88150 - Measurement Instrumentation P

Course Unit Page

Academic Year 2021/2022

Learning outcomes

After successfully attending the Course, the student understands the basic analytical tools for the representation of physical quantities both in the time- and frequency-domain; knows and understands the operation of modern instrumentation, with particular emphasis to sampling-based instruments; is capable of achieving a deep insight of instrument specifications, and thus evaluating their actual performance in the application of interest and comparing different commercial instruments; knows the modern standards and methodologies for the evaluation and expression of the uncertainty of measurement; understands and is capable of applying the main algorithms for signal analysis in the frequency-domain; is capable of programming, in the framework of commercial software, the remote control both of single instruments and entire automated measurement set-ups.

Course contents

Fundamentals of Metrology and Measurement Science

The measurement process: definition of measurand, interest/influence quantities, resources, activities. The model of a measurement process. Uncertainty of measurement: definition, evaluation and expression in accordance with international standards. Examples of evaluation of the uncertainty of measurement.

Frequency-Domain Representation and Analysis of Signals

Fourier series. Fourier transform and integral. The notion of bandwidth of a signal. Dirac operator. Transfer function and pulse response of a linear system. Energy and power spectra. Representation of correlation between signals. Time series. Discrete-Time Fourier transforms. Basic properties of stochastic processes.

Analogue-to-Digital (A/D) Conversion

Ideal A/D conversion: quantization and encoding. Quantization error. Classification of non-idealities in A/D conversion. Quantization noise. Model and effective bits for a real A/D Converter (ADC). Main ADC architectures of interest for modern instrumentation. Non-ideality and uncertainty sources within ADC architectures.

Digital Multimeter (DMM)

Instrument fundamentals and general architecture. Input conditioning network, ranges, integration time, sensitivity. Input equivalent circuit. DC voltage measurement. DC current and resistance measurement. Use of the digital multimeter for AC measurements. Main parameters and specifications in DMM datasheets. Uncertainty evaluation.

Digital Wattmeter

Instrument fundamentals and general architecture. Voltage measurement. Main parameters and specifications in the datasheets. Measurement of electrical active and reactive powers, and power factor.

Sampling Oscilloscope (DSO)

Instrument fundamentals, functional block diagram. Front-end circuits for the input signal conditioning. Analogue-to-digital acquisition channel: input impedance, sample/hold, A/D converter. Trigger circuit and methods. Time base. Real-time equally-spaced sampling, Shannon/Nyquist criterion. Ideal continuous-time reconstruction of the sampled signal and practical methods based on finite impulse response digital filters. Equivalent-time and random sampling. Architectures for the maximization of the equivalent sampling frequency. Main parameters and specifications in DSO datasheets. Analysis of the instruments on the market: comparison and choice criteria in the framework of different industrial/ICT applications.

Instrumentation and Techniques for Spectral Analysis.

Spectrum Analyzer (SA): multiple-conversion architectures, bandwidth, frequency resolution, dynamic range. Main operative parameters and related optimization for best measurement accuracy in the different applications. Analysis of the instruments on the market: comparison and choice criteria in the framework of different industrial/ICT applications. Digital spectral analysis: sampling-based techniques and DFT/FFT algorithms. Measurement of power spectrum. Architectures for the integration of sweep operation (scalar SA) and FFT-based operation (vector SA). Fundamentals of real-time SAs.

Sensors and Transducers for Industrial and Automotive Applications

Sensors for dimensional and strain measurement. Sensors for mechanical quantities (torque, force, power, velocity). Sensors for temperature and flow rate measurement.


Slides and notes edited by the Teacher. Commercial component and instrumentation datasheets. User manuals.

Teaching methods

Class lectures.

Assessment methods

Oral exam (possible practical verification in laboratory).

Teaching tools

PC and digital projector. Measurement set-ups available at Department of Electrical, Electronic and Information Engineering "Guglielmo Marconi" - DEI.

Office hours

See the website of Gian Piero Gibiino