Articles | Volume 7, issue 2
https://doi.org/10.5194/jsss-7-489-2018
© Author(s) 2018. 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-7-489-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regular research article
| 
20 Sep 2018
Regular research article |
| 20 Sep 2018
| 20 Sep 2018
DAV3E – a MATLAB toolbox for multivariate sensor data evaluation
Manuel Bastuck
CORRESPONDING AUTHOR
Lab for Measurement Technology, Saarland University, 66123
Saarbrücken, Germany
Applied Sensor Science, SAS, IFM, Linköping University, 58183
Linköping, Sweden
Tobias Baur
Lab for Measurement Technology, Saarland University, 66123
Saarbrücken, Germany
Andreas Schütze
Lab for Measurement Technology, Saarland University, 66123
Saarbrücken, Germany
Related authors
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.
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.
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. 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
Tanja Dorst, Tizian Schneider, Sascha Eichstädt, and Andreas Schütze
J. Sens. Sens. Syst., 12, 45–60, https://doi.org/10.5194/jsss-12-45-2023, https://doi.org/10.5194/jsss-12-45-2023, 2023
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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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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.
Tilman Sauerwald, Tobias Baur, Martin Leidinger, Wolfhard Reimringer, Laurent Spinelle, Michel Gerboles, Gertjan Kok, and Andreas Schütze
J. Sens. Sens. Syst., 7, 235–243, https://doi.org/10.5194/jsss-7-235-2018, https://doi.org/10.5194/jsss-7-235-2018, 2018
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For detection of benzene, a multichannel gas sensor system was tested in two different laboratories at the concentration range from 0.5 ppb up to 10 ppb. A model is used to extract the channels and multilinear regression is done to compensate cross interference to other gases. Depending on the measurement conditions, the quantification accuracy is between ±0.2 ppb and ±2 ppb. Regression models for one laboratory were transferable between the labs under comparable measurement conditions.
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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Measurement systems: Multi-sensor systems
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Miguel-David Méndez-Bohórquez, Sebastian Schramm, Robert Schmoll, and Andreas Kroll
J. Sens. Sens. Syst., 13, 123–133, https://doi.org/10.5194/jsss-13-123-2024, https://doi.org/10.5194/jsss-13-123-2024, 2024
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3D thermograms are a good alternative when a single traditional 2D thermal image does not reveal enough information to analyze a complex object. However, the 3D thermography field is still under exploration. This paper shows a comparison of a thermography system operated with two different 3D sensors. The results indicate that the depth sensor with more accurate measurements captures the object geometry better, and therefore the interpretation of the 3D thermograms is improved.
Yann Sperling and Ralf Bernhard Bergmann
J. Sens. Sens. Syst., 13, 1–7, https://doi.org/10.5194/jsss-13-1-2024, https://doi.org/10.5194/jsss-13-1-2024, 2024
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Phase-measuring deflectometry is an optical shape measurement technique for reflective surfaces. The basic idea is that a pattern that is observed through reflection on a curved surface gets distorted and reveals information about its shape. In this work we describe a method to move the pattern to obtain data for quantitative shape determination. The experimental setup is calibrated. With a laser tracker we reveal calibration errors and discuss their influence on the reconstructed shape.
Hendrik Wulfmeier, Niklas Warnecke, Luca Pasquini, Holger Fritze, and Philippe Knauth
J. Sens. Sens. Syst., 11, 51–59, https://doi.org/10.5194/jsss-11-51-2022, https://doi.org/10.5194/jsss-11-51-2022, 2022
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A newly developed experimental setup to characterize thin polymeric films during dehydration and hydration is presented. The great advantage of this measurement device and technique is that it monitors the mass change and conductivity of the films in situ and simultaneously at virtually identical conditions. The feasibility of the technique is demonstrated by characterizing ionomer thin films. A mass resolution of ±7.9 ng is achieved. The precision of relative humidity (RH) control is ±0.15 %.
Robert Schmoll, Sebastian Schramm, Tom Breitenstein, and Andreas Kroll
J. Sens. Sens. Syst., 11, 41–49, https://doi.org/10.5194/jsss-11-41-2022, https://doi.org/10.5194/jsss-11-41-2022, 2022
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The method of non-contact temperature measurement in conjunction with a 3D sensor described in this paper can be used to determine the heat loss of technical devices and industrial plants. This measurement tool thus helps to optimize the energy efficiency of these devices and plants.
