Aalto Gear Fault datasets for deep-learning based diagnosis.

Accurate system health state prediction through deep learning requires extensive and varied data. However, real-world data scarcity poses a challenge for developing robust fault diagnosis models. This study introduces two extensive datasets, Aalto Shim Dataset and Aalto Gear Fault Dataset, collected under controlled laboratory conditions, aimed at advancing deep learning-based fault diagnosis.

Secure Exchange of Digital Metrological Data in a Smart Overhead Crane.

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.

Friction RandomPOD-A new method for friction measurement in noncyclic, multidirectional, dynamic pin-on-disk tests for orthopaedic bearing materials.

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.

Metrological Challenges in Collaborative Sensing: Applicability of Digital Calibration Certificates.

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.

Effect of random variation of input and various daily activities on wear in a hip joint simulator.

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.

IoT connected device for vibration analysis and measurement.

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.