Simcenter Testing Solutions
Simcenter Testlab Array Data Reporting
Microphone arrays are fast and reliable tools to localize sound sources and quantify their contribution. Array data measurements are straight-forward: the array is pointed at the object under test, and microphone data, pictures and video images are all measured in a single shot. Analyzing individual runs requires a little bit of expertise, although the process itself is quickly understood.
But how to be more efficient and productive, when the goal is to analyze and compare multiple datasets or frequency ranges at the same time? This article gives some common processing and analysis scenarios.
Contents: 1. Loading Array Data Reporting 2. How to get an overview of sound sources? 3. How to display multiple results? 4. How to compare different datasets? 5. How to display and compare sound power results? 6. Interested in more?
1. Loading Array Data Reporting
Array Data Reporting is a powerful tool to analyze microphone array data. It is targeted on efficiently selecting, displaying, and comparing data from Simcenter Testlab HD Acoustic Camera and Simcenter Testlab 3D Acoustic Camera workbooks.
Array Data Reporting consist of two Simcenter Testlab add-ins, Array Data Selection & Comparison, and Array Batch Processing:
The Array Data Selection & Comparison add-in is a free add-in on Desktop and can be considered the ‘desktop for Sound Source Localization’.
These two add-ins are turned on under "Tools -> Add-ins" in the main Simcenter Testlab menu as shown in Figure 1:
Figure 1: The add-ins "Array Data Selection & Comparison" and "Array Batch Processing" if found under "Tools -> Add-ins".
After loading these two add-ins, a new worksheet will pop up called ‘Array Data Reporting’. It consists of two tabs, called "Array Data Selection" and "Array Data Viewer" as shown in Figure 2.
Figure 2: ‘Array Data Reporting’" worksheet consists of two tabs, called "Array Data Selection" and "Array Data Viewer"
In the Array Data Selection tab, multiple array databases (*.bdd files) can be loaded. Existing calculated results are visible in the Results list. New lines can be added with different processing parameters for time segment, frequency range, and calculation method. Lines for which a result is not calculated are marked ‘NOK’. By using the Start calculation button – that’s actually the Array Batch Processing add-in – the results will be calculated. Depending on the additional processing add-ins that are available, such as Enhanced Resolution, also advanced processing results can be calculated.
Once the results are calculated, the results can be viewed in the Array Data Viewer tab. Up to 12 resulting holograms can be viewed in a single view, in a grid of 3 rows by 4 columns. Users can choose an auto-arrangement of the first 12 results or assign results to specific displays as shown in Figure 3.
Figure 3: ‘Array Data Viewer’" tab can visualize twelve holograms in a 3x4 grid.
In this article we’ll have a look at the following common processing scenarios:
How to get an overview of sound sources?
How to calculate multiple results?
How to compare different datasets?
How to display and compare sound power results?
2. How to get an overview of sound sources?
A quick way to get an overview of sound sources is to display a series of 3rd octave bands. With 12 available displays, that means that for example all 3rd octave bands from 400Hz to 5000Hz can be viewed in a single display grid of 4 by 3.
Expand the result, so that they appear as separate entries in the results list
Display will automatically arrange the results in the 4x3 grid
3. How to display multiple results?
The next scenario is how to calculate and display multiple results in one or more datasets. That could be for example to localize sources belonging to different peaks in a spectrum. Or for non-stationary events, different time segments in the same recording.
The video below shows how to create multiple results:
The spectrum display shows the averaged Array spectrum: that gives an overview of the phenomena captured by all microphones. This can be done for mulitple array databases, making it easy to find the differences
The time display can be switched from Time to Colormap: a colormap of time-vs-frequency gives a very good overview of all the sound phenomena that are present in the data
Time segments and frequency ranges can be set for multiple results at the same time
In the Array Data Viewer, Ctrl-A selects all displays. A single display can be selected with Shift-Click. The same operation is used to deselect.
Once multiple holograms are selected, the properties of all displays can be changed in a single operation. The hologram can be zoomed with the mouse wheel or moved; it will be applied to all selected holograms. Also, the scales can be aligned for all selected displays are the same time.
4. How to compare different datasets?
The next scenario extends the previous one and shows how to compare multiple results over one or more datasets.
When analyzing multiple datasets, that could be to do a comparison before/after a modification, or to compare different design variants.
Apply the same processing, but to different results
Organize results in the 4x3 grid
5. How to display and compare sound power results?
The final scenario shows how to process sound power results, and how to define and compare groups of different components.
When the Enhanced Resolution add-in is loaded, it’s possible to process with any of available advanced methods: iNAH, Bayesian Focusing, CIRA and Clean-SC. What they all have in common is that they produce sound power results. That can be used to quantify the contribution of a specific components, or even the whole object, by means of a microphone array.
In Array Data Reporting that’s done by first changing the processing result from Pressure to Power (Pressure/Power column) and set the method to any of the available methods (Method column). In the example below it shows Bayesian Focusing. Afterwards it is then possible to define groups and display as sound power spectrum (Type column), which will add an additional 2D graph.