lesson 2 digital data acquisition and data processing
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Digital data acquisition and processing are important for nondestructive evaluation (NDE). Data acquisition is needed to obtain quantitative information from test specimens in complex field environments. Data analysis techniques like noise reduction, feature extraction, and multi-parameter discrimination can then be used to interpret the data. Proper data acquisition, digital signal processing algorithms, and discrimination methods now allow NDE procedures to be automated and problems previously considered unsolvable to be addressed.
![Introduction To Linear Systems
Signals
x(t)
t
Continuous-Time Signal
Discrete-Time Signal
x[n]
x(t)
Input
y(t)
Output
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Input
y[n]
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1.5
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Continuous-Time System Discrete-Time System](https://image.slidesharecdn.com/2lesson2digitaldataacquisitionanddataprocessing-150930173943-lva1-app6891/85/lesson-2-digital-data-acquisition-and-data-processing-7-320.jpg)
![If x1[n] y1[n]
x2[n] y2[n]
Linearity ax1[n] + bx2[n] ay1[n] + by2[n]
Similarly, ax1(t) + bx2(t) ay1(t) + by2(t)
Properties of Systems
Linearity
x[n]
x(t)
y[n]
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lesson 2 digital data acquisition and data processing
- 1. Digital Data Acquisition and Processing for Nondestructive Evaluation Prof. Krishnan Balasubramaniam Professor of Mechanical Engineering and Head of Centre for Nondestructive Evaluation Department of Mechanical Engineering, IIT Chennai 600 036 balas@iitm.ac.in Lesson 2: Advanced Nondestructive Evaluation
- 2. Why Data Acquistion ? • Complex specifications leads to difficulty in decision making. • Field environment requires un-biased, quick decisions. • Seeing is sometimes deceiving. • Quantitative information is essential. • Degree of automation is process and product dependent.
- 3. Why Data Analysis ? • Reduce Data Volume • Noise Reduction • Feature Extraction for Discrimination Analysis • Multi-facet approach to data interpretation (time, frequency,…domains)
- 4. Nondestructive Evaluation Excitation Source Test Specimen Signal Conditioning Inverse Model Input Transducer Output Transducer
- 5. Systems Based Approaches Signal Conditioning Output Transducer Response Characterization Results Signal Conditioning Sampling and Quantization Signal Enhancement Signal Restoration Inverse Model
- 6. Signal Classification • Analog Digital -4 -3 -2 -1 0 1 2 3 4 1 2 3 4 5 6 7 8 9 -4 -3 -2 -1 0 1 2 3 4 1 2 3 4 5 6 7 8 9
- 7. Introduction To Linear Systems Signals x(t) t Continuous-Time Signal Discrete-Time Signal x[n] x(t) Input y(t) Output x[n] Input y[n] Output 1 2 1 3 1.5 n 0 1 2 3 4 Continuous-Time System Discrete-Time System
- 8. If x1[n] y1[n] x2[n] y2[n] Linearity ax1[n] + bx2[n] ay1[n] + by2[n] Similarly, ax1(t) + bx2(t) ay1(t) + by2(t) Properties of Systems Linearity x[n] x(t) y[n] y(t)
- 9. Types of Data • Transient 1 dimensional Signals • Spatially Distributed-Time Signals • Static Images (photos) • Dynamic Images (movies)
- 10. Signal Domains • Time/Spatial Domain • Frequency Domain (Amplitude) • Frequency Domain (Phase) • Time (Space)-Frequency Domain (Wavelets, STFT) • Transfer Function Domains
- 11. Digital Signal Analysis • Acquire digital data using DAQ. • Process Data for Noise Reduction. • Extract Features • Multi-parameter Discrimination. • Damage Estimation. • Damage Reporting
- 13. DAQ Hardware • Analog to Digital Convertors – Ni 5102/5112 – up to 2.5 GHz. Data Aq Boards – DAQ Boards – Slow (1-1 MHz) – DSO – Agilent, Tektronics • Frame Grabbers
- 14. Image Grabbers
- 15. Triggering • Allows you to efficiently capture short- duration and high-speed events by eliminating the need to continuously acquire data while waiting for the event to occur • Usually done using a voltage signal input. • The Trigger level and +/- values are key. • Both analog and digital triggers are possible.
