Diagnostic Signal Processing

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Mathematics

Synopsis:

The course is devoted to modern techniques of the analog and digital signal processing used in physics, measurements and information science. Basic signal transforms and their discrete equivalents are explained to describe signals and their transfer in different representations. Practical training is based on MATLAB software with Signal and Wavelet Toolboxes.

Requirements:

Basic courses in mathematical analysis in real and complex range, general courses in physics, informatics, and mathematical statistics within the scope of first 3 years study at FNSPE CTU in Prague.

Syllabus of lectures:

1. Methods and signals in Nondestructive (non-invasive) Testing, Evaluation and Diagnostics (ultrasonic, acoustic, electromagnetic, optical, radiation, mechanical). 2. Digital systems and techniques in diagnostics (nuclear sciences, transport, civil engineering, medicine). 3. Measurement devices and sensors. Principles of various detectors. Mathematical fundamentals of signal sampling. Computerized data acquisition and process control Analog-Digital converters, digital filters, oscilloscopes, signal generators, amplifiers, spectrometers. 4. Signal preprocessing and recording (amplification, filtration, parameterization, envelope analysis, data transfer and storage). Methods of diagnostic data evaluation. 5. Linear and nonlinear systems. Transfer function and impulse response. Nonlinear methods, time reversal algorithms, tomography. 6. Measurement and processing of deterministic signals. Convolution and deconvolution, analysis in time-, frequency-, and time-frequency domain. Wavelet analysis and filtration. 7. Processing of stochastic signals. Analysis and rejection of noise. Signal features and statistical parameters, higher-order statistical analysis (HOSA), principal component and factor analysis, signal arrival detection, (threshold, probabilistic). 8. Selected methods of of signal recognition and diagnostic data analysis. Principles of acoustic emission source location, artificial neural networks, relevant features for signal classification. 9. Introduction to programming in MATLAB Simulink and NI LabView, and program examples.

Syllabus of tutorials:

Practical examples and computer presentations of diagnostic methods are integral parts of the course and they are performed in NDT Laboratory of the Institute of Thermomechanics AS CR.

Study Objective:

Basic knowledge on methodology of data mining in nondestructive testing and evaluation of materials and structures. Structural health monitoring and analogical medical diagnostics. Physical principles of diagnostic systems and fundamentals of digital measurement and signal processing. Skills: Design and use of digital measurement and data evaluation equipments. Mathematical methods of data conversion, denoising, and modification for object diagnostics and monitoring. Automation of measurements, data evaluation, and making decision.

Study materials:

Key references:

[1] www.ndt.net, www.ndt-ed.org,

[2] Klyuev V.V., Zusman G.V., eds.: Nondestructive Testing and Diagnostics Hanbook. (RSNDTD, Moscow, Metrix Instruments Co., Houston, 2004)

Recommended references:

[3] Shull P.J., ed. : Nondestructive Evaluation - Theory, Techniques, and Applications. (Marcel Dekker, Inc., N.Y., Basel, 2002),

[4] Klyuev V.V., Zusman G.V., eds.: Nondestructive Testing and Diagnostics Hanbook. (RSNDTD, Moscow, Metrix Instruments Co., Houston, 2004),

[5] Nondestructive Testing Handbook, Vol. I - IX. (The American Society for NDT, Columbus, USA),

[6] www.cndt.cz , www.asnt.org, www.dgzfp.de,

[7] Journals: NDT-Welding Bulletin (CNDT), Materials Evaluation (ASNT, USA), Research in Nondestructive Evaluation (ASNT, USA), NDTandE (Elsevier), Journal of Acoustic Emission (AEWG, USA), Ultrasonics (Elsevier)

Media and tools: Training room with computer projection, laboratory with equipment for ultrasonic and acoustic emission nondestructive testing

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• Matematické inženýrství (elective course)