Marc Pillarz, Axel von Freyberg, and Andreas Fischer
J. Sens. Sens. Syst., 9, 273–282, https://doi.org/10.5194/jsss-9-273-2020, https://doi.org/10.5194/jsss-9-273-2020, 2020
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The necessary reliability of wind turbine gearboxes increases the requirements for large gear measurements. However, standard measuring methods reach their limits for large gears with diameters > 1 m. Therefore a scalable optical gear measurement approach is presented. At first, simulation and experimental results prove the principle applicability of the measuring approach for small gear measurements. Geometric parameters of gears can be determined with a single-digit micrometer uncertainty.
Marcin Uradzinski and Hang Guo
J. Sens. Sens. Syst., 9, 7–13, https://doi.org/10.5194/jsss-9-7-2020, https://doi.org/10.5194/jsss-9-7-2020, 2020
Sebastian Hagemeier, Markus Schake, and Peter Lehmann
J. Sens. Sens. Syst., 8, 111–121, https://doi.org/10.5194/jsss-8-111-2019, https://doi.org/10.5194/jsss-8-111-2019, 2019
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In this contribution a multi-sensor measuring system is presented. With this measurement system comparative measurements using five different surface measurement sensors are performed under identical conditions in a single set-up. The presented measurement results show different transfer behaviour of each sensor and indicate unique advantages for tactile and optical sensors. Comparative measuring enables the investigation of measurement deviations and helps to improve appropriate techniques.
Pierre Bellier, Philippe Laurent, Serguei Stoukatch, François Dupont, Laura Joris, and Michael Kraft
J. Sens. Sens. Syst., 7, 299–308, https://doi.org/10.5194/jsss-7-299-2018, https://doi.org/10.5194/jsss-7-299-2018, 2018
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An original platform embedding multiple sensors and an energy harvesting unit is described. It is versatile and requires little or no maintenance. Multiple platforms can be connected to a hub device in a wireless sensor network. Emphasis was put on the reduction of power consumption and on the energy harvesting unit. With the addition of a small solar panel the system can be fully autonomous indoors. Characterization of power consumption and a test in real-world operation are presented.
Max Koeppel, Stefan Werzinger, Thomas Ringel, Peter Bechtold, Torsten Thiel, Rainer Engelbrecht, Thomas Bosselmann, and Bernhard Schmauss
J. Sens. Sens. Syst., 7, 91–100, https://doi.org/10.5194/jsss-7-91-2018, https://doi.org/10.5194/jsss-7-91-2018, 2018
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Optical temperature sensors offer unique features which make them indispensable for key industries such as the energy sector. However, commercially available systems are designed to perform either distributed or hot spot temperature measurements. We have combined two measurement concepts to overcome this limitation, which allow distributed temperature measurements to be performed simultaneously with read-outs of optical hot spot temperature sensors at distinct positions along a fiber.
Jajnabalkya Guhathakurta, Daniela Schurr, Günter Rinke, Roland Dittmeyer, and Sven Simon
J. Sens. Sens. Syst., 6, 223–236, https://doi.org/10.5194/jsss-6-223-2017, https://doi.org/10.5194/jsss-6-223-2017, 2017
Christoph Kandlbinder, Alice Fischerauer, Mario Mösch, Tobias Helling, Gerhard Fischerauer, and Martin Siegl
J. Sens. Sens. Syst., 6, 135–143, https://doi.org/10.5194/jsss-6-135-2017, https://doi.org/10.5194/jsss-6-135-2017, 2017
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In this work we present a cost- and energy-efficient measurement system for the spatial detection of gas phases in liquid fluids with a low permittivity value. We showed that we can simulate the system and its environment and use the calculated results to interpret the results originating from measurements of the electrical capacitance between different electrodes. The proposed system can be modified for, e.g., observation of fluid behaviour in cryogenic tanks for reigniteable space propulsion.
