When performing a Fourier Transform, there are several types of spectral functions that can be computed. Two of these functions, Autopower and Spectrum can yield very different results.
When selecting between the two functions, as shown in Figure 1, great care should be taken to understand how the functions are calculated, and how the results can vary.
Results can be affected by amplitude, phase, and averaging. This article explains the background and differences between the two functions and when to use them.
Background
Both the Spectrum and Autopower functions produce results of amplitude versus frequency.
The main difference between the two functions is in the handling of phase:
Figure 2 shows a Spectrum and an Autopower for the same signal:
In Figure 2, a single average was performed, and the amplitude portion of both functions is identical. The only difference is that the Spectrum has phase, while the Autopower does not contain phase information (phase is zero at all frequencies).
To understand how important the phase can be when processing spectral data, it is helpful to review the Fourier Transform and how it handles phase.
Fourier Transform and Phase
When performing a Fourier Transform of any time signal, it is broken down into a unique set of individual sine waves. These sine waves, when summed together, equal the original time signal (Figure 3).
Each individual sine wave not only has an amplitude, but has a phase value as well. Both the phase and amplitude values are uniquely determined for each sine wave by the Fourier Transform. The amplitude and phase values are determined so that sum of the sine waves is equal to the original signal.
Because every signal is a collection of single sine waves, much of this article shows examples using single sine waves.
Take the two sine waves in Figure 4. They have the same amplitude, but the phase is different by 45 degrees.
The phase is relative to the value at the beginning of the time block. In Figure 4, the red sine wave is considered to have zero degrees phase and the blue sine wave is considered to have 45 degrees phase.
This shift in the time domain is evident in the Fourier Transform of both signals as shown in Figure 5.
The fact that the Spectrum preserves differences in phase while the Autopower function does not, are key to understanding when to use one or the other.
The next section covers how a Fourier Transform is related to a Spectrum or an Autopower.
Mathematical Difference between Spectrum and Autopower
In many digital signal processing algorithms, the Fourier Transform results in a double sided spectrum which is mirrored about 0 Hertz. This mirroring around zero Hertz is eliminated, so the Spectrum (S_{x}). only contains frequencies from 0 Hertz and higher. The Spectrum is a complex function having both amplitude and phase, which can be expressed as real and imaginary (a+ib), versus frequency.
The Autopower (G_{xx}) goes one step further and performs a multiplication of the complex conjugate of the Spectrum as shown Equation 1. This conjugate is calculated separately at each frequency line in the Spectrum.
By performing the complex conjugate operation, the Spectrum becomes an Autopower function which only contains amplitude, but is without phase.
The complex conjugate leaves the units squared (Example: g^{2} or power units). It is common to take the square root so that linear units are restored (Example: g). This is called a ‘Autopower Linear’ function. ‘Linear’ indicates the square root was performed after the complex conjugate multiplication.
Selecting either Autopower or Spectrum is also an important consideration if averaging of multiple functions or samples will be performed, which is discussed in the next section.
Averaging Considerations
In Figure 6, the time domain and frequency domain of two different sine waves are shown. The two sine waves are 180 degrees out of phase.
If the two sine waves are averaged, the result would be zero. Whether performing the average in the time domain or in the frequency domain, the average would be zero. Using a Autopower, however, it can be made so the average will not be zero in the frequency domain.
In Figure 7, the Autopower of both sine waves is shown. Notice that the phase of the Autopower of both sine waves is zero, and identical. The phase of the Autopower in the frequency domain is the same, even though the two sine waves are clearly out of phase in the time domain.
In this case, while the average in the time domain would be zero, the average of the Autopower functions in the frequency domain would be correct. The average would not be zero in the frequency domain, thanks to the Autopower function!
Correct Amplitude by Eliminating Phase
How is the correct amplitude of the average made possible by the Autopower function? How does eliminating phase do this? Figure 8 contains an illustrative example. For clarity, the example is based on time data, but it holds true in the frequency domain:
In fact, in this example, the two squared time functions are completely identical for a very consistent average.
In practice, the average of a Spectrum is not always zero after two acquisitions. For example, when measuring a broadband random signal, the amplitude of the signal is reduced gradually with averaging. The more averages, the lower the amplitude as shown in Figure 9.
Some observations:
Using a Spectrum function, the amplitude gets progressively lower by averaging! Since getting the correct amplitude is of importance, the use of averaging with a Spectrum should be avoided, unless special precautions have been taken to assure the phase is consistent (i.e., a trigger or something similar).
Phase Referenced Spectrum
What if correct amplitude, phase, and averaging are desired? For example, an Operational Deflection Shape (ODS) analysis requires correct amplitude and phase with averaging:
The best alternative is an option called Phase Referenced Spectrum.
