Rebecca Wagner

Firefighters, paramedics, nursing staff, and other occupational groups are in constant need of fast and proper cleaning of their professional workwear, not only during a pandemic. Thus, laundry technology needs to become more efficient and automated. Unfortunately, some steps of the cleaning process, such as finding and removing foreign items from pockets or belts, are still completed manually. This is not just time-consuming but potentially dangerous for the workers due to the hazardous nature of items such as scissors, scalpels, or syringes. Additionally, some items may damage the garments by staining or harm the laundry machines, causing malfunctions and process failure. On the one hand, these foreign items are often hidden inside the clothes, making detection very challenging with conventional superficial sensors. On the other hand, these items can be diverse and cannot be detected by metal detectors alone. X-ray transmission has proven to be a powerful tool for detecting items inside of objects. The dual-energy approach (DE-XRT) even allows obtaining quantitative information about the chemical composition of the measured materials. In this study, working garments were accompanied and filled with realistic foreign items. The potential of DE-XRT to detect those items was successfully shown.

Even outside of the instance of a global pandemic, the proper cleaning of professional work wear is crucial—thus, laundry technology becomes more and more efficient and automated. A bottleneck in the professional laundry process of working garments is the detection of foreign items in pockets and belts; undetected items may not only stain the clothes, but also harm the laundry machines and cause malfunctions or damages. However, the process of locating them is also potentially dangerous, as state-of-the-art is the manual scanning of every piece of garment to find items such as scissors, highlighters, syringes, screwdrivers, scalpels, paper notepads, and sweets. Some of the found objects are completely harmless, but several bare a high potential of injury for the worker involved in the laundry process. Due to the variety of the objects’ materials—plastics, paper, metal, and glass—the items are very challenging to detect with conventional sensors, such as cameras or metal detectors. In non-destructive testing, X-ray transmission (XRT) proved to be a powerful tool for detecting items inside of objects that can not be found by superficial sensors. Unfortunately, XRT does not allow for the distinction between thick objects with low X-ray mass attenuation coefficient and thin objects of stronger attenuation. Thus, similar gray values may be detected, for instance, for components of clothes, such as reflective stripes and pens. In this case, a segmentation by simple thresholding would be hopeless. In contrast, dual energy XRT allows for the obtainment of quantitative information concerning the chemical composition of the scanned materials, which helps to identify objects. In this study, different kinds of working garments were loaded with realistic foreign items in order to show the potential of dual energy XRT in the laundry industry.

X-ray transmission (XRT) and computed tomography (CT) was used on five samples from the Niaz porphyry Cu–Mo deposit in Iran, representing different alteration zones. Analysis of three-dimensional CT data revealed structural information and groups of elements with low, medium and high attenuation, which were assigned to minerals previously determined by scanning electron microscopy. Thus, the mineralization can be located, and the metal/waste ratio can be estimated, leading to more precise ore body modelling and process parameter determination. CT is useful for selected samples as it is time consuming. XRT can be used as real-time process on conveyor belts.

Dual and multi energy X-ray transmission imaging (DE-/ME-XRT) are powerful tools to acquire quantitative material characteristics of diverse samples without destruction. As those X-ray imaging techniques are based on the projection onto the imaging plane, only two-dimensional data can be obtained. To acquire three-dimensional information and a complete examination on topology and spatial trends of materials, computed tomography (CT) can be used. In combination, these methods may offer a robust non-destructive testing technique for research and industrial applications. For example, the iron ore mining and processing industry requires the ratio of economic iron minerals to siliceous waste material for resource and reserve estimations, and for efficient sorting prior to beneficiation, to avoid equipment destruction due to highly abrasive quartz. While XRT provides information concerning the thickness, areal density and mass fraction of iron and the respective background material, CT may deliver size, distribution and orientation of internal structures. Our study shows that the data provided by XRT and CT is reliable and, together with data processing, can be successfully applied for distinguishing iron oxide rich parts from waste. Furthermore, heavy element bearing minerals such as baryte, uraninite, galena and monazite can be detected.