Condition Monitoring and Faults Diagnosis of Induction Motors : Electrical Signature Analysis

The book covers various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, faults for induction motors failures, new trends in condition monitoring, and the fault identification process using motor currents electrical signature analysis. It aims to present a new non-invasive and non-intrusive condition monitoring system, which has the capability to detect various defects in induction motor at incipient stages within an arbitrary noise conditions. The performance of the developed system has been analyzed theoretically and experimentally under various loading conditions of the motor. Covers current and new approaches applied to fault diagnosis and condition monitoring. Integrates concepts and practical implementation of electrical signature analysis. Utilizes LabVIEW tool for condition monitoring problems. Incorporates real-world case studies. Paves way a technology potentially for prescriptive maintenance via IIoT. Content: Cover Half Title Title Page Copyright Page Dedication Table of Contents Preface Authors List of Abbreviations Nomenclatures Chapter 1: Introduction to Condition Monitoring of Electrical Machines 1.1 Background 1.2 Condition Monitoring 1.3 Present Issues on CM 1.4 Outlines of the Book Chapter 2: Background on Condition Monitoring Techniques 2.1 Introduction 2.2 Structure of the Induction Motor 2.3 Various Faults Types of the Induction Motor 2.3.1 Mechanical Defects 2.3.1.1 Bearings Defects 2.3.1.2 Air-Gap Eccentricity Defects 2.3.1.3 Abnormalities in Mechanical Transmission System2.3.2 Electrical Defects 2.3.2.1 Stator Winding Defects 2.3.2.2 Rotor Defects 2.4 Invasive Condition Monitoring Techniques 2.4.1 Acoustic Emission 2.4.2 Thermal Monitoring 2.4.3 Sound Monitoring 2.4.4 Chemical Analysis 2.4.5 Vibration Analysis 2.5 Summary Chapter 3: Noninvasive Methods for Motor Fault Diagnosis 3.1 Introduction 3.2 MCSA for Bearings Localized Faults 3.3 MCSA for Gear Faults 3.4 IPA for Bearings Localized Faults 3.5 Impact of Environment Noise on MCSA and IPA-Based Fault Detection 3.6 PVA for Bearings Localized Faults3.7 Noninvasive Methods for Diagnosis of Bearings Distributed Faults 3.8 Condition Monitoring Issues 3.9 Summary Chapter 4: Design and Development of a Noninvasive Condition Monitoring System 4.1 Introduction 4.2 Design and Development of Test Rig for Noninvasive Condition Monitoring System 4.2.1 Test Rig Base 4.2.2 Gear Box under Test 4.2.2.1 Creation of Gear Defects 4.2.2.2 Calculation of Gear Characteristic Defect Frequencies 4.2.3 Brake 4.2.4 Mechanical Coupling 4.2.5 Bearing under Test 4.2.5.1 Creation of Bearing Localized Defects 4.2.5.2 Calculation of Characteristic Defect Frequencies Related to Bearing Localized Defects4.2.6 Induction Motor Connection Scheme 4.2.7 DAQ and Processing 4.3 Design of LabVIEW Program 4.4 Adaptive Threshold Design for IPA 4.4.1 No-Load Conditions 4.4.2 Medium-Load Conditions 4.4.3 Full-Load Conditions 4.5 Development of Noninvasive CM Method for Bearing Distributed Faults 4.6 Summary Chapter 5: Faults Analysis and Evaluations via IPA and PVA Methods 5.1 Introduction 5.2 Analysis of Gear Faults 5.3 Analysis of Bearing Localized Faults 5.3.1 Analysis of Bearings Outer Race Defects5.3.2 Analysis of Bearing Inner Race Defects 5.3.3 Threshold Design for Variable Frequency Drive (VFD) Operation of the Motor 5.4 Comparison of the Proposed Fault Diagnosis Scheme with previously used Schemes 5.5 Park Vector Analysis for the Diagnosis of Mechanical Faults in Induction Motor 5.5.1 Park Vector Analysis of Gear Defects 5.5.2 Park Vector Analysis of Bearing Localized Defects 5.5.3 Park Vector Analysis of Bearing Distributed Defects 5.6 Analysis of IPA Technique 5.7 Summary The purpose of this book is to explore developments in the condition monitoring and diagnostic approach of induction motors using electrical signature analysis of motor currents. It covers various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, faults for induction motors failures, new trends in condition monitoring, and pays special attention to the fault identification process using motor currents electrical signature analysis. The book presents a new non-invasive and non-intrusive condition monitoring system, which has the capability to detect various defects in induction motor at incipient stages within an arbitrary noise conditions. An adaptive threshold has been designed to deal with signal noise ambiguities for decision-making on the existence of small fault signatures. The performance of the developed system has been analyzed theoretically and experimentally under various loading conditions of the motor Provided by publisher The book explores developments in the condition monitoring and diagnostic of induction motors using electrical signature analysis. It presents noninvasive on-line condition monitoring system in detecting induction motors’ bearings and gear faults at early stages within arbitrary noise conditions.