Articles | Volume 12, issue 1
https://doi.org/10.5194/jsss-12-45-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/jsss-12-45-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regular research article
| 
27 Jan 2023
Regular research article |
| 27 Jan 2023
Influence of measurement uncertainty on machine learning results demonstrated for a smart gas sensor
ZeMA – Center for Mechatronics and Automation Technology gGmbH, Saarbrücken, Germany
Lab for Measurement Technology, Department of Mechatronics, Saarland University, Saarbrücken, Germany
Tizian Schneider
ZeMA – Center for Mechatronics and Automation Technology gGmbH, Saarbrücken, Germany
Lab for Measurement Technology, Department of Mechatronics, Saarland University, Saarbrücken, Germany
Sascha Eichstädt
Fachbereich 9.4, Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Germany
Andreas Schütze
ZeMA – Center for Mechatronics and Automation Technology gGmbH, Saarbrücken, Germany
Lab for Measurement Technology, Department of Mechatronics, Saarland University, Saarbrücken, Germany
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Tanja Dorst, Yannick Robin, Sascha Eichstädt, Andreas Schütze, and Tizian Schneider
J. Sens. Sens. Syst., 10, 233–245, https://doi.org/10.5194/jsss-10-233-2021, https://doi.org/10.5194/jsss-10-233-2021, 2021
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Synchronization problems within distributed sensor networks are a major challenge in the field of Industry 4.0. In this paper, artificially generated time shifts between sensor data and their influence on remaining useful lifetime prediction of electromechanical cylinders are investigated. It is shown that time shifts within sensor data lead to poor remaining useful lifetime predictions. However, this prediction can be significantly improved using various methods as shown in this contribution.
Tanja Dorst, Yannick Robin, Sascha Eichstädt, Andreas Schütze, and Tizian Schneider
J. Sens. Sens. Syst., 10, 233–245, https://doi.org/10.5194/jsss-10-233-2021, https://doi.org/10.5194/jsss-10-233-2021, 2021
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Synchronization problems within distributed sensor networks are a major challenge in the field of Industry 4.0. In this paper, artificially generated time shifts between sensor data and their influence on remaining useful lifetime prediction of electromechanical cylinders are investigated. It is shown that time shifts within sensor data lead to poor remaining useful lifetime predictions. However, this prediction can be significantly improved using various methods as shown in this contribution.
Tobias Baur, Manuel Bastuck, Caroline Schultealbert, Tilman Sauerwald, and Andreas Schütze
J. Sens. Sens. Syst., 9, 411–424, https://doi.org/10.5194/jsss-9-411-2020, https://doi.org/10.5194/jsss-9-411-2020, 2020
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Applications like air quality, fire detection and detection of explosives require selective and quantitative measurements in an ever-changing background of interfering gases. One main issue hindering the successful implementation of gas sensors in real-world applications is the lack of appropriate calibration procedures for advanced gas sensor systems. This article presents a calibration scheme for gas sensors based on gas profiles with unique randomized gas mixtures.
Caroline Schultealbert, Iklim Uzun, Tobias Baur, Tilman Sauerwald, and Andreas Schütze
J. Sens. Sens. Syst., 9, 283–292, https://doi.org/10.5194/jsss-9-283-2020, https://doi.org/10.5194/jsss-9-283-2020, 2020
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We present a work on gas sensors that can for example be used for the assessment of indoor air quality. These sensors suffer from deterioration by siloxanes, so we investigated these effects by a distinct operation mode and exposition to this gas that allows us to interpret different reactions on the sensor surface. We found that all processes on the sensor surface are slowed down by this treatment and a self-compensation by the evaluation of oxygen adsorption processes is likely to be found.
Marius Rodner, Manuel Bastuck, Andreas Schütze, Mike Andersson, Joni Huotari, Jarkko Puustinen, Jyrki Lappalainen, and Tilman Sauerwald
J. Sens. Sens. Syst., 8, 261–267, https://doi.org/10.5194/jsss-8-261-2019, https://doi.org/10.5194/jsss-8-261-2019, 2019
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To fulfil today's requirements, gas sensors have to become more and more sensitive and selective. In this work, we present a novel method to significantly enhance the effect of gate bias on the response of a SiC field-effect transistor by placing a lithium-doped tungsten oxide film beneath the gate. This enhancement, compared to undoped samples, opens new perspectives for static and transient signal generation, e.g. gate bias-cycled operation, and, thus, increasing sensitivity and selectivity.
