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Kalasalingam University, Digital Signal Processing and Applications, Nondestructive Evaluation using Barkhausen Noise V.K. Madan, PhD BTech (IITD), PhD.

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Presentation on theme: "Kalasalingam University, Digital Signal Processing and Applications, Nondestructive Evaluation using Barkhausen Noise V.K. Madan, PhD BTech (IITD), PhD."— Presentation transcript:


2 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

3 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

4 To Be a Centre of Excellence of International Repute in Education and Research To Produce Technically Competent, Socially Committed Technocrats and Administrators Through Quality Education and Research MISSION VISION 3

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

6 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 cant 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.

7 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

8 Digital Signal Processing (DSP) and Applications

9 What is DSP Used For? …And much more!

10 What is DSP? Digital Signal Processing – the processing or manipulation of signals using digital techniques ADCDAC Digital Signal Processor Analogue to Digital Converter Digital to Analogue Converter Input Signal Output Signal

11 Transforms Transforms -- a mathematical conversion from one way of thinking to another to make a problem easier to solve. Example: Logarithmic transformation transform solution in transform way of thinking inverse transform solution in original way of thinking problem in original way of thinking

12 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

13 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

14 Propagation of the Dogma of Circle Astronomy (disappeared) reappeared in Physics (e i t ) 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

15 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

16 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: –Dont converge at discontinuity (Gibbs). Information intensive points: discontinuities. –requires infinite sinusoidal waves. –Noncausal: O/p before I/p –Negative frequency

17 Faith vs Reason in Science (contd.) Fermat conjectured in 1640 that all the Fermat numbers (2 2 m + 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 ).

18 Facts J. Finlaisons report to House of Commons, London 1829 (used digital filter) Many digital filters with excellent properties were existing in 19 th century. FFT algorithm existed (1805) before Fourier transform (1822). Rediscovered in 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

19 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 signals autocorrelation function.

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

21 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...

22 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

23 Sanskrit, Vedic Arithematic (useful in computer Science) Multiply: by Answer: 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

24 Evariste Galoiss work is useful in DSP

25 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: ie06_popup.html ) ie06_popup.html

26 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

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

28 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

29 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.

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

31 Speech Processing

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

33 Speech signal Hood and TF Analysis

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

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

36 A Gamma Ray Spectrum

37 Fourier Transforms of the Spectra

38 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 doent prevail: pounds vs. kg Metre vs. feet

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

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

41 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

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

43 Fall Detection

44 Nondestructive Evaluation using Barkhausen Noise

45 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 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)

47 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

48 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

49 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

50 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

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

52 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

53 Randomly Oriented Domains


55 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

56 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

57 Barkhausen Noise System

58 Commercial Instrument

59 Magnetizing Curve and Barkhausen Noise Bursts

60 Barkhausen Noise and Stress

61 Barkhausen Noise and Hardness

62 MBN Signal and Associated Parameters

63 Instrumented test specimen used for stresses measurement


65 Experiment: MBN Burst from A Stressed Pipe

66 Autopower Spectral Evolution RMS = 8.63

67 Autopower Spectral Evolution RMS = 14.34

68 Autopower Spectral Evolution RMS = 17.04

69 RMS Value vs Relative Time Duration of Domain Movement

70 Experimental Results: MBN signals for different hardness

71 MBN Signal and Spectrogram

72 MBN Signal and Scalogram

73 Please feel free to me at:

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