Certification of SRM1960: Nominal 10 μm Diameter Polystyrene Spheres (“Space Beads”)
Experimental, theoretical, and calculational details are presented for the three independent micrometrology techniques used to certify the mean diameter of Standard Reference Materisd 1960, nominal 10 μm diameter polystyrene spheres (“space beads”). The mean diameters determined by the three techniques agreed remarkably well, with all measurements within 0.1% of each other, an unprecedented achievement in the dimensional metrology of microspheres. Center distance finding (CDF), a method based on optical microscopy, gave a value of 9.89 ± 0.04 μm, which was chosen to be the certified mean diameter. The supporting measurements were done using metrology electron microscopy (MEM) and resonance light scattering (RLS). The MEM technique, based on scanning electron microscopy, yielded 9.89±0.06 μm for the mean diameter of the microspheres in vacuum, while the RLS value was 9.90 ±0.03 μm for the microspheres in liquid suspension. The main peak of the diameter distribution for SRM 1960 is nearly Gaussian with a certified standard deviation of 0.09 μm, as determined by CDF. Off the main peak, there are about 1% oversized particles and a negligible amount of undersized particles. The report gives a detailed description of the apparatus, the experimental methods, the data-reduction techniques, and an error analysis for each of the micro-metrology techniques. A distinctive characteristic of this SRM is that it was manufactured in microgravity aboard the NASA space shuttle Challenger and is the first commercial product to be made in space.
The measurement and uncertainty of a calibration standard for the scanning electron microscope
National Institute of Standards and Technology, Gaithersburg, MD 20899-0001 Standard Reference Material 484 is an artifact for calibrating the magnification scale of a Scanning Electron Microscope (SEM) within the range of 1000 X to 20000 X. Seven issues, SRM484, and SRM-484a to SRM-484f, have been certified between 1977 and 1992. This publication documents the instrumentation, measurement procedures and determination of uncertainty for SRM-484 and illustrates with data from issues 484e and 484f.
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.