To predict what will happen over time after a repair, you need to trend measurements over a period of time rather than just a few instantaneous measurements.
When measuring a certain value, there are cases where it is necessary to measure the instantaneous value, and there are cases where it is necessary to understand the trend of how the measured value changes over a certain period of time.
If a passenger weighs their bag at the airport to board an aircraft, they only have to weigh their bag at the time requested by the counter and pass.
Let’s think about a person’s weight for a moment.
If there is a weight limit when trying to ride an amusement ride, measure it before riding it to determine whether it is possible or not.
However, even if the same weight is measured, if an athlete in a weight class controls his weight or a person on a diet wants to reach his goal by a certain time, he must check his weight periodically to check for changes while trying to maintain his weight.
Measuring data over time is called a time series, and it is a statistical model that predicts future changes based on past data.
Once a diving regulator is repaired, it takes hundreds of dives before the next repair.
If the repair person sets the parameters using only a few measurements and feel, we cannot be sure that the regulator is working as designed by the manufacturer.
Since the internal parts continue to operate under various conditions, it is necessary to check how the measured values change over a certain period of time in order to predict how this will change even after it is shipped to the diver.
SRSD has an analyzer mode that allows you to see trends in these measurements. By averaging 256 data per second and drawing a trend at 1-second intervals, you can see how the intermediate pressure or cracking pressure you set changes. Of course, instantaneous measurement values can be checked with the attached analog gauge.