Kalasalingam University, Digital Signal Processing and Applications, Nondestructive Evaluation using Barkhausen Noise

V.K. Madan, PhD

BTech (IITD), PhD (IITB), PDF (U. Sask., Canada) Fellow: IETE, IE (India); LM: INS, IPA, NTSI, ASI, ISTE Senior Professor

Kalasalingam University

Ex:

Scientific Officer (H), Bhabha Atomic Research Centre, Mumbai Professor, Homi Bhabha National Institute , Mumbai Professor, BITS, Pilani Teacher, PhD(Tech) Electronics Engrg, U of Mumbai Research Board Member, Kalasalingam University

KALASALINGAM UNIVERSITY

Kalasalingam Academy of Research and Education (under section 3 of UGC act 1956) Accredited by NAAC with B grade with CGPA of 2.81 on 4 point scale

2

VISION To Be a Centre of Excellence of International Repute in Education and Research MISSION To Produce Technically Competent, Socially Committed Technocrats and Administrators Through Quality Education and Research

3

MoU with International Universities

Global Association s

• Carnegie Mellon University, USA • University of Oklahoma, USA • Ball State University, USA • East Tennessee State University, USA • Georgetown University, USA • University of Applied Sciences, Western Switzerland • Centro De Investigacion Y De Estudios Avanzados Del IPN, Mexico • INM Leibniz-Institute for New Materials gGmbH, H-66123 Saarbrucken, Germany • Centre for Combinatorics, Nankai University, China • Hannam University, South Korea • Soongsil University, South Korea • Technical University of Kosice, The Slovak Republic 4

Science, Technology, Art, Religion, Music … • Earlier: One state scientist like Archimedes, Nobility, Professors, Common people • Newton: Philosophy of Natural Science • Philosophy: An obstinate attempt to think clearly • Disciplines, specialization • Multidisciplinary, synthesis, fusion, merging of tools • Hermann Hesse: The Glass Bead Game (Das Glasperlenspiel) • Inspiration from Leonardo da Vinci: There is no man from whom I can’t learn something • Moral: Keep mind open to all disciplines and try to integrate them with your expertise. Respect the great people but question their work.

John Masefield

(Poet Laureate)

Adventure on, for, from the littlest clue Has come whatever worth man ever knew; The next to lighten all men may be you

Digital Signal Processing (DSP) and Applications

What is DSP Used For?

…And much more!



What is DSP?

Digital Signal Processing

or manipulation of signals using digital techniques – the processing Input Signal ADC Analogue to Digital Converter Digital Signal Processor DAC Digital to Analogue Converter Output Signal

Transforms

• Transforms -- a mathematical conversion from one way of thinking to another to make a problem easier to solve. • Example: Logarithmic transformation

problem in original way of thinking transform solution in transform way of thinking inverse transform solution in original way of thinking

DSP: Applied

• 2012 IEEE Intl. Conf Emerging Signal Processing

Applications (ESPA), Las Vegas (emerging applications)

• 3D technology for gaming, telepresence • Gesture recognition for games and natural user interfaces • Digital photography • 4G wireless • Robotics • Multimedia tablets • SP in automobiles: speech interfaces, cameras • Voice search • SP with multicore processors • IPTV

     

Dogma of Circle



DSP

The Greek Philosopher Plato Claudius Ptolemy (all the phenomena in the sky are produced by uniform and circular motion) Eudoxus: superposition of rotating spheres. Aristotle used upto 54 spheres Claudius Ptolemy replaced spheres by circles    Vasco da Gamma  Columbus  Magellan  world India America Nicholas Copernicus  Luther: “fool “ Johannes Kepler

Propagation of the Dogma of Circle

• Astronomy (disappeared) Physics (e i  t )   reappeared in Electrical Engineering (e j  t ) • Phasor: first used by Lord Raleigh in sound • Phasor: introduced in EE by Oliver Heaviside • Popularized by Kennelly and Steinmetz in USA in early 1900s. Still very important.

• Sinusoids are bread and butter of EEE

Circle: Astronomy to Power System, DSP, Communication Engineering • Power System: Phasor Analysis • DSP: unit circle in the complex plane • Communication Engineering: modulator Modulator or mixer 

Faith vs Reason in Science

• Last 100 years Fourier transforms are being used. Only uses for which the transforms are good are developed. Selective development. However it generated lot of knowledge base.

• Arthur Koestler: The sleepwalkers (challenges the habitual idea of a progressive science) • Fourier transforms: – Don’t converge at discontinuity (Gibbs). Information intensive points: discontinuities.

– requires infinite sinusoidal waves.

– Noncausal: O/p before I/p – Negative frequency

Faith vs Reason in Science

numbers (2 2m

(contd.)

