Here I have added color to the three Plotly projections as XY (blue), XZ (orange) and YZ (green) And I hoped for a way to do this that would work with the many different compasses and accelerometers I had been using since I began development in 2013, because most of those flow sensors are still running. So the goal of calibration was to transform displaced eliptical shapes into nice balanced spheres centered on the origin. But since I haven’t seen a matrix operation since high school, most of that went right over my head. It didn’t help that there are so many different ways of defining a “standard” reference frame, making many code examples hard for a newbie like me to interpret. But even without the math I came away understanding that hard iron shifts the entire sensors output, while soft iron distorts it. Sensors Online: Compensating for Tilt, Hard-Iron, and Soft-Iron EffectsĪN4246: Calibrating an eCompass in the Presence of Hard and Soft-Iron InterferenceĪnd if that Freescale paper didn’t leave you in the dust, you could try Alec Myer’s extensive blog entries on magnetometer calibration. The Sensor Fusion tech talk from InvenSense provides a fairly broad overview Rather than waffle on about it I am simply going to provide links here to some of the better references I came across: I tackled the topic of calibration with little knowledge beforehand, and there was quite a bit of background material to wade through. But once my loggers started consistently reaching a year of operation, that “later” finally arrived. Since I could not trust the electronic compass in the units, I simply installed the Pearls with a magnetic compass in my hand, making sure I knew which accelerometer axis was physically aligned North. When I started building a flow sensor based on the drag/tilt principle, I knew that leaving sensors on their default factory calibration settings was not optimal, but I had so many other things to sort out regarding power use, memory handling, etc., that I left calibration to deal with later. To see the kind of data we get from these pendulum sensors, see case study #2 in Cave Pearl Data Logger: A Flexible Arduino-Based Logging Platform for Long-Term Monitoring in Harsh Environments In 2020 we released a 3-Part build tutorial based on that paper & in 2022 a 2-Part logger that runs on a coin cell Reading the compass bearing is more important with the open water units, as passage geometry controls flow direction in caves.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |