Articles | Volume 14, issue 2
https://doi.org/10.5194/jsss-14-169-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/jsss-14-169-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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11 Aug 2025
Regular research article | Highlight paper |
| 11 Aug 2025
| 11 Aug 2025
Efficient hardware implementation of interpretable machine learning based on deep neural network representations for sensor data processing
Julian Schauer
CORRESPONDING AUTHOR
Lab for Measurement Technology, Saarland University, Saarbrücken, 66123, Germany
Payman Goodarzi
Lab for Measurement Technology, Saarland University, Saarbrücken, 66123, Germany
Andreas Schütze
Lab for Measurement Technology, Saarland University, Saarbrücken, 66123, Germany
Tizian Schneider
Lab for Measurement Technology, Saarland University, Saarbrücken, 66123, Germany
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Payman Goodarzi, Andreas Schütze, and Tizian Schneider
J. Sens. Sens. Syst., 14, 119–132, https://doi.org/10.5194/jsss-14-119-2025, https://doi.org/10.5194/jsss-14-119-2025, 2025
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Selecting the best model for monitoring industrial machines is challenging due to limited data and varying conditions. While deep learning (DL) is often considered ideal, it does not always perform well. We compared DL with traditional methods focused on feature extraction and classification. Our tests on seven datasets revealed that traditional methods are more reliable when machine conditions change, highlighting the importance of simpler, interpretable models for industrial monitoring.
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
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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.
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
Related subject area
Measurement systems: Sensor signal processing and electronics
Domain shifts in industrial condition monitoring: a comparative analysis of automated machine learning models
Suppression of polarization random noise in a two-dimensional force sensorbased on random forest
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Extraction of nanometer-scale displacements from noisy signals at frequencies down to 1 mHz obtained by differential laser Doppler vibrometry
Simple in-system control of microphone sensitivities in an array
Wireless surface acoustic wave resonator sensors: fast Fourier transform, empirical mode decomposition or wavelets for the frequency estimation in one shot?
Ultrasonic measurement setup for monitoring pre-thawing stages of food
Digital twin concepts for linking live sensor data with real-time models
Assisting the automated analysis of chemical–analytical measurements in spirits using validated algorithms and an intuitive user interface
Simulation-based investigation of the metrological interface structural resolution capability of X-ray computed tomography scanners
Design of a CMOS memristor emulator-based, self-adaptive spiking analog-to-digital data conversion as the lowest level of a self-x hierarchy
Smart in-cylinder pressure sensor for closed-loop combustion control
Efficient transient testing procedure using a novel experience replay particle swarm optimizer for THD-based robust design and optimization of self-X sensory electronics in industry 4.0
Intelligent fault detection of electrical assemblies using hierarchical convolutional networks for supporting automatic optical inspection systems
Measurement uncertainty analysis of field-programmable gate-array-based, real-time signal processing for ultrasound flow imaging
Compilation of training datasets for use of convolutional neural networks supporting automatic inspection processes in industry 4.0 based electronic manufacturing
Employing correlation for wireless components and device characterization in reverberation chambers
Impedance model for a high-temperature ceramic humidity sensor
Non-destructive testing of arbitrarily shaped refractive objects with millimetre-wave synthetic aperture radar imaging
Determining the dimension of subsurface defects by active infrared thermography – experimental research
Inverse calculation of strain profiles from ETDR measurements using artificial neural networks
An ultra-low noise capacitance to voltage converter for sensor applications in 0.35 µm CMOS
Development of a non-contact torque transducer based on the laser speckle contrast method
Development of a chopper charge amplifier for measuring the cavity pressure inside injection moulding tools and signal optimisation with a Kalman filter
Optimized mixed-domain signal synthesis for broadband impedance spectroscopy measurements on lithium ion cells for automotive applications
High-accuracy current measurement with low-cost shunts by means of dynamic error correction
A compact readout platform for spectral-optical sensors
High-speed camera-based measurement system for aeroacoustic investigations
Shutter-less calibration of uncooled infrared cameras
A novel approach for detecting HMDSO poisoning of metal oxide gas sensors and improving their stability by temperature cycled operation
Micro- and nanocoordinate measurements of micro-parts with 3-D tunnelling current probing
An electrical characterisation system for the real-time acquisition of multiple independent sensing parameters from organic thin film transistors
Piezoelectric transceiver matching for multiple frequencies
Metal oxide semiconductor gas sensor self-test using Fourier-based impedance spectroscopy
Work area monitoring in dynamic environments using multiple auto-aligning 3-D sensors
Principal component analysis for fast and automated thermographic inspection of internal structures in sandwich parts
Near-field interrogation of SAW resonators on rotating machinery
Magnetic properties of CHAMP and their effects on in-orbit calibration
Payman Goodarzi, Andreas Schütze, and Tizian Schneider
J. Sens. Sens. Syst., 14, 119–132, https://doi.org/10.5194/jsss-14-119-2025, https://doi.org/10.5194/jsss-14-119-2025, 2025
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Selecting the best model for monitoring industrial machines is challenging due to limited data and varying conditions. While deep learning (DL) is often considered ideal, it does not always perform well. We compared DL with traditional methods focused on feature extraction and classification. Our tests on seven datasets revealed that traditional methods are more reliable when machine conditions change, highlighting the importance of simpler, interpretable models for industrial monitoring.
Jian Liu
J. Sens. Sens. Syst., 14, 1–11, https://doi.org/10.5194/jsss-14-1-2025, https://doi.org/10.5194/jsss-14-1-2025, 2025
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To improve the accuracy of polarization random noise signal recognition and the noise suppression effect, a polarization random method of noise suppression in a two-dimensional force sensor based on random forest is proposed.
Majid Monajjemi, Fatemeh Mollaamin, Motahareh Dehghandar, Sara Shahriari, Parisa Latifi, and Samira Mohammadi
J. Sens. Sens. Syst., 13, 245–261, https://doi.org/10.5194/jsss-13-245-2024, https://doi.org/10.5194/jsss-13-245-2024, 2024
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We present a sensor platform that can detect the oral cancer signature of biomarkers in saliva. This system works by arraying metal–oxide–semiconductor field-effect transistors (MOSFETs) and electrolyte-gated transistors (EGTs), with each targeting a biorecognition element (BRE) from a DNA sequence found in the promoter region of most biomarker genes. This system is also applicable to the simultaneous diagnosis of TNF-α and IL-1β immune-modulator biomarkers.
Dhyan Kohlmann, Marvin Schewe, Hendrik Wulfmeier, Christian Rembe, and Holger Fritze
J. Sens. Sens. Syst., 13, 167–177, https://doi.org/10.5194/jsss-13-167-2024, https://doi.org/10.5194/jsss-13-167-2024, 2024
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A very small, anharmonic but periodic signal is separated from a noise background that is orders of magnitude larger than the pure signal. The approach consists of a sequence of filters and transformations and is demonstrated on an interferometric measurement of the high-temperature chemical expansion of a thin film, containing heat haze, thermal length drift, and parasitic vibrations. The displacement is 38 % larger and the uncertainty 35 % lower than when evaluated with previous approaches.
Artem Ivanov
J. Sens. Sens. Syst., 13, 81–88, https://doi.org/10.5194/jsss-13-81-2024, https://doi.org/10.5194/jsss-13-81-2024, 2024
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The presented approach allows users to perform measurements of microphone responses directly in the array using the internal hardware and so to characterize the whole signal chain of microphone–preamplifier–ADC. The measurements do not need special equipment and can be carried out in ordinary reverberant locations. A loudspeaker driven by a voltage pulse is used to produce a sound wave with a short first wavefront. Processing only this wavefront suppresses reflected waves that arrive later.
