Experimental verification of novel spectral analysis algorithms
for Laser Doppler Anemometry data.
P. Gjelstrup, H. Nobach, F.E. Jørgensen1
K. E. Meyer2
12Dantec Measurement Technology A/S
Dept. of Energy Engineering, Technical University of Denmark

Abstract
Two novel algorithms for estimating turbulence power spectra from Laser Doppler Anemometry (LDA)
data, the Refined sample and hold reconstruction (RR) and the Improved slot correlation (SC), have beentested on two test cases: grid turbulence and cylinder wake flow.
The algorithms were developed by Nobach et al. (1998), and van Maanen et al (1999) as a follow up on abenchmark comparison of some 15 algorithms reported by Benedict et al (1998). They were tested on
simulated data generated from a known input spectrum, which was then used as a reference for evaluationof the algorithms.
In the present work, an experimental evaluation has been carried out, using reference spectra obtainedwith a Constant Temperature Anemometer (CTA), to evaluate spectra based on the RR, the SC and thetraditional sample-and-hold reconstruction and resampling (S&H) algorithms.
It is shown, that RR and SC produce correct spectra up to frequencies above the data rate, whereas S&H,
produces low-pass filtered spectra with a cut-off frequency corresponding to the data rate divided by 2π,
the so-called the particle rate filter effect first reported by Adrian and Yao (1987). They recommended
that data rates of 20 times the highest frequency of interest should be used for S&H.
The RR and SC thus have great relevance because they make it possible to obtain correct turbulence
spectra at much lower data rates than with S&H. The practical implications of this are that less seeding isrequired, and that smaller lasers may be used.
Since RR is much faster than SC, and they produce very similar results, Dantec’s LDA software has been
extended with an on-line implementation of the RR algorithm.
The figure below compares the spectra obtained using CTA, and the RR, SC and S&H algorithms, for thecylinder wake flow.
Cylinder wake turbulence, 4 kHz data rate
1.E+00spectral power

1.E-01
rr high dr

1.E-02

sc high dr1.E-03

s&h high dr

1.E-04CTA

1.E-05
1.E-0610100

1000
frequency [Hz]10000100000

Fig. 1: Comparison of RR, SC and S&H LDA spectra with a reference CTA spectrum

Page 1

Introduction
Measurement of turbulence spectra using the LDA technique has been a challenge for many years. The
often used S&H algorithm suffers from the particle rate filter effect reported by Adrian and Yao (1987).
They recommended a validated data rate of at least 20 times the frequency range of interest.
The results presented in the present paper show that with SC and RR, a data rate of the same order ofmagnitude as the frequency range of interest is sufficient. This is of great practical importance, because inmany cases it is impossible to inject enough seeding into a flow to obtain the very high data rates required
for the S&H method.
Additional advantages of the new techniques are that there are no systematic errors at high frequencies(particle rate filter) or at low frequencies (aliasing errors). This prevents misinterpretation such as
interpreting low pass filtered noise as a turbulence spectrum.
CTA is recognised as the reference for the measurement of turbulence spectra. For each test case, a CTA
measurement was made in order to get a reference spectrum. Since the velocity signal from a CTA iscontinuous, equidistant sampling of the low-pass filtered signal and classical spectrum analysis using theFast Fourier Transform can be used. The spectra produced from LDA data by the different algorithms canthen be assessed by comparison with the CTA spectra.
In the literature, numerous algorithms for spectral analysis of non-equidistantly sampled velocity datahave been reported. Some of the challenges are: signal reconstruction minimising bias and variance of thespectrum estimators, overcoming the effects of the particle rate low pass filter, and, not least, computing
efficiency. RR is much faster than SC, so for the purpose of selecting a method for integration into LDA
data processing software it is important to compare the results of the two.
This paper compares the results using
1. the RR algorithm
2. the SC algorithm
3. the S&H algorithm
All three were tested on high and low data rate data sets, and the results are compared with FFT processed
CTA data from the same flows.
Two test cases were chosen to test different aspects:
Grid turbulence, which produces a broad band spectrum with a slope of –5/3 in the inertial subrange anda steeper slope in the dissipation range. CTA is capable of measuring this very well, but LDA spectra
usually have the noise floor somewhere in the inertial subrange.
A cylinder wake flow has a pronounced peak in the turbulence spectrum due to vortex formation. The
frequency of the peak can be predicted based on the Strouhal number. The cylinder dimension and flow
velocity were chosen to produce this peak at 1 kHz. The tested data rates were 4 kHz and 0.4 kHz, i.e.
above and below this frequency, in order to demonstrate the performance of the algorithms depending on
the data rate.

