Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Electrical signal parameter measurement system
Reexamination Certificate
2000-04-25
2002-10-22
Hoff, Marc S. (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Electrical signal parameter measurement system
C702S067000, C702S069000, C702S075000, C702S076000, C702S189000
Reexamination Certificate
active
06470285
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to a digital pulse processor and, more particularly, relates to a processor that uses multiple parameters and criteria for rejecting piled or contaminated pulses.
BACKGROUND OF THE INVENTION
In electronic sensing applications where information occurs randomly in time, such as in nuclear processes, there is a finite and calculable probability that two or more discrete pulse events will overlap to form a contaminated or “piled-up” pulse event. Similarly, in sensing applications involving two or more constant frequency but asynchronous sources whose inputs are summed into one, there is also a calculable probability of a piled-up pulse event.
Many such applications require integration of a pulse over a time interval to determine its energy content or to analyze its shape for Doppler or other determinations. If the pulse is contaminated or piled-up, a significant decrease in measurement quality will result. Consider, for example, an example from the field of nuclear spectroscopy. A first X- or Gamma-ray of energy E
1
enters a sensor at time T
1
, and a second ray of energy E
2
enters the sensor at time T
2
, where T
2
−T
1
is less than the integration time IT. The energy integral is a composite of rays E
1
and E
2
, and is accumulated in the spectrum being collected as a pseudo ray of energy E
3
, where E
1
<E
3
<=E
1
+E
2
. This contamination of the spectrum decreases the accuracy of the resultant spectrographic analysis.
FIGS. 1
a
-
1
c
graphically depict the phenomenon of pulse pileup. In
FIGS. 1
a
-
1
c,
the horizontal axis represents time (ns) and the vertical axis represents the digitized pulse amplitude. Eight digitized pulses
1
-
8
are depicted, with the pulses being numbered in time sequence order.
FIG. 1
a
plots pulses
1
,
3
,
5
and
8
and
FIG. 1
b
plot pulses
2
,
4
,
6
and
7
. In the first plot, pulses
1
,
3
,
5
and
8
are single events contained within integration zones depicted by the vertical dashed lines. Similarly, in the second plot, pulses
2
,
4
,
6
and
7
are single events contained within integration zones depicted by the vertical dashed lines. The energy of the X- or Gamma-ray that pulses
1
-
8
might represent is determined by computing the sum of n-points of digitized pulse data within an integration zone, dividing this sum by a fixed number, and truncating the result to an integer. The resultant integer is an energy bin or channel into which the pulse event is placed to become a part of the spectra.
FIG. 1
c
plots the combination of pulses
1
-
8
. The overlap of the pulses within the integration zones results in four pulses: pulse
1
,
2
is the combination of pulses
1
and
2
; pulse
3
,
4
is the combination of pulses
3
and
4
; pulse
5
,
6
is the combination of pulses
5
and
6
; and pulse
7
,
8
is the combination of pulses
7
and
8
. In a sensor that cannot determine that these pulses are not from single rays, i.e. a sensor without pileup rejection, pulses
1
,
2
;
3
,
4
;
5
,
6
; and
7
,
8
would be processed as single pulses and be recorded in the measured spectra. Since these piled-up pulses are not analytically meaningful, however, the spectra of singularly measured rays are contaminated and spectral analysis errors result.
In random processes, such as those encountered in nuclear applications, POISSON Statistics are used to calculate the probability of pulse pileup or contamination during an integration period. POISSON Statistics are explained in detail in Glenn F. Knoll, “Radiation Detection and Measurement”, 2
nd
Edition, John Wiley & Sons, New York, 1989, pages 96-97 (hereinafter “Knoll”). Over an integration period t with an average count rate r, the probability that a first event will be contaminated by a second event is given by equation 1:
P
(
r,t
)=
e
−rt
.
Equation 1 is derived by integrating Equation 3-60 on page 97 of Knoll over the interval 0 to t.
Table 1, which follows this detailed description, outlines the pulse pileup probability for various integration periods and count rates, calculated using Equation 1. For high count rates, pulse pileup occurs a relatively large percentage of the time. For example, referring to Table 1, if the count rate is 400,000 events/second, and the integration period is 400 ns, P(400000,400 ns)=0.147856, meaning that there will be pulse pileup 14.78% of the time. For low count rates, conversely, the probability of pulse pileup is much lower. For a count rate of 10,000 events/second and an integration period of 400 ns, P(10000,400 ns)=0.003992, or only 0.4% of the time. Similarly, as the integration period is increased, the pulse pileup probability also increases.
Before pulse digitization and microprocessor integration techniques were available, analog methods were used. Conventional analog methods employed an integrating operational amplifier. After a pulse passes through the amplifier, the voltage on the output of the amplifier is proportional to the area under the pulse. A multi-channel analyzer read this voltage and tallied the events in electronic memory bins or channels. The number of the bin or channel was proportional to the size of integrated voltage and the energy or size of the pulse event. The result was a spectrum of energy or size. Between pulses, the integrating capacitor on the amplifier was shorted to ground to discharge the integral voltage.
Analog techniques such as this also have difficulty in detecting pulses that have been contaminated with pileup from other randomly occurring events, particularly small pulses overlaid on large pulses, and vice-versa. One type of analog pileup rejection utilizes a constant fraction timing approach on both the leading and trailing edges of the analog pulse to determine key aspects of the pulse's shape. This method has been commercialized and is discussed in “Modular Pulse-Processing Electronics and Semiconductor Radiation Detectors”, EG&G ORTEC, 100 Midland Road, Oak Ridge, Tenn. 37831, 1997/98 catalog, pages 2.234-2.236 and 2.242-2.243. A second type of analog pileup rejection is described by Marshall, U.S. Pat. No. 4,152,596. This patent describes a system utilizing slow and fast amplifiers and a pulse width determining means, wherein for a pulse to be classified as accepted as a single event, it was required that (1) the amplitudes of the outputs of both amplifiers be consistent with a single event producing both outputs, and (2) the width of the output pulse from the fast amplifier must also be consistent with that of a single event.
In view of the above, it can be seen that a means for reliably filtering or rejecting contaminated or piled-up pulses is necessary for accurate and quality pulse processing and analysis.
SUMMARY OF THE INVENTION
An extremely sensitive method and apparatus for rejection of pulses contaminated by pulse pileup or other interference is provided. In spectroscopy, the present invention greatly improves the purity and quality of spectra. The invention is especially useful in high count rate applications, where the probability of random pulse overlap during the energy integration period is significant. The present invention can be implemented off-line or in real-time without loss of throughput. A plurality, preferably several, parameters that characterize the shape of ideal or non-piled pulses are chosen. The parameters are chosen to effectively discriminate piled pulses from non-piled pulses. Typically, these parameters are checked against measured values for non-piled pulses that are stored in a lookup table or library. Statistical multipliers of the standard deviations of each measured parameter are typically use to control the rejection sensitivity. The method utilizes digitized pulses or portions of pulses.
Thus, in one aspect, the present invention provides a method for processing a pulse. The method involves comparing at least one, but preferably a plurality of parameters for a pulse, with those parameters for a non-piled pulse. The comparison for a parameter c
Analyser Systems AG
Hoff Marc S.
Murphey John J.
Tsai Carol S
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