Henrik Lensch, Manuel Bastuck, Tobias Baur, Andreas Schütze, and Tilman Sauerwald
J. Sens. Sens. Syst., 8, 161–169, https://doi.org/10.5194/jsss-8-161-2019, https://doi.org/10.5194/jsss-8-161-2019, 2019
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The measurement of humidity in industrial applications is still an important research issue. Especially under rough operation conditions the current humidity sensor comes to its limitations. To this end, we are developing an integrated sensor system using a metal oxide sensor with impedance spectroscopy as multi-signal generation allowing the discrimination of humidity and reducing gases. The submitted paper focuses on the modeling of the humidity-dependent aspects of impedance.
Manuel Bastuck, Tobias Baur, and Andreas Schütze
J. Sens. Sens. Syst., 7, 489–506, https://doi.org/10.5194/jsss-7-489-2018, https://doi.org/10.5194/jsss-7-489-2018, 2018
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Predictions about systems too complex for physical modeling can be made nowadays with data-based models. Our software DAV³E is an easy way to extract relevant features from cyclic raw data, a process often neglected in other software packages, based on mathematical methods, incomplete physical models, or human intuition. Its graphical user interface further provides methods to fuse data from many sensors, to teach a model the prediction of new data, and to check the model’s performance.
Tobias Baur, Caroline Schultealbert, Andreas Schütze, and Tilman Sauerwald
J. Sens. Sens. Syst., 7, 411–419, https://doi.org/10.5194/jsss-7-411-2018, https://doi.org/10.5194/jsss-7-411-2018, 2018
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A novel method for the detection of short pulses of gas at very low concentrations is presented. Applying the method to a doped SnO2 detector, gas pulses down to a dosage of 1 ppb times seconds can be detected. The gas transport inside the detector is simulated using the finite element method (FEM) to optimize the gas transport and to keep response and recovery time as short as possible. With this approach, we have demonstrated a detection limit for ethanol below 47 fg.
Andreas Schütze, Nikolai Helwig, and Tizian Schneider
J. Sens. Sens. Syst., 7, 359–371, https://doi.org/10.5194/jsss-7-359-2018, https://doi.org/10.5194/jsss-7-359-2018, 2018
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“Industrie 4.0” or the Industrial Internet of Things (IIoT) describe the current (r)evolution in industrial automation and control. This is fundamentally based on smart sensors, which generate data and allow further functionality from self-monitoring and self-configuration to condition monitoring of complex processes. The paper reviews the development of sensor technology over the last 2 centuries and highlights some of the potential that can be achieved with smart sensors and data analysis.
Sascha Eichstädt, Clemens Elster, Ian M. Smith, and Trevor J. Esward
J. Sens. Sens. Syst., 6, 97–105, https://doi.org/10.5194/jsss-6-97-2017, https://doi.org/10.5194/jsss-6-97-2017, 2017
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The challenges in the analysis of dynamic measurements significantly limit the use of existing calibration facilities and mathematical methodologies. Several international research projects have developed methodologies for the treatment of dynamic measurements at the NMI level. The transfer to industry, though, remains challenging. Therefore, this work provides a link from these activities to industrial end-users by means of the new versatile and comprehensive software package
PyDynamic.
Martin Leidinger, Joni Huotari, Tilman Sauerwald, Jyrki Lappalainen, and Andreas Schütze
J. Sens. Sens. Syst., 5, 147–156, https://doi.org/10.5194/jsss-5-147-2016, https://doi.org/10.5194/jsss-5-147-2016, 2016
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For the application of indoor air quality monitoring, two types of tungsten oxide gas sensor layers were prepared via pulsed laser deposition. Analysis of the structure of the produced layers showed that they consist of nanoparticles and agglomerates of nanoparticles. The sensors showed significant sensitivity and selectivity towards naphthalene in the ppb concentration range. The results were achieved using temperature cycled operation of the sensors and pattern recognition signal treatment.
M. Schüler, T. Sauerwald, and A. Schütze
J. Sens. Sens. Syst., 4, 305–311, https://doi.org/10.5194/jsss-4-305-2015, https://doi.org/10.5194/jsss-4-305-2015, 2015
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We study the effect of HMDSO vapor on an SnO2-based gas sensor in temperature cycled operation (TCO). The poisoning can be quantified at early stages with a resolution of ±85 ppm*min using TCO. This approach provides a simple method for early detection of HMDSO poisoning.