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Experimental set-up
The experiments were carried out in a closed loop wind tunnel. The test section had a cross section of 300
× 300 mm.
Two sets of measurements were carried out, in both cases using a free stream velocity of 30 m/s. The firstset of measurements were made 133 mm downstream of a rectangular grid made of 1.5 mm diameter wirewith a spacing of 6.5 mm.
The second set of measurements was made 26 mm downstream of a 6 mm diameter cylinder placed
perpendicular to the flow direction. The Reynolds numbers are for both cases (based on grid spacing andcylinder diameter, respectively) about 12000. For each case, measurements were first made with CTA andthen repeated with the LDA measuring volume positioned in the same position. For the LDA
measurements the air was seeded with atomised droplets of glycerine with a size of approximately 2 µm.
The LDA consisted of Dantec two-component FiberFlow optics mounted on a two-axis traverse, twoBSA enhanced processors, and BSA Flow Software. A 5 W Coherent Innova 90 Argon-Ion laser wasused, running at 2 W (all lines). Only the 514.5 nm wavelength was used, measuring the velocity
component in the main flow direction. The system was operating in back scatter mode.
The CTA was a Dantec StreamLine system. For grid turbulence, a 55P11 single wire probe was used.
For the cylinder wake flow, a 55P61 X probe was used to resolve the horizontal and vertical velocity
components, and the horizontal component was compared to the horizontal component measured byLDA.
Table 1 compares the measurement volumes of the LDA and CTA systems.
Table 1: measurement volume dimensions
LDA
2.5 × 0.15 × 0.15 mm3CTA
55P11 probe
1.2 × 0.005 × 0.005 mm355P61probe
0.8 × 0.8 × 1 mm3

The hot-wire signal was passed through a signal conditioner with adjustable gain, offset and low passfilter cut-off frequency before being sampled using an A/D converter. Dantec StreamWare software
controlled the A/D converter and converted the conditioned data to velocity data. The velocity data wereprocessed using sample-and-hold reconstruction and FFT for the spectral analysis.
The same software was used to process LDA data, giving the possibility to compare the same algorithm(sample-and-hold reconstruction and FFT) on equidistantly sampled and non-equidistantly sampled data.
The LDA data were also processed in a separate program, computing the spectrum based on the SC or theRR algorithms.

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Results
Grid turbulenceFigs. 2 and 3 show RR, SC and S&H processed LDA data taken with 4 kHz and 0.4 kHz data rate
respectively, with the CTA spectrum as reference.
Grid turbulence, 4 kHz data rate
1.E-02

spectral power

1.E-03rr high dr
1.E-04sc high dr
s&h high dr

1.E-05CTA
1.E-06
1.E-07
10100

1000

10000

100000frequency

Fig. 2: Grid turbulence, 4 kHz data rate LDA spectra compared with CTA spectrum

Grid turbulence, 0.4 kHz data rate
1.E-02

spectral power

1.E-03rr low dr

1.E-04sc low dr
s&h low dr

1.E-05CTA
1.E-06
1.E-07
10100

1000

10000

100000frequency

Fig. 3: Grid turbulence, 0.4 kHz data rate LDA spectra compared with CTA spectrum
The RR and SC spectra were based on 10 blocks of 100000 samples each. The S&H spectra were updated
during acquisition, and were stable with 20000 or more samples. Therefore, the S&H spectra are based on100000 samples.
The CTA data reveal both the inertial subrange and the dissipation range slopes.

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The RR and SC spectra are in excellent agreement with the CTA till 5 to 6 kHz (4 kHz data rate) and till 3
to 4 kHz (0.4 kHz data rate). The RR spectra have slightly higher variance at high frequencies than theSC.
The S&H spectra are cut off from data rate/2π as described by Adrian and Yao. They also predicted thatS&H would increase the energy content of the low frequencies as data rate decreases. This is clearly seenin the data.
Correct estimation of the turbulence spectrum using S&H would have required data rates of 100 kHz ormore, which is often impossible in practice.

Comparison of 4 kHz and 0.4 kHz data rate for RR
Grid turbulence
1,E-02

spectral power

1,E-03rr low dr

1,E-04rr high dr
1,E-05CTA

1,E-061,E-07
10100

1000

10000

100000frequency

Fig. 4: Grid turbulence, 4 and 0.4 kHz data rate RR spectra compared with CTA spectrum
The comparison shows that the variance of the spectrum is higher for the low data rate case than for thehigh data rate case, and the noise floor is also higher. The SC shows the same characteristica.