With a Phase Referenced Spectrum, instead of relying on the phase relative to start of each acqusition, a different type of phase will be used. The phase between different data channels on a vibrating structure will be used instead to make averaging possible.
Consider the vibrating structure animation in Figure 10:
By taking advantage of the fixed phase relationship between different locations on a vibrating structure, it is possible to do averaging, even using a Spectrum function.
With a Phase Referenced Spectrum one measurement location of a multiple channel acquisition is designated as the phase reference. The reference channel is used to keep the phase consistent between all channels to allow averaging.
Data was acquired on the vibrating structure and is shown in Figure 11:
Even though all the sine waves shown have the same amplitude, any resulting average will not have the correct amplitude.
The phase referenced spectrum will make this data consistent so it can be averaged by (Figure 12):
Because there is a fixed relationship in phase between the data channels and the reference channel, the inconsistent data will be made consistent, as shown in Figure 12.
This allows the averaging to be done properly and results in the correct amplitude value. Of course, at frequencies where there is no relationship between channels, this will not be the case.
For example, phase referencing will not work with data channels being acquired on a vehicle if the phase reference channel is on the laboratory floor. The phase reference channel instead should be a data channel on the vehicle that is very active.
Will the phase referenced spectrum and an autopower have exactly the same amplitude Probably not. Any random vibration in the structure that has no fixed phase relationship to other locations will be averaged out. So there can be differences depending on how much the vibration of different locations on the structure are related to each other.
Note that this example is shown for one frequency in the time domain for illustrative purposes. The ‘Phase Referenced Spectrum’ will work on all frequencies independently in the spectrum. The amount of phase subtracted is not always 0, 90, or 180 degrees. It can be any phase amount (33, 48, 56 degrees) that is present in the vibrating structure between different locations.
Phase Referenced Spectrum in Simcenter Testlab
To calculate a Phase Referenced Spectrum in Simcenter Testlab (formerly called LMS Test.Lab), change the function to ‘Spectrum’ and click on the checkbox next to ‘Phase Referenced Spectrum’ as shown in Figure 13.
Under ‘References’ click the ‘Define…’ button and select a single channel to use as a reference.
Conclusions
A Spectrum and Autopower are both functions of amplitude versus frequency. In the case of Spectrum, the phase is also preserved, while with an Autopower it is not.
Enjoy Spectrums and Autopowers!
Questions? Post a reply, email peter.schaldenbrand@siemens.com, or contact Siemens PLM GTAC support.
Digital Signal Processing
Thanks for the information.
Really very useful this tutorial.
Well, respect at this subject. I had make some experimental tests with NI DAQ Systems and recorded the measurements obtained of these tests, keeping one fixed sensor as reference and 7 roves sensors and my doubt is: With the imported measurements into LMS Test.Lab to animate the ODS, how to adjust the phase of the fixed sensor, to have correct animations ODS?. Because, althougth I use the reference sensor, for example in three tests, the measurements recorded of this reference sensor don't have the same phase (according this tutorial). I can't use Siganture Adquisition beacuse I have imported data, and for that, I can't check "phase reference spectra" box. I will be very gratefully if can help me.
Grettings
Alvaro Cotaquispe
Alvaro,
Sounds like you need to use Signature Throughput Processing. You start with a already recorded time file and re-process your data.
In the Channel Processing Settings, you can select Spectrum and Phase reference, for re-processing data from an already recorded time file.
Really I'm grateful for your answer, so that help us to lose the fear to understand the software hehehe.
I'm feel more happy to have get this software, is really fantastic it perforrmance and relativity easy to use it with your help.
Congratulations for this great contribution to the enginering maintenance.
Grettings
Alvaro
Hi friends!
I'm using Operational PolyMAX Modal Analysis (Add-in) to identificate natural modes of my model of a plate. By four tests in differents times (keeping two sensors and roving six sensors around the plate each time) I obtained the measurements and when I upload the measurements to make the Operational PolyMAX Modal Analysis, I need to use the Phase Referenced Spectrum too? I think of yes, because at each test (four), the reference sensors (two) aren't in phase, but I don't find this option in the Operational PolyMAX Modal Analysis (Add-in). In addition, the time waves recorded of the references sensors for each test are differents (not only in phase, in amplitud and shape too, obiously) there is not problem with that rigth?
Or maybe I should use the Signature Throughput Processing Add-in to calculate the Crosspower PSD (considering the Phase Referenced Spectrum) and then go to PolyMAX to identificate the modes shapes and can animated correctly.
Grettings
Alvaro
can you explaine shock responce sepctrum (SRS)?
Did you look at FAQ 340 on the GTAC website? It's titled: How to use the SRS option in the Conditioning Toolbar?
In rev 17 of LMS Test.Lab, you can search the FAQ's from the Help and Search Manuals, Theory and FAQ menu pick to find the same FAQ 340. It is also described in the Help for Mission Synthesis.