1. Kalasalingam University
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

2. 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

3. 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

4. MoU with International Universities
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 Saarbrucken, Germany
Centre for Combinatorics, Nankai University, China
Hannam University, South Korea
Soongsil University, South Korea
Technical University of Kosice, The Slovak Republic
Global Associations

5. 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.

6. John Masefield (Poet Laureate) Has come whatever worth man ever knew;
Adventure on, for, from the littlest clue
Has come whatever worth man ever knew;
The next to lighten all men may be you

7. Digital Signal Processing (DSP) and Applications

8. What is DSP Used For?
…And much more!

9. What is DSP?
Digital Signal Processing – the processing or manipulation of signals using digital techniques
Digital Signal Processor
Input Signal
Output Signal
ADC
DAC
Analogue to Digital Converter
Digital to Analogue Converter

10. 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
solution in original way of thinking
transform
solution
in transform
way of
thinking
inverse
transform

11. 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

12. 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  India
Columbus  America
Magellan  world
Nicholas Copernicus
Luther: “fool “
Johannes Kepler

13. Propagation of the Dogma of Circle
Astronomy (disappeared)  reappeared in Physics (eit)  Electrical Engineering (ej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

14. 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 

15. 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

16. Faith vs Reason in Science (contd.)
Fermat conjectured in 1640 that all the Fermat
numbers (22m + 1 ) are prime. In 1732 Euler pointed out that the Fermat number 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).

17. Facts
J. Finlaison’s report to House of Commons, London 1829 (used digital filter)
Many digital filters with excellent properties were existing in 19th 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 1930.
Spread spectrum communication invented by by Hollywood actress Lamarr and composer Antheil. Used by US Navy during Cuba blocade by President Kennedy

18. 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 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.

19. 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 numerical algorithm of our lifetime (Strang, 1994)." (Kent & Read 2002, 61)

20. 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 . . .

21. 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

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

23. Evariste Galois’s work is useful in DSP

24. 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: )

25. 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

26. Signal Classification
Periodic and aperiodic
Determinstic and random
Energy and power
Analog and digital
Type I and Type II (new classification)

27. 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

28. 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.

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

30. Speech Processing

31. Bill Gates and Speech Technology
Microsoft is pushing touchscreen and speech technology to replace keyboards

32. Speech signal “Hood” and TF Analysis

33. Speech Coding – Prediction
Transmit error
s(n) + –
d(n)
d(n) …
A(z)  
se(n) +
sr(n) +
A(z)
se(n)

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

35. A Gamma Ray Spectrum

36. Fourier Transforms of the Spectra

37. (DSP based: <2.5KB core part; 43KB full program)
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

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

39. PET/CT CT PET CT+PET (Siemens in 2011)
General Electric Medical Systems

40. 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

41. DSP Processor: Texas Instruments
fixed-point/ floating point
“Harvard architecture”
separate instruction, data memories
Accumulator
Specialized instruction set
Load and Accumulate
Instruction
Memory
Processor
Data
Memory
Datapath:
Mem
T-Register
Multiplier
P-Register
ALU
Accumulator

42. Fall Detection

43. Nondestructive Evaluation using Barkhausen Noise

44. Barkhausen Noise Testing
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)

45. Barkhausen Noise Testing
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)

46. 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

47. 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

48. 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

49. 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

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

51. 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

52. Randomly Oriented Domains

54. 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

55. 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

56. Barkhausen Noise System

57. Commercial Instrument

58. Magnetizing Curve and Barkhausen Noise Bursts

59. Barkhausen Noise and Stress

60. Barkhausen Noise and Hardness

61. MBN Signal and Associated Parameters

62. Instrumented test specimen used for stresses measurement

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

64. Experiment: MBN Burst from A Stressed Pipe

65. Autopower Spectral Evolution RMS = 8.63

66. Autopower Spectral Evolution RMS = 14.34

67. Autopower Spectral Evolution RMS = 17.04

68. RMS Value vs Relative Time Duration of Domain Movement

69. Experimental Results: MBN signals for different hardness

70. MBN Signal and Spectrogram

71. MBN Signal and Scalogram

72. Please feel free to email me at: KLvkmadan@gmail.com
Thank You