Nick Rüssmeier, Axel Hahn, Daniela Nicklas, and Oliver Zielinski
J. Sens. Sens. Syst., 6, 37–52, https://doi.org/10.5194/jsss-6-37-2017, https://doi.org/10.5194/jsss-6-37-2017, 2017
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Maritime study sites utilized as a physical experimental test bed for sensor data fusion, communication technology and data stream analysis tools can provide substantial frameworks for design and development of e-navigation technologies. Increasing safety by observation and monitoring of the maritime environment with new technologies meets forward-looking needs to facilitate situational awareness. The study highlights research potentials and foundations achieved by distributed optical sensors.
Jan-Friedrich Ehlenbröker, Uwe Mönks, and Volker Lohweg
J. Sens. Sens. Syst., 5, 337–353, https://doi.org/10.5194/jsss-5-337-2016, https://doi.org/10.5194/jsss-5-337-2016, 2016
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This paper presents a novel method for the detection of sensor defects. Here, the consistency between measurements of sensor groups are utilized for this method. The sensor groups are pre-determined by the structure of an existing sensor fusion algorithm, which is in turn used to determine the health of a monitored system (e.g. a machine). Defect detection results of the presented method for different test cases and the method's capability to detect a number of typical sensor defects are shown.
Dietrich Imkamp, Jürgen Berthold, Michael Heizmann, Karin Kniel, Eberhard Manske, Martin Peterek, Robert Schmitt, Jochen Seidler, and Klaus-Dieter Sommer
J. Sens. Sens. Syst., 5, 325–335, https://doi.org/10.5194/jsss-5-325-2016, https://doi.org/10.5194/jsss-5-325-2016, 2016
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Strategic considerations and publications dealing with the future of industrial production are significantly influenced these days by the concept of "Industrie 4.0". For this reason the field of measurement technology for industrial production must also tackle this concept when thinking about future trends and challenges in metrology.
Hanieh Safari, Thomas Fricke, Björn Reddersen, Thomas Möckel, and Michael Wachendorf
J. Sens. Sens. Syst., 5, 301–312, https://doi.org/10.5194/jsss-5-301-2016, https://doi.org/10.5194/jsss-5-301-2016, 2016
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This study aimed to explore the potential of a multi-sensor system for assessment of biomass in pastures under different grazing intensities. Prediction accuracy with a mobile application of sensors was always lower than when sensors were applied statically. However accuracy of biomass prediction improved with increasing grazing intensity. Although the limitations associated with the system especially in very lenient pastures, the finding opens up a perspective for future grazing management.
Sebastian Felix Reinecke and Uwe Hampel
J. Sens. Sens. Syst., 5, 213–220, https://doi.org/10.5194/jsss-5-213-2016, https://doi.org/10.5194/jsss-5-213-2016, 2016
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Sensor particles with buoyancy control and position detection are presented, which are used for flow tracking in large vessels, such as biogas digesters and waste water tanks. They were tested in the realistic flows of a biogas digester. The buoyancy control allows taring for good flow tracing by the sensor particles, and it lets them float to the surface after data acquisition for easy recovery. The fluid mixing was estimated from detected passages of sensor particles at a magnetic coil.
A. Loderer and T. Hausotte
J. Sens. Sens. Syst., 5, 1–8, https://doi.org/10.5194/jsss-5-1-2016, https://doi.org/10.5194/jsss-5-1-2016, 2016
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This article describes a new qualification concept for dimensional measurements on optical measuring systems, using the example of a prototypical multi-scale multi-sensor fringe projection system for production-related inspections of sheet-bulk metal-formed parts. A new concept is developed for determining the orientations and positions of the sensors' measuring ranges in a common coordinate system. The principle element of the concept is a newly developed flexible reference artefact.
S. Sachse, A. Bockisch, U. Enseleit, F. Gerlach, K. Ahlborn, T. Kuhnke, U. Rother, E. Kielhorn, P. Neubauer, S. Junne, and W. Vonau
J. Sens. Sens. Syst., 4, 295–303, https://doi.org/10.5194/jsss-4-295-2015, https://doi.org/10.5194/jsss-4-295-2015, 2015
C. W. Zecha, J. Link, and W. Claupein
J. Sens. Sens. Syst., 2, 51–72, https://doi.org/10.5194/jsss-2-51-2013, https://doi.org/10.5194/jsss-2-51-2013, 2013
Cited articles
Abdi, H.: Partial least squares regression and projection on latent structure
regression, WIREs Comput. Stat., 2, 97–106, https://doi.org/10.1002/wics.051, 2010.
