The measurement principle shows how to measure calibration torque moment shunts in a 5 MN m torque standard machine using an interferometer and hinge flexure stiffness. The analysis of the measurement uncertainty influences shows that the measurement uncertainty of transversal force measurement ranges from 0.61 % to 3.04 % and stays constant at 1.7 % for torque measurement. A FE validation was performed. The measurement uncertainty of the calibration torque moment sank from 0.106 % to 0.100 %.

We describe the development and characterization of a three-dimensional (3D) magnetic coil system that is able to produce magnetic flux densities of up to 2 mT in an arbitrary field direction. The coil system can be used to calibrate 3D magnetometers efficiently, and the measurements are traceable to national SI units.

Industrial X-ray computed tomography is a holistic measurement technique for dimensional metrology. However, the relatively long measurement time is a hindrance to its application. A possibility to reduce measurement times, the continuous scan mode, is characterized in this work. The question is how much the time reduction impacts the accuracy of the dimensional measurements. The core result of the paper is an estimate of the effect along with experimental proof that this estimate is reasonable.

We motivate how integrated waveguides (WGs) can be part of an on-chip non-dispersive infrared sensor system for environmental sensing. We report the hurdles in maintaining WG quality when integrating emitter and detector structures on the same chip. Thus, we introduce the concept of how to determine the intrinsic loss and a process scheme to protect WG structures from damage caused during fabrication. This could pave the way to systems for environmental sensing with a minimal footprint.

We pursue a promising novel self-adaptive spiking neural analog-to-digital data conversion (SN-ADC) design that uses spike time to carry information. Thus, SN-ADC can be effectively translated to aggressive new technologies to implement reliable advanced sensory electronic systems. The SN-ADC supports self-x (self-calibration, self-optimization, and self-healing) and machine learning required for the internet of things and Industry 4.0 and is based on a self-adaptive CMOS memristor.