Input count rate measurement

Abstract

A method of measuring input count rate λ of radiation impinging on a radiation detector. A detector signal is received as a digital or analogue function of an independent signal parameter (such as time). The detector signal comprises or is derived from a series of radiation pulses from the detector. A plurality of signal thresholds θ is defined. For each θ a set of durations d of the independent signal parameter is calculated relating to a comparison between the signal threshold θ and the detector signal. For each signal threshold θ a frequency distribution of the durations d is calculated. A frequency surface F(θ, d) is then calculated as a function of at least signal threshold θ and duration d. The input count rate λ is determined by calculating a count rate estimator φ incorporating a characteristic feature of F(θ,d) that is sensitive to input count rate λ.

Description

FIELD

[0001] The present invention relates to the measurement of input count rate in radiation detectors, in particular to a method of measurement that provides an improved measurement of high count rates. The invention may be applied to detectors designed to detect pulses of radiative energy ("radiation pulses") of any kind and of any energies, including particle detectors designed to detect quantum mechanical particles such as photons, subatomic particles, ions, atoms, or detectors designed to detect classical radiation pulses such as seismic waves SONAR, SODAR, ultrasound or other material vibrations, or classical radar or light pulses, including LiDAR.

[0002] Applications in which radiation pulse detectors would benefit from the invention include but are not limited to security scanning, baggage scanning, medical imaging, materials analysis, meteorological sensing, minerals processing, minerals analysis, reflection seismology, and DNA sequencing. Previous patent applications of the current applicant described various applications of radiation pulse detectors applicable to the current invention as described in more detail in published international patent applications PCT / AU2005 / 001423, PCT / AU2009 / 000395, PCT / AU2009 / 001648, PCT / AU2012 / 000678, PCT / AU2014 / 050420, PCT / AU2017 / 050514 and PCT / AU2017 / 050512 the contents of each of which is hereby incorporated by reference in its entirety, as examples of applications and apparatuses in which embodiments of the current invention may be implemented in appropriate software. The current invention therefore extends to such apparatuses appropriately programmed with the method of the current invention and the applications of those apparatuses described in the above-mentioned international patent applications . BACKGROUND

[0003] In radiation detectors, individual particles or packets of radiation enter the detectors and generate individual signal pulses. Typically for particle detectors the individual signal pulses are an electrical signal resulting from a cascade of photons responding to the impinging radiation particle on the detector material. Depending on the intensity of the radiation, the number of radiation pulses interacting with the detector material per unit time varies. This parameter is called the input count rate, and is important to measure for reasons depending on the application. By contrast, the output count rate is the number of individual radiation pulses actually detected by the detection circuitry, which in general is less than the input count rate for various reasons discussed below. Estimating the input count rate enables a reliable representation of the intensity of radiation, which is important in accurate quantitative radiation detection. For example, in radiation imaging, each pixel is represented by an intensity being the incident flux of individual radiation pulses (such as quantum particles). In a materials characterisation device, the input count rate is needed to normalise a concentration of a mineral or other component identified by characteristics of the radiation measured. In an X-ray diffraction application, an accurate measure of intensity of the diffraction rings is important in characterising the structure of the material being examined.

[0004] In radiation particle detectors, the individual signal pulses may pass through electronic pre-processing, such as to convert a ramp signal into a pulse signal, and as such may involve analogue and digital stages or components.

[0005] Because each individual signal pulse has a finite duration, and the time of arrival of each individual signal pulse is random and independent, it is common that more than one individual signal pulse can arrive at the detector within that finite duration, resulting in "pulse pileup" whereby the signal is caused by a superposition of two or more closely arriving individual signal pulses. At very high radiation fluxes or in detectors with long individual signal pulse durations, it may be that the aggregate detector signal is continuously above a baseline level.

[0006] Pulse pileup itself does not prevent the discrimination of all multiple overlapping pulses and therefore detection of many multiple individual signal pulse arrivals in a piled up signal is still possible. Many signal processing techniques exist to reliably count some or many individual signal pulses within a piled up signal. Simple techniques may involve temporal differentiation to detect each individual signal pulse arrival by detecting a rapid increase in signal to define the start of each pulse. More complex techniques are required if the energy of each pulse is required to be resolved. For example, the current applicant has invented several such techniques, most of which rely on a measured or assumed pulse shape of each individual pulse and a mathematical technique to disentangle the individual pulses and assign arrival time and energy (amplitude) to each individual pulse.

