1st Edition

Machinery Condition Monitoring Principles and Practices

By Amiya Ranjan Mohanty Copyright 2015
    282 Pages
    by CRC Press

    282 Pages 181 B/W Illustrations
    by CRC Press

    Find the Fault in the Machines

    Drawing on the author’s more than two decades of experience with machinery condition monitoring and consulting for industries in India and abroad, Machinery Condition Monitoring: Principles and Practices introduces the practicing engineer to the techniques used to effectively detect and diagnose faults in machines. Providing the working principle behind the instruments, the important elements of machines as well as the technique to understand their conditions, this text presents every available method of machine fault detection occurring in machines in general, and rotating machines in particular.

    A Single-Source Solution for Practice Machinery Conditioning Monitoring

    Since vibration is one of the most widely used fault detection techniques, the book offers an assessment of vibration analysis and rotor-dynamics. It also covers the techniques of wear and debris analysis, and motor current signature analysis to detect faults in rotating mechanical systems as well as thermography, the nondestructive test NDT techniques (ultrasonics and radiography), and additional methods. The author includes relevant case studies from his own experience spanning over the past 20 years, and detailing practical fault diagnosis exercises involving various industries ranging from steel and cement plants to gas turbine driven frigates. While mathematics is kept to a minimum, he also provides worked examples and MATLAB® codes.

    This book contains 15 chapters and provides topical information that includes:

    • A brief overview of the maintenance techniques
    • Fundamentals of machinery vibration and rotor dynamics
    • Basics of signal processing and instrumentation, which are essential for monitoring the health of machines
    • Requirements of vibration monitoring and noise monitoring
    • Electrical machinery faults
    • Thermography for condition monitoring
    • Techniques of wear debris analysis and some of the nondestructive test (NDT) techniques for condition monitoring like ultrasonics and radiography
    • Machine tool condition monitoring
    • Engineering failure analysis
    • Several case studies, mostly on failure analysis, from the author’s consulting experience

    Machinery Condition Monitoring: Principles and Practices presents the latest techniques in fault diagnosis and prognosis, provides many real-life practical examples, and empowers you to diagnose the faults in machines all on your own.


    Machinery Condition Monitoring

    Present Status

    Fault Prognosis

    Future Needs

    Principles of Maintenance


    Reactive Maintenance

    Preventive Maintenance

    Predictive Maintenance

    Enterprise Resource Planning

    Bath Tub Curve

    Failure Modes Effects and Criticality Analysis (FMECA)

    Fundamentals of Machinery Vibration


    Single Degree-of-Freedom Motion

    Forced Vibration Response

    Base Excitation

    Force Transmissibility and Vibration Isolation

    Tuned Vibration Absorber

    Unbalanced Response

    Characteristics of Vibrating Systems

    Vibration of Continuous Systems

    Mode Shapes and Operational Deflection Shapes

    Experimental Modal Analysis



    Simple Rigid Rotor-Disc System

    Unbalance Response and Critical Speed

    Journal Bearings

    Oil Whirl and Oil Whip

    Squeeze Film Dampers

    Condition Monitoring in Large Rotor Systems

    Digital Signal Processing


    Classification of Signals

    Signal Analysis

    Frequency Domain Signal Analysis

    Fundamentals of Fast Fourier Transform

    Computer-Aided Data Acquisition

    Signal Conditioning

    Signal Demodulation

    Cepstrum Analysis




    Measurement Standards

    Measurement Errors

    Calibration Principles

    Static and Dynamic Measurements

    Frequency Response

    Dynamic Range

    Basic Measuring Equipment


    Force Measurements

    Rotational Speed

    Noise Measurements

    Temperature Measurements

    Laser-Based Measurements

    Current Measurements

    Chemical Composition Measurement

    Ultrasonic Thickness Measurement

    Data Recorders

    Vibration Monitoring

    Principles of Vibration Monitoring

    Misalignment Detection

    Eccentricity Detection

    Cracked Shaft

    Bowed and Bent Shaft

    Unbalanced Shaft



    Bearing Defects

    Gear Fault

    Faults in Fluid Machines

    Noise Monitoring


    Acoustical Terminology

    Noise Sources

    Sound Fields

    Anechoic Chamber

    Reverberation Chamber

    Noise Measurements

    Noise Source Identification

    Electrical Machinery Faults


    Construction of an Electric Motor

    Faults in Electric Motor

    Fault Detection in Electric Motors

    MCSA for Fault Detection in Electrical Motors

    Instrumentation for Motor Current Signature Analysis

    Fault Detection in Mechanical Systems by MCSA

    MCSA for Fault Detection in any Rotating Machine

    Fault Detection in Power Supply Transformers

    Fault Detection in Switchgear Devices



    Thermal Imaging Devices

    Use of IR Camera

    Industrial Applications of Thermography

    Applications of Thermography in Condition Monitoring

    Wear Debris Analysis


    Mechanisms of Wear

    Detection of Wear Particles

    Common Wear Materials

    Oil Sampling Technique

    Oil Analysis

    Limits of Oil Analysis

    Other Methods in Condition Monitoring


    Eddy Current Testing

    Ultrasonic Testing


    Acoustic Emission

    Machine Tool Condition Monitoring


    Tool Wear

    Sensor Fusion in Tool Condition Monitoring

    Sensors for Tool Condition Monitoring

    A Tool Condition Monitoring System

    Other Manufacturing Operations

    Engineering Failure Analysis


    Overview of Failure Analysis

    Failure Modes

    Failure Analysis

    Failure Analysis Sampling Guide

    Case Studies


    Bend Pulley Failure Analysis

    Root Cause Analysis of Torsion Shaft Failure in a Cement Plant

    Failure Analysis of a Conveyor System Support Structure

    Vibration Measurements on a Motor-Multistage Gearbox Drive Set





    Amiya R. Mohanty has been a faculty member at the Indian Institute of Technology Kharagpur, India, since 1996, and is currently a professor of mechanical engineering. He has a B.ScEngg (Hons) in mechanical engineering from the National Institute of Technology, Rourkela. He holds a master’s degree in machine design specialization from the Indian Institute of Technology, Kharagpur, and a PhD in the area of noise control from the University of Kentucky in the United States. Prof. Mohanty is a fellow of the Acoustical Society of India. He has consulted more than 50 companies, and published more than 100 journal articles.

    "This book brings together condition monitoring content in a single text, a definite improvement over the single discipline-based texts that are currently on the market. The approachable writing style and limited use of equations make the text desirable reading for the practitioner, not just the academic reader. …The signal processing sections provide a succinct and effective overview to a subject matter that baffles the typical mechanical engineering or engineering technology student. The examples focus on real data and how to set up DSP for good practical results."
    —Nancy L. Denton, Purdue University, West Lafayette, Indiana, USA

    "The author presents an unbiased coverage of signal processing and instrumentation, without unwarranted focus on any particular technique, process, instrument or piece of equipment. …This work is obviously based on extensive knowledge and experience as an engineering researcher and consultant. …Like the author, I have struggled to find one suitable resource book on this broad subject. In my opinion, this book will solve that problem for a significant number of instructors as well as practitioners of machine condition monitoring."
    —Chris Mechefske, Queen’s University, Ontario, Canada