The stability of gas discrimination by linear discriminant analysis (LDA) can be improved using normalization, which in turn facilitates a more accurate determination of the poisoning state by hierarchical LDA discrimination.
B. Schmitt, C. Kiefer, and A. Schütze
J. Sens. Sens. Syst., 4, 239–247, https://doi.org/10.5194/jsss-4-239-2015, https://doi.org/10.5194/jsss-4-239-2015, 2015
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A novel sensor principle for determining binary fluid mixtures of known components is presented. A bluff body is placed in the fluid channel, causing the formation of a stationary pair of vortices behind the body. The length of the vortex pair depends on the mixture’s viscosity and thus its composition. It is measured by placing a microheater in the vortex area and making use of forced convection which changes with the size of the vortices.
D. Puglisi, J. Eriksson, C. Bur, A. Schuetze, A. Lloyd Spetz, and M. Andersson
J. Sens. Sens. Syst., 4, 1–8, https://doi.org/10.5194/jsss-4-1-2015, https://doi.org/10.5194/jsss-4-1-2015, 2015
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This study aims at the development of high-performance and cost-efficient gas sensors for sensitive detection of three specific hazardous gases, i.e., formaldehyde, naphthalene, and benzene, commonly present in indoor environments in concentrations of health concern. We used silicon carbide field effect transistors to investigate the sensor performance and characteristics under different levels of relative humidity up to 60%, demonstrating excellent detection limits in the sub-ppb range.
C. Bur, M. Bastuck, A. Schütze, J. Juuti, A. Lloyd Spetz, and M. Andersson
J. Sens. Sens. Syst., 3, 305–313, https://doi.org/10.5194/jsss-3-305-2014, https://doi.org/10.5194/jsss-3-305-2014, 2014
M. Leidinger, T. Sauerwald, W. Reimringer, G. Ventura, and A. Schütze
J. Sens. Sens. Syst., 3, 253–263, https://doi.org/10.5194/jsss-3-253-2014, https://doi.org/10.5194/jsss-3-253-2014, 2014
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An approach for detecting hazardous volatile organic compounds (VOCs) in ppb and sub-ppb concentrations is presented. Using metal oxide semiconductor (MOS) gas sensors in temperature cycled operation, VOCs in trace concentrations are successfully identified against a varying ethanol background of up to 2 ppm. For signal processing, linear discriminant analysis is applied to single sensor data and sensor fusion data. Integrated gas sensor systems using the same MOS sensors were characterized.
M. Schüler, T. Sauerwald, and A. Schütze
J. Sens. Sens. Syst., 3, 213–221, https://doi.org/10.5194/jsss-3-213-2014, https://doi.org/10.5194/jsss-3-213-2014, 2014
T. Bley, E. Pignanelli, and A. Schütze
J. Sens. Sens. Syst., 3, 121–132, https://doi.org/10.5194/jsss-3-121-2014, https://doi.org/10.5194/jsss-3-121-2014, 2014
M. Bastuck, C. Bur, A. Lloyd Spetz, M. Andersson, and A. Schütze
J. Sens. Sens. Syst., 3, 9–19, https://doi.org/10.5194/jsss-3-9-2014, https://doi.org/10.5194/jsss-3-9-2014, 2014
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Structure of digital metrological twins as software for uncertainty estimation
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Test equipment and its effect on the calibration of instrument transformers
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Christian Orgeldinger, Florian Wohlgemuth, Andreas Michael Müller, and Tino Hausotte
J. Sens. Sens. Syst., 11, 219–223, https://doi.org/10.5194/jsss-11-219-2022, https://doi.org/10.5194/jsss-11-219-2022, 2022
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Industrial X-ray computed tomography is a holistic measurement technique for dimensional metrology. However, the relatively long measurement time is a hindrance to its application. A possibility to reduce measurement times, the continuous scan mode, is characterized in this work. The question is how much the time reduction impacts the accuracy of the dimensional measurements. The core result of the paper is an estimate of the effect along with experimental proof that this estimate is reasonable.