Angel Scipioni, Pascal Rischette, and Agnès Santori
J. Sens. Sens. Syst., 12, 247–260, https://doi.org/10.5194/jsss-12-247-2023, https://doi.org/10.5194/jsss-12-247-2023, 2023
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Many applications which measure physical quantities rely on wireless surface acoustic wave sensors. The accuracy of this sensor depends directly on the measurement of its main frequency. This paper aims to compare three methods for this measurement in one shot: fast Fourier transform, discrete wavelet transform, and empirical mode decomposition. Results show that the choice of the method is conditioned by the disturbance level and that the wavelet method is the best way for harsh environments.
Ruchi Jha, Walter Lang, and Reiner Jedermann
J. Sens. Sens. Syst., 12, 133–139, https://doi.org/10.5194/jsss-12-133-2023, https://doi.org/10.5194/jsss-12-133-2023, 2023
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In order to save time and avoid overheating of food during unfreezing, the study of ice content can be very useful. The aim of the research is to design an ultrasound-based sensor system that is able to comment on the content of ice in the sample food product. Some sample food products are tested, and the observations and challenges concerning the same are mentioned in the research paper.
Reiner Jedermann, Kunal Singh, Walter Lang, and Pramod Mahajan
J. Sens. Sens. Syst., 12, 111–121, https://doi.org/10.5194/jsss-12-111-2023, https://doi.org/10.5194/jsss-12-111-2023, 2023
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Mathematical models are often required to process sensor data in a digital twin platform. The translation of models to an updateable format enables predicting hidden states of the physical object, which are not directly measurable. The linking of different models is demonstrated by data from field tests on fruit transportation in refrigerated containers. We programmed a streaming platform that enables easy integration of such updatable models with only a few milliseconds of processing overhead.
Andreas T. Grasskamp, Satnam Singh, Helen Haug, and Tilman Sauerwald
J. Sens. Sens. Syst., 12, 93–101, https://doi.org/10.5194/jsss-12-93-2023, https://doi.org/10.5194/jsss-12-93-2023, 2023
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In this work, we have developed and validated a semi-automatic approach that greatly reduces the amount of interaction and effort needed for analyzing samples via gas chromatography–mass spectrometry. Further, unlike many other approaches, our developed tool is accessible to the novice and does not require any programming experience. Using whisky as an example substance, we show how the analysis method compares to conventional software, and we validate our approach against that.
Matthias Busch and Tino Hausotte
J. Sens. Sens. Syst., 12, 1–8, https://doi.org/10.5194/jsss-12-1-2023, https://doi.org/10.5194/jsss-12-1-2023, 2023
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The paper presents a specimen and evaluation method for interface structural resolution testing of X-ray computed tomography systems based on CT simulations. The geometry is oriented to the norms of image quality investigation. The evaluation is based on profile lines of the cross-sectional images that pass through the boreholes. All statements on resolution refer to the entire measurement chain and, thus, in addition to the reconstruction algorithm also to the surface determination method used.
Hamam Abd and Andreas König
J. Sens. Sens. Syst., 11, 233–262, https://doi.org/10.5194/jsss-11-233-2022, https://doi.org/10.5194/jsss-11-233-2022, 2022
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We pursue a promising novel self-adaptive spiking neural analog-to-digital data conversion (SN-ADC) design that uses spike time to carry information. Thus, SN-ADC can be effectively translated to aggressive new technologies to implement reliable advanced sensory electronic systems. The SN-ADC supports self-x (self-calibration, self-optimization, and self-healing) and machine learning required for the internet of things and Industry 4.0 and is based on a self-adaptive CMOS memristor.
Dennis Vollberg, Peter Gibson, Günter Schultes, Hans-Werner Groh, and Thomas Heinze
J. Sens. Sens. Syst., 11, 1–13, https://doi.org/10.5194/jsss-11-1-2022, https://doi.org/10.5194/jsss-11-1-2022, 2022
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We developed a smart in-cylinder pressure sensor for closed-loop combustion control. The sensor concept is based on a robust and reliable steel membrane equipped with highly strain-sensitive and temperature-stable thin films. The sensor system is complemented by a smart electronics allowing real-time data processing for calculation of different combustion parameters. The data are utilized to control the igniting timing of a spark plug for efficient operation of a combustion engine.