[0007] Individual signal pulse identification techniques of the current applicant are described in more detail in published international patent applications PCT / AU2005 / 001423, PCT / AU2009 / 000395, PCT / AU2009 / 001648, PCT / AU2012 / 000678, PCT / AU2014 / 050420, incorporated by reference above.

[0008] Despite the fact that it is possible to disentangle many individual signal pulses in a piled up signal, even with sophisticated algorithms it is nonetheless inevitably the case that individual signal pulses occasionally arrive effectively simultaneously, so that the pulse shape formed by the sum of an individual signal pulse of energy E-^ and an individual signal pulse from a particle of energy E2 is indistinguishable from an individual signal pulse of approximately energy E± + E2.

[0009] Furthermore, the physics of particle detection in some particle detectors may more generally involve a period of no sensitivity or reduced sensitivity after each detection event whereby a subsequent particle arrival arriving within the period of no sensitivity or reduced sensitivity is unable or less able to produce the expected individual signal pulse.

[0010] At high count rates, as the mean interval between counts reduces the number of undetected individual signal pulse arrivals increases, making the number of detected individual signal pulse arrivals arriving per second an increasingly poor under-estimate of the actual input count rate.

[0011] A conventional approach to this problem, which is sometimes called the "dead time correction problem", is to estimate a parameter called the "dead time" Tdead which corresponds to a fixed time period after the detection of each pulse which the detector is supposed to be completely unable to detect or discriminate another pulse, and to effectively stop the clock for the amount of the dead time after each detected pulse, triggered by the signal rising above a threshold. This adjusts the time period T downwards by the dead time multiplied by the number of pulses detected, to a corrected time period Tcorr. A problem with this approach is that the concept of a dead time is simplistic, and prior attempts to improve the approach have focused on increased sophistication of the dead time concept in better modelling the dead time, improving the T downwards adjustment of the time period in the formula p. = corr / ^ Another problem with this approach is that the maximum possible measured count rate is limited by the time spent above the trigger threshold.

[0012] A "non-paralyzable" improvement to the time above threshold method introduces a re-triggering function which artificially re-triggers counts when the signal remains above threshold for more multiples of an interval which is set to be slightly larger than the assumed dead time of the detector. Nonetheless, assuming a pulse width of about 100 ns, even the re-triggering improvement shows more than 10% inaccuracy at 1 million counts per second (1 Mcps) and correction factors need to be applied at such high count rates, since the retriggering is approximate only, with complete failure above 10 Mcps.

[0013] In PCT / AU2019 / 050366, the current applicant disclosed an improved method of estimating input count rate, utilising the pulse detection algorithms capable of disentangling piled up pulses well above the detection threshold used in the threshold triggered methods, such as are disclosed in PCT / AU2005 / 001423, PCT / AU2009 / 000395, PCT / AU2009 / 001648, PCT / AU2012 / 000678, PCT / AU2014 / 050420 discussed above. The method introduces the concept of a minimum reliable detection gap using such piled up pulse detection algorithms, and excluding time periods inside the minimum reliable detection gap after each detected pulse. This has been shown to generate a highly reliable measure of input count rate up to 10 Mcps. Despite this advance over the prior art, there is still room for improvement as the method of PCT / AU2019 / 050366 is parallelizable by virtue of excluding time points within the minimum reliable detection gap, even though the minimum reliable detection gap of the piled up pulse detection is much less than the dead time of the threshold triggered methods .

[0014] Also in PCT / AU2019 / 050366, another method of indirectly measuring input count rate to very high count rates is disclosed. In this method the fact is exploited that the average over time of the detector signal is directly proportional to the input count rate. The average over time of the detector signal can be measured without any pulse counting or discrimination. A proportionality constant must be first calculated by calibrating the system using a direct method of input count rate measurement valid at lower count rates, such as the minimum reliable detection gap method of PCT / AU2019 / 050366, or other less accurate methods of the prior art. The limitation of this method is that the proportionality constant is sensitive to the spectrum of the radiation, and while useful where the spectrum is constant, in most detection applications the spectrum is variable and can only be ascertained by reliably detecting each pulses and measuring its amplitudes. At very high input count rates, discriminating each pulse and measuring its amplitude becomes inaccurate, due to the same pulse pile up problem.

