Alexander Lauber

The problem of applying modern uncertainty concepts to the measurement of instrument specific parameters

This paper present discusses a number of problems that occurs when implementing GUM to modern instruments. These are often automatic which makes it difficult to evaluate the uncertainty components in each measurement step, since it is difficult to control and analyses them. Many of these instruments try to quantify instrument specific parameters, parameters that are difficult to compare with other ones having the same dimension but being measured with another technique. Often these parameters lack traceable calibration which may result in a sizeable uncertainty component. This article also includes the human part of the measurement process.

The role of measurement in industrial recycling

The increase of environmental awareness has made reycling an important part of industrial activity. Products and processes must be designed to enable the reuse of raw materials and/or components used, once the resulting product is mature enough for scrapping. Measurement and sensing enter this process because the identity and the properties of the materials/components to be recycled are in most cases only approximately known-in some cases not at all. There has, however, been limited effort until now to analyse where and how sensing should be used to ease effective recycling of industrial products. In this paper, two obvious applications of sensing in the recycling of industrial products will be presented and discussed: sensor controlled automatic disassembly of industrial products (e,g, small electrical motors, micro-ovens) and sensing-based guard systems to protect the health of people working with those parts of recycling that cannot be automatised.

Viscosity model uncertainties in an ash stabilization batch mixing process

Recycling wood ash from burnt wood (back to the forest grounds) is of great ecological importance. However, the ash cannot be recycled directly after combustion. There are several reasons for this, one being the volatility of wood ashes. Mixing ash/dolomite/water in order to obtain granular material is one method to stabilize wood ashes. The main problem is predicting the quantity of water to be added, since the necessary amount varies with the wood ash quality. One possible solution is to measure the mixture viscosity and study whether this parameter can be used to control the amount of added water. In this paper, the viscosity is estimated in the batch mixing process by measuring the normalized effective power P/sub e/(t), that represents the rate of useful work being performed by the three-phase asynchronous machine used for the stirrer drive. The coherence function is used in order to detect any nonlinear relationship between the input-output data-the variable water flow and the normalized effective power P/sub e/(t). It is shown that measuring P/sub e/(t) is extraordinary well suited for future control of the amount of added water. First and second stage experiments are carried through in order to obtain a model of the viscosity dynamics.

On the importance of a good workplace environment for industrial measurement quality

Abstract When planning and implementing measurement in industry, we spontaneously concentrate on the instrumentation needed for performing the prescribed measurement, from sensor to display or graphic recorder. We tend to forget that a technically perfect measurement system will often fail if the personnel responsible for its well-functioning lacks interest and motivation for the task. In this article the problem is discussed, especially in relation to the quality of the workplace environment. It is emphasized that there are no standard solutions to this problem, which can be applied mechanically by uninterested managers. Instead, the solution is to create a human climate where all the singular solutions needed to ensure high-quality measurement emerge spontaneously, in the minds of motivated personnel, be it individuals or groups.

Modeling of Industrial Measurement Systems Considering the Human Factor

Although there is a fairly large number of articles concerning the validation of technical measurement systems, there are only a few which take into account all the components of a measurement system, from technical and human to environmental. This paper presents an analysis of the reliability of the on-line validation of industrial automated measurement systems, in order to understand the measurement process and to improve its quality. The analysis shows that the human factor cannot be overlooked even though the measurement process is fully automated

Auto-test in situ of real time measurement system of SLRC

A method of in situ test of a real time measurement system, RTMS, is presented. The method involves superposing a probing signal on one of the measurement signals of the RTMS, The RTMS is used in a control system of a series loaded resonant converter, SLRC. The power spectrum of a SLRC is specific, the energy is concentrated in narrow bands. The energy of the probing signal is then chosen for certain frequency bands not used by the SLRC. The evaluation of the measurement channel state can be made by identification based on simple frequency or correlation methods.