Dynamic calibration still poses many challenges for measurement and data analysis. However, we show that without a proper dynamic calibration misleading results are obtained as static calibration approaches to dynamic measurement applications are inappropriate. We illustrate expected improvement in uncertainties when dynamic calibration information is available, and we conclude that further research in this direction is necessary in order to improve measurement capabilities and reliability.

The utilization of dynamic methods for the measurement of operating parameters of road vehicles is beginning to grow due to small time-consuming and low initial investment funds. Dynamic measurement of power parameters of the engine or brake are generally based on the knowledge of the moment of inertia of the rotating masses both of engine and transmission system including driving wheels. Based on the same assumption, dynamic measurement methods can be used to determination of athlete’s physical performance. The results may serve primarily in the sports training area to determine the readiness of the athletes. Secondarily, results may serve as feedback data for optimal couching and they can help to increase of athlete’s technique. This paper deals with dynamic measurement methodology and with measurements results obtained on group of 85 students.

Contributions of uncertainty budgets suitable for special applications of reference torque calibration facilities are calculated with a Monte Carlo method implemented in a spreadsheet software application. The simulations were combined with measurements of parameters with a high number of observations and compared with usual simplified uncertainty estimations for examples of uncertainty contributions concerning traceability of voltage ratio, noise, resolution and position effect. The results are more differentiated and detailed than usual GUM estimations and provide deeper understanding about uncertainty contributions than with GUM methods exclusively. New proposals for the uncertainty estimation of the examined contributions are offered.

This paper present the completion and the measurement uncertainty budget of a multi-component measuring facility. The new facility is part of the 1 MN force standard machine of the PTB. It enables the simultaneous generation of a torque in the range from 20 N·m to 2 kN·m in addition to axial forces 20 kN to 1 MN. This allows the characterization of measuring systems which require combined loads of axial forces F_z and torques M_z like friction coefficient sensors. The aim is a measurement uncertainty of (k = 2) for M_z < 0.01% and F_z < 0.002%. The physical model yields to extended measurement uncertainties (k = 2) for 20 N·m of 5.9 · 10^-5 and for the maximum load step 2000 N·m 4.2 · 10^-5.

A new dead weight type force calibration machine with a 1 kN loading capacity both in tension and compression is installed both in force laboratory of UME and TSE. This paper describes the preliminary results of the performance of the newly developed 1 kN dead weight force machine at the Force Laboratory. The machine is designed and manufactured by UME. The performance test results show that relative reproducibility error with rotation (b) ± 5,5 × 10^-3 and relative repeatability error without rotation (b’) ± 3,5 × 10^-3 for a range of 0,2 kN to 1 kN of a new 1 kN machine of TSE.