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Cylinder wake
Based on the Strouhal number the frequency of the vortex shedding behind the cylinder can be predicted
to be 1000 Hz.
Figs. 5 and 6 show S&H, RR and SC spectra with 4 kHz and 0.4 kHz data rate respectively, with the CTA
spectrum as reference.
Cylinder wake turbulence, 4 kHz data rate

1.E+00spectral power

1.E-01
rr high dr

1.E-02

sc high dr

1.E-03s&h high dr

1.E-04CTA

1.E-05
1.E-0610100

1000
frequency [Hz]10000

100000Fig. 5 Cylinder wake turbulence, 4 kHz data rate LDA spectra compared with CTA spectrum
Cylinder wake turbulence, 0.4 kHz data rate
1.E+00spectral power

1.E-01s&h low dr

1.E-02CTA

1.E-03rr low dr

1.E-04sc low dr

1.E-05
1.E-0610100

1000
frequency [Hz]10000

100000Fig. 6 Cylinder wake turbulence, 0.4 kHz data rate LDA spectra compared with CTA spectrum
The CTA data show two distinct peaks at 1 kHz and 2 kHz, corresponding to the vortex shedding
frequency and a harmonic.
The RR and SC spectra capture these peaks both at high and at low data rate. For clarity, a graph zoomed
in on the frequency range 100 to 10000 Hz for the low data rate case, is shown in fig. 7. It shows that theRR and SC overestimate the peaks compared to the CTA. This may be due to differences in themeasurement volume size between the LDA and CTA systems, see table 1.
The S&H spectrum falls off due to the particle rate filter effect, captures the main peak (with data rate 4kHz) but not the harmonic, and it shows too high energy at low frequencies.
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Cylinder wake turbulence, 0.4 kHz data rate
1.E+00spectral power

1.E-01
1.E-02

rr low dr

1.E-03

sc low drCTA

1.E-04
1.E-05
1.E-061001000
frequency [Hz]10000

Fig. 7 Cylinder wake turbulence, 0.4 kHz data rate: frequency axis zoomed in on the peaks

Comparison of 4 kHz and 0.4 kHz data rate for RR

Cylinder wake turbulence
1.E+00spectral power

1.E-01
1.E-02

rr low dr

1.E-03rr high dr

1.E-04CTA

1.E-05
1.E-06
10100

1000

10000

100000frequency [Hz]Fig. 8 Cylinder wake turbulence, 4 and 0.4 kHz data rate RR spectra compared with CTAspectrum
The high data rate spectrum agrees quite well with the CTA spectrum up to 4 to 5 kHz, after which theLDA spectrum reaches its noise floor.
The low data rate spectrum has higher variance than the high data rate spectrum, and slightly
overestimates the spectrum (but still performs much better than S&H, high data rate). It is important to
notice that the spectrum is still reasonably good up to four times the data rate.
The low data rate spectrum has its noise floor at a higher level than the high data rate spectrum, asexpected.
Page 7

Conclusion
It has been shown that the two new algorithms Refined sample and hold reconstruction (RR), and Slotcorrelation (SC), are well suited to compute turbulence spectra from LDA data. The required data rate isin the same order of magnitude as the frequency range of interest. The traditional Sample and hold andresampling (S&H) requires 10 to 20 times higher data rate to minimise the particle rate filter effect.
It has further been shown that RR produces results which are very similar to SC. Because RR is much lesscomputation intensive, it is well suited for on-line data analysis during experiments. Dantec has therefore
implemented this algorithm in its LDA data analysis software.
The two reported test cases have most of their energy content in the frequency range up to 10 kHz. Data
rates in this range can be obtained experimentally in most cases. The traditional method requires at least
100 kHz data rate to cover the same frequency range, which is difficult to obtain in practical experiments.

References
Adrian, R. J. and Yao, C.S.: Power spectra of fluid velocities measured by laser Doppler velocimetry.
Exp. in Fluids, 5:17-28. 1987
Benedict, L. H., Nobach, H. and Tropea, C.: Benchmark tests for the estimation of power spectra fromLDA signals. Proc. 9th Int. Symp. on Appl. of Laser techn. to Fluid Mechanics, Lisbon, Portugal, Paper
32.6. 1998.
Nobach H, Müller E and Tropea C: Efficient estimation of power spectral density from laser Doppler
anemometer data. Experiments in Fluid vol. 24, no 5/6, pp. 499-509. 1998
Van Maanen, H.R.E., Nobach, H., and Benedict, L.H.: Improved estimator for the slotted autocorrelation
function of randomly sampled LDA data, Meas. Sci. Technol. 10, L4-L7. 1999.

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