Measuring systems . Digital measuring apparatus . Analog signal and its entry into the digital processing (basic principle of AD converters).
Praktical digitalization of a signal. Sampling rate vs. frequency spectrim width.
Preamplifying of a signal. Analog, digital filtration anf their properties
Aliasing. The Nyquist criterion. Synchronous signal detection (lock-in amplifier).
Connection of different types of sensors to digital signal processing
For example: signal processing from piezoelectric accelerometers, optical sensors,(vibrometer, triangulation sensors and its connection to PC).
Reading of specific signals : acoustic signals, optical, vibration, use of relative units – noise and vibration (B, dB).
Basic principles of mathematical signal processing. Fourier signal analysis (Fourier series, Fourier integral, Fourier transform). Fast Fourier transform. Transformation in measuring and control systems.
Haar transform. Window transformation. Wavelet transform
Correlation analysis. Autocorrelation. Cross -correlation.
Processinf of measured sata by means of filtration. Background. Filter.
Frequency analysis of the filtration process. Regeneration of actual spectrum.
Basic s of experimental modal analysis. Modal analysis.
Measurement of modal model (geometric model creation, control measurements,
results processing, animation mode). Modification of a structure. Identification.
Interpretative methods and their selection in relation to applications in different fields of science and technology.
Curriculum of exercises : use of MATLAB software resp. MATHEMATICA, ORIGIN.
1. Initial exercise to become familiar with a program used for signal processing.
2. Introduction to basic types of sensors according to their physical principle.
Signal sampling, principles of sampling. Practical considerations for digitizing a signal.
Sampling rate vs. frequency spectrum width. Preamplifying of signals.
Analog, digital filtration and their properties. Aliasing. The Nyquist criterion.
3. Introduction to basic methods of signal processing.
4. Processing of harmonic and periodic signal. Fourier series of periodic signals.
5. Aperiodic signals, spectral function and the Fourier transform
6. Processing of harmonic and discrete periodic signals. Fourier series
7. Aperiodic discrete signals. Spectral function.
8. Correlation function of periodic signals.
9. Correlation function of aperiodic signals.. Basic aperiodic signals –
unit jump and unit impulse.
10. Correlation function of aperiodic discrete signals.
11. Processing of measured data by means of filtering.
12. Measurement of signals by means of selected physical quantities sensor.
13. Signals processing by means of spectral analysis, filtering and correlation analysis.
Praktical digitalization of a signal. Sampling rate vs. frequency spectrim width.
Preamplifying of a signal. Analog, digital filtration anf their properties
Aliasing. The Nyquist criterion. Synchronous signal detection (lock-in amplifier).
Connection of different types of sensors to digital signal processing
For example: signal processing from piezoelectric accelerometers, optical sensors,(vibrometer, triangulation sensors and its connection to PC).
Reading of specific signals : acoustic signals, optical, vibration, use of relative units – noise and vibration (B, dB).
Basic principles of mathematical signal processing. Fourier signal analysis (Fourier series, Fourier integral, Fourier transform). Fast Fourier transform. Transformation in measuring and control systems.
Haar transform. Window transformation. Wavelet transform
Correlation analysis. Autocorrelation. Cross -correlation.
Processinf of measured sata by means of filtration. Background. Filter.
Frequency analysis of the filtration process. Regeneration of actual spectrum.
Basic s of experimental modal analysis. Modal analysis.
Measurement of modal model (geometric model creation, control measurements,
results processing, animation mode). Modification of a structure. Identification.
Interpretative methods and their selection in relation to applications in different fields of science and technology.
Curriculum of exercises : use of MATLAB software resp. MATHEMATICA, ORIGIN.
1. Initial exercise to become familiar with a program used for signal processing.
2. Introduction to basic types of sensors according to their physical principle.
Signal sampling, principles of sampling. Practical considerations for digitizing a signal.
Sampling rate vs. frequency spectrum width. Preamplifying of signals.
Analog, digital filtration and their properties. Aliasing. The Nyquist criterion.
3. Introduction to basic methods of signal processing.
4. Processing of harmonic and periodic signal. Fourier series of periodic signals.
5. Aperiodic signals, spectral function and the Fourier transform
6. Processing of harmonic and discrete periodic signals. Fourier series
7. Aperiodic discrete signals. Spectral function.
8. Correlation function of periodic signals.
9. Correlation function of aperiodic signals.. Basic aperiodic signals –
unit jump and unit impulse.
10. Correlation function of aperiodic discrete signals.
11. Processing of measured data by means of filtering.
12. Measurement of signals by means of selected physical quantities sensor.
13. Signals processing by means of spectral analysis, filtering and correlation analysis.