• Fermat conjectured in 1640 that all the Fermat + 1 ) are prime. In 1732 Euler pointed out that the Fermat number 4294967297 was not prime. (

90 years

) (Fermat numbers are useful in DSP) • Minsky and Papert published from MIT in 1969 a book “Perceptron” and wrote "...our intuitive judgment that the extension (to multilayer systems) is sterile“. In simple language it means that multilayer perceptron cannot realize Exclusive-OR gate. The research in neural networks was halted for 10 years until it was proved that their judgement was wrong. (

10 years

).

Facts

• J. Finlaison’s report to House of Commons, London 1829 (used digital filter) • Many digital filters with excellent properties were existing in 19 1930.

th century.

• FFT algorithm existed (1805) before Fourier transform (1822). Rediscovered in 1965.

• Fourier transform remained questionable till a paper by Norbert Wiener from MIT in • Spread spectrum communication invented by by Hollywood actress Lamarr and composer Antheil . Used by US Navy during Cuba blocade by President Kennedy

Fourier Theory • Fourier introduced the idea of representing an arbitrary periodic function as a trigonometric series, eminent mathematicians such as Lagrange resisted it.

• Till 1930 : Fourier theory was useful for analyzing periodic and aperiodic functions, but not for random functions. • Norbert Wiener from MIT in 1930 applied Fourier theory for analyzing random functions. Presently it is known as “Wiener Khinchin theorem'' stating that the power spectrum is the Fourier transform of signal’s autocorrelation function.

Fast FourierTransform (FFT) • C.F. Gauss had written in 1805, 'Experience will teach the user that this method will greatly lessen the tedium of mechanical calculation.' • this method is FFT. It was rediscovered by Cooley and Tukey in 1965.

• "The FFT rediscovery has been called the most important 2002, 61) numerical algorithm of our lifetime (Strang, 1994)." (Kent & Read

A Peep Beyond Fourier Transform • Numerous orthogonal transforms exist other than Fourier transform. Fourier transform is, however, most popular and most widely used compared to any other transform.

• Walsh-Hadamard transform • Number theoretic transform • Hartley transform • Householder transform • and many more . . .

Third Century Chinese Verse by Sun Tzu (useful in Computers) We have things of which we do not know the number, If we count them by

three

, the remainder is 2, If we count them by

five

, the remainder is 3, If we count them by

seven

, the remainder is 2, How many things are there?……..

Moduli: 3, 5, 7 Remainders: 2, 3, 2 Answer: 23

Sanskrit, Vedic Arithematic (useful in computer Science) Multiply: 1 1 1 by 1 1 1 Answer: 1 2 3 2 1 Trick: ascending, descending, symmetry Square: (52) x (52) Answer: 2704 (mental time 5 seconds) Trick: any number 30 to 70 50/2 = 25+2 = 27 and 2x2 = 4

Evariste Galois’s work is useful in DSP

Cochlea: A bank of filters

Human ears do not hear wave-like oscillations, but constant tone Often it is easier to work in the frequency domain (for cochlear animation: http://www.rockefeller.edu/labheads/hudspeth/mov ie06_popup.html

)

Analog, Discrete-time, and Digital Signal y(t) = A sin (2  ft +  ) Analog signal?

Discrete time signal?

Digital signal: t and y(t) are quantized

Signal Classification

• Periodic and aperiodic • Determinstic and random • Energy and power • Analog and digital • Type I and Type II (new classification)

New Classification of Digital Signals: Type I and Type II (Madan et al) Type I and Type II; based on fundamental problems of aliasing and quantization noise (q.n.). The classification has enhanced the scope of DSP in many disciplines: – Type I: aliasing and q.n. are addressed along the abscissa and ordinate respectively – Type II: aliasing and q.n. are addressed along the abscissa

Type I and Type II Signals • Type II: Nuclear spectra like gamma, x ray spectra, population sciences etc.

• “DSP methods widely used for Type I signals, are generally not used for Type II signals.” DSP methods have demonstrated numerous advantages for processing Type II signals,… .” Presently not many Type II signals are processed employing DSP.

DSP Applications Developed • Nuclear Spectral Processing • Power Transformers (Maximum Entropy Spectral Analysis) • Population Sciences • Electric Arcs • Speech Processing • Magnetic Barkhausen Noise

Speech Processing

Bill Gates and Speech Technology

Bill Gates : Microsoft is pushing touchscreen and speech technology to replace keyboards

Speech signal “Hood” and TF Analysis

Speech Coding – Prediction

• Transmit error

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s e

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d

(

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…

d

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s e

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s r

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Gamma Radiation and its Uses • Medical Uses • Academic and Scientific Applications • Industrial Uses • Nuclear Power Plant

A Gamma Ray Spectrum

Fourier Transforms of the Spectra

SAMPO has 25,000 lines of FORTRAN, 10,000 lines of C, and 12,000 lines of assembler ( DSP based: <2.5KB core part; 43KB full program )

IAEA Intercomparison

(about SAMPO and other programs)

“Evidently, therefore success in evaluating these spectra is not so much dependent on the principle of the method used.”

