Intermediate energy x-ray backscatter characteristics from the interaction with macroscopically thick layered media

Transcription

1 11th European Conference on Non-Destructive Testing (ECNDT 2014), October 6-10, 2014, Prague, Czech Republic Intermediate energy x-ray backscatter characteristics from the interaction with macroscopically thick layered media Morteza ESMAEILI 1, Andrii SOFIIENKO 2, Geir A. JOHANSEN 3, Marie B. HOLSTAD 4, David M. PONCE-MARQUEZ 5 1 Visuray AS, Strandbakken 10, 4070 Randaberg, Norway, phone: , morteza.esmaeili@visuray.com 2 University of Bergen, Allegaten 55, PO Box 7803, 5020 Bergen, Norway, phone: , asofienko@gmail.com 3 University of Bergen, Allegaten 55, PO Box 7803, 5020 Bergen, Norway, phone: , geiranton.johansen@ift.uib.no 4 Christian Michelsen Research AS, Fantoftveien 38, PO Box 6031, NO-5892 Bergen, Norway, phone: , marie.holstad@cmr.no 5 Visuray AS, Strandbakken 10, 4070 Randaberg, Norway, phone: , david.ponce@visuray.com Abstract In this paper we investigate the overall backscatter characteristics of hard X-rays of intermediate energy between E>30 kev and E 450 kev. We measured the backscattered X-ray spectrum characteristics as well as the integrated flux signals from diverse representative material sample as function of depth of penetration distance and incident beam angle using a single voxel scanning technique. In this initial set of experiments, we demonstrate that is possible to sample macroscopic, semi-uniform semi-isotropic heterogeneous layered media of diverse densities up to a radial depth of 70 mm and that deeper probe penetration benefits from higher photon energy. We find that the detected signal is Compton scatter dominated and the signal is attenuated by the different materials mass attenuation coefficients. Furthermore, our measurements show that there is sufficient contrast to differentiate the different material layers, thicknesses and boundaries through the different material density signatures. Radial integrated photon count rate profile maps as a function of test sample depth are presented. These count rate profile maps contain the convoluted density profiles of the sample under study. Future work will be focused on developing a theoretical model and analytical algorithms to de-convolve and extract the proper density profiles. Keywords: X-rays, backscattering, radial scanning, layered sample 1. Introduction The use of X-rays have become an important tool in many fields, especially in the nondestructive testing and material evaluation field. Complimentary to transmitted X-rays, as are commonly used in radiography, it is of increasing importance to understand the information content of backscattered X-rays coming off from large bulk materials when these are irradiated with an incident X-ray probe beam. As a general practical case in industrial or security scenarios, one encounters very often that the materials under evaluation are in the form of semi-uniform and semi-isotropic heterogeneous layered media of macroscopic thickness. Furthermore, the information obtained from these backscattered X-rays becomes especially important when such bulk materials are only accessible from one direction, either because of the size or construction of the test object, making this backscattered radiation the primary means for obtaining quantitative information of the materials under test. The aim of this paper is to report on the ongoing investigation of the characteristics of the X-rays backscattered by the different inner layers of optically opaque and dense composite objects and to show preliminary results of a larger study, to be presented in future reports, that will lead to the development of analytical algorithms for the reconstruction of the density profile of the probed layered media. 1

