AiMT Advances in Military Technology
Vol. 1, No. 2, January 2007
Digitized Two-Parameter Spectrometer for NeutronGamma
Mixed Field
Z. Matěj1
, J. Cvachovec1*
, F. Cvachovec2
, and V. Přenosil1
1
Faculty of Informatics, Masaryk University in Brno, Czech Republic
2
University of Defence, Brno, Czech Republic
The manuscript was received on 2011 and was accepted after revision for publication on 2012.
Abstract:
This paper shows the results of digital processing of output pulses from combined
photon-neutron detector using a commercially available digitizer ACQUIRIS DP 210.
The advantage of digital processing is reduction of the apparatus in weight and size,
acceleration of measurement, and increased resistance to pile-up of pulses. The neutron
and photon spectrum of radionuclide source 252
Cf is presented.
Keywords:
Two-parameter spectrometer, digitization, stilbene, pulse shape discrimination
1. Introduction
The recent development in the area of digital data processing enables dramatic
reduction of the spectrometric system; this is achieved by converting the time course
of the detected pulse into numeric samples at the output of the digitizer. Further data
transmission and processing can be done exclusively digitally. The above described
procedure has a lot of advantages:
• Down-sizing of the spectrometric devices
• Increased measurement rate (i.e. a shorter and thus cheaper measurement is
sufficient)
• Possibility of advanced pulse shape analysis – e.g. evaluation of
superimposed impulses caused by fast sequence of particle detections.
• In certain cases, another characteristic of the output impulse can be
determined – the characteristic duration (time constant) of the output pulses.
The last mentioned parameter sometimes carries very useful information about
the nature of the detected particle. This applies e.g. to organic scintillator of type
stilbene or NE-213. The distinguishing of nature of the particles (in our case neutron /
*
Corresponding author: Faculty of Informatics, Masaryk University, Botanická 68a, 602 00
Brno, Czech Republic. E-mail: cvach@mail.muni.cz
2 Z. Matěj, J. Cvachovec, F. Cvachovec, and V. Přenosil
photon) is based on the different relation of the probability of triplet state excitation in
the molecule of the scintillator (the de-excitation generates the slow part of the
fluorescence) to the linear stopping power of the detected charged particles. The
neutron scintillation (a neutron is detected by means of a scattered proton) has a longer
decay than the photon impulse (a photon is detected by means of a scattered electron).
Fig. 1(a). Example time courses of neutron (solid) and photon (dashed) negative
anode pulses in case of a big load resistance
By setting a big load resistance at the output of the scintillation detector, we can
achieve a state where the speed of the increasing part of the output voltage impulse
(rise time) reflects the differences in the time course of the current impulses. This
different information carried by the time courses can be utilized to distinguish the
neutron impulse from the photon one. The time courses of a neutron and photon pulse
are shown in Fig. 1(a). In this case, the scintillation time constant is significantly
smaller than the time constant of the circuit consisting of a working resistance and
parasitic capacitance. We can see that a neutron pulse rises 2-3 ns longer than a photon
pulse.
3Digitized Two-Parameter Spectrometer for Neutron-Gamma Mixed Field
Fig. 1(b). Example time courses of neutron (solid) and photon (dashed) negative
anode pulses for load resistance 50 Ω
In the other case, when the load resistance at the output of the scintillation
detector is set to a small value (ca. 50 Ω), the decay of the output voltage pulse
corresponds to scintillation time constants, i.e. the decay slightly longer for neutrons
than for photons. The rise time is equal for both types of particles. The pulses are short
(several tens of ns) which is favorable as it decreases the frequency of superimposed
pulses. (The parameters of superimposed pulses are usually evaluated wrongly – both
type of particle and amplitude / energy.) The whole pulse may be sampled, which is
not possible in the previous case of a big load resistance when a pulse lasts a few µs.
On the other hand, the signal-to-noise ratio is worse. The time course of a pulse in case
of small load resistance is shown in Fig. 1(b).