Qummar Zaman, Senan Alraho, and Andreas König
J. Sens. Sens. Syst., 10, 193–206, https://doi.org/10.5194/jsss-10-193-2021, https://doi.org/10.5194/jsss-10-193-2021, 2021
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A novel experience replay particle swarm optimization algorithm is presented and successfully deployed to improve the optimization performance for reconfigurable analog integrated circuits of industry 4.0. An optimization approach is introduced that relied on THD-based indirect measurement method that varies from the traditional calibration approach. Instead, the proposed calibration methodology optimizes all characteristics of the reconfigurable amplifier at once.
Alida Ilse Maria Schwebig and Rainer Tutsch
J. Sens. Sens. Syst., 9, 363–374, https://doi.org/10.5194/jsss-9-363-2020, https://doi.org/10.5194/jsss-9-363-2020, 2020
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In order to further increase the performance of neural networks in the field of optical quality assurance of soldered joints, a hierarchical classifier can be used instead of a single network. The global expansion of the classifier enables the inspection task to be distributed over several subnetworks, which results in higher accuracy. Since the individual sub-models only concentrate on the identification of certain characteristics, categorical problems can be solved more effectively.
Richard Nauber, Lars Büttner, and Jürgen Czarske
J. Sens. Sens. Syst., 9, 227–238, https://doi.org/10.5194/jsss-9-227-2020, https://doi.org/10.5194/jsss-9-227-2020, 2020
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To improve the energy efficiency of industrial processes, such as continuous steel casting, lab-scale experiments with liquid metals are performed. We present an ultrasound Doppler signal process for multiplane, high-frame-rate flow imaging. We achieve real-time operations with an efficient implementation in a field-programmable gate array (FPGA). We analyze the contributions to the uncertainty of the velocity measurement and relate it to its fundamental limit.
Alida Ilse Maria Schwebig and Rainer Tutsch
J. Sens. Sens. Syst., 9, 167–178, https://doi.org/10.5194/jsss-9-167-2020, https://doi.org/10.5194/jsss-9-167-2020, 2020
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This article presents a classification concept based on deep learning as an additional optical test method for real-time visualization and analysis of electrical assemblies in the production environment. For this purpose, a neural convolutional network is used to identify the quality of the solder joint of surface-mounted chip components in the inspection images. The concept can be used to increase the detection performance of the solder joint inspection systems.
Christoph Cammin, Dmytro Krush, Ralf Heynicke, and Gerd Scholl
J. Sens. Sens. Syst., 8, 185–194, https://doi.org/10.5194/jsss-8-185-2019, https://doi.org/10.5194/jsss-8-185-2019, 2019
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Reverberation chambers are well-proven test environments for RF measurements. Typically, mean values are taken from the measurements to characterize the equipment under test. In the novel approach presented in this paper, the correlation of measured sample sequences is utilized to detect deviations, in particular of the radiation characteristics, from reference equipment.
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.
Ingrid Ullmann, Julian Adametz, Daniel Oppelt, Andreas Benedikter, and Martin Vossiek
J. Sens. Sens. Syst., 7, 309–317, https://doi.org/10.5194/jsss-7-309-2018, https://doi.org/10.5194/jsss-7-309-2018, 2018
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Millimetre-wave radar is an emerging technique for non-destructive testing: it is less costly than X-rays and has no ionizing radiation. Compared to ultrasound it does not require the device under test to be immersed in water. This article presents methods for high-resolution millimetre-wave radar imaging without a priori knowledge of the object's shape. A polymer device with simulated material defects is examined, which could be depicted precisely.