2 2. Experimental methods The experiments described here were carried out at the X-ray laboratory of Visuray AS, in Randaberg, Norway. The experimental setup consists of an X-ray source, radiation detectors and test samples. The X-ray source is an industrial bipolar 450 kv X-ray source tube (COMET MXR-451) that incorporates a massive tungsten anode as a primary electron-to-photon converter. The source tube is fitted with a tungsten collimator to produce a pencil-like beam. The detectors in use fall into two specific types: a direct conversion solid state pixelated photon counting imager (PCI) that is used to measure the X-ray beam spot and beam divergence; and a scintillator-photomultiplier tube (PMT) photon counter that is used to measure the energy spectrum and X-ray flux. The PCI is a pixels, 100 micron per pixel CdTe detector (XCounter PDT25-DE). Our particular PCI features a 2 mm thick CdTe crystal with energy integrated photon counting capabilities that is sensitive to energies up to 250 kev. The PCI operates similar to a CMOS or CCD optical camera capturing image frames and then sending the photon count per pixel data to a computer via USB. The PMT detector consists of a 2.54 cm diameter 2.54 cm long NaI(Tl) cylindrical crystal scintillator detector integrated to a photomultiplier tube (Saint-Gobain). The PMT detector preamplifier is then connected to the analogue input of a multichannel analyzer (MCA) (Canberra DSA-1000). The digitized spectrometric data is transferred from the MCA to a PC via USB interface. The PMT detector has been energy calibrated using three standard point sources: 241 Am, 57 Co and 133 Ba for a calibration energy range starting from 30 kev up to 700 kev. The energy resolution for the PMT was estimated to be 4% at 662 kev (emission line of 137 Cs) and provides a peak-to-compton ratio at least 2.5 for the photon energy of 250 kev and 0.9 for the photon energy of 450 kev. To shield and reduce background noise (natural background, unwanted environmental source multiple scattering, etc.), the PMT is positioned in a lead box with a wall thickness of 20 mm. The NaI(Tl) crystal of the PMT is fitted with a tungsten collimator that consists of a 40 mm long cylindrical tungsten block with a 1.2 mm diameter collimation through hole that produces an X- ray acceptance cone that subtends a steradians solid angle. Figure 1 shows a schematic of the experimental setup. The measuring technique used on the multilayer sample is based on collecting all of the backscattered X-rays that originate from a voxel that is defined by the intersection of the two cones generated by the X-ray beam divergence and the PMT detector collimator. First, the generated X-rays traverse, from the source s target to the source collimator, a 200 mm path length that includes a 5 mm beryllium window. Once the beam exits the source collimator, it traverses 293 mm in open air before reaching the sample s outer surface. The source collimator is exactly the same size and dimensions as the PMT detector collimator (cylindrical tungsten block with 1.2 mm diameter through hole and 40 mm long) producing a 9 milliradian divergent X-ray beam that produces a 4.3 mm diameter spot size on the sample s first material layer outer boundary plane. This beam spot size includes 95% of the total X-rays of the Gaussian distributed beam profile. The X-ray beam divergence cone axis is angularly displaced relative to the sample surface by the angle α, as shown in Figure 1. The X-ray beam subtended solid angle is steradians. The PMT collimator s acceptance cone axis is made to always coincide with the normal vector to the test sample s outer surface, i.e., the PMT detector always probes and acquires photons perpendicularly to the test sample surface. The PMT s collimator exit standoff distance relative to the sample surface is maintained at a constant 67 mm. In order to select different probe depths, the PMT detector box and its collimator are mounted on top of a high precision stepper motor translation stage which is placed in parallel to the edge of the sample. With the ability to move the PMT detector parallel to the sample edge, we can measure the backscattering photons from different selected voxels since the intersection created by the two cones will move inward (or outward) in the sample as the PMT is translated to the right (left) along the sample s 2

3 edge. The sampling domain range (abscissa) has its origin 8 mm perpendicular to the outer test sample surface and extends up to 65 mm deep into the sample. This choice allows us to make a measurement in air before moving into the sample. The test samples studied are a composite of single material layers of different thicknesses. The layers include well understood elemental materials such as titanium, magnesium, aluminium; and commonly found materials such as plastics, steel, cement mixtures and natural occurring rock. The material choice was made to include and characterize compound materials that are commonly found in a wide range of industrial environments. In particular the results presented here correspond to a sample composed of Poly-methyl-methacrylate (PMMA) (8 mm, 1.2 g/cc), steel (8 mm, 7.86 g/cc), light cement (25 mm, 1.2 g/cc) and granite (66 mm, 2.6 g/cc) layers which are bound by a custom made sample holder. The height and length of sample is 100 mm and 250 mm respectively. The sample was positioned in a motorized jack in order to adjust the height of the sample relative to the incident X-ray beam and also to rotationally adjust the sample at either an angle of α = 30 or α = 45 relative to the incoming X- ray beam as shown in Figure 1. Fig. 1. A schematic of the experimental set-up used for the X-ray radial imaging of the composite objects. Top figure shows the general arrangement with relevant dimensions. Bottom figure shows the details of the voxel definition and general sampling technique. 3