In the past, analog circuits were used to distinguish the courses. Since 2000,
attempts have been made to evaluate both parameters (energy, type of particle) from
the digitized output impulse. It is usual to arrange the measured data into a 3-D
representation where one axis (e.g. x) represents the rise time (type of the detected
particle), another (y) stands for amplitude (energy), and the last one (z) records counts
of impulses of the same parameters. This distribution, which we measured with
ACQUIRIS DP 210 digitizer, is shown in Fig. 2(a). We can clearly distinguish
neutrons and gamma part in this distribution. Moreover, other types of charged
particles, noise, disturbances can be identified. Further processing leads to spectral
energetic distribution.
2. Experimental Data Processing
The digitizer ACQUIRIS DP 210 converts the whole input pulse or its initial part (i.e.
output signal from the detector) into 100 samples with a repetition frequency of 1 or 2
GHz. These 100 values (obtained as discrete data) represent the most important part of
4 Z. Matěj, J. Cvachovec, F. Cvachovec, and V. Přenosil
the pulse containing information on the amplitude (energy) and the timing of the rising
part of the pulse (nature of the particle). The usually measured neutron spectra in the
interval 0.5 to 10 MeV require the recording of about one million pulses. Since the
neutron pulses are sampled simultaneously with the photon ones without knowing the
nature of the particle and the ratio of neutrons to photons in the mixed fields is more
than ten, we receive relatively large amounts of data. The data is transported to
memory, where it is stored for off-line processing because on-line processing cannot
be performed quickly enough.
Further data processing is performed so that for each pulse (100 numbers) we
find the largest number – amplitude – and then we determine the parameter τ
corresponding to the time interval between 5 and 95 per cent of the amplitude in the
initial part of the pulse.
Fig. 2(a). 3-D distribution of output pulses from stilbene detector. The x-axis
represents pulse rise time (parameter τ corresponding to the time interval between 5
and 95 percent of the amplitude), y-axis amplitude, and z-axis count of pulses of the
same parameters. Gamma part on the left, neutron part on the right.
According to that τ we should ideally be able to divide all pulses into two groups
– neutrons and photons. However, reality is more complex and the result is a
distribution as shown in Fig. 2(a). It is obvious that the n/γ pulses can be easily
distinguished for higher amplitudes but human interaction is still required for lower
energies. This distribution is then split into neutron and photon parts; further, it is
adjusted into a form required by the codes solving the Fredholm integral equation for
the evaluation of the final product, i.e. the neutron and photon energy spectrum.
In case of a small load resistance, neutron and photon pulses differ in decay. The
preferred method of processing is then comparison of integrals from time courses u(t)
of the voltage pulses:
∫
∫
= 3
2
3
1
dt)t(u
dt)t(u
r
5Digitized Two-Parameter Spectrometer for Neutron-Gamma Mixed Field
where 1 is the starting time of the voltage pulse, 3 corresponds to the end of the pulse
and 2 is an empirically found time between 1 and 3 when the decay of a neutron pulse
starts to differ from a photon pulse. Obviously . The value of r is ca. 110 for
neutrons and ca. 70 for photons – see Fig. 2(b).
Fig. 2(b). Discrimination of output pulses from scintillation detector NE-213 using
parameter r
3. The Evaluation of the Energy Spectrum
When evaluating experimental data from the detector, we meet the linear inverse
problem that can be formulated in case of neutron spectrum as follows: Let )( pEg
and ),( pn EEA be (continuous) functions. A (continuous) function )( nEf is to be
found such that
∫ nnpnp EEfEEAEg d)(),(=)( (1)
The above equation models the process of measurement using various devices or e.g.
the output of a graphical device. It is a Fredholm integral equation of the first kind
where
• ),( pn EEA is the kernel, a characteristic of the measuring device, often called
the response function. Its discrete approximation is determined by Monte
Carlo modelling and measurement of monoenergetic neutron sources.
• )E(g p is the measured proton spectrum, i.e. experimental data. (Neutrons
are detected by means of protons.)
• )E(f p is the result to be found, i.e. the neutron spectrum.
