Content
Overview
Dynamic measurements can be found in many areas of metrology and industry such as, for instance, in the measurement of time-dependent forces or accelerations. Methods from signal processing are often applied in the analysis of dynamic measurements. In many applications linear time-invariant systems are appropriate to model dynamic measurements, where the output signal is obtained as a convolution of the input signal and the measurement system’s impulse response. Input and output signal are not proportional to each other, and estimation of the system’s input signal from its output signal constitutes one important task in the analysis of dynamic measurements. Often digital filters are employed for this purpose. The evaluation of the uncertainty associated with the estimated input signal is particularly important from a metrological perspective.
Typical examples are measurements of mechanical quantities as, for example, force, torque and pressure. Further examples are oscilloscope measurements for the characterization of high speed electronics, hydrophone measurements for the characterization of medical ultrasound devices, the spectral characterization of radiation sources, spectral color measurements and camera-aided temperature measurements.
Research
One focus of PTB‘s Working Group 8.42 is the development of methods for the estimation of the input signal from the output signal when the dynamic behavior of the measurement system has been characterized. This includes the development of procedures for the evaluation of the uncertainty associated with the estimated input signal. Another focus is the development of methods for the analysis of dynamic calibration measurements aimed at determining the dynamic behavior of a measurement system.
Software
Publications
Publication single view
Article
| Title: | Evaluation of measurement uncertainty in the presence of combined random and analogue-to-digital conversion errors |
|---|---|
| Author(s): | C. Elster |
| Journal: | Measurement Science and Technology |
| Year: | 2000 |
| Volume: | 11 |
| Issue: | 9 |
| Pages: | 1359 |
| DOI: | 10.1088/0957-0233/11/9/315 |
| Web URL: | http://stacks.iop.org/0957-0233/11/i=9/a=315 |
| Tags: | 8.42, Dynamik |
| Abstract: | The evaluation of the uncertainty in measurement in the presence of combined random errors and errors due to the analogue-to-digital conversion of measuring signals is studied. The following situation is investigated. Analogue measuring signals of a measurand under study are obtained. The signals are assumed to contain random errors with a Gaussian distribution and they are converted into the digital form. Only the resulting digital signals are to be available. The Bayesian theory of measurement uncertainty is applied to the analysis. An estimator is assigned to the measurand and the distribution of this estimator is determined. This distribution can then be used to numerically calculate a best estimate of the measurand and its associated uncertainty. The application of this approach to some examples is presented and compared with results obtained by treating random and analogue-to-digital conversion errors additively and independently, which is frequently done. In some cases, remarkable differences are found which can justify the increased time and effort involved in the approach proposed. |