4 3. Results and discussion 3.1 Spectrometric measurements of backscattered X-rays To be able to characterize the measured data both qualitatively and quantitatively in a proper way, we have to understand the X-ray spectra produced by our source. The X-ray spectra produced by the COMET source tube were measured to estimate the intensity in the collimated X-ray beam and the energy distribution of the generated photons as a function of the accelerating potential. The measured X-ray spectra (with 30 mm Al filter) normalized on the tube power for the accelerating potentials of 150 kv, 250 kv, 350 kv and 450 kv are shown in Figure 2. These tube spectral output is representative of the photon energy distribution in the collimated beam used as probe in the test samples. Fig. 2. The measured X-ray spectra, normalized to the tube power, of MXR-451 X-ray tube with massive tungsten anode for the accelerating potentials of 150 kv (1), 250 kv (2), 350 kv (3) and 450 kv (4). Measurements were done using 30 mm thick aluminum attenuation. All experimental results presented here were carried out with an electron beam current setting of 2 ma DC over a 600 sec live acquisition time and two different X-ray tube accelerating potentials: 450 kv and 350 kv. The measured intensity of the collimated incident on the sample X-ray beam was photons per second and photons per second over the beam spot at 450 kv and 350 kv respectively integrated over all energies. Once the collimated beam reaches and penetrates the sample, the beam undergoes scattering from the bulk materials. The measured backscattered photons collected by the detector exhibit two dominant features: general attenuation and Compton energy downshift. The measured backscattered spectra are downshifted to the low energy range due to the energy transfer from the photons to the electrons after incoherent scattering interactions. This is described by Compton s equation [1]: hν 0 hν = hν 1+ 1 cos m c 0 2 e ( ( θ )), (1) 4

5 where hν 0 is the energy of the incident X-ray photon before the interaction, hν is the energy of the scattered X-ray photon, θ is the scattering angle and m e c 2 is the electron rest energy. The measured spectra of backscattered photons for four different sample depths are shown in Figure 3. Fig. 3. The measured X-ray backscattered spectra from different layers of the composite sample at 4 mm in Plexiglass (1), 5 mm in steel wall (2), 11 mm in cement (3) and 11 mm in granite (4). Accelerating potential and beam current of X-ray tube was 450 kv and 2 ma respectively. As it is expected, Figure 3 shows that the backscattered spectra undergoes larger lower energy attenuation (beam hardening) from the deeper layers inside the sample compared to the outer layers. Nevertheless the lower energy tail end should be further suppressed, especially for spectrum number 3 and spectrum number 4 of Figure 3. In particular, these spectra show a significant count rate at this lower end and displaying what appears to be the characteristic lines of tungsten fluorescence, which are not consistent with the anticipated results. One can hypothesize that this enhanced signal at the lower end is caused by photon noise originating from the initial scatter interaction point of the X-ray beam and the sample and/or fluorescence of the tungsten collimator produced by the more energetic backscattered photons coming into the detector from the sampled voxel region. Regardless, this is an issue that needs to be investigated and measures taken to clean the detected signal and improve on the signal-to-noise ratio (SNR) for future measurements. Another approach in the effort to understand the noise sources and evaluate the SNR of the collected signal is to evaluate the spectral mean energy. The mean energy in the measured spectra, collected at each sample depth, can be computed for the different scanning depths to estimate its value as a function of sample depth: E k = 1024 Ni, k Ei t, (2) N i= i= 1 t i, k 5