Ivan Poroskun, Christian Rothleitner, and Daniel Heißelmann
J. Sens. Sens. Syst., 11, 75–82, https://doi.org/10.5194/jsss-11-75-2022, https://doi.org/10.5194/jsss-11-75-2022, 2022
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Jacques Hameury, Guillaume Failleau, Mariacarla Arduini, Jochen Manara, Elena Kononogova, Albert Adibekyan, Christian Monte, Alexander Kirmes, Eric Palacio, and Holger Simon
J. Sens. Sens. Syst., 10, 135–152, https://doi.org/10.5194/jsss-10-135-2021, https://doi.org/10.5194/jsss-10-135-2021, 2021
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A TIR100-2 emissometer is used to measure the emissivity of thermal insulation products using the
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Manuel Kaufmann, Ira Effenberger, and Marco F. Huber
J. Sens. Sens. Syst., 10, 101–108, https://doi.org/10.5194/jsss-10-101-2021, https://doi.org/10.5194/jsss-10-101-2021, 2021
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Andreas Michael Müller and Tino Hausotte
J. Sens. Sens. Syst., 9, 61–70, https://doi.org/10.5194/jsss-9-61-2020, https://doi.org/10.5194/jsss-9-61-2020, 2020
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The framework of the single point uncertainty presents a methodology to determine the local measurement uncertainty for a measurement setup. The targets of the investigation were spur (involute) steel gear wheels using a CMM in scanning mode in combination with a rotatory table, as well as a single scan of the complete gear profile without the use of a rotatory table, using the
free-form scanCMM functionality. Both methods were examined with respect to their obtained single point uncertainty.
Andreas Michael Müller, Dominik Schubert, Dietmar Drummer, and Tino Hausotte
J. Sens. Sens. Syst., 9, 51–60, https://doi.org/10.5194/jsss-9-51-2020, https://doi.org/10.5194/jsss-9-51-2020, 2020
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This paper aims to demonstrate the complete workflow of the determination of the local measurement uncertainty and its components (systematic and random measurement error) for a given measurement task. It was shown for an optical measurement setup in combination with an industrial X-ray computed tomography reference measurement system that different necessary colouring methods of polymer gear wheels have a measurable influence on the local distribution of the measurement uncertainty.
Nadine Schiering and Olaf Schnelle-Werner
J. Sens. Sens. Syst., 8, 251–259, https://doi.org/10.5194/jsss-8-251-2019, https://doi.org/10.5194/jsss-8-251-2019, 2019
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When using pressure gauges in industry the uncertainty contribution due to the calibration should be expanded by the uncertainty contributions due to specific application. There the end user must investigate these sources or other additional influences. In addition, the new challenges in terms of calibration and traceability when applying Smart Sensor Technologies and Digitally Networked Measurement Systems were addressed.
Giulio D'Emilia, Antonella Gaspari, and Emanuela Natale
J. Sens. Sens. Syst., 8, 223–231, https://doi.org/10.5194/jsss-8-223-2019, https://doi.org/10.5194/jsss-8-223-2019, 2019
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A method for amplitude–phase calibration of tri-axial accelerometers in the low-frequency range is proposed, based on a linear slide, used to excite all the axes of the accelerometer at the same time, and a laser Doppler vibrometer (LDV) as a reference. Results show that the phase is a critical aspect to consider in calibration, more than the amplitude, and the comparison with the theoretical model is useful to verify the hypotheses. Different behaviours result, depending on the measuring chain.
Paula Weidinger, Gisa Foyer, Stefan Kock, Jonas Gnauert, and Rolf Kumme
J. Sens. Sens. Syst., 8, 149–159, https://doi.org/10.5194/jsss-8-149-2019, https://doi.org/10.5194/jsss-8-149-2019, 2019
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To determine the efficiency of multi-MW wind turbines, the torque measurement in wind turbine test benches has to be performed with a high accuracy. To this end, the torque measurement has to be traced to national standards. This can be done by using a novel torque transfer standard in combination with a newly developed torque calibration procedure under constant rotation. The calibration procedure was performed on a wind turbine test bench.
Mathias Ziebarth, Niclas Zeller, Michael Heizmann, and Franz Quint
J. Sens. Sens. Syst., 7, 517–533, https://doi.org/10.5194/jsss-7-517-2018, https://doi.org/10.5194/jsss-7-517-2018, 2018
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We propose a measurement uncertainty model of two complementary optical sensors: a deflectometric and a plenoptic sensor. The deflectometric sensor uses active triangulation and works best on specular surfaces, while the plenoptic sensor uses passive triangulation and works best on textured, diffusely reflecting surfaces. The predicted uncertainties can be used to obtain optimized measurements for varying surface properties. The models are validated exemplarily based on real measurements.
