Initial performance of sealed straw modules for large area neutron science detectors
Alternative neutron detection technologies must be considered, to overcome limitations imposed by a depleting 3He supply. We have developed a detector technology based on close-packed arrays of boron-coated straws (BCS) in two configurations: (1) each is 4 mm in diameter and 1 m long, and are packaged in groups of 7 that fit inside a single sealed aluminum tube (1.27 cm in diameter, 1 m long); (2) each is 7.5 mm in diameter and 2 m long, and are packaged in groups of 7 that fit inside a single sealed aluminum tube (2.54 cm in diameter, 2 m long). It thus allows operation of the straw detectors in sealed mode, for indefinite periods of time, and in vacuum environments, as required in neutron scattering instruments. The sealed detector modules form a large area (e.g., 1×1 m2, 2×1 m2) neutron imager. Initial testing of the sealed straw detector bundles showed promising results in straw decoding, detector life time, longitudinal resolution, and gas gain stability. The 3D resolution is expected to be 4 mm × 4 mm × 4 mm in configuration #1 and 2.5 cm × 2.5 cm × 2.5 cm in configuration #2, throughout the entire imaging area. Negligible gas gain change was seen over the long test period, in different sealed straw detectors. In addition to facilitating operation in vacuum, another advantageous aspects of the sealed straw detector bundle technique are high portability and structural versatility. Detector modules are easy to transport and detector arrays can be easily installed and tailored to a multitude of different scattering experimental setups. The depth of the detector array can be easily tailored to the desired neutron wavelength and the size and configuration of panels varied of a wide range while utilizing the same elemental modules.
Experimental study of boron-coated straws with a neutron source
Abstract Multiple types of high quality neutron detectors are proposed for the first phase of the China Spallation Neutron Source (CSNS), which will be commissioned in 2018. Considering the shortage of  3 He supply, a detector module composed of 49 boron-coated straws (BCS) was developed by Proportional Technologies Inc. (PTI). Each straw has a length of 1000 mm and a diameter of 7.5 mm. Seven straws are tightly packed in a tube, and seven tubes are organized in a row to form a detector module. The charge division method is used for longitudinal positioning. A specific readout system was utilized to output the signal and simultaneously encode each straw. The performance of this detector module was studied using a moderated  252 Cf source at the Institute of High Energy Physics (IHEP). The signal amplitude spectrum indicates its n-gamma discrimination capability. Despite the complex readout method, a longitudinal resolution of FWHM=6.1 ± 0.5 mm was obtained. The three-dimensional positioning ability qualifies this BCS detector module as a promising detector for small angle neutron scattering.
Surface roughness monitoring by singular spectrum analysis of vibration signals
Abstract This study assessed two methods for enhanced surface roughness (Ra) monitoring based on the application of singular spectrum analysis (SSA) to vibrations signals generated in workpiece-cutting tool interaction in CNC finish turning operations i.e., the individual analysis of principal components (I-SSA), and the grouping analysis of correlated principal components (G-SSA). Singular spectrum analysis is a non-parametric technique of time series analysis that decomposes a signal into a set of independent additive time series referred to as principal components. A number of experiments with different cutting conditions were performed to assess surface roughness monitoring using both of these methods. The results show that singular spectrum analysis of vibration signal processing discriminated the frequency ranges effective for predicting surface roughness. Grouping analysis of correlated principal components (G-SSA) proved to be the most efficient method for monitoring surface roughness, with optimum prediction and reliability results at a lower analytical-computational cost. Finally, the results show that singular spectrum analysis is an ideal method for analyzing vibration signals applied to the on-line monitoring of surface roughness.