Time Signals.
31: The Local Maxima Method for Enhancement of Time-Frequency Map.
32: Reconstruction of the Instantaneous Angular Speed Variations Caused by a Spall Defect on a Rolling Bearing Outer Ring Correlated with the Length of the Defect.
33: Instantaneous Angular Speed: Encoder-Counter Estimation Compared with Vibration Data.
34: Non-Linear Geometric Approach to Friction Estimation and Compensation.
35: Empirical Mode Decomposition of Acoustic Emission for Early Detection of Bearing Defects.
36: Signal Processing Diagnostic Tool for Rolling Element Bearings Using EMD and MED.
37: Influence of Stopping Criterion for Sifting Process of Empirical Mode Decomposition (EMD) on Roller Bearing Fault Diagnosis.
38: On the Use of Vibration Signal Analysis for Industrial Quality Control: Part I.
39: On the Use of Vibration Signal Analysis for Industrial Quality Control: Part II.
40: Experimental and Numerical Modeling of Machine Dynamics.
41: Non-Clustering Method for Automatic Selection of Machine Operational States.
42: Simple Relations for Estimating the Unknown Functions of Incomplete Experimental Spectral and Correlation Response Matrices.
43: Condition Monitoring under Non-Stationary Operating Conditions Using Time&#x2013;Frequency Representation-Based Dynamic Features.
44: Comparison of Torsional Vibration Measurement Techniques.
45: Numerical Investigations on the Accuracy of an Automated Modal Identification Technique.
46: The Principles of Operation and Equipment Design in Modelling of Separating-System Dynamics.
47: Test Bench for the Analysis of Dynamic Behavior of Planetary Gear Transmissions.
48: A Novel Gear Test Rig with Adjustable Shaft Compliance and Misalignments Part I: Design.
49: A Novel Gear Test Rig with Adjustable Shaft Compliance and Misalignments. Part II: Instrumentation.
50: A Distributed Control System for a Field of Spin-Elevation Heliostats.
51: Mechanical Systems Diagnostics.
52: Preliminary Investigations on Automatic Detection of Leaks in Water Distribution Networks by Means of Vibration Monitoring.
53: An Application of Statistical Tools in the Identification of the Transient Vibrations of Bucket-Wheel Excavators under Random Loads.
54: Effectiveness of Advanced Vibration Processing Techniques for Fault Detection in Heavy Duty Wheels.
55: Chatter Marks and Vibration Analysis in a S6-High Cold Rolling Mill.
56: Advanced Testing of Heavy Duty Gearboxes in Non-Stationary Operational Conditions.
57: Spatial Acceleration Modulus for Rolling Elements Bearing Diagnostics.
58: Artificial Neural Networks-Based Decoupling Approach in the Vector Control Block of the Single-Phase Induction Machine.
59: Fault Identification on Electrical Machines Based on Experimental Analysis.
60: Fault Diagnosis in Induction Motor Using Motor&#x0027;s Residual Stator Current Signature Analysis.
61: Advanced Data Mining Techniques for Power Performance Verification of an On-Shore Wind Farm.
62: Virtual Assessment of Damage Detection Techniques for Operational Wind Turbine.
63: Data-Driven Wind Turbine Power Generation Performance Assessment Using ni Labviews Watchdog Agent Toolkit.
64: Art-2 Artificial Neural Networks Applications for Classification of Vibration Signals and Operational States of Wind Turbines for Intelligent Monitoring.
65: Software Applications for Wind Turbine Vibrations Analysis.
66: Experimental Characterization of Chatter in Band Sawing.

Advances in Condition Monitoring of Machinery in Non-Stationary Operations.css-1p8rvzy{position:absolute;padding-left:8px;}

Advances in Condition Monitoring of Machinery in Non-Stationary Operations