In my preliminary investigation concerning the motion of pint glasses, I affixed an ADXL330 accelerometer to the bottom of a pint glass. Through a long cable connected to a microcontroller, I was able to record the motion of the glass on 3 axes over time.
I created a simple Python program allowing me to graph and view this data. Through these graphs, I have started to understand how to best implement accelerometers embedded in my pint glasses.
The first image represents a hand-held pint glass which is repeatedly ‘cheersed’ against another pint glass. In this diagram, the outlying points represent the accelerometer data at the moment of the cheers. The cluster of points occurred as I was simply holding the glass in my hand. This image can be compared with the fourth image where the glass was merely resting on the table.
The second image is a representation over time of the glass being cheersed 12 times over 50 seconds. As expected, there were spikes in the data in both the x-axis (green) and y-axis (blue) signifying the contact of the pint glass against another glass.
The third image is a 3-dimensional plot of one cheers of the glass. I chose to visualize the data in this fashion because I was curious to see if one of the dimensions would be more effected than the others. Interestingly, it seems like the Z-axis has more extreme outliers compared to the X and Y axes. This comes to a surprise to me since the glass impacted the other glass on a horizontal plane and the Z-axis acceleration does not deal with the horizontal plane.
The fourth image is the accelerometer values I recieved when the glass was sitting on the table for 50 seconds. Just like the first image, there are two different blobs of points because two different plots were overlayed over each other (X-axis over Z-axis, Y-axis over Z-axis).
The fifth image is a 2 dimensional graph of aggregated accelerometer data as liquid is consumed out of a pint glass. The large group of points on the left represents the accelerometer data when the glass rested on the table. These points extended towards the right when the glass is lifted off of the table and brought it towards the lips. These points moved back to the left as the glass was brought back to the table. The outlyers in this graph occurred of the impact of the glass being placed back on the table.
The sixth image is a representation of the x-axis (green) and the y-axis (blue) over time as I took 5 sips of liquid out of the pint glass. Again, the spikes of data occured as the glass made contact with the table as I was setting down the glass.
The seventh image is the plotting of 3-axis accelerometer data as the glass is lifted from the table to the mouth and back to the table.
notes:
I used voltage levels on the axes of the graphs as opposed to the gravitational constant (denoted G). The voltage does not have a direct relationship to G’s, and at this point of my investigation, I do not find it important to find a polynomial fit for the G’s. For my application of the accelerometer, I am really only concerned with the voltage levels going into the analog pins of my microcontroller. I am not sure if knowing G’s are going to become important for my application.
Due to a crashed hard drive right after the completion of this experiment, some of the documentation was lost. I plan to update this entry with graphs comparing the accelerometer values of a glass rest on a table and a glass being held in the hand. I find the subtle differences of these two graphs quite interesting. Also, I will need to rewrite python graphing code in order to continue investigating accelerometer output. Once this code is completed, I plan to include it into this entry.
