Industrial Dynamic Measurements:
A Best Practice Guide
This guide has originally been produced by the EURAMET project Traceable Dynamic Measurement of Mechanical Quantities. More information about this collaborative project can be found on the project’s web site and the linked EURAMET publishable summary of the project. The aim of the guide is to provide practical information and advice to engineers and technicians in industry who carry out dynamic measurements in the course of their work.
We assume that readers of this guide have a basic understanding of the concept of measurement uncertainty and are familiar with the key general technical terms that arise in understanding measurement and measurement uncertainty. Further information about these topics can be found in the Guide to the expression of uncertainty in measurement (GUM) and the International Vocabulary of Metrology (VIM). A basic introduction to measurement can be found here and a link to a beginner's guide to measurement uncertainty is here.
In the main text of this guide we try to explain concepts in plain language and to avoid as much as possible the introduction of mathematical notation. Nevertheless some mathematical concepts (especially terms associated with signal processing and system identification) are unavoidable and we provide links to resources (textbooks, scientific papers, web pages) that help explain the necessary background.
Any mention of commercial products within these web pages is for information only; it does not imply recommendation or endorsement by the partners in this project.
The views expressed in this guide are those of the authors.
Please note that when selecting many of the links included here you will be leaving our web pages. We have provided these links to other web sites because they have information that may be useful to you. We do not necessarily endorse the views expressed, or concur with the facts presented on these sites.
Acknowledgement of funding
The initial production of this guide was funded by the European Metrology Research Programme (EMRP). The EMRP is jointly funded by the EMRP participating countries within EURAMET and the European Union.
Preparation of the initial version of this best practice guide was led by Andy Knott and Trevor Esward of the National Physical Laboratory (UK) with extensive input from members of the EMRP IND09 project team. The original version can be found here.
We have provided a glossary of technical terms that arise frequently in almost all dynamic measurement applications to assist readers who may be new to this topic.
This best practice guide covers the following topics:
- Understanding the performance of measuring systems
- Introduction to mathematical modelling of dynamic systems
- Dynamic Pressure
- Dynamic Torque
- Dynamic Force
What the guide does NOT cover
The guide is not intended to cover all forms of measurement of time varying quantities but to concentrate on the three mechanical quantities that formed the work tasks of EMRP project IND09, dynamic force, torque and pressure. There are many application areas that we do not address such as dimensional, electrical, flow, optical, mass and acoustical metrology and process control. However these applications share many problems in common with measurements of dynamic force, pressure and torque and knowledge from one application domain may be transferred to other related application domains. For example, the boundary between dynamic pressure for mechanical applications and acoustics (both airborne and underwater) is not well-defined and measurement techniques in these application areas are related, for example, in both applications piezoelectric sensors are employed and the frequencies of interest overlap (especially frequencies for underwater acoustics applications).
This guide does not provide detailed advice on digital signal processing (DSP) and digital filter design. We concentrate specifically on those mathematical topics that are directly related to data analysis and uncertainty evaluation and to the correction of time series data for measurement system effects (e.g., deconvolution). However we provide links to information on DSP and related topics for readers who require more detailed information.