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# Introduction to Sensors and Data Analysis (Fall 2018) | |
## Lab #5 Mass Measurement Device with Cantilever beam | |
# Mass measurement contest | |
![Mass measurement cantilever](./contest_diagram.png) | |
*Figure 1: Diagram of cantilever with unknown mass in position 2 out of 3 total | |
positions. Measure changes in the natural frequencies to determine mass of | |
object.* | |
In the mass measurement contest, you will use natural frequency shifts to | |
determine the mass of an object. There are three locations you can mount the | |
object as seen in Figure 1, where the object is mounted in position 2. The | |
experimental procedure only involves measuring natural frequency with the mass | |
mounted in different positions. You can create an *engineering model* as we will | |
do with experimental results from Ghatkesar *et al.* 2007 | |
[\[1\]](./ghatkesar-et-al-2007_higher-mode-mass-sensors.pdf), as described in | |
section 2. | |
You can use the modal analysis in **Ansys** | |
[\[2\]](https://ansyshelp.ansys.com/account/secured?returnurl=/Views/Secured/corp/main_page.html) | |
and apply a point mass to get predicted changes in natural frequencies. This | |
will create a table of values for your given cantilever for known masses for | |
*interpolation* as described in section 3. | |
**Rules of Contest** | |
1. The masses must not leave the lab | |
2. You cannot mount other known masses to the cantilever | |
3. You must report your uncertainty in your mass measurement to enter the | |
competition | |
4. You must report your serial number "TJM 01-TJM 12" to enter the competition | |
6. You may use the following tools and software: strain gage or accelerometer | |
(not both), calipers, Ansys, Labview, Python, Matlab, and Excel | |
**Winners of the contest** | |
There will be two sets of winners for the contest: | |
1. Lab group with the most accurate mass measurement calculated with | |
$A=|m_{reported}-m_{actual}|$ | |
2. Lab section with the most precise mass measurement calculated with | |
$P=\sum_{i=1}^{N}(m_{reported}-m_{actual})^2$ | |
Where $A$ is the accuracy, $P$ is the precision, $m_{reported}$ is the reported | |
mass from your experiment, and $m_{actual}$ is the actual mass of the object, | |
and $N$ is the total number of lab groups in a section. The group and section | |
with smallest A and P, respectively will win prizes. The prizes are as such | |
1. ** \$100 cash prize** put into your student accounts ($50/group member for | |
group of 2) | |
2. **Donuts/cookies** brought to your lab section | |
**Lab #5 report** should include details of the following | |
1. Your design of experiments | |
2. Your measured results | |
3. Your predicted results from Ansys | |
4. Your final calibration process for measuring a mass based upon natural | |
frequency changes |