- 19. Speed of Acquisition • Images of a moving toy motorcycle taken with a progressive scan camera using exposure times of 33 ms, 10 ms, and 1 ms, respectively
- 27. Nyquist Criterion SR at least = 2*fmax
- 32. Digitization Basics • Horizontal Resolution (Sampling 100 kHz.) • Vertical Resolution (Bits =16 bits) • Amplitude Range (+10V to –10V) • Gain (10 dB) • Multiplexing • Effective bits Rv = 20/216 = 3.05* 10-4V Rh = 1/100*103=10-5s
- 33. Delays and Offsets and ….. • DC Bias Offset • Trigger Delay • Pre-trigger • Equivalent Time Sampling for stationary signals
- 34. Interfaces • RS-232 • RS-170 • IEEE 488.2 GPIB • IEEE 1394 • PCI bus Analog Cameras Parallel Digital Cameras Camera Link Cameras IEEE-1394 Cameras Data Rate Slow Fast Fast Slow Spatial Resolution Low High High Medium Functionality Simple and easy Advanced Advanced Simple and easy Pixel Depth 8-bit to 10-bit Up to 16-bit Up to 16-bit Typically 8-bit Cabling Simple BNC cabling Thicker, custom cabling Simple, standard cabling Simple, standard cabling USB 2.0 RJ 45 PCIe
- 37. Time Frequency • Fourier Transform F(t) = aicos(wi) • Fast Fourier Transform (FFT) – Complex Operation • Discrete Fast Fourier Transform (DFFT)
- 38. Time-Freq. Paradox • A classic trade-off. • High resolution in Time – Poor resolution in Freq. – vice versa. • New time-freq. Analysis such as wavelets allow a more balanced approach – SIMULTANEOUSLY. EXAMPLE
- 39. Data Reduction • Fourier Domain • JPEG • MPEG • CODEC • WT • ……. EXAMPLE
- 40. NOISE Reduction • SNR improvement • Filtering • Time Averaging • Spatial Averaging • Split Spectrum Processing • Wide Spectrum Processing EXAMPLE
- 41. Median Filtering RAW DATA MEDIAN FILTERED
- 44. Filte
- 45. Feature Extraction • Time Domain Features – Peak to Peak Amplitude, +Peak/-Peak, Pulse Duration, ……….. • Envelope Domain Features – Energy, Skewness, Kurtosis ,……. • Frequency Domain Features – Peak Frequency, Mag of Peak Freq., Slope of Phase Spectrum…. EXAMPLE
- 46. Multiple Domains The figure below shows the RF signal and the Amplitude Spectrum. Controls such as Zeropadding, Undersampling, phase wrap/unwrap, window type, are provided. The signal can be windowed by dragging the ends of the red bar over the RF signal.
- 47. Multiple Domains The figure below shows the Envelope of the RF signal and the Phase Spectrum. It is possible to analyze several signal simultaneously by using data name patterns using wildcard (*).
- 48. Feature Extraction The extracted features are imaged here using a intensity plot. Each sample is displayed separately and the selector can be used to dynamically change the feature type. The histogram is also provided for the 5 samples. The color bar and the # of bins can also be dynamically changed. Mean and Standard deviation are provided for each sample.
- 49. Discrimination Analysis It can be observed by looking at the two feature scatter plot, that the samples 1 and 2 are clustered near the origin (0,0) location while the Samples 3 and 4 are at relatively large distance from the origin. Y-Feature X-Feature
- 50. Some Applications • Find the hidden echo and reduce dead zone effect. ` • Find thickness of thin coatings/structures in frequency domain • Find Grain Characteristics from noise data analysis. • Discrimination between defect types. • Computer Aided Tomography EXAMPLE EXAMPLE EXAMPLE
- 51. Defect Discrimination Extraction of Signal Shape will allow for discrimination between defect types.
- 52. Digital Industrial Laminography Ewert, Redmer, BAM-VIII.3 Camera trip through the object: 3D- reconstruction of the crack range after numeric filtering. Reconstruction from the line scan measurements at 180 kV Mechanized Weld Inspection by Tomosynthesis from 5 Projections 3D Representation
- 53. Summary • Data Acquisition is the single most important step in an NDE procedure. • Good Data Acquisition, Data Archiving, Digital Signal Processing, Discrimination Algorithms are all now feasible with low cost hardware and software. • Good DAQ is a combination of hardware, software, and settings, and the data is only as good as the weakest link in this chain. • Signal Analysis solves problems, previously declared un-solvable. • Signal Analysis will not fully compensate for poor data acquisition since new information cannot be created.