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Digitalization and the rapid development of IoT systems has posed challenges for metrology because it has been comparatively slow in adapting to the new demands. That is why the digital transformation of metrology has become a key research and development topic all over the world including the development of machine-readable formats for digital SI (D-SI) and digital calibration certificates (DCCs). In this paper, we present a method for using these digital formats for metrological data to enhance the trustworthiness of data and propose how to use digital signatures and distributed ledger technology (DLT) alongside DCCs and D-SI to ensure integrity, authenticity, and non-repudiation of measurement data and DCCs. The implementation of these technologies in industrial applications is demonstrated with a use case of data exchange in a smart overhead crane. The presented system was tested and validated in providing security against data tampering attacks.

RESUMEN

The 16-station, computer-controlled RandomPOD wear test device was re-designed into a friction measurement device, Friction RandomPOD. The motion was implemented by a servo-electric x-y-stage and the load was proportional-pneumatic. The direction of sliding, velocity (v), acceleration, and the magnitude of the load (L) varied randomly and continuously. The nominal contact pressure p varied between 0 and 2.4 MPa and v between 0 and 40 mm/s. In the first version of the device, the frictional force components were continuously measured by two miniature load cells in two perpendicular directions. In the second version, the measurement was done with a three-axial, commercial load cell. The resultant frictional force was divided by the instantaneous load in order to obtain the coefficient of friction (µ) at a frequency of 200 Hz. Due to the light and accurate design of the device, vibrations were absent in the measured signals although the measurements were most dynamic. Hence no filtering was needed. Serum lubricated polyethylene/CoCr tests revealed non-symmetric distributions of µ, friction power Pµ, and µ vs. pv.

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RESUMEN

IoT systems based on collaborative sensor networks are becoming increasingly common in various industries owing to the increased availability of low-cost sensors. The quality of the data provided by these sensors may be unknown. For these reasons, advanced data processing and sensor network self-calibration methods have become popular research topics. In terms of metrology, the self-calibration methods lack the traceability to the established measurement standards of National Metrology Institutes (NMIs) through an unbroken chain-link of calibration. This problem can be solved by the ongoing digitalization of the metrology infrastructure. We propose a conceptual solution based on Digital Calibration Certificates (DCCs), Digital SI (D-SI), and cryptographic digital identifiers, for validation of data quality and trustworthiness. The data that enable validation and traceability can be used to improve analytics, decision-making, and security in industrial applications. We discuss the applicability and benefits of our solutions in a selection of industrial use cases, where collaborative sensing has already been introduced. We present the remaining challenges in the digitization and standardization processes regarding digital metrology and the future work required to address them.

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The ISO 14242-1 standard specifies fixed, simplified, sinusoidal motion and double-peak load cycles for wear testing of total hip prostheses. In order to make the wear simulation more realistic, random variation was added for the first time to the motion and load control signals of a hip joint simulator. For this purpose and for the simulation of various daily activities, computer-controlled, servo-electric drives were mounted on a biaxial hip simulator frame and successfully introduced. Random variation did not result in a statistically significant difference in the wear factor of large diameter VEXLPE liners compared with fixed sinusoidal waveforms. However, level walking according to biomechanical literature surprisingly resulted in a 134 per cent higher, and jogging in a 57 per cent lower wear factor compared with the fixed sinusoidal waveforms. These wear phenomena were likely to be caused by a variation in the lubrication conditions and frictional heating. Simplified motion waveforms may result in an underestimation of wear in walking.

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RESUMEN

Accelerometers are widely used in applications, such as condition measurement, motion tracking, and vehicle monitoring. Most handheld smart devices, such as smart phones and tablets, employ accelerometers for motion tracking. The size constraints of such devices has provided the impetus to develop precise, affordable, compact, and power-efficient accelerometers. Microelectromechanical systems (MEMS) accelerometers meet these strict requirements, thus explaining their wide adoption in the smart device market. The increasing cost-performance ratio, particularly regarding accuracy and bandwidth, of modern MEMS accelerometers enables their use in demanding measurement applications. This research introduces an open source battery-powered Internet of Things MEMS accelerometer called Memsio. Memsio is a versatile wireless sensor unit that can be deployed to measure a wide range of different motions. It is operated from a web browser, thus rendering it remotely accessible via smart phone, tablet, or computer. Furthermore, Memsio offers high-speed motion data acquisition capabilities and can store extended measurement periods lasting dozens of minutes; in addition, its wireless and portable nature eases integration in condition monitoring applications. The study presented reports on the construction and functionality of Memsio. Additionally, the functionality of Memsio is demonstrated in the measurement of translational movement of a linear actuator and the vibrations of large rotating machinery.