Slawomir Grys
J. Sens. Sens. Syst., 7, 153–160, https://doi.org/10.5194/jsss-7-153-2018, https://doi.org/10.5194/jsss-7-153-2018, 2018
Robin Höhne, Pawel Kostka, and Niels Modler
J. Sens. Sens. Syst., 6, 389–394, https://doi.org/10.5194/jsss-6-389-2017, https://doi.org/10.5194/jsss-6-389-2017, 2017
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This paper focuses on a novel carbon fibre sensor technology that exploits the low-cost and low-energy electrical reflectometry method for a spatially resolved strain measurement. The application of artificial neural networks for mapping the measured electrical signal to the existing strain profile is demonstrated. The potential and current limits are highlighted. The sensor is a promising part for the next generation of light-weight structures with operando health monitoring systems.
Alexander Utz, Christian Walk, Norbert Haas, Tatjana Fedtschenko, Alexander Stanitzki, Mir Mokhtari, Michael Görtz, Michael Kraft, and Rainer Kokozinski
J. Sens. Sens. Syst., 6, 285–301, https://doi.org/10.5194/jsss-6-285-2017, https://doi.org/10.5194/jsss-6-285-2017, 2017
Alberto Garinei and Roberto Marsili
J. Sens. Sens. Syst., 6, 253–258, https://doi.org/10.5194/jsss-6-253-2017, https://doi.org/10.5194/jsss-6-253-2017, 2017
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When a torque measurement is required, torque transducers show many drawbacks during their use: the usual limits are the need for contact and the effects on shaft line parameters. A new approach is proposed in this work: a non-contact torque meter for a machine shaft has been developed, based on a laser speckle contrast method. It carries out torque measurements evaluating the torsional displacement between two distinct sections of the shaft, through the monitoring of their roughness.
Manuel Schneider, Alexander Jahn, Norbert Greifzu, and Norbert Fränzel
J. Sens. Sens. Syst., 6, 199–210, https://doi.org/10.5194/jsss-6-199-2017, https://doi.org/10.5194/jsss-6-199-2017, 2017
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This article describes a chopper amplifier which has been specially developed for piezoelectric pressure sensors. It is shown that the amplifier provides good results for pressure measurement in injection moulds. A special feature of this work is the signal optimisation through the use of a Kalman filter.
Peter Haußmann and Joachim Melbert
J. Sens. Sens. Syst., 6, 65–76, https://doi.org/10.5194/jsss-6-65-2017, https://doi.org/10.5194/jsss-6-65-2017, 2017
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A method to generate broadband waveforms with low peak-to-peak amplitude based on distinct frequency domain profiles is presented, which includes random phase variation and numerical optimization. The peak-to-peak amplitude can be reduced by 71 % compared to zero-phase pulses with equal frequency domain characteristics. Used as excitation signals for impedance spectroscopy, the waveforms yield good results at significantly reduced measurement duration compared to established measurement methods.
Patrick Weßkamp and Joachim Melbert
J. Sens. Sens. Syst., 5, 389–400, https://doi.org/10.5194/jsss-5-389-2016, https://doi.org/10.5194/jsss-5-389-2016, 2016
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Measurement of electrical current is important for many scientific and industrial applications. Often shunt resistors are used. However, thermal effects due to self-heating and ambient temperature variation limit the achievable accuracy.
In this work, a dynamic compensation method is presented which takes static and dynamic temperature drift effects into account. It significantly reduces the remaining measurement errors. The approach can also be used to improve existing measurement systems.
Roland Wuchrer, Sabrina Amrehn, Luhao Liu, Thorsten Wagner, and Thomas Härtling
J. Sens. Sens. Syst., 5, 157–163, https://doi.org/10.5194/jsss-5-157-2016, https://doi.org/10.5194/jsss-5-157-2016, 2016
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The continuous monitoring of industrial and environmental processes is becoming an increasingly important aspect with both economic and societal impact. To realize this task, spectral-optical sensors with their outstanding properties in terms of sensitivity and reliability are a potential solution. However, for exploiting these sensors in a cost- and energy-efficient sensing system, a miniaturized readout unit is needed. Here we present a card-size, inexpensive, and robust readout electronics.