SAMPO is still most popular. It has generated lot of knowledge base, friendly platform, available commercially…

Some common examples where the rationality doen’t prevail: pounds vs. kg Metre vs. feet

PET camera State of the art PET scanners are full-ring systems that completely surround the patient.

PET/CT

CT PET CT+PET (Siemens in 2011)

General Electric Medical Systems

Walsh Convolution

• Arithmetic convolution is “the least successful area” using Walsh functions • Absence of shift theorem • “ Computer processing… one of the best field of Walsh ” functions

DSP Processor: Texas Instruments

 fixed-point/ floating point  “Harvard architecture”  separate instruction, data memories

Processor

 Accumulator

Datapath:

 Specialized instruction set  Load and Accumulate

Mem Instruction Memory Data Memory T-Register Multiplier P-Register ALU Accumulator

Fall Detection

Nondestructive Evaluation using Barkhausen Noise

NDE (NDT) Methods • Ultrasonic Testing • Magnetic-Particle testing • Liquid Penetrant Testing • Visual/Optical Testing • Eddy Current Testing • Radiographic Testing • Low Cohorence Interferometry • Acoustic Emission Testing • Barkhausen Noise Testing –Acoustic –Magnetic (MBN)

NDE (NDT) Methods • Ultrasonic Testing • Magnetic-Particle testing • Liquid Penetrant Testing • Visual/Optical Testing • Eddy Current Testing • Radiographic Testing • Low Cohorence Interferometry • Acoustic Emission Testing • Barkhausen Noise Testing –Acoustic –Magnetic (MBN)

MBN Applications • • • Residual stress in steel the level of carburisation(the increase of carbon content) Remaining-life estimates of critical component in operational plant, for example in thermal power stations and the petrochemical industry

MBN Applications

• surface treatments like grinding, shot peening, carburizing and induction hardening modify stress and microstructure.

• dynamic processes like creep and fatigue involve changes in stress and microstructure • Barkhausen noise method is useful for the above

MBN Applications • Barkhausen noise analysis is uesful for surface defects, processes and surface treatments that may involve changes in both stresses and microstructure like: – Detection of grinding defects and grinding process control – Detecting surface defects through Cr-coating – Evaluation of shot-peening effect in steel – Measurement of residual surface stresses in steel mill rolls and steel sheet

MBN Applications • Residual stress, retained austenite, grinding burn and heat treat defect detection: • grinding burns • heat treat defects • hardness changes • residual stresses • retained austenite contents

MBN Applications

Controlling the quality of: • grinding, • heat treating, • shot peening or • machining of • camshafts, crankshafts, ball bearings, gears, valves, etc.

Barkhausen Noise • Professor Heinrich Barkhausen in 1919 • AKA: Magnetoelastic or Micromagnetic technique • magnetic field is applied to a ferromagnetic sample • Ferromagnetic materials: domains, separated from one another by boundaries known as domain walls

Randomly Oriented Domains

Barkhausen Noise

• • • • • AC magnetic fields will cause domain walls to move back and forth.

Coil of conducting wire is placed near the sample while the domain wall moves, the resulting change in magnetization will induce an electrical pulse in the coil.

Magnetization process: hysteresis curve. Abrupt steps caused when the magnetic domains move under an applied magnetic field. When the electrical pulses by domain movements generate a noise-like signal called Barkhausen noise

Magnetoelastic Interaction

• • • • • Barkhausen Noise Signal measures elastic stresses magnetoelastic interaction: elastic properties interacting with domain structure and magnetic properties of material.

compressive stresses will decrease the intensity of Barkhausen noise.

tensile stresses increase the intensity of Barkhausen noise. the intensity of Barkhausen noise helps determine the amount of residual stress

Barkhausen Noise System

Commercial Instrument

Magnetizing Curve and Barkhausen Noise Bursts

Barkhausen Noise and Stress

Barkhausen Noise and Hardness

MBN Signal and Associated Parameters

Instrumented test specimen used for stresses measurement

INSPECTION FOR GRINDER BURN DETECTION IN GROUND CRANKSHAFT SURFACES (Cummins Engine Company)

Experiment: MBN Burst from A Stressed Pipe

Autopower Spectral Evolution RMS = 8.63

Autopower Spectral Evolution RMS = 14.34

Autopower Spectral Evolution RMS = 17.04

RMS Value vs Relative Time Duration of Domain Movement

Experimental Results: MBN signals for different hardness 1 0 -1 0 10 20 30 time(ms) 41.2 HRc 40 50 1 0 -1 0 10 53.6 HRc 20 30 time(ms) 37.2 HRc 40 50 1 0 -1 0 10 20 30 time(ms) 40 50 43.4 HRc 1 0 -1 0 10 20 30 time(ms) 38.5 HRc 40 50 1 0 -1 0 10 20 30 time(ms) 40 50

MBN Signal and Spectrogram

MBN Signal and Scalogram

Please feel free to email me at: [email protected]