[0015] There is therefore a need for a further improved methods of measuring input count rate. SUMMARY OF THE INVENTION

[0016] The inventors have conceived an improved method which exploits more information from the time profile of the input signal from a radiation detector to more reliably measure input count rate to high values, without recourse to discriminating or measuring radiation pulses.

[0017] Therefore in accordance with a broad aspect of the invention there is provided a method of measuring input count rate as recited in claim 1, with optional or preferred features recited in the dependant claims. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is an example of a time profile of a detector signal 10 from a radiation detector.

[0019] Figure 2 shows a plurality of thresholds according to an embodiment of the invention superimposed over the sample detector signal of figure 1;

[0020] Figure 3 shows the frequency surface according to an embodiment measured at a count rate of 25 Mcps;

[0021] Figure 4 shows the frequency surface according to an embodiment measured at a count rate of 55 Mcps;

[0022] Figure 5 Shows the frequency surface according to an embodiment measured at a count rate of 95 Mcps;

[0023] Figure 6 shows a characteristic feature of the frequency surface area for the example of Figure 4 at 55 Mcps;

[0024] Figure 7 shows a plot of the count rate estimator vs actual count rate using the characteristic feature of figure 6 over a wide range of count rates ranging up to nearly 100 Mcps;

[0025] Figure 8 shows the ridge line on the surface of the frequency surface area of Figure 6 used in determination of a count rate estimator according to another embodiment; DETAILED DESCRIPTION OF EMBODIMENTS

[0026] Embodiments of the current invention will now be described.

[0027] Referring first to Figure 1, an example is shown of a time profile of a detector signal 10 from a radiation detector, after pre-processing if necessary to convert a ramp signal into a signal of pulses, each pulse rising above zero for a finite time. At high count rates, the pulses are piled up and the signal remains above zero. A threshold level 11 is shown intersecting with the time profile 10 at various times C1( t2, t3, t^, t5. It will be understood that in most instances, the signal is a time series of discrete digital samples, but analogue implementations are within the scope of the invention. The points of intersection t1( t2, t3, t4, t5 provide a basis for comparison of the threshold level 11 with the detector signal 10. Time intervals 30,31 between the points of intersection where the detector signal 10 is less than the threshold level 11 are shown. In this embodiment, the durations of each such time interval over a sampling period are accumulated and a frequency histogram is formed for suitably chosen duration bin sizes.

[0028] This task is repeated for a plurality of thresholds. Typically, for maximum utility the number of thresholds is greater than 2 and most commonly about 10 or more. The set of thresholds range from a minimum to a maximum value chosen to span the values of signal strength up to the maximum likely value of signal strength having regard the maximum count rate expected. Referring now to Figure 2, a plurality of thresholds is shown superimposed over the sample detector signal of figure 1.

[0029] In Figures 3, 4 and 5 a plot is shown of the histograms obtained in a Monte Carlo simulation of a detector signal at count rates of of 25 million counts per second (Mcps), 55 Mcps and 95 Mcps respectively. The simulation data was generated by producing simulated detector waveforms of pulses of 200 nanoseconds in duration. For each of the count rates under consideration, time series of 25 million sample points were produced at a sample rate of 250 million samples per sec for a total of 25 million ADC samples. As can be seen in each case, the histograms for the range of thresholds form a twodimensional frequency surface z = F(6, d) in a z axis extending above the plane of threshold 0 in a y axis and time duration bin d in an x axis. As the count rate increases, it can be seen that the shape of the surface changes and moves.

[0030] The broad idea of the invention is to incorporate a characteristic feature of the surface in a count rate estimator. The range of potential choices of the characteristic feature is wide, and several examples are provided herein.

[0031] As a first simple example illustrating proof-of-principle, it can be shown that for a fixed spectrum, the count rate is proportional to an area on the horizontal plane z = c bounded by intersection with the frequency surface z = F(0,d) , the plane 0 = 0 , the plane d = 0 and the plane d = dmax, where c is a constant and dmax is a maximum duration.

[0032] Figure 6 shows an example of such area in diagonal hatching for the case of c = 0 at the count rate of 55 Mcps. The count rate can be obtained by determining in a calibration, a proportionality constant K. This can be performed by utilising a reliable prior art method of count rate estimation at one count rate using actual pulse identification techniques, such as are described in the prior art and in particular preferably the gap method of PCT / AU2019 / 050366.

[0033] Figure 7 shows the result of computing this area over a wide range of count rates ranging up to nearly 100 Mcps, where the excellent linearity of the relationship between actual and estimated count rate is seen.

