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Found 4 results

1. ## Converting a Saw-Tooth Signal into a Continuously Increasing Signal

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)
2. ## Identifying Changes in Signal Noise

Background: I have a sensor that shows a step change in the amplitude of the signal noise a couple of days prior to instrument failure. It would be useful to be able to identify that step change in the amplitude of the noise so that preventative maintenance can be scheduled rather than running the instrument to failure and causing an unplanned shutdown or production loss event. Solution: Use a combination of Formula and the Value Search tool to identify when this increased signal noise is occurring. Starting signal: 1. Use Seeq Formula and the runningDelta() and Abs() functions to calculate the absolute value of the running delta of the signal of interest. The formula code to achieve this is: //calculates absolute value of running delta of signal \$signal .runningDelta() .abs() 2. Use the Value Search tool to identify the periods of time when this absolute value of running delta signal is above some threshold. In this example we use the remove short capsules/gaps functionality to remove capsules and gaps shorter than 1 hour to capture a single event each time the instrument noise increases.
3. ## Comparing start and end values during an event

FAQ: 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. Solution: In order to compare the actual value of the signal before and after some event, you must first identify the event. Method 1: Running Delta. Note: an approach using the running delta function can be preferred to the derivative function (Method 2) when step changes are present as the derivative is infinite during these steps. Using the derivative function works best if the signal is first cleansed/filtered and the interpolation method changed to linear. Use Seeq Formula to create a new signal that is the running delta of the original signal. Use the syntax: \$OrigianlSignal.runningdelta() Use the “Search Documentation” bar on the right side of the Formula window to learn more about the running delta function and syntax Once the new running delta signal has been created, do a value search on when it exceeds some threshold to identify the time periods over which you would like to know the start and end values. Note: if the step changes are occurring in both the increasing and decreasing directions, you can still identify all events by using Seeq Formula to take the absolute value of your running delta function (\$runningDeltaSignal.abs()) and applying the value search tool to the absolute value signal. The time periods identified using value search can be further manipulated to yield exactly the time periods that you are interested in using Seeq formula and the grow(), shrink(), and/or move() functions. Once the events during which the step change occurs have been identified, you can calculate statistics on them using the Signal from Condition tool. The inputs to the tool will be your original signal and the new condition that you’ve created to identify the events. A few statistics that you may be interested in: Delta: the end value minus the start value of the signal. This would give you the value drop (or gain) during one of these events. Value at start: this will grab the value of the original signal at the start of the event Value at end: this will grab the value of the original signal at the end of the event Method 2: Derivative. Best approach for most rate of change problems, excluding step changes. Use Low Pass Filter tool or Seeq Formula agileFilter() function to cleanse the original signal to remove typical noise from signal. Use Seeq Formula to create a new signal that is the derivative of the cleansed signal. Use the syntax: \$CleansedSignal.derivative() Use the “Search Documentation” bar on the right side of the Formula window to learn more about the derivative() function and syntax Once the new derivative signal has been created, do a value search on when it exceeds some threshold to identify the time periods over which you would like to know the start and end values. Note: if the value changes are occurring in both the increasing and decreasing directions, you can still identify all events by using Seeq Formula to take the absolute value of your derivative function (\$derivativeSignal.abs()) and applying the value search tool to the absolute value signal. The time periods identified using value search can be further manipulated to yield exactly the time periods that you are interested in using Seeq formula and the grow(), shrink(), and/or move() functions. Once the events during which the value change occurs have been identified, you can calculate statistics on them using the Signal from Condition tool. The inputs to the tool will be your original signal and the new condition that you’ve created to identify the events. A few statistics that you may be interested in: Delta: the end value minus the start value of the signal. This would give you the value drop (or gain) during one of these events. Value at start: this will grab the value of the original signal at the start of the event Value at end: this will grab the value of the original signal at the end of the event
4. ## Calculating Sample to Sample Changes

Hello, Using Seeq Tools, are there ways to easily calculate the change in value from one sample to the next, as well as the corresponding sample time? These types of calculations can be useful in a variety of applications (e.g., tank fill/drain, irregularly spaced process samples, equipment status transitions, etc.). Ted Williams
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