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Found 4 results

  1. We often would like to summarize data in a table to reflect something similar to below: There are a couple ways to achieve this in Seeq. In this example, we'll explore using Simple Scorecard Metrics to get this result. If you're interested instead in using Conditional Scorecard Metrics, I would take a look at this Seeq.org post! Step 1: Goto Tables & Select Simple Under Columns, ensure Average, Last Value, and Name are selected Step 2: Rearrange & rename the Headers; Last can be moved to 2nd column and renamed to Current. Avg (now 3rd column) can be renamed to 1 hr avg. Step 3: Copy the link and paste it into an organizer topic. Create a new Date Range named 1 hr (with a duration of 1 hr) to assign to your table. After clicking the table & Update Seeq Content: Step 4: Can be done on the same worksheet, or a new worksheet. I will create a new worksheet. Back to Simple table, remove the Name column so only Average is selected. Rename this column to 24 hr avg. Step 5: Paste this worksheet into your organizer next to your other table. Create another Date Range named 24 hr (with a duration of 24 hr) to assign to this newly added table (similar to Step 3). Step 6: Click each table to then click the Toggle Margin button. When complete, the table should look like one single table. To update the date range for the entire table, simply click the "Step to current time signal" next to Fixed Date Ranges.
  2. This question came in through the support channel today and I thought it was a good opportunity to explain some of the nuances in the Scorecard tool and give a couple of potential work arounds. Question: In this example we are using two simple Value Searches on the Example -> Area A dataset Running -> Compressor Stage !~ "off" Stage 2 Running -> Compressor Stage ~ "stage 2" Unfortunately in Seeq there is not an easy way to directly perform Math or formula like operations on Scorecard Metrics created using the "Simple" option like you see here above. The "Simple" metrics are reactive to your display range and so have more limitations as compared to the "Condition" and "Continuous" options. In order to create this calculation we need to first decide on a calculation range that matches our engineering or business need. In this case we want to calculate this value per month. Option 1 - Convert to Signal from Condition Calculations Create a Monthly condition using the Periodic Condition tool Create Monthly Total duration in each mode calculations using the Signal from Condition Tool Use Formula to Create your % Time running calculation ($Stage2Duration/$RunningDuration).convertUnits("%") Create Scorecard using Condition Option Option 2 - Create Continuous Calculation Signal The main downside of Option 1 is that you cant see at any given point in time how the last running 30 days have been performing like you could with the original simple scorecard metrics. The following formula will build a calculation of the % Time in Stage 2 of total running time for the trailing 30 days calculated every hour $aggPeriods = periods(30days,1h) $RunningDuration = $Running.removeLongerThan(1d).aggregate(totalduration(),$aggPeriods,endkey()) $stage2Duration = $Stage2Running.removeLongerThan(1d).aggregate(totalduration(),$aggPeriods,endkey()) ($stage2Duration/$RunningDuration).convertUnits("%") This calculation can be added in a simple scorecard metric as well and as long as the simple scorecard duration is 30 days it will give you the desired results.