Altman, Y. M.: Undocumented Secrets of MATLAB-Java Programming, CRC Press,
2012.
Andersson, M., Pearce, R., and Spetz, A. L.: New generation SiC based field
effect transistor gas sensors, Sensor. Actuat.-B Chem., 179, 95–106,
https://doi.org/10.1016/j.snb.2012.12.059, 2013.
Apetrei, C., Rodríguez-Méndez, M. L., Parra, V., Gutierrez, F., and
De Saja, J. A.: Array of voltammetric sensors for the discrimination of
bitter solutions, Sensor. Actuat.-B Chem., 103, 145–152,
https://doi.org/10.1016/j.snb.2004.04.047, 2004.
Apetrei, C., Apetrei, I. M., Nevares, I., del Alamo, M., Parra, V.,
Rodríguez-Méndez, M. L., and De Saja, J. A.: Using an e-tongue based
on voltammetric electrodes to discriminate among red wines aged in oak
barrels or aged using alternative methods. Correlation between
electrochemical signals and analytical parameters, Electrochim. Acta, 52,
2588–2594, https://doi.org/10.1016/j.electacta.2006.09.014, 2007.
Bastuck, M. and Fricke, T.: Temperature-modulated gas sensor signal (Version
1.0.0), Data set, Zenodo, https://doi.org/10.5281/zenodo.1411209, 2018.
Bastuck, M., Puglisi, D., Huotari, J., Sauerwald, T., Lappalainen, J., Spetz,
A. L., Andersson, M., Schütze, A., Lloyd Spetz, A., Andersson, M., and
Schütze, A.: Exploring the selectivity of WO3 with iridium catalyst in an
ethanol/naphthalene mixture using multivariate statistics, Thin Solid Films,
618, 263–270, https://doi.org/10.1016/j.tsf.2016.08.002, 2016a.
Bastuck, M., Baur, T., and Schütze, A.: Fusing cyclic sensor data with
different cycle length, 2016 IEEE International Conference on Multisensor
Fusion and Integration for Intelligent Systems (MFI), IEEE, Baden-Baden,
Germany, 19–21 September 2016, 72–77, 2016b.
Bastuck, M., Daut, C., and Schütze, A.: Signalkompensation mittels
Gate-Potential bei gassensitiven Feldeffekttransistoren, in 13. Dresdner
Sensor-Symposium, 277–282, 2017.
Baur, T., Schütze, A., and Sauerwald, T.: Optimierung des
temperaturzyklischen Betriebs von Halbleitergassensoren, tm – Tech. Mess.,
82, 187–195, https://doi.org/10.1515/teme-2014-0007, 2015.
Böhm, C., Berchtold, S., and Keim, D.: Searching in high-dimensional
spaces: Index structures for improving the performance of multimedia
databases, ACM Comput. Surv., 33, 322–373, https://doi.org/10.1145/502807.502809, 2001.
Browne, M.: Cross-Validation Methods, J. Math. Psychol., 44, 108–132,
https://doi.org/10.1006/jmps.1999.1279, 2000.
Bur, C.: Selectivity Enhancement of Gas Sensitive Field Effect Transistors by
Dynamic Operation, Linköping University Electronic Press/Shaker Verlag,
2015.
Cetó, X., Apetrei, C., Del Valle, M., and Rodríguez-Méndez, M.
L.: Evaluation of red wines antioxidant capacity by means of a voltammetric
e-tongue with an optimized sensor array, Electrochim. Acta, 120, 180–186,
https://doi.org/10.1016/j.electacta.2013.12.079, 2014.
Chang, R. M., Kauffman, R. J., and Kwon, Y.: Understanding the paradigm shift
to computational social science in the presence of big data, Decis. Support
Syst., 63, 67–80, https://doi.org/10.1016/j.dss.2013.08.008, 2014.
Darmastuti, Z., Bur, C., Lindqvist, N., Andersson, M., Schütze, A., and
Lloyd Spetz, A.: Chemical Hierarchical methods to improve the performance of
the SiC-FET as SO2 sensors in flue gas desulphurization systems, Sensor.
Actuat.-B Chem., 206, 609–616, https://doi.org/10.1016/j.snb.2014.09.113, 2015.
