Measurement Technology

A tantárgy neve magyarul / Name of the subject in Hungarian: Méréstechnika

Last updated: 2017. június 21.

Budapest University of Technology and Economics
Faculty of Electrical Engineering and Informatics

Electrical engineering

Bachelor of science program

Course ID Semester Assessment Credit Tantárgyfélév
VIMIAB01 4 3/2/0/f 5  
3. Course coordinator and department Dr. Sujbert László,
Web page of the course
4. Instructors Balázs Bank, PhD.
5. Required knowledge Mathematics, physics, digital design, signals and systems, probability theory.
6. Pre-requisites
(TárgyEredmény( "BMEVIHVAB01" , "aláírás" , _ ) = -1
VAGY TárgyEredmény( "BMEVIHVA200" , "aláírás" , _ ) = -1 )

ÉS NEM ( TárgyEredmény( "BMEVIMIA206" , "jegy" , _ ) >= 2
TárgyEredmény("BMEVIMIA206", "FELVETEL", AktualisFelev()) > 0)

ÉS (Training.Code=("5N-A7") VAGY Training.Code=("5N-A7H") VAGY Training.Code=("5NAA7"))

A fenti forma a Neptun sajátja, ezen technikai okokból nem változtattunk.

A kötelező előtanulmányi rendek grafikus formában itt láthatók.

7. Objectives, learning outcomes and obtained knowledge

The aim of the subject is to give insight into metrology, measurement theory, measurement technology and instrumentation. Besides the theoretical aspects, the course also prepares students for laboratory practices. Model building and problem solving skills of the students are developed. The subject focuses on the measurement of electrical quantities but emphasizes the analogies with non-electrical problems.

8. Synopsis
  1. Introduction. Aim of the subject, main topics. Connection between measurement and modeling. Basic measurement methods. Measurement errors: absolute and relative error.
  2. Measurement errors: bias and random error. Offset, gain, linearity, hysteresis, and quantization error. Error propagation (1): mathematical model. Addition of errors. Examples.
  3. Error propagation (2), examples. Overview of probability theory: probability density, probability distribution function, important distributions. Determination of the expected value, variance, etc.
  4. Properties of the normal distribution. Central limit theorem. Standard normal distribution. Evaluation of measurement data: mathematical model, averaging, variance of the average, sample standard deviation.
  5. Curve fitting. Fitting of line and polynomial. Confidence calculus (1). Utilization of normal, chi-square, and Student-t distribution. Derivation of the distributions and formulas.
  6. Confidence calculus (2). Chebyshev inequality. Overview of basic confidence problems. Utilization of confidence calculus for error evaluation. Standard expression of uncertainty in measurement (GUM).
  7. Measurement of voltage and current (1). Structure of analog and digital meters. Extension of the range, input resistance. Errors of the meters and their evaluation.
  8. Measurement of voltage and current (2). AC measurement. Representation of AC signals: Fourier series, different mean values, dB scale. Comparison of meters of different measurement principle. Description of the noise, signal to noise ration, noise filtering.
  9. Signal transformers. Introduction to non-ideal behavior of passive elements (resistor, capacitance, inductance). Voltage dividers: resistive, inductive, and capacitive divider. Compensated resistive divider.
  10. Signal transformers. Voltage and current transformer. Overview in electronics: basic amplifier circuits, instrumentation amplifiers. Application possibilities.
  11. Impedance measurement: DC low accuracy methods, series and shunt ohmmeter. AC measurement: impedance models. Connection between mathematical and physical models. AC low accuracy methods. Power measurement.
  12. Impedance measurement: voltage comparison method. High accuracy methods, Wheatstone-type bridge circuits. Examples. Balancing impedance bridges.
  13. Ratio transformer and current comparator based bridges. Canceling parasitic impedances. Disturbance sensitivity of measuring circuits: application of shielding.
  14. Canceling of the effect of cabling and stray impedances. 2, 3, 4, and 5 wires methods. In-circuit measurement. Overview of the complete impedance measurement problem.
  15. Time and frequency measurement. Counter based frequency, period, and average period meter. Error analysis. Constant gate time period time meter. Digital phase shift measurement.
  16. Analog and digital oscilloscope. Conditions for displaying a right graph: the role of trigger logic/circuit. Oscilloscope functions. Signal processing overview: sampling theorem and its applications.
  17. Spectrum analysis. Analog methods: parallel, tuned filter, and heterodyne spectrum analyzer. Application of the discrete Fourier transform. Windowing.
  18. Analog to digital converters: flash, successive approximation, dual-slope ADCs. Subranging ADC. The role of short time and long time stability. Calculation of conversion time, noise suppression.
  19. Digital to analog converters: ladder DACs. Switched capacitor DACs. Comparison of different types of ADCs and DACs. Errors of ADCs and DACs: integral and differential nonlinearity.
  20. Quatization error, the noise model of quantization. Effect of sampling on quantization noise. Calculation of effective number of bits. Structure and operation of delta-sigma ADCs and DACs.
  21. Reserved for compensation of any delay (fallen lectures, slow pace, etc.)
9. Method of instruction 3 lectures and 2 seminars each week.
10. Assessment During the semester:
  • one mid-term exam must be written with satisfactory results (40%)
  • 5 (five) small mid-term exams must be written with satisfactory results (30%)

The final result is calculated from the results of the mid-term exam and the small mid-term exams (the weighting is 50-50%). Credits are granted for students achieving 40% final result.

11. Recaps The mid-term exam can be repeated on an organized repeated mid-term exam during the semester, and on a 2nd organized repeated mid-term in the repetition period following the semester.
12. Consultations Consultations are by appointment.
13. References, textbooks and resources

Schnell, L. (Ed.): Technology of Electrical Measurements. Wiley, 1993.

14. Required learning hours and assignment
Preparation for lectures
Preparation for practice
Preparation for short test
Preparation for mid-term exam

Personal curriculum processing

15. Syllabus prepared by

Prof. Gábor Péceli, László Sujbert, and István Zoltán, Dept. of Measurement and Information Systems