[0034] In practice, as described above in most desired applications, the spectrum will be variable and therefore any spectrum sensitivity of the characteristic feature chosen will be reflected in a less reliable count rate estimation. In the above area method, the spectrum sensitivity is believed to be superior to the method of computing the average over time of the detector signal (Mean ADC) described in PCT / AU2019 / 050366, and consequently without further improvement the area method invention will have wider applicability.

[0035] Nonetheless, because the method of the current invention provides a two-dimensional surface which samples the time profile of the detector signal at different threshold levels, the two-dimensional surface varies in shape and position as count rate, spectrum and pulse shape varies. The area method estimator and any other estimator 0 which is initially established for a fixed spectrum can therefore be improved by incorporating measurement of additional features of F(f), d) that will vary with spectrum or pulse shape variation. So, for one or more calibration count rates, we can measure F(0, d) for one or more different spectra or pulse shapes, identify feature parameters of F(0, d) variation with spectrum or pulse shape, and using those feature parameters of F(0, d) variation, we can determine a count rate estimator 0 which is insensitive to variation of spectrum or pulse shape. Such features may in practise be different in nature depending on the type of variation in spectrum or pulse shape which is encountered in particular applications.

[0036] As described above, the invention for the first time enables a measurement of input count rate to levels well exceeding the count rate limits of the prior art, potentially providing estimators that are robust to variation of spectrum or pulse shape. Development of robust estimators according to the scenario outlined above is currently under way by the inventors.

[0037] A spectrum insensitive method under investigation, different to the area shape feature discussed above, is to define a curve in the (0, d) plane of values of threshold 0 for which F is maximal at fixed duration bin d (after appropriate smoothing using polynomial fits). This curve is a vertical projection down to z = 0 of the ridge line shown white dashed in Figure 8. This curve can be parametrized according to the form Gpeak = ail°ge d + cto , or equivalently        d = a0 * eai6Peak Unlike the area feature, which is a single numerical value, the parameters a0 and ai can provide a degree of spectrum invariance. For any given spectrum and count rate 2 there will be different values of a0 and , and so to the extent that the spectrum variation appropriate to the particular physical application results in a smooth single valued function form of count rate 2 as a function of a0 and alf a spectrum insensitive estimator is given by measuring the shape values a0 and and reading off (p = A(a0, a^. Multiparameter shape features having more than two such parameters for this curve example or more generally can be envisaged which produce better discrimination between a wider range of spectral variations, such as 0peak = ao + ai^ +  + or d CLq +            + &N—l^peak   •

[0038] In principle, spectrum insensitivity can also be further enhanced by incorporating additional parameters not directly calculated from the surface but nonetheless easily calculable directly from the detector signal, such as the average signal value mean(ADC) discussed above, or shape parameters of a Fourier transform of the detector signal. An improved multiparameter estimator may be of the form (p = A(a0..aN_ltx), where the are the shape parameters calculated from the frequency surface, and X denotes one or more other parameters calculable directly from the detector signal.

[0039] Persons skilled in the art will also appreciate that many variations may be made to the invention without departing from the scope of the invention, which is determined from the broadest scope and claims.

[0040] For example, while the examples provided above use a set of durations d associated with time intervals where the detector signal is below the threshold 0, other durations extracted from comparisons between the threshold 0 and the detector signal can be used in the invention. For example, durations d associated with time intervals where the detector signal is above the threshold 0 contain complementary statistical information and can clearly be used in the same way, as an alternative or in combination. Further, the thresholds can be chosen in any of a number of different ways, and equally spaced thresholds are only one choice. The thresholds even may not be constant and could be functions of the time or other independent signal parameter. Further also, while the number of thresholds is conveniently sufficiently large to provide the desired discriminatory power, typically 10 or more and preferably more than 5, in certain circumstances as few as 2 thresholds may provide sufficient discriminatory power in order to take advantage of the invention. Further still, while most cases the implementation will be based on computations from a digitally sampled version of the detector signal obtained through an analogue to digital converter, implementations are possible and within the scope of the invention where the detector signal is analogue and comparison between the thresholds and the detector signal is performed by analogue comparators to provide the durations such as time intervals which can be measured and accumulated using analogue timing circuits as are known in the art. Therefore, the invention can be implemented using digital circuitry, analogue circuitry or a combination .