6 where N i,k / t is the detected count rate for MCA i-bin from the k-voxel and E i is the energy of MCA energy calibrated i-bin. The computed mean energy of the backscattered photons as a function of voxel position in the sample for the two different X-ray tube accelerating potentials (350kV, 450kV) and the two different X-ray beam incident angles (α = 30 0 and 45 0 degrees) are shown in Figure 4. Fig. 4. The obtained dependencies of the mean energy of backscattered photons as a function of sample depth for different X-ray tube accelerating potentials and different X-ray beam incident angles: 45 0 (1) and 30 0 (2). The boundaries between the different layers of the sample are shown: I is between the air and PMMA, II is between the PMMA and steel, III is between the steel and cement and IV is between the cement and granite. Figure 4 also shows the boundaries between the different layers of the sample: I is between the air and Plexiglas, II is between the Plexiglas and steel, III is between the steel and cement and IV is between the cement and granite. The way to interpret this plot is by knowing a priori what is the curve generated in an ideal setup (zero photon noise) where all of the collected photon signal only originates from the sampled voxel. This ideal curve, where only photon absorption, attenuation and scattering affects the measured signal, would be a monotonically increasing trace that would reach a maximum and then asymptote at this maximum average energy value. As can be seen from Figure 4, the traces exhibit local maxima and minima as well as a dependence on X-ray beam incident angle. Local minimums are caused by an increase of lower energy photons contributing to the energy sum average. This can very well be caused by lower energy photon noise pollution in the measured signal. These photons can be originated from the first beam-tosample interaction neighbourhood. This would also explain to some extent the sensitivity of the traces to different beam incident angles. The mean energy from the deeper layers is expected to be greater in value due to the greater attenuation, but the experimental data show some reduction of this value in the cement and granite layers. This behaviour can be explained by the systematic biasing of the detector signal due to the existence of low energy background radiation. This assessment is consistent with the hypothesis that some unfiltered radiation field around the shielding of the X-ray tube and multiple scattering radiation originating from inside the test sample in the neighbourhood outside of the probed voxel make it into the detector in the form of noise. With this knowledge in hand now and for the purposes of further analysis of the collected data, we can account for this measurement error and perform some noise filtering in the digital domain. 6

7 3.2 Radial intensity mapping of a composite object The integrated counts over all the measured X-rays backscattered spectra per voxel for all voxels give the radial X-ray intensity map of the studied sample. This mapping can be seen in Figure 5 and Figure 6. By radial here we mean the sample data acquisition is done in the direction of the normal vector to the surface of the sample. While we are not in a cylindrical symmetric geometry, we believe that the usage of the word radial conveys the correct idea and certainly the measurement technique can be applied in such cylindrical symmetrical environments. In itself, the radial intensity map contains the line integral of the X-ray mass attenuation coefficients through the X-ray beam traversed length convoluted with the macroscopic local voxel coherent and incoherent scattering cross sections. From here one can unfold, theoretically, densities as a function of radial (depth) position in the sample. It needs to be mentioned here that macroscopic means the signal detected from the observed voxel provides a volumetric average over the voxel volume. In order to clean the data from the systematic error produced by the photon noise, we have applied high energy pass threshold windows. Different energy thresholds were applied to the radial maps to evaluate the influence on the shape and intensity on the maps. Figure 5 shows the application of these threshold windows (20 kev, 40 kev, 60 kev, 80 kev and 100 kev) to the same energy integrated counts per second as a function of sample radial depth map. The layer boundaries denoted in both Figure 5 and Figure 6 are the same as in Figure 4, namely: I is between the air and PMMA, II is between the PMMA and steel, III is between the steel and cement and IV is between the cement and granite. As can be appreciated from Figure 5, the higher the threshold the lower the baseline becomes. Fig. 5. Effect of applying different low energy thresholds on the measured radial data from sample at 450 kv and beam angle of 45 0 : 20 kev (1), 40 kev (2), 60 kev (3), 80 kev (4) and 100 kev (5). The boundaries between the different layers of the sample are shown: I is between the air and PMMA, II is between the PMMA and steel, III is between the steel and cement and IV is between the cement and granite. While a 100 kev threshold seems still appropriate, we have chosen to use 60 kev to err on the side of caution and take a conservative approach. It is noteworthy to emphasis here that better detector shielding needs to be implemented in future measurements. Under ideal, noise free conditions, the count rate signal would increase evenly up to a maximum just after boundary I. This finite slope rise is due to the finite volume of the probing voxel: as the voxel starts to 7