Ding, H., Ge, H., and Liu, J.: High performance of gas identification by
wavelet transform-based fast feature extraction from temperature modulated
semiconductor gas sensors, Sensor. Actuat.-B Chem., 107, 749–755,
https://doi.org/10.1016/j.snb.2004.12.009, 2005.
Eicker, H.: Method and apparatus for determining the concentration of one
gaseous component in a mixture of gases, US Pat. 4012692, 1977.
Geladi, P. and Kowalski, B. R.: Partial least-squares regression: a tutorial,
Anal. Chim. Acta, 185, 1–17, https://doi.org/10.1016/0003-2670(86)80028-9, 1986.
Graham, L. and Oppacher, F.: Hill-Valley Data Set, UCI Machine Learning
Repository, 2008, available at:
http://archive.ics.uci.edu/ml/datasets/hill-valley, last access: 14
September 2018.
Gramm, A. and Schütze, A.: High performance solvent vapor identification
with a two sensor array using temperature cycling and pattern classification,
Sensor. Actuat.-B Chem., 95, 58–65, https://doi.org/10.1016/S0925-4005(03)00404-0, 2003.
Gutierrez-Osuna, R.: Pattern analysis for machine olfaction: A review, IEEE
Sens. J., 2, 189–202, https://doi.org/10.1109/JSEN.2002.800688, 2002.
Gutierrez-Osuna, R. and Nagle, H. T.: A method for evaluating
data-preprocessing techniques for odor classification with an array of gas
sensors, IEEE T. Syst. Man Cy. B, 29, 626–632, https://doi.org/10.1109/3477.790446,
1999.
Hastie, T., Tibshirani, R., and Friedman, J.: The Elements of Statistical
Learning, Springer, 2009.
Hawkins, D. M.: The Problem of Overfitting, J. Chem. Inf. Comput. Sci., 44,
1–12, https://doi.org/10.1021/ci0342472, 2004.
HDF5 Group: HDF5, available at: https://www.hdfgroup.org/HDF5/, last
access: 13 February 2016.
Heilig, A., Bârsan, N., Weimar, U., Schweizer-Berberich, M., Gardner, J.
W., and Göpel, W.: Gas identification by modulating temperatures of
SnO2-based thick film sensors, Sensor. Actuat.-B Chem., 43, 45–51,
https://doi.org/10.1016/S0925-4005(97)00096-8, 1997.
Helwig, N., Schüler, M., Bur, C., Schütze, A., and Sauerwald, T.: Gas
mixing apparatus for automated gas sensor characterization, Meas. Sci.
Technol., 25, 055903, https://doi.org/10.1088/0957-0233/25/5/055903, 2014.
Helwig, N., Pignanelli, E., and Schütze, A.: Condition monitoring of a
complex hydraulic system using multivariate statistics, 2015 IEEE
International Instrumentation and Measurement Technology Conference (I2MTC)
Proceedings, 210–215, https://doi.org/10.1109/I2MTC.2015.7151267, 2015.
Helwig, N., Pignanelli, E., and Schütze, A.: Condition monitoring of
hydraulic systems Data Set, UCI Machine Learning Repository, 2018, available
at:
https://archive.ics.uci.edu/ml/datasets/Condition+monitoring+of+hydraulic+systems,
last access: 14 September 2018.
Huang, X. J., Choi, Y. K., Yun, K. S., and Yoon, E.: Oscillating behaviour of
hazardous gas on tin oxide gas sensor: Fourier and wavelet transform
analysis, Sensor. Actuat.-B Chem., 115, 357–364,
https://doi.org/10.1016/j.snb.2005.09.022, 2006.
James, G., Witten, D., Hastie, T., and Tibshirani, R.: An introduction to
statistical learning: with applications in R, Springer, 2013.
Kitchin, R.: Big Data, new epistemologies and paradigm shifts, Big Data Soc.,
1, 1–12, https://doi.org/10.1177/2053951714528481, 2014.
Kohavi, R.: A Study of Cross-Validation and Bootstrap for Accuracy Estimation
and Model Selection, IJCAI'95 Proceedings of the 14th international joint
conference on Artificial intelligence, 14, 1137–1143, 1995.
