LMS Test.Lab Throughput Processing Tips
Data processing can be an arduous task, but it does not have to be! Here are some tips for navigating the processing settings and organizing results.
In LMS Test.Lab, any time data can be analyzed using the Time Data Processing worksheet (Picture 1) which is located at the bottom of the screen.
This worksheet can be accessed via Tools -> Add-ins -> Signature Throughput Processing (Picture 2).
After pressing “OK” in the Add-in menu, the Time Data Processing worksheet should appear as a new worksheet at the bottom of the screen. Any data selected in the Time Data Selection worksheet can be processed.
See the article below are three tips for using throughput processing:
1. Measurement mode: Stationary versus Tracked
In the Time Data Processing worksheet, a major data processing choice is made by selecting either ‘Tracked’ or ‘Stationary’ measurement mode under “Change Settings” in the “Acquisition Parameters” section.
One can select between ‘Tracked’ and ‘Stationary’ measurement mode (Picture 3). Depending on which one is selected, the processed data results will be very different.
When ‘Stationary’ Measurement mode is selected, the processed results consist of a single averaged spectrum for each time data channel (Picture 4).
When should stationary mode be used?
Imagine that the issue you are tasked with occurs only when the engine is at 2400 rpm. You can measure using the stationary method at 2400 rpm for 30 seconds. The results will show you a single spectrum revealing the highest amplitude frequencies so you can apply damping or other countermeasures to solve the issue.
In stationary mode, one can specify free run averaging with a specific overlap. Different types of averaging methods (maximum, minimum, average, etc) can also be selected.
Setting ‘Tracked’ for the measurement mode results in several spectra at user defined increments. With this mode it is easy to visualize how the data changes as a function of time, rpm, or angle (Picture 5).
Imagine you work for an automotive manufacturer and customers are complaining about a noise they hear while driving. You are tasked with solving the issue but the only information you are given is that the noise gets worse as engine rpm increases. You can instrument the vehicle with accelerometers, microphones, and an engine tachometer on the drive shaft. Using the tracked method, you can identify any high amplitude signals that change with engine rpm. In throughput processing, one can perform order analysis.
Tracked processing: Increment and Frame Settings
Often when using tracked processing, a tachometer is specified as a tracking channel (Picture 6). For example, one might process data from 1000 to 3000 rpm in increments of 25 rpm using the tachometer tracking channel.
Tracked processing results in a buildup of several frequency functions, usually calculated spectra, and are often displayed in three dimensional plots called waterfalls (Picture 7) or colormaps. Each curve in the waterfall display is a separate processing calculation (or measurement), taken from the raw time data. It is calculated based on user defined acquisition parameters, namely the increment and frame size.
Increments are the intervals between frame calculations. These intervals are usually either time or rpm based. For example in the Picture 7, a spectrum is calculated every 25 rpm, therefore our increment is 25 rpm.
If tracking on time, the increment is the time interval (in seconds) between acquisitions.
Picture 8 illustrates points of data acquisition in time at 1 second, 2 second, and 0.25 second increments.
The frame size is the how much data is used for a calculation at each interval. For example, an increment of 0.5 seconds and a frame of 1 second, would result in overlap processing of 50%.
When windows, such as Hanning windows, are used they are applied to the frame.
The relationship between the size of the increment and the size of the frame determines what data is used for processing. Depending on the setting, it is possible that some data will not be used (ie, data “gaps”) or that some data will be used multiple times (ie, data “overlap”).
One frame of data is collected, modified with a window, and reported as a single data point. The increment is the time between these data points.
When the frame size and increment match, all data are processed with no overlap, meaning no missed data (Picture 11). However, if there was a window applied, an amplitude and/or energy error could occur. This is because a Hanning window zeros much of the data at the beginning and end of the frame. If a large event coincided with the beginning of a frame, the Hanning window would significantly reduce the amplitude.
Using a frame size larger than the increment can help with that (Figure 12). The ‘overlap’ allows more averages within the time duration of the test and helps reduce the error associated with the window.
The combination of the frame size and increment determines the overlap. For example, frame size of 1 second, with a 0.5 second increment, corresponds to a 50% overlap.
2. Data Naming
By default the results from a Throughput Processing calculation are saved into the active section under a new run name. The default is “Tp” which is an abbreviation of “Throughput Processing”.
When looking back at processed data, if they are all named “Tp 1”, “Tp 2”, “Tp 3”, rather than “Run 1 with High Load”, “Run 2 with Medium Load”, “Run 3 with Low Load”, it can be difficult to tell which run the data came from originally, which is useful information when analyzing and reporting.
The button next to the Name field opens the ‘Results destination options’ window (Picture 13). If the ‘Run name’ setting is changed to ‘Run Name Postscript’ the results will be saved into a new run as before, but with the new run name appended to the original run name making it easy to tell where the data came from as shown in Picture 14.
If data was processing without the ‘Run Name Postscript’ enabled, one can still find the original run name in the data properties.
Right click on any processed data and select “Properties” to see information like:
3. Original Section versus Active Section
Take a LMS project with two sections: ‘Baseline’ and ‘Modified’. Three data acquisition runs were performed in a baseline condition, and three runs were done in a modified condition.
Both the ‘Baseline’ and ‘Modified’ section contain runs with the same name: “Run 1”, “Run 2”, and “Run 3” as shown in Picture 16.
If all six runs are processed at once, the default “Active section” setting in Throughput processing would create multiple runs of similar names in one section (Picture 17). This is confusing, because it is not clear which runs are associated with ‘Modified’ and which as associated with ‘Baseline’.
When performing throughput processing, there is an important setting that can avoid this confusing situation (Picture 18). The ‘Save Destination’ can be changed from the default ‘Active Section’ to ‘Original Section’.
After processing the data, it is clear which data is from the ‘Baseline’ section and which data is from the ‘Modified’ section as shown in Picture 19.
Note that if “Original Section” is selected, one must have the original project open.
Time files that are located outside the currently opened project cannot be processed with the ‘Original Section’ setting. This is because processed data can only be stored in the currently open project.
Hope you find these tips helpful for using Throughput Processing!
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