State University of New York at Stony Brook
ESE 211 Electronics Laboratory A
Department of Electrical and Computer Engineering
2009
¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
1
Lab 2: Measurement of DC voltages and currents
1.
Objectives.
1)
Familiarization with barcode resistor marking. Measurement of resistance using the DMM.
2)
Setting up the DC power supply for operation as a voltage source and for operation as a current source.
Selection of a ground node.
3)
Measurement of voltages and currents using DMM. Measurement of IV characteristics.
2.
Introduction.
There is no such thing as a perfect measurement. Each measurement contains a degree of uncertainty due to
either fundamental reasons or, more often, due to limitations of the methodologies, instruments and the people
using them.
Random error present in the results of the measurement can be minimized by averaging over multiple
measurements. Assuming normally distributed data, the error bars for the results of measurements of R using
ohmmeter can be calculated based on standard deviation
σ
R
.
()
N
R
R
,
1

N
R
R
σ
N
1
i
i
N
1
i
2
i
R
∑
∑
=
=
=
−
=
,
(
1
)
where N is number of measurements (for instance, the number of times you measure the same resistance using
ohmmeter). Each time you might get slightly different value R
i
. After averaging over N (ideally N should be
rather big number) experiments one can calculate an average value
R and the actual value of the resistance will
be with 68% of certainty in the range from
R
σ

R
t
o
R
σ
R
+
. There is 95% likelihood that the actual value is
within range from
R
σ
2

R
⋅
to
R
σ
2
R
⋅
+
. From equation (1) one can see that precision of measurement
improves as square root of number of experiments. Hence, in order to minimize the contribution of the random
noise it is advised to perform multiple measurements and average the results.
There is also systematic errors that can affect the accuracy of the measurements (precision can be improved
by averaging but final result could still be not accurate since the errors are not necessarily come in the form of
random noise). Good example of the systematic error are offset voltages and currents, i.e. when R is calculate
based on I and V there is constant shift in either one or even in both of these parameters, hence averaging alone
could not improve the accuracy. One way to deal with this is to use known functional dependences of one
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
This is the end of the preview.
Sign up
to
access the rest of the document.
 Spring '07
 BELENKY
 Resistor, Electrical resistance, Stony Brook Department

Click to edit the document details