Lee, A. P. and Reedy, B. J.: Temperature modulation in semiconductor gas
sensing, Sensor. Actuat.-B Chem., 60, 35–42,
https://doi.org/10.1016/S0925-4005(99)00241-5, 1999.
Leidinger, M., Huotari, J., Sauerwald, T., Lappalainen, J., and Schütze,
A.: Selective detection of naphthalene with nanostructured WO3 gas sensors
prepared by pulsed laser deposition, J. Sens. Sens. Syst., 5, 147–156,
https://doi.org/10.5194/jsss-5-147-2016, 2016.
Lichman, M.: UCI Machine Learning Repository, Univ. California, Irvine, Sch.
Inf. Comput. Sci., available at: http://archive.ics.uci.edu/ml (last
access: 14 September 2018), 2013.
Marco, S. and Gutierrez-Galvez, A.: Signal and data processing for machine
olfaction and chemical sensing: A review, IEEE Sens. J., 12, 3189–3214,
https://doi.org/10.1109/JSEN.2012.2192920, 2012.
Moreno-Barón, L., Cartas, R., Merkoçi, A., Alegret, S., Del Valle,
M., Leija, L., Hernandez, P. R., and Muñoz, R.: Application of the
wavelet transform coupled with artificial neural networks for quantification
purposes in a voltammetric electronic tongue, Sensor. Actuat.-B Chem., 113,
487–499, https://doi.org/10.1016/j.snb.2005.03.063, 2006.
Næs, T. and Mevik, B. H.: Understanding the collinearity problem in
regression and discriminant analysis, J. Chemom., 15, 413–426,
https://doi.org/10.1002/cem.676, 2001.
Reimann, P. and Schütze, A.: Sensor Arrays, Virtual Multisensors, Data
Fusion, and Gas Sensor Data Evaluation, in Gas Sensing Fundamentals, vol. 15,
edited by: Kohl, C.-D. and Wagner, T., Springer Berlin Heidelberg, Berlin,
Heidelberg, 67–107, 2014.
Risvik, H.: Principal component analysis (PCA) & NIPALS algorithm, 2007.
Sampson, D. and Tordoff, B.: GUI Layout Toolbox, available at:
https://de.mathworks.com/matlabcentral/fileexchange/47982-gui-layout-toolbox,
last access: 28 January 2017.
Sauerwald, T., Baur, T., Leidinger, M., Spinelle, L., Gerboles, M., and
Schütze, A.: Laborübertragbare Kalibrierung von Sensoren für die
Messung von Benzol, 13. Dresdner Sensor-Symposium, Dresden, Germany, 4–6
Dezember, 2017, 105–110, 2017.
Schultealbert, C., Baur, T., Schütze, A., Böttcher, S., and
Sauerwald, T.: A novel approach towards calibrated measurement of trace gases
using metal oxide semiconductor sensors, Sensor. Actuat.-B Chem., 239,
390–396, https://doi.org/10.1016/j.snb.2016.08.002, 2017.
Schütze, A., Gramm, A., and Rühl, T.: Identification of organic
solvents by a virtual multisensor system with hierarchical classification,
IEEE Sens. J., 4, 857–863, https://doi.org/10.1109/JSEN.2004.833514, 2004.
Smola, A. J. and Schölkopf, B.: A tutorial on support vector regression,
Stat. Comput., 14, 199–222, https://doi.org/10.1023/B:STCO.0000035301.49549.88, 2004.
van den Berg, R. a, Hoefsloot, H. C. J., Westerhuis, J. a, Smilde, A. K., and
van der Werf, M. J.: Centering, scaling, and transformations: improving the
biological information content of metabolomics data, BMC Genomics, 7, 142,
https://doi.org/10.1186/1471-2164-7-142, 2006.
Winquist, F., Wide, P., and Lundström, I.: An electronic tongue based on
voltammetry, Anal. Chim. Acta, 357, 21–31,
https://doi.org/10.1016/S0003-2670(97)00498-4, 1997.
Yamazoe, N. and Shimanoe, K.: Theory of power laws for semiconductor gas
sensors, Sensor. Actuat.-B Chem., 128, 566–573,
https://doi.org/10.1016/j.snb.2007.07.036, 2008.
Short summary
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.
Predictions about systems too complex for physical modeling can be made nowadays with data-based...
