At the beginning of this week, I read through all of the academic papers and datasets that Adithi found last week. I found these papers to have useful information regarding data collection and processing. For instance, I found that all these papers used acoustic emission (AE) sensors for structural health monitoring (SHM). AE sensors are specialized, high-frequency piezoelectric devices that detect transient stress waves (ultrasonic energy) in materials caused by structural, mechanical, or manufacturing defects. They provide real-time monitoring to identify leaks, cracks, and friction. I began looking into how AE sensors work and finding one within our budget constraints for purchase. I also continued my search for an existing dataset. My minimum requirement for a dataset was that it must include acoustic data labeled with the defects we are focusing on (corrosion and air leaks) from the duct material we are focusing on (sheet metal and fiberglass duct board). I was able to find two datasets that directly used AE sensors to collect acoustic data of corrosion and air leaks on galvanized steel.
However, when I presented my findings to our supervising professor on Wednesday, he said we should create our own dataset. In this way, our robot would perfectly interact with our physical system and we wouldn’t have to worry about fitting our physical system to that which was experimented on in the studies that produced the existing datasets we found. I shared our professor’s opinion with the rest of my group, who were unable to attend the meeting. Together, we have decided to focus all our energy on purchasing the robotic base and AE sensor as well as the HVAC duct system. I found an AE sensor that fits our frequency needs and I found an HVAC duct that fits our measurement requirements. We have put in the purchase orders for these.
This week, I also looked into acoustic features we can pull from the acoustic data to make meaningful conclusions about structural defects. I found a bias shift method and a denoising process specific to AE sensor data. I also discussed with my team that our visual odometry system may not be required, since we are able to calculate the distance our robot has travelled relative to its starting position based on its speed and the amount of time it moves. The visual odometry system would add unnecessary complications. My teammates agreed with me, so this system is not included in the design anymore. However, we still require a camera to allow the remote-control user to see where the robot is and whether the robot needs to turn. I also started creating the design presentation that we must deliver next week.
Next Week Goals:
- In the coming week, our purchases will come in and we can begin construction of our robot and HVAC duct system.
- Then, we can begin the process of data collection.
- Simultaneously, I can continue looking into data processing techniques.
- We must also have our design presentation ready for Monday.
My work for this week can be found here: https://docs.google.com/document/d/1ixLqQD6Fis3x61WQpO9HzGfW2eAyp14MxrCl1U2Xk7k/edit?tab=t.0