Andreas Schütze, Nikolai Helwig, and Tizian Schneider
J. Sens. Sens. Syst., 7, 359–371, https://doi.org/10.5194/jsss-7-359-2018, https://doi.org/10.5194/jsss-7-359-2018, 2018
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“Industrie 4.0” or the Industrial Internet of Things (IIoT) describe the current (r)evolution in industrial automation and control. This is fundamentally based on smart sensors, which generate data and allow further functionality from self-monitoring and self-configuration to condition monitoring of complex processes. The paper reviews the development of sensor technology over the last 2 centuries and highlights some of the potential that can be achieved with smart sensors and data analysis.
Enrico Mohns and Peter Räther
J. Sens. Sens. Syst., 7, 339–347, https://doi.org/10.5194/jsss-7-339-2018, https://doi.org/10.5194/jsss-7-339-2018, 2018
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Test centres supplying accuracy tests for instrument transformers must provide measurement uncertainties for their quality management. In this work, ratio error and phase displacement of instrument transformers are discussed. The traceability to the national standards of PTB, the attainable uncertainty and the permitted error limits of test equipment for testing instrument transformers are presented.
An example of an uncertainty budget for a current transformer of the class 0,2 S is given.
Silke Augustin, Thomas Fröhlich, Marc Schalles, and Stefan Krummeck
J. Sens. Sens. Syst., 7, 331–337, https://doi.org/10.5194/jsss-7-331-2018, https://doi.org/10.5194/jsss-7-331-2018, 2018
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In the data sheets of the thermometer manufacturers, different specifications can be found to describe the dynamic properties of contact thermometers. The present paper describes the results of a bilateral comparison made for the first time for determining dynamic parameters for two thermocouples in the laboratories of the JUMO GmbH & Co. KG Fulda company and at the Institute of Process Measurement and Sensor Technology of the TU Ilmenau with similar facilities, but different results.
Gunter Hagen, Antonia Harsch, and Ralf Moos
J. Sens. Sens. Syst., 7, 79–84, https://doi.org/10.5194/jsss-7-79-2018, https://doi.org/10.5194/jsss-7-79-2018, 2018
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Monitoring hydrocarbon concentrations in automotive exhausts is affected by flow rate changes. The signal of thermoelectric gas sensors is a thermovoltage. Its origin is a temperature difference that depends on the flow rate. To avoid this noise effect, the sensor can be installed in a defined bypass position. As shown by simulation and experiments, the gas flow around the sensor is almost turbulence-free and the signal only depends on the hydrocarbon concentration and not on the flow rate.
Marc Fischer, Marcus Petz, and Rainer Tutsch
J. Sens. Sens. Syst., 6, 145–153, https://doi.org/10.5194/jsss-6-145-2017, https://doi.org/10.5194/jsss-6-145-2017, 2017
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For optical measurement systems, camera noise is the dominant uncertainty factor when optically cooperative surfaces are measured in a stable environment. In this work it will be shown that the resulting spatial noise can be estimated by means of a noise model. The capability of this approach will be demonstrated for a fringe projection system. This provides a valuable tool for a statistical comparison of different evaluation strategies, which is shown for two different triangulation procedures.
Sascha Eichstädt, Clemens Elster, Ian M. Smith, and Trevor J. Esward
J. Sens. Sens. Syst., 6, 97–105, https://doi.org/10.5194/jsss-6-97-2017, https://doi.org/10.5194/jsss-6-97-2017, 2017
Short summary
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The challenges in the analysis of dynamic measurements significantly limit the use of existing calibration facilities and mathematical methodologies. Several international research projects have developed methodologies for the treatment of dynamic measurements at the NMI level. The transfer to industry, though, remains challenging. Therefore, this work provides a link from these activities to industrial end-users by means of the new versatile and comprehensive software package
PyDynamic.
M. P. Henry, M. S. Tombs, and F. B. Zhou
J. Sens. Sens. Syst., 3, 97–103, https://doi.org/10.5194/jsss-3-97-2014, https://doi.org/10.5194/jsss-3-97-2014, 2014
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Short summary
A fundamental problem of machine learning (ML) is measurement uncertainty and the influence on ML results. Measurement uncertainty, which is critical in hazardous gas detection, is directly addressed in this paper. A previously published toolbox is extended for regression. One of the benefits of this approach is obtaining a better understanding of where the overall system should be improved. This can be achieved by either improving the trained ML model or using a sensor with higher precision.
A fundamental problem of machine learning (ML) is measurement uncertainty and the influence on...
