Conferences and Exhibitions

2022 Exhibiting Conferences

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Calibrating tomorrow together

At the Measurement Science Conference (MSC), Fluke will be celebrating its 75th anniversary and the release of three exciting new multi-product calibrators:

5560A, 5550A and 5540A Multi-Product Calibrators. Most comprehensive workload coverage, latest technology, intuitive redesigned front panel, MET/CAL compatibility and much more. 

Also at MSC, look for a full day course by Jeff Gust:

Wednesday April 5
Fundamentals of Metrology and Conformity Decisions. The tutorial will answer questions about conformity decisions, decision rules, guardbanding, risk and more. 

And Fluke's Marty Conway will be presenting a session on Portable Pressure Measurements, on Thursday, April 6.

We hope to see you at MSC and the ITS 10 Symposium!

Speakers for the ITS 10 Symposium

Find out more about the program here.

Long Term Behavior of Radiation Thermometers with Pyroelectric Detectors
Frank Liebmann (Fluke Corporation, USA)
While photon detector-based radiation thermometers form the basis for primary traceable radiation thermometry above the silver-point, their use below the silver point is limited due to lack of thermal radiation at lower temperatures. There is some work being done with these type of detectors down to 0 °C. However, in this region, there are radiation thermometers being used for traceable calibration work which are pyroelectric detector-based instruments. This family of radiation thermometers went under great scrutiny as traceable instruments during the TRIRAT project. Fluke Calibration's American Fork Laboratory has established traceability using radiation thermometers with pyroelectric detectors. The work on this project began in 2006, with traceable calibrations being done starting in 2007. Since this time, a significant amount of data has been accumulated on four reference standards. The data are applied to these standards for use in calibrating flat plate thermal radiation sources. The data are also used as a quality control on each radiation thermometer's drift. This paper presents this drift history of over 15 years. It discusses the initial drift observed on the instruments, plus the steady state drift observed in these instruments. It also looks at the repeatability of these calibrations looking at the variance of these readings over time. An examination of any other time related factors with these radiation thermometers is considered.

Certification and Implementation of the Argon Triple Point in the Fluke SPRT Calibration Laboratory
Michael Coleman (Fluke Corporation, USA); Rong Ding (Fluke Electronics Corporation, USA)
This paper summarizes the project to certify and implement an argon triple point system into the Fluke SPRT calibration laboratory. For more than twenty years Fluke has provided ISO/IEC 17025 accredited SPRT calibration by fixed point over the range of -197 °C to 962 °C. Fixed point cells were used at all points except for -197 °C where a comparator device using the boiling point of liquid nitrogen and a NIST-calibrated capsule SPRT was used in place of the argon triple-point. To improve upon this setup the laboratory acquired an argon triple-point system, calibrated it, and implemented it into the SPRT calibration process. This paper gives the results of the project including heat flux (immersion) testing, well-to-well temperature uniformity testing, plateau repeatability testing, plateau stability testing, realization temperature verification, interlaboratory comparison results, and the certification uncertainty analysis. A description of the argon triple-point system is provided along with methods of dealing with non-ideal results when measuring with metal sheath SPRTs.

Study on Immersion Effects and Self-heating in Various Heat Sources
Frank Liebmann (Fluke Corporation, USA)
In contact thermometry calibration of resistive probes, there are a number of factors which cause measurement uncertainty. Among these are measurement noise and repeatability, uncertainty due to the measurement readout, true temperature of the heat source, immersion effects, and self-heating. Both immersion effects (sometimes referred to as stem effect) and self-heating can be influenced by a number of factors. The obvious factors include thermal conduction of the probe's stem, immersion depth of the probe into the heat source medium, excitation current, and probe resistance. These factors are all directly related to the probe itself. There are other factors related to heat transfer between the probe and the heat source medium that effect both immersion effects and self-heating. These are mainly due to the convective or conductive heat transfer between the probe and the heat source. These will change with temperature, the heat source medium used, and if a stirred liquid medium is used, it will also change based on the stirring velocity of the bath fluid. This paper covers a few basic concepts and terms related to a resistive temperature probe calibration. It speaks to the basics of heat transfer in a temperature probe calibration. It then discusses the results of an immersion effect and self-heating study. The study is based on data in different heat sources including stirred liquid baths, a fixed-point, and a dry-block calibrator. The paper discusses the results and speaks to how results of such tests may be interpreted by the user.

Applications of Evolutionary Search Algorithms to Improve Measurement Models
Alex Cimaroli (Fluke, USA)
Many measurements are modelled by a functional relationship between input quantities and the output quantity, or measurand. To reduce errors introduced by external stimuli (e.g., internal device temperature, atmospheric pressure, ambient temperature, local gravity), measurement models can be made to incorporate the effects of these stimuli. In doing so, curve fitting of complex, large parameter models become increasingly difficult, if not impossible, using conventional curve fitting algorithms such as linear least squares regression and gradient-descent approaches. Genetic algorithms, or evolutionary search algorithms, utilize elements of random number generation and natural selection to offer a more robust and computationally intense method of curve fitting. Given enough time, a genetic algorithm is guaranteed to find the global minimum in parameter space for even the most complex models. Genetic algorithms, applied to curve fitting, allow a measurement model to be as complex as need be to account for any number of sources of measurement error. Two use-cases are presented: the response curve of an infrared radiation thermometer and a photonic thermometer. Steps are shown that begin with a simple model and progressively incorporate more error compensation to greatly reduce the overall measurement uncertainty. At a certain point of complexity, conventional gradient-descent-based curve fitting algorithms are not suitable, and an evolutionary search algorithm is needed to fit the radiation thermometer measurement model.
 

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