Figure 1: Simcenter Testlab Neo process for order cuts, overall level and run comparison.
The article also explains how to do perform statistics (average, maximum, minimum, etc) on multiple runs and how to quickly display the results.
Article contents: 1. Background 2. Getting Started 3. Spectrum Map 4. Overall Level and Order Sections 5. Run Average 6. Calculations and Results Viewing 7. Additional Processing
1. Background
Recordings of three runups will be used in this article. They were acquired on the Siemens Simrod vehicle shown in Figure 2.
Figure 2: Left – Runup data from one acquisition, Right – Simrod Vehicle used in testing.
Several vibration channels were measured in addition to motor and vehicle speed. Each runup went from 300 rpm to 3500 rpm. Three runs were acquired to check repeatability of the measurements.
2. Getting Started
The three runups will need to be placed in the “Input Basket” to be used for processing. In the data navigation tree of either the Desktop or Processing tab of Simcenter Testlab Neo, right click on the runup data and choose “Replace in Input Basket” as shown in Figure 3.
Figure 3: Right click on the data runs and choose “Replace in Input Basket” to make the runups available for processing.
The “Input Basket” is a list of pointers to data to be processed. Data can be selected from multiple locations (network drives, local directories) and added to the Input Basket.
The Process Designer with assorted methods is used to process data. Under “File -> Add-ins” turn on Process Designer, Run Averaging, and Signature Analysis add-ins as shown in Figure 4:
Figure 4: Three add-ins (Process Designer, Run Averaging, and Signature Analysis) are needed to do the spectral processing, order, and overall level analysis described in this article.
The first method that is required is a “Spectrum Map”. This will calculate a series of frequency spectrums versus rpm that can be used subsequently for order and overall level analysis.
From the Method Library, drag and drop the “Spectrum Map” method in the Process area as shown in Figure 6:
Figure 6: Drag and drop the Spectrum Map method in the process area from the Method Library.
Then connect the Input to the Spectrum Map method. Small handles (small squares) appear on the methods to connect them when hovering the mouse over the method. This is shown in Figure 7 below.
Figure 7: Left – Hovering mouse over method makes squares appear to make connections, Right – Connect bottom of Input method to top of Spectrum map method.
Connect the bottom square of the Input method to the Top of the Spectrum Map method.
Next, highlight the Spectrum Map method. This will allow the Properties to be edited as shown in Figure 8.
Figure 8: Highlight the Spectrum map method to select “Tracked on channel” as the Tracking strategy in the method properties.
Change the Tracking Strategy from “Tracked on time” (the default) to “Tracked on channel” to be able to process the data versus rpm.
Then click on the “…” button next to Channel and select the rpm channel to be used for processing (Figure 9). Be sure the Quantity field is set to “RotationalSpeed” so only rpm channels appear in the list.
Figure 9: Use the “…” button next to Channel to select the RPM channel for processing.
In this case, the following will also be set:
Slope Method: Set to “Imm Up”, unlike “Up” which would require the rpm to pass through the minimum rpm, “Imm Up” (short for Immediate Up) will automatically start processing the data if it has rpm above the minimum.
Minimum: Lowest rpm for processing. Data will be processed between the minimum and maximum rpm.
Maximum: Highest rpm for processing. Data will be processed between the minimum and maximum rpm.
Increment: A frequency spectrum will be calculated at each rpm increment between the minimum and maximum.
Don't have a RPM trace? The "Extract RPM" method in Simcenter Testlab Neo can be used to calculate the RPM from a vibration or sound trace. More information in the knowledge article: RPM Extraction in Simcenter Testlab.
3. Overall Level and Order Sections
Now order cuts and overall levels can be calculated from the spectral map. There are specific methods that are used to calculate orders and overall levels. They must be added to the process and connected to the Spectral map method.
Two additional ways of connecting methods are shown in Figure 10 below:
Figure 10: Top – Order sections method can be connected to Spectral map by dragging and dropping the method on top of Spectrum map. Bottom – Click on a method once to add it to the process.
Once the additional methods are added to the process, right click in the process area and choose “Auto Arrange” to make them orderly as shown in Figure 11.
Figure 11: Right click in the process area background and choose “Auto Arrange” to make methods orderly.
Set the orders to be calculated from the spectral map in the “Properties” of the Order sections method as shown in Figure 12.
Figure 12: Enter the orders to be calculated separated with semi-colons, using Automatic as the channel selection mode automatically uses the same rpm channel defined in the previous spectral map method.
Setting “Channel selection mode” to “Automatic” means that the tracking method and channel specified by the Spectral map process will also be used for the order section analysis. The mode and bandwidth affect the amplitude of the calculated orders.