Johannes Gürtler, Daniel Haufe, Anita Schulz, Friedrich Bake, Lars Enghardt, Jürgen Czarske, and Andreas Fischer
J. Sens. Sens. Syst., 5, 125–136, https://doi.org/10.5194/jsss-5-125-2016, https://doi.org/10.5194/jsss-5-125-2016, 2016
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The interaction of sound and flow enables an efficient noise damping. Understanding this aeroacoustic damping phenomenon requires simultaneous measurement of flow and sound fields. Using a high-speed CMOS camera, two-component flow velocity measurements are performed in a three-dimensional region of interest. The sensor system can simultaneously capture sound and turbulent flow velocity oscillations. The presented measurements reveal that the sound energy is transferred into flow energy.
A. Tempelhahn, H. Budzier, V. Krause, and G. Gerlach
J. Sens. Sens. Syst., 5, 9–16, https://doi.org/10.5194/jsss-5-9-2016, https://doi.org/10.5194/jsss-5-9-2016, 2016
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Infrared cameras based on microbolometer focal plane arrays (FPAs) are the most widely used cameras in thermography. For acceptable measurement uncertainty values, the disturbing influences of changing ambient temperature have to be considered. We propose a TEC-less and shutter-less correction approach based on additional temperature measurements inside the IR camera. The effects on the pixel responsivity and offset voltage are considered separately.
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.
A. Schuler, T. Hausotte, and Z. Sun
J. Sens. Sens. Syst., 4, 199–208, https://doi.org/10.5194/jsss-4-199-2015, https://doi.org/10.5194/jsss-4-199-2015, 2015
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Measurement tasks of modern micro- and nanometrology with decreasing structure sizes and rising aspect ratios require nanometre-resolving 3-D capable sensors. A 3-D probing system based on electrical interaction is presented which is operated on a nanopositioning system NMM-1. New 3-D measurement procedures for the probing system as well as for micrometrology measurement tasks in general are shown.
A. Dragoneas, L. Hague, and M. Grell
J. Sens. Sens. Syst., 4, 169–177, https://doi.org/10.5194/jsss-4-169-2015, https://doi.org/10.5194/jsss-4-169-2015, 2015
A. Ens and L. M. Reindl
J. Sens. Sens. Syst., 4, 9–16, https://doi.org/10.5194/jsss-4-9-2015, https://doi.org/10.5194/jsss-4-9-2015, 2015
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
Y. Wang, D. Ewert, T. Meisen, D. Schilberg, and S. Jeschke
J. Sens. Sens. Syst., 3, 113–120, https://doi.org/10.5194/jsss-3-113-2014, https://doi.org/10.5194/jsss-3-113-2014, 2014
D. Griefahn, J. Wollnack, and W. Hintze
J. Sens. Sens. Syst., 3, 105–111, https://doi.org/10.5194/jsss-3-105-2014, https://doi.org/10.5194/jsss-3-105-2014, 2014
J.-M. Boccard, P. Katus, R. Renevier, L. M. Reindl, and J.-M. Friedt
J. Sens. Sens. Syst., 2, 147–156, https://doi.org/10.5194/jsss-2-147-2013, https://doi.org/10.5194/jsss-2-147-2013, 2013
H. Lühr, F. Yin, and R. Bock
J. Sens. Sens. Syst., 2, 9–17, https://doi.org/10.5194/jsss-2-9-2013, https://doi.org/10.5194/jsss-2-9-2013, 2013
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Short summary
Robust and interpretable machine learning algorithms, which have been proven in various applications, often lack efficient implementation on limited hardware. The novel approach is to convert the inference of the interpretable ML into a deep neural network, which is efficiently executable on edge hardware. This approach was validated in terms of runtime efficiency, memory requirements, and accuracy and resulted in a significant improvement in terms of runtime and memory requirements.
Robust and interpretable machine learning algorithms, which have been proven in various...
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