We have been working on a way to visualize damper performance for a while. Over the years of analyzing data, there were still some lingering questions we had about damper performance and quantifying what you are feeling. We pay close attention to the compression and rebound terminal velocities. From the picture below, you can see that every stroke, compression or rebound, has an acceleration phase followed by a deceleration phase. Between these two phases, you achieve max velocity. At the end of the stroke, you are at zero velocity and you are starting another stroke.
We’ve been mounting sensors to bikes for 3+ years now. Some bikes are really easy, others are really really difficult. There are a class of bikes that have placed the shock deep in the frame, making it really difficult to mount to. As long as we can take some simple measurements and we know the leverage curve of the bike, we can measure something other than the shock and translate that motion to the rear axle motion.
This blog will cover topics about data analytics on bicycles. For many of you, this will be your first look at data specific to bikes. Rest assured, these are not abstract concepts and we encountered all of this for the first time when designing our system from scratch. Before we dive into data, we'll explore what your goals should be when tuning your bike. Then we’ll go into how you go about this process using data.
This will be an evolving thread on examples of how to mount the rear sensor. We are constantly improving our mounting options. Most of the parts will be available for purchase and may be in prototype form when the picture was taken. If you want any bracket you see that is 3D printed, we can either have one made for you, or you can get the file from us and print it yourself if you have a printer.