  3. It is common in manufacturing processing plants such as oil and gas refineries, to monitor the temperature trend in furnaces. Example in the refineries, the furnaces tube metal temperature (TMT) monitoring severity increases for dirty services such as crude distillation and coker units. Operation team uses this information to decide either to go for rate cut or feed rate skewing before the TMT reaching mechanical limits to prolong the run length. Upon reaching the limit, the furnace will be taken out-of-service by means of spalling or pigging, and consequently impacts the production rate. Use case: The objective is to highlight the highest and the second highest temperature out of several temperatures in a matrix. Seeq enables users to build a matrix table (or Scorecard prior to R51) to highlight the temperature priority sequence by using a combination of functions and tools including max(), splice(), composite condition and scorecard metrics. Step 1: Start by loading all of the signals we want to include in the matrix into the display. Step 2: Use max() to look for the highest value signal at any time in the formula tool. Type in formula below into formula editor. $t.max($t2).max($t3).max($t4).max($t5).max($t6).max($t7).max($t8) Step 3: Create the second highest signal using splice() and composite condition. To capture the second highest signal, we need first to exclude a signal with the highest temperature at any time and then identify the highest value out of the remaining seven signals. To achieve that, use the highest temperature signal we created in step 2, we then create a condition when a signal reads the highest value, for each eight signals. //Which is the max $if_t1_is_the_max = $t1 == $max $if_t2_is_the_max = $t2 == $max $if_t3_is_the_max = $t3 == $max $if_t4_is_the_max = $t4 == $max $if_t5_is_the_max = $t5 == $max $if_t6_is_the_max = $t6 == $max $if_t7_is_the_max = $t7 == $max $if_t8_is_the_max = $t8 == $max Prior to looking for the max a second time, we must remove or replace the values from each of the signals when they are equal to the max. In this method, we will replace the highest signal values with zero using the splice function during the condition when that signal was the max. With these highest values replaced by zero (or removed), applying the same technique with the max function will yield the value of the second highest signal. //replace the max with 0 $removing_the_max_value = ($t1.splice(0,$if_t1_is_the_max)) .max($t2.splice(0,$if_t2_is_the_max)) .max($t3.splice(0,$if_t3_is_the_max)) .max($t4.splice(0,$if_t4_is_the_max)) .max($t5.splice(0,$if_t5_is_the_max)) .max($t6.splice(0,$if_t6_is_the_max)) .max($t7.splice(0,$if_t7_is_the_max)) .max($t8.splice(0,$if_t8_is_the_max)) .toStep() return $removing_the_max_value Step 4: Create Metric Threshold Limits Subtract the highest signal by a fairly small value using Formula tool in order to use signal as a threshold limit. Repeat the step for second highest limit. $max-0.001 Step 5: Create scorecard metric for each signal. Create scorecards for all 8 signals, as an example we choose value at the end for statistic for daily condition and apply the threshold accordingly. In the table view: Do check this post by Nick. He used different approach to yield the maximum of three signals, and displayed signal string in a matrix table.
  4. I have an interesting question that I need some assistance on. We have a signal that generally has no dominant frequency. However, it sometimes does get a dominant frequency and when it does, we are really interested in two things: What is the dominant frequency? How dominant is it? ( Let's call this "magnitude." ) Tracking both the dominant frequency and the intensity over time using a rolling 2 to 3 hour window every 5 minutes. This value has predictive capability when it does show up, and it intensifies as it gets closer to a particular event we are trying to predict. I've been able get the peak frequency because the formulas are clear enough to figure this out. The problem is the magnitude. The "Frequency Analysis" panel results show something like this: How do I get that peak value? I don't want to have to specify a hard-coded frequency band for this. The problem is that I don't see a function for that. I can call the fft() function in a way in which it returns a "Table" type. signal.fft ( bounds , period , units ) : Table Create a table of frequency magnitudes by analyzing the signal in the bounds. The table will have 2 columns, frequency and magnitude. Then I can use the top() function to return the top 1 row ordered by the greatest "magnitude" column: table.top ( limit , columnName , direction ) : Table However, I cannot for the life of me figure out how to get the "mangitude" value out of the first row returned in "Table" the above function and convert it into a sample at the ending point of the rolling 3 hour/5min period. Is this even possible. Is there a better way? // Getting a rolling 3 hour window every 5 minutes. $periods = periods(3h, 5min) // for condition, get a signal with samples ending at each capsule representing: // key: end of 3hr window // value: peak magnitude of the fft of the $waveSignal $periods.transformToSamples( $cap -> { // excute the expression for each capsule in condition. $tbl = $waveSignal.fft($cap, 1s, 's') // want the results in period lengths, not frequencies. // get the largest magnitude, filtering for the frequency/period length range of interest // get the first row of that table. $r = $tbl.filter('frequency'. isBetween(30s, 150s)) .top(1, 'magnitude', 'desc') .getFirstRow() // *******HOW DO I DO THIS???****** // convert that magnitude calculated to sample located at the end of this capsule. sample($cap.getEnd(), $r.get('magnitude')) } ) Thanks in advance! Even better would be: getting the sum of the values in the peakFrequency +-/ 2s window.
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