[0041] Further, the term "radiation" in the claims encompasses pulsatile radiation of any kind and of any energy, including quantum mechanical particles such as photons, subatomic particles, ions, atoms, or classical radiation pulses such as seismic waves SONAR, SODAR, ultrasound or other material vibrations, or classical radar or light pulses, including LiDAR.

[0042] Further, claim 1 uses the phrase "receiving a detector signal as a digital or analogue function of an independent signal parameter, the detector signal comprising or derived from a series of radiation pulses from the detector". This is intended to encompass possible transformation, typically but not necessarily reversible, of a raw detector signal. The signal may be transformed such the independent signal parameter no longer represents time (for example an FFT), and the term "duration" therefore in general refers to interval size in the independent signal parameter. 0043] Further, F(0, d) in the detailed examples is a two dimensional shape in the dimensions given by the parameters 6,d, but in other embodiments F could include dependence on additional dimensions or indices such as a channel number in multichannel systems. The term "function of at least signal threshold. 0 and duration d" in claim 1 is intended to encompass such embodiments .

[0044] In the claims which follow and in the preceding description of the invention, except where the context requires otherwise due to express language or necessary implication, the word "comprise" or variations such as "comprises" or "comprising" is used in an inclusive sense, i.e. to specify the presence of the stated features but not to preclude the presence or addition of further features in various embodiments of the invention. Further, any method steps recited in the claims are not necessarily intended to be performed temporally in the sequence written, or to be performed without pause once started, unless the context requires it.

[0045] It is to be understood that, if any prior art publication is referred to herein, such reference does not constitute an admission that the publication forms a part of the common general knowledge in the art, in Australia or any other country.

Claims

1. A method of measuring input count rate 2 of radiation impinging on a radiation detector, the method comprising the steps of:receiving a detector signal as a digital or analogue function of an independent signal parameter, the detector signal comprising or derived from a series of radiation pulses from the detector;defining a plurality of signal thresholds 6 ;calculating for each signal threshold 8 a set of durations d of the independent signal parameter relating to a comparison between the signal threshold 8 and the detector signal;calculating for each signal threshold 6 a frequency distribution of the durations d;calculating a frequency surface F(8,d) as a function of at least the signal thresholds 8 and the durations d; and determining the input count rate 2 by calculating a count rate estimator (p incorporating a characteristic feature of F(8, d) that is sensitive to input count rate 2.

2. The method of claim 1, wherein the durations d are either durations during which the detector signal is below the signal threshold, or durations during which the detector signal is above the signal threshold, or a combination thereof.

3. The method of claim 1 or 2, wherein the estimator (p is a single valued shape parameter proportional to count rate multiplied by a calibration factor K, K being determined in a calibration step, the calibration step including measuring F(8, d) at least one known calibration count rate to determine K.

4. The method of claim 3, wherein the durations d are durations during which the detector signal is below the signal threshold, and the estimator (p comprises a shape of the frequency surface z = F(0,d), being the calibration factor K multiplied by an area on the horizontal plane z = c bounded by intersection with the frequency surface z = F(0, d) , the plane 0 = 0 , the plane d = 0 and the plane d = dmax, where c is a constant and dmax is a maximum duration.

5. The method of claim 1 or claim 2, wherein the characteristic feature incorporated in the estimator (p is a shape feature of F(0, d) parameterized by a number N of parameters ai, i = 0 to N — 1, (p being determined in a calibration step by measuring the a, from F(0, d) for a number of known count rates 2 and different spectra, to obtain 2 as a function of the as the estimator (p = 2(a0.. a^-i) •6. The method of claim 5, wherein a further one or more parameters denoted X calculated from the detector signal during the calibration step are incorporated into the estimator (p = 2(^..^^,%).

7. The method of claim 5 or 6, wherein the shape feature is a N-parameter parametrization (a0> aN-i) of a curve in the (0,d) plane of values of threshold 0 = Opeak for which F is maximal at fixed duration bin d.8 .       The method of claim 7 , wherein N = 2 and theparametrization is 0peak — ai loge d + a0 .9 .       The method of claim 7 , wherein N = 2 and theparametrization is d = a0 * eai6veak .

10. The method of claim 7, wherein the parametrization is a polynomial defined by 0peak = ao + ai& + —I"        •11. The method of claim 7, wherein the parametrization is a polynomial defined by d = a0 + ^0^^ + —I-           •12. The method of any one of claims 1 to 11, wherein the independent signal parameter is time.

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