BMM3532 - MEASUREMENT & INSTRUMENTATION
ASSIGNMENT 3
NAME : ABDUL RAOUF BIN ABAS
MATRIC NO. : MA17238
SECTION : 02
LECTURER NAME : DR. ZAMRI BIN MOHAMED
1. Sketch and explain what a white noise is?
In signal processing, white noise is a random signal having equal intensity at different
frequencies, giving it a constant power spectral density. The term is used, with this or
similar meanings, in many scientific and technical disciplines, including physics,
acoustical engineering, telecommunications, and statistical forecasting. White noise
refers to a statistical model for signals and signal sources, rather than to any specific
signal. White noise draws its name from white light, although light that appears white
generally does not have a flat power spectral density over the visible band.
2. The acceleration measurement made by an accelerometer is as follow:
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Figure 1
If the accelerometer used for this measurement was replaced by LVDT (not
accelerometer anymore), plot its signal?
3. If the sampling rate for a measurement is 2 kHz and the block size is 4096,
calculate the time for one block size.
4096 (8) = 32768
√32768 = 181.02 ~ 182
4. What is real time process in performing FFT? By referring to Question (3), if the
percentage of overlapping is +10%, what is the processing time to perform FFT?
A fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier
transform (DFT) of a sequence, or its inverse (IDFT). Fourier analysis converts a
signal from its original domain (often time or space) to a representation in the
frequency domain and vice versa. If the percentage of overlapping is +10% so
advantage in speed, which it gets by decreasing the number of calculations needed
to analyze a waveform.
5. What is the minimum percentage of overlapping so that the FFT process is
called real rime process?
The Real-time FFT chart displays the instantaneous Fast Fourier Transform (FFT)
signature of the RF signal seen by the radio. The Fast Fourier Transform (FFT)
converts an RF signal from time domain to frequency domain. The frequency domain
representation divides RF signals into discrete frequency bins; small frequency ranges
whose width depends on the resolution bandwidth of the spectrum monitor (that is,
how many Hz are represented by a single signal strength value). Each frequency bin
has a corresponding signal strength value. Because there may be a large number of
FFT signatures received by the radio every second, an algorithm selects one FFT
sample to display in the Real-time FFT chart every second.
6. Explain two important elements in signal conditioning.
A signal conditioner is a device that converts one type of electronic signal into another
type of signal. Its primary use is to convert a signal that may be difficult to read by
conventional instrumentation into a more easily read format. In performing this
conversion a number of functions may take place. Signal conditioning plays an
important role to achieve signal at a particular level when there are many inputs or
outputs between the PLC controller and the outside world and also to isolate it from
possible electrical hazards such as high voltages.
7. With reference to Figure 2, form an equation to represent the signal and sketch
its frequency domain plot.
8. Sketch the filtered signal if high pass Butterworth filter at cut-off frequency of
5 Hz is used. (assume the filter is ideal)
5
4
amplitude, mV
3
2
1
0
-1
-2
-3
-4
-5
0
0.2
0.4
0.6
0.8
1
1.2
time, s
Figure 2: Output signal
9. The voltage output signal in the Figure 2 was taken from acceleration
measurement of cantilever beam using an accelerometer PCB Model 352C22
with sensitivity of 10 mV/g. Sketch the velocity and displacement plot of the
cantilever beam.