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This video demonstrates various formula functions in Seeq to calculate the rate of change or change in behavior in a process variable by leveraging the .derivative(), .runningDelta(), and .isDelta() formula functions.

I want to identify the change in value of my signal after a change has occurred. My signal is generally constant (with typical noise) aside from when an event occurs during which there is a step change in the value of the signal.

FAQ: I want to create a condition where a trend is within a specific range of slope so as to identify instances where it falls inside and outside these ranges. Is this possible?

Background: Sensors or calculated tags that totalize a value over time often need to be reset due to maxing out the range of the sensor or the number of available digits in the calculation database. This can create a saw-tooth signal that resets every time this range maximum is reached. In actuality, the signal is constantly increasing rather than building up to the range max and then stepping down to zero to begin counting back up towards the max. Solution: Use Seeq Formula to convert the saw-tooth signal into a continuously increasing signal bounded in time by some reset period determined by the Subject Matter Expert. 1. In this example we begin with a saw-tooth counter signal that resets every time the sensor reaches its range max of 100. 2. Use Seeq Formula to convert the sawtooth signal into a continuous, increasing signal. Note that in order for Seeq to do this calculation, a bounding condition is required. This can either be a repeating periodic condition, or a condition created using the custom condition tool. This can be done in one step using the following code: //creates a bounding condition for running sum calculation $reset = years() //calculates running delta of signal between each sample, compares to zero to ignore negative running delta values, //calculates the running sum of the running delta signal over the bounding condition $signal .runningDelta() .max(0) .runningAggregate(sum(),$reset)

FAQ: Why does the derivative look funny? When taking a derivative and the result looks like the screenshot below, but a smoother signal is expected it is likely that the input signal is step interpolated. To verify this, click on the item properties “I” on the input signal and check the interpolation method. Item Properties View The interpolation method can be corrected by simply adding toLinear() in front of the derivative. See screen shot below of the formula. Final Results