This document summarizes an individual project investigating the use of microprocessors like the Arduino and Raspberry Pi to demonstrate rotor dynamics. The aims of the project were to assess microprocessors' ability for signal processing and compare results to computational predictions. The solution involved using an Arduino to collect vibration data from a rotating disk with an imbalance and sending it over USB to a Raspberry Pi for processing and visualization. Results showed the setup could produce orbit plots and waterfall plots showing resonances, though processing on the Raspberry Pi was limited. Further work could explore faster sampling, closed-loop speed control, additional sensors, and a graphical user interface.

1. INVESTIGATING MICROPROCESSORS
FOR USE IN
DEMONSTRATING ROTOR DYNAMICS
Nicholas Robson
Supervisor: Emiliano Rustighi
Individual Project
FEEG3003
Motivation Simulation
Results
Conclusions
Methods
Aims
1. Assess the ability of microprocessors for signal processing.
2. Compare the results against computational predictions for
analytical methods.
Solution:
• Rotor dynamics is not demonstrated
efficiently
• Bently Nevada Kit simulates large
machinery
• Arduino and Raspberry Pi are very good
at data-processing
Combine an Arduino and a
Raspberry Pi to create an
interface to demonstrate with
• Orbit plots show the position of the rotor at the sensors
• The graphs are highly customisable
• The sensor sensitivity can be accounted for
• Transient responses visualise the sampling rate and sinusoidal shape
• Waterfall plots were used to
show the frequency
response of the rotor at
different speeds, Ω
• Peaks were bigger at
resonant frequencies
• Harmonics at 1Ω, 2Ω and
3Ω were observed, caused
by non-ideal properties in
the rotor and bearings
2Ω
3Ω
1Ω
• My design took advantage of the fact that
wiring the output leads through an
operational amplifier and into the ADC
inputs of the Arduino allowed the readings
to be sent via USB to the Raspberry Pi,
and parsed with bespoke python code
• By placing a grub screw in the edge of the
rotor disk, an imbalance that excited the
rotor to vibrate was created
• Vibration was measured and recorded as
x-y data by the rotor sensors
• The tachometer signal was passed through
a voltage divider to reduce the reading lag
References. Jet Image: http://adrenaline.uol.com.br/forum/papo-cabeca/267964-cutaway-drawing-diagramas-em-3d-de-maquinas-mostrando-partes-internas-fotos.html
Max Sample rate: http://frenki.net/2013/10/fast-analogread-with-arduino-due/
• Models were written in python, to simulate the
rotor vibration using fundamental equations
• The image to the right is a simplified model of the
rotor drawn in solidworks
• The images below show simulated orbits of the
rotor, below, at and above the resonant frequency
• The irregular plots were
caused by loose bearings
• The Arduino is good at
collecting data
• The Raspberry Pi didn’t have
enough processing power to
cope with python efficiently
• A second pair of sensors could be used to
create an accurate insight into mode shapes
of rotors with a maximum of one node.
Vibrations with more nodes will require more
sensors
• Arduino has a sampling capability that was
untested in this project. A sampling rate
1000x faster is possible
• The project could be extended to control the
rotor speed, using the Arduino’s DAC output
and a feed-back loop from the tachometer
signal
• Create a graphical user interface for the
Raspberry Pi, to interact with viewers and
display graphs aesthetically
Further Work