In general, equation (1) has no analytical solution and thus must be solved in a discrete
form:
,= fg A (2)
6 Z. Matěj, J. Cvachovec, F. Cvachovec, and V. Přenosil
where T
mgg ),,(= 1 Kg , A is a nm× matrix, and T
nff ),,(= 1 Kf . ( T
means
transposition.) For stilbene and NE-213 detectors . Our options for stilbene are
. We solve (2) by the maximum likelihood method [1]. It is a
standard statistical tool for point estimations. For the maximizing of the likelihood
function, we use a general iterative algorithm called Expectation Maximization,
originally developed for image reconstruction in astronomy, medicine etc.
4. Measurement Result and Energy Spectrum Evaluation for Neutrons
and Photons from the 252
Cf Source
By the above described procedure we measured and evaluated neutron and photon
spectrum of the 252
Cf source. The choice of this radiation source producing mixed field
is not random. It is an artificial radionuclide and the neutrons originate from
spontaneous fission of the Cf nuclei. Its neutron spectrum is widely regarded as
standard and its shape can be used for testing correctness of the experimental method
and accuracy of the evaluation process. It is very close to fission spectrum. Fig. 3
shows the neutron spectrum and Fig. 4 the photon spectrum of this source (measured
with stilbene 45 x 45 mm).
Fig. 3. Neutron spectrum )E( nϕ from spontaneous fission of 252
Cf
7Digitized Two-Parameter Spectrometer for Neutron-Gamma Mixed Field
Fig. 4. Photon spectrum )E( nϕ from spontaneous fission of 252
Cf
5. Discussion
The first measurement results of energy spectra show prospects of the experimental
methods used and the possibility of further improvement. The methodology of
discrimination of impulses belonging to different types of radiation (in our case,
neutrons and photons) requires more precise mathematical methods for finding the
characteristics in which the pulses of the two types of radiation differ. These can be
various, e.g. Fourier analysis, the use of neural networks, machine learning etc. We
have recently used the Support Vector Machines (SVM) technique. It is a machine
learning method which seeks optimum classification of the training data into two
categories separated by a hyperplane. Simply said, this hyperplane maximizes the
minimum distance between those two data sets. As SVM is a binary classifier, it can
be used to distinguish neutron and proton pulses. Preliminary results, shown in Fig. 5,
look very promising. Fig. 5(a) depicts training data representing well separated
neutron and photon pulses corresponding to higher energy values. Fig. 5(b) shows the
result of the SVM classification / separation. You can compare these results with Fig.
5(c) that illustrates the classical separation according to pulse rise time (e.g. between 5
and 95 percent of the amplitude). Fig. 5(d) shows the result of neutron-gamma
separation using parameter r – see Section 2.
The processing of the pulses with the current digitizer is not ideal because of its
low dynamic range of quantization (8 bits). For neutrons from energy interval 0.5 to
10 MeV, the ratio between the lowest and the highest pulse amplitudes is ca. 1:200.
We solved this problem by taking the measurements at three different voltage levels
for the photomultiplier; the resulting amplitude distributions have been merged by a
software routine.
Two-parameter measurements of neutron and gamma spectra were only possible
in laboratory conditions until recently. The digitized spectrometer is perspective for in
8 Z. Matěj, J. Cvachovec, F. Cvachovec, and V. Přenosil
situ measurements e.g. in working environment next to nuclear reactors, accelerators,
and also for monitoring unwanted transport of neutron sources through security
frames.
Fig. 5. (a) Training data, (b) Result of SVM separation, (c) n/γ discrimination based
on pulse rise time, (d) n/γ discrimination based on parameter r
References
[1] CVACHOVEC, J., CVACHOVEC, F. Maximum Likelihood Estimation of a
Neutron Spectrum and Associated Uncertainties. Advances in Military
Technology, 2008, vol. 1, no. 2, p. 67-79.
[2] CVACHOVEC, F., CVACHOVEC, J., TAJOVSKY, P., Neutron response
function for stilbene detector in energy range 0.5 to 20 MeV, International
Workshop on Neutron Field Spectrometry in Science, Technology and Radiation
Protection (NEUSPEC 2000), June 04-08, 2000, Pisa, Italy.
Acknowledgement
The work presented in this paper has been supported in the frame of the Organization
Development Project (the project of the Department of Mathematics and Physics)
awarded by the Ministry of Defence of the Czech Republic and research project
SPECTRUM, No. TA01011383 of the Technology Agency of the Czech Republic.