8 penetrate through the material layer, the number of contributing scattering particles increases in direct proportion to the voxel volume inside the layer up to the maximum when all of the voxel is inside the material layer. As the voxel progresses into the layer, the signal is just simply attenuated exponentially through the mass absorption in that particular layer. Layer boundary identification can be readily done by observing this increase of signal in the boundary, as it can also be seen in boundaries II and IV. This effect is not noticeable in boundary III since the voxel traverses a layer of higher density to a layer of lower density. When there is a transition from higher to lower density, one has to rely on the attenuation slope difference. Although the integrated count rate is plotted in a semi-logarithmic scale, the traces do not show a constant slope for each layer, especially as the data represented is deeper into the sample. This is due to the voxel volume dependence on the radial position. The voxel becomes larger the deeper is into the sample. The data can be corrected simply by dividing by the corresponding voxel volume for each depth, although the correct volume needs to be computed numerically [7]. In terms of accounting for this in the experimental set up, one can arrange for a fixed beam and detector position (fixed voxel of fixed volume) and simply move the test sample accordingly. Choosing this arrangement is just a simple matter of experimental practicality. Fig. 6. The measured radial map of the test sample using accelerating potentials of 450 kv (1) and 350 kv (2), and normalized on the X-ray tube power. Beam angle is of 45 0 and low energy threshold is of 60 kev. The boundaries between the different layers of the sample are shown: I is between the air and PMMA, II is between the PMMA and steel, III is between the steel and cement and IV is between the cement and granite. One of the various questions addressed is to understand the quality of the backscattered signal measured as a function of X-ray tube accelerating potential. This in effect translates into how deep into the test sample we can observe with a certain photon energy. While high energy X-rays are becoming more easily obtainable with commercial X-ray equipment, one would always prefer to operate with the lowest possible energies due to available power at a particular 8

9 site or simply because of safety concerns. As can be seen from Figure 6, the increase of the accelerating potential of X-ray tube from 350 kv to 450 kev for the same electrical power does affect the detected intensity of backscattered X-rays. The observed difference for the steel wall (first 3 voxels inside the steel) is about 23% which is in good agreement with the theoretically expected increase of the efficiency of the bremsstrahlung generation from 2.07% for 350 kv to 2.66% for 450 kv calculated as follows: η k Z U, (3) X 0 T T where k 0 = (V -1 ) is an empirical constant [2-4], Z T = 74 is the atomic number of the target of the X-ray tube (tungsten) and U T is the accelerating potential of the X-ray tube (V). The difference for the cement layer is about 35%, so we can roughly estimate that 12% is related to the different attenuation effects, given that higher energy photons produced at higher potentials have a higher probability of penetrating deeper and be less attenuated on the backscattered trajectory to the detector as opposed to the lower energy photons. It should be noted that the benefit of increasing the energy of the X-rays at the source is only partially compensated by the energy decrease after Compton scattering in reduced attenuation, but the Compton cross section also decreases reducing the backscatter probability. 4. Conclusions and future work The backscattered X-ray spectrum characteristics as well as the integrated flux signals from a composite dense object were measured using a single voxel technique. By utilizing a voxel technique, it is possible to sample specific regions of a macroscopic bulk material. The measured X-ray backscattered data was used to produce radial energy integrated photon count rate spatial maps for different accelerating potentials (350 kv and 450 kv) and different X-ray beam incident angles (30 0 and 45 0 ). We have been capable of sampling regions as deep as 70mm in a multilayer test sample. The layers include well understood elemental materials such as titanium, magnesium, aluminium and commonly found materials such as plastics, steel, cement mixtures and natural occurring rock. The material choice was made to include and characterize compound materials that are commonly found in a wide range of industrial environments. We also have discovered the experimental sensitivities to external radiation noise and proposed alternatives to either mitigate them or compensate for them through data processing for future experimental work. We also have shown that the technique utilized has sufficient contrast to differentiate between different material densities and their physical boundaries. Finally we make an evaluation of the probing penetration efficiency of the photons as a function of their energy. It is our intention to examine further the measurement of samples that contain localized inhomogeneities and irregularities to evaluate the practical aspects and limits of minimal spatial detected resolution and minimal density contrast that can be observed. Furthermore, we will work on the development of a general theoretical model and algorithms to extract the particular density profiles of any particular test sample. 9

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