More information about processing orders and overall levels in the knowledge articles:
Next add the “Run average” method to the end of the process as shown in Figure 13:
Figure 13: Process with Run average method added.
The “Run average” method is used to calculate statistics upon the processing results over multiple runs. For example, if 1st order was calculated from three different runs, the average/minimum/maximum of the 1st order between all three runs can be calculated.
In the Properties of the Run average method, select the desired statistics. In this example, the minimum, maximum, and average will be calculated (Figure 14):
Figure 14: The average, minimum, and maximum of all functions will be calculated from multiple runs.
If interested in performing six sigma analysis, standard deviations can also be calculated.
Other options include:
Average type: Different schemes can be used for the averaging including energetic, linear, linear amplitude (no phase), etc.
Result X- Axis values: The different runs may not have the same X-axis spacing. This option allows the user to select which axis to use to interpolate the results.
Result X-axis range Choose between “Union” and ‘Intersection”. Intersection will produce results to common range between all results, whereas Union will cover the full range. For example, while an individual run may go from 1000 to 3000 rpm, and the common range is 1500 to 2000, then intersection will produce results from 1500 to 2000, while union would be from 1000 to 3000 rpm.
With the data runs in the input basket and the process created, press the “Run” button in the lower left to run the process (Figure 15):
Figure 15: In the Process ribbon, choose either “Manual” or “Auto” to determine how results are stored immediately after the calculations are finished.
After the calculations are finished, the results are stored either in the project file or “Active Analysis”.
6.1 Results Storage
Where to view the results depends on whether “Manual” or “Auto” is set under the ‘Process” ribbon (Figure 16):
Figure 16: In the Process ribbon, choose either “Manual” or “Auto” to determine how results are stored immediately after the calculations are finished.
If the Process ribbon is on “Manual”, the results are not stored immediately in the project. They are temporarily placed in the “Active analysis” where it can be viewed (Figure 17).
Figure 17: With the “Manual” setting, results are temporarily stored in the “Active Analysis” where they can be viewed until they are either accepted or rejected.
After viewing the results, pressing “Accept” will store the data in the active project and section. Pressing “Reject” does not store the data.
If the Process ribbon is set to “Automatic”, results will be stored directly in the project.
6.2 Results Viewing
With the results in either the project or active analysis, there are a lot of data and different ways to view the data. In this case, there are 3 runs, 6 orders plus an overall level, and 5 channels. That is at least 105 individual functions to view.
One way of viewing is to use the “List” view of the “Home” ribbon as shown in Figure 18.
Figure 18: List View requires clicking into individual folders to find data for viewing.
The “List” view requires clicking into the individual folders to find the specific data that is desired to be viewed.
Another type of view is the “DOFID vs Function” as shown in Figure 19 below.
Figure 19: The “DOFID vs Function” view shows all data in a summary table from the highlighted level in the project.
With the “DOFID vs Function” pivot table, highlight a specific level of project. All data from that level of the project hierarchy and below will be in the summary table. The summary table contains cells with numbers. The numbers reflect the number of data functions that meet the criteria in the table.
In this case, the “6” in the cell means that there are 6 overall levels available: an overall level from each run, and the maximum, minimum, and average overall level of the three runs.
The legend in the display can be updated with useful information like the “Run Name”. Right click on the legend and choose “Options”. Find “Run name” in the list (Hint: Type in the ‘Quick find’ the word “run”) and move it from the Available fields (left side) to the Selected fields (right side) of the display. This is shown in Figure 20 below:
Figure 20: To add the run name to the legend, right click on the legend and choose “Options”, then find “Run name” in the available columns and use the arrow to put it on the Selected side.
Other attributes that can be helpful to put in the legend include:
Average Runs: List of runs used in the run statistics
Run average statistical method: How the run statistic was calculated. Average, minimum, maximum, etc.
One of the cells has “36” in it – there are 6 orders from 6 different runs. Displaying all 36 orders may not make sense.
To break out the individual orders, click on the “+” in the pivot table and add “Section value” to the table as shown in Figure 21.
Figure 21: In the Pivot Table, click on the + to add additional properties for sorting the data. For example, “section value” is used to separate the data by order number.
After “section value” is added to the list, the 36 pieces of data are broken out into 6 groups of 6 orders each as shown in Figure 22.
Figure 22: After adding "Section Value" to the Pivot Table, each order can be viewed separately.
Additional parameters can be added to the pivot table like the run name.
There is a small triangular pulldown on the attributes that can be used to filter by the data attributes as shown in Figure 23.
Figure 23: Clicking on the down arrow at the head of a column in Pivot Table allows a subset of the data to be selected.
More information on the pivot table and displays in the following knowledge articles: