High-energy X-ray Imaging Systems Research Articles

Effectiveness of Non-Local Means Algorithm with an Industrial 3 MeV LINAC High-Energy X-Ray System for Non-Destructive Testing.

Industrial high-energy X-ray imaging systems are widely used for non-destructive testing (NDT) to detect defects in the internal structure of objects. Research on X-ray image noise reduction techniques using image processing has been widely conducted with the aim of improving the detection of defects in objects. In this paper, we propose a non-local means (NLM) denoising algorithm to improve the quality of images obtained using an industrial 3 MeV high-energy X-ray imaging system. We acquired X-ray images using various castings and assessed the performance visually and by obtaining the intensity profile, contrast-to-noise ratio, coefficient of variation, and normalized noise power spectrum. Overall, the quality of images processed by the proposed NLM algorithm is superior to those processed by existing algorithms for the acquired casting images. In conclusion, the NLM denoising algorithm offers an efficient and competitive approach to overcome the noise problem in high-energy X-ray imaging systems, and we expect the accompanying image processing software to facilitate and improve image restoration.

Preliminary study of total variation noise reduction algorithm with high-energy industrial X-ray imaging system in nondestructive testing field

Abstract Over the past years, many studies have evaluated the performance of nondestructive testing high-energy X-ray imaging methods. In these high-energy industrial X-ray imaging systems, the noise is very important when accurately assessing the nondestructive analysis of faults inside the object volume. A common way to improve the noise performance is the total variation (TV) noise reduction algorithm. Thus, the purpose of this study is to establish a high-energy industrial X-ray imaging system using 450 kVp energy and to confirm the feasibility of our designed TV noise reduction algorithm. We used an X-ray generator (including source, power supply, and cooler) and a flat panel detector made of an amorphous silicon material. In addition, we acquired the X-ray image for a battery and an air pump and then applied our designed TV noise reduction algorithm to these images. To evaluate the image performance, we used normalized noise power spectrum (NNPS), contrast to noise ratio (CNR), and coefficient of variation (COV). According to the NNPS result, the noise performance of our method was improved compared to conventional noise reduction methods. In addition, the CNR of our TV noise reduction algorithm was 1.58, 1.30, and 1.26 times greater than that achieved for the noisy image, median filter and Wiener filter, respectively. We also acquired excellent COV results for the high-energy X-ray imaging system (about 1.93 times higher than that of the noisy image). Our results suggest that a TV noise reduction algorithm can be constructed with an improved image performance in high-energy industrial X-ray imaging systems.

A stochastic approach to quantifying the blur with uncertainty estimation for high-energy X-ray imaging systems

One of the primary causes of blur in a high-energy X-ray imaging system is the shape and extent of the radiation source, or ‘spot’. It is important to be able to quantify the size of the spot as it provides a lower bound on the recoverable resolution for a radiograph, and penumbral imaging methods – which involve the analysis of blur caused by a structured aperture – can be used to obtain the spot’s spatial profile. We present a Bayesian approach for estimating the spot shape that, unlike variational methods, is robust to the initial choice of parameters. The posterior is obtained from a normal likelihood, which was constructed from a weighted least squares approximation to a Poisson noise model, and prior assumptions that enforce both smoothness and non-negativity constraints. A Markov chain Monte Carlo algorithm is used to obtain samples from the target posterior, and the reconstruction and uncertainty estimates are the computed mean and variance of the samples, respectively. Synthetic data-sets are used to demonstrate accurate reconstruction, while real data taken with high-energy X-ray imaging systems are used to demonstrate applicability and feasibility.

Liquid-Metal/Water Direct Contact Heat Exchange: Flow Visualization, Flow Stability, and Heat Transfer Using Real-Time X-Ray Imaging

Advanced reactor system designs are being considered with liquid-metal cooling connected to a steam power cycle. In addition, current reactor safety systems are considering auxiliary cooling schemes that assure ex-vessel debris coolability utilizing direct water injection into molten material pools to achieve core quenching and eventual coolability. The phenomenon common in both applications is direct contact heat exchange. The current study focuses on detailed measurements of liquid-metal/water direct contact heat exchange that is directly applicable to improvements in effective heat transfer in devices that are being considered for both of these purposes.In this study, a test facility was designed at the University of Wisconsin-Madison to map the operating range of liquid-metal/water direct contact heat exchange. The test section (184-cm height, 45.75-cm width, and 10-cm depth) is a rectangular slice of a larger heat exchange device. This apparatus was used not only to provide measurements of integral thermal performance (i.e., volumetric heat transfer coefficient), but also local heat transfer coefficients in a bubbly flow regime with X-ray imaging based on measured parameters such as bubble formation time, bubble rise velocity, and bubble diameters.To determine these local heat transfer coefficients, a complete methodology of the X-ray radiography for two-phase flow measurement has been developed. With this methodology, a high-energy X-ray imaging system is optimized for our heat exchange experiments. With this real-time, large-area, high-energy X-ray imaging system, the two-phase flow was quantitatively visualized. An efficient image processing strategy was developed by combining several optimal digital image-processing algorithms into a software computational tool written in MATLAB called T-XIP. Time-dependent heat transfer-related variables such as bubble volumes and velocities, were determined. Finally, an error analysis associated with these measurements has been given based on two independent procedures. This methodology will allow one to utilize X-ray attenuation for imaging vapor bubbles with acceptable errors (bubbles ~1 to 5 cm ± 5 to 20%).Subcooled water (Tsat – Twater [approximately equal to] 10°C) was brought into contact with liquid lead (or lead alloys) at an elevated temperature (Tlm = 500°C and Tlm – Tmelting [approximately equal to] 200°C). The study was conducted over a range of ambient pressures (1 to 10 bar) with four different water injection rates (1.5 to 8 g/s; 0.1 to 1 kg/m2·s). The results showed that the system pressure has a slight effect on volumetric heat transfer coefficient, the bubble formation time, and the bubble rise velocity. Increasing the system pressure, however, resulted in an increase in the bubble average heat transfer coefficient. Increasing the water injection rate directly had only a small effect on the bubble rise velocity or formation rate. Increasing the water injection rate resulted in a decrease in the local bubble heat transfer coefficient.Direct contact heat transfer also has some key disadvantages; e.g., flow instabilities caused by local vapor explosion is one of the issues related to direct contact heat exchange, particularly for liquid/liquid exchange with high temperature differences. In this study, the region of stable heat transfer was mapped and the effects of the liquid metal temperature, the water injection rate, and the operating pressure were investigated. The pressure required to stabilize the heat exchange process was found to be a function of the water injection rate but generally increasing the system pressure helped stabilize the system. It was also found that the larger the injection rate, the higher the pressure required to stabilize the system.

Scatter considerations in ultra-high-resolution high-energy X-ray transmission imaging systems

The existence of Compton scatter will lower the performance of radiation imaging systems. Scatter considerations in high-energy X-ray imaging systems are different from low-energy ones. We have developed a method for analytically calculating scatter point spread function (PSF) in ultra-high-resolution, high-energy (UHR-HE) X-ray transmission systems with parallel slat collimator, and applied it to several typical dense objects: a homogeneously attenuating medium, a straight-edge object, and a more practical axisymmetric model (a circular cylindrical object). The scatter distribution along the detector plane can be theoretically calculated by integrating scatter PSF over the full-width of collimator scatter response function. Our method is compared with Monte Carlo simulation for a straight-edge object, and the results fit well. In UHR-HE CT systems, projection error due to scatter is step-like near the sharp edge, and it may evoke high-frequency artifacts in the final reconstruction image, and consequently decreases the system dectectability of high-contrast, microdefects in industrial applications.

Design of a high energy x-ray imaging system for the Tandem Mirror Experiment-Upgrade (abstract)

We want to image the hot, mirror-confined electrons produced by electron cyclotron resonant heating in the end cells of the Tandem Mirror Experiment-Upgrade. Preliminary spectroscopic measurements with NaI(Tl) detectors indicate tail electron temperatures in the range of 100–300 keV. Our goal is to image x-rays in the energy range 10–200 keV, for plasma densities as low as 1011 cm−3. A spatial resolution of one part in forty at framing rates of 200 Hz should be achieved. The imaging system will consist of an x-ray converter (phosphor or scintillator) and image intensifier (diode or microchannel plate), followed by a video readout (silicon intensifier tube). We will outline the steps we are taking to implement this system.