TY - JOUR A1 - Pogorzelski, Jens A1 - Horsthemke, Ludwig A1 - Homrighausen, Jonas A1 - Stiegekötter, Dennis A1 - Gregor, Markus A1 - Glösekötter, Peter T1 - Compact and Fully Integrated LED Quantum Sensor Based on NV Centers in Diamond JF - Compact and Fully Integrated LED Quantum Sensor Based on NV Centers in Diamond N2 - Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in diamond nano or microcrystals is a promising technology for sensitive, integrated magnetic-field sensors. Currently, this technology is still cost-intensive and mainly found in research. Here we propose one of the smallest fully integrated quantum sensors to date based on nitrogen vacancy (NV) centers in diamond microcrystals. It is an extremely cost-effective device that integrates a pump light source, photodiode, microwave antenna, filtering and fluorescence detection. Thus, the sensor offers an all-electric interface without the need to adjust or connect optical components. A sensitivity of 28.32nT/Hz−−−√ and a theoretical shot noise limited sensitivity of 2.87 nT/Hz−−−√ is reached. Since only generally available parts were used, the sensor can be easily produced in a small series. The form factor of (6.9 × 3.9 × 15.9) mm3 combined with the integration level is the smallest fully integrated NV-based sensor proposed so far. With a power consumption of around 0.1W, this sensor becomes interesting for a wide range of stationary and handheld systems. This development paves the way for the wide usage of quantum magnetometers in non-laboratory environments and technical applications. KW - Diamond Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:836-opus-175692 VL - 2024 IS - 24(3) ER - TY - JOUR A1 - Homrighausen, Jonas A1 - Horsthemke, Ludwig A1 - Pogorzelski, Jens A1 - Trinschek, Sarah A1 - Glösekötter, Peter A1 - Gregor, Markus T1 - Edge-Machine-Learning-Assisted Robust Magnetometer Based on Randomly Oriented NV-Ensembles in Diamond JF - Sensors N2 - Quantum magnetometry based on optically detected magnetic resonance (ODMR) of nitrogen vacancy centers in nano- or micro-diamonds is a promising technology for precise magnetic-field sensors. Here, we propose a new, low-cost and stand-alone sensor setup that employs machine learning on an embedded device, so-called edge machine learning. We train an artificial neural network with data acquired from a continuous-wave ODMR setup and subsequently use this pre-trained network on the sensor device to deduce the magnitude of the magnetic field from recorded ODMR spectra. In our proposed sensor setup, a low-cost and low-power ESP32 microcontroller development board is employed to control data recording and perform inference of the network. In a proof-of-concept study, we show that the setup is capable of measuring magnetic fields with high precision and has the potential to enable robust and accessible sensor applications with a wide measuring range. Y1 - 2023 UR - https://www.mdpi.com/1424-8220/23/3/1119 U6 - http://dx.doi.org/10.3390/s23031119 VL - 23 IS - 3 ER - TY - JOUR A1 - Wetter, Christof A1 - Brügging, Elmar A1 - Häner, Jurek A1 - Jantze, H.-A. A1 - Annas, Sven A1 - Glösekötter, Peter A1 - Horsthemke, L. A1 - Heller, A. A1 - Scholz, Dieter A1 - Reineck, S. A1 - Baumkötter, Daniel A1 - Grüner, Victoria A1 - Budelmann, J. T1 - NeoBio: Neue Entwicklungswerkzeuge zur Optimierung der Mischregime in Bioreaktoren JF - Fachagentur Nachwachsende Rohstoffe Y1 - 2023 UR - https://www.fh-muenster.de/egu/fue/fue_gebiete/biogas--und-landwirtschaft/neobio.php ER - TY - CHAP A1 - Löchte, Andre A1 - Thranow, Jan-Ole A1 - Winters, Felix A1 - Glösekötter, Peter T1 - Analysis of switching electronics for metal-air batterie T2 - ICECET, Prag N2 - The subject of this paper is the analysis of various switching electronics for batteries with separate electrodes for charging and discharging. The aim is to find a switching method that is energy-efficient on the one hand, but also economically viable on the other. Both relays and MOSFETs are suitable for switching between the electrodes. Both variants have advantages and disadvantages. The results show that a solution with MOSFETs is generally more energy-efficient, but requires a large number of cycles to be economically viable compared to the relay. KW - Analysis Y1 - 2022 U6 - http://dx.doi.org/10.1109/ICECET55527.2022.9872910 ER - TY - CHAP A1 - Gómez Zuluaga, Mauricio Andrés A1 - Ordikhani, Ahmad A1 - Bauer, Christoph A1 - Glösekötter, Peter T1 - Development and implementation of a neural network-based abnormal state prediction system for a piston pump T2 - IWANN2021 N2 - Piston pumps play a key role in factory automation and their availability is very critical for the smooth running of production processes. Modern installations, such as production plants and machines, are becoming increasingly complex. Therefore, the probability of a complete system failure due to a single critical component also increases. Maintenance processes with intelligent devices are therefore very important to achieve maximum economic efficiency and safety. Periodic or continuous monitoring of system components provides key information about the current physical state of the system, enabling early detection of emerging failures. Knowledge of future failures makes it possible to move from the concept of preventive maintenance to intelligent predictive maintenance. In this way, consequential damage and complete system failure can be avoided, maximizing system availability and safety. This paper reflects the development and implementation of a neural network system for abnormal state prediction of piston pumps. After a short introduction into piston pumps and their potential abnormal states, statistical and periodical analysis are presented. Then the design and implementation of suitable neural networks are discussed. Finally, a conclusion is drawn and the observed accuracies as well as potential next steps are discussed. KW - Development and implementation Y1 - 2021 SN - 978-3-030-85029-6 U6 - http://dx.doi.org/10.1007/978-3-030-85030-2_24 PB - Springer Nature Switzerland AG 2021 ER - TY - CHAP A1 - Rörup, Tim A1 - Glösekötter, Peter A1 - Pomares, Hector A1 - Ruiz, Ignacio T1 - Deep Learning Based Neural Network for Six-Class-Classification of Alzheimer's Disease Stages Based on MRI Images T2 - IWANN2021 N2 - State of the art classifiers split Alzheimer’s disease progression into a limited number of stages and use a comparatively small database. For the best treatment, it is desirable to have the highest resolution from the progression of the disease. This paper proposes a reliable deep convolutional neural network for the classification of six different Alzheimer’s disease stages based on Magnetic Resonance Imaging (MRI). The peculiarity of this paper is the introduction of a new, sixth, disease stage, and the large amount of data that has been taken into account. Additionally, not only the testing accuracy is analyzed, but also the robustness of the classifier to have feedback on how certain the neural network makes its predictions. KW - Deep Learning Y1 - 2021 U6 - http://dx.doi.org/10.1007/978-3-030-85030-2_1 SP - 3 EP - 14 PB - Springer International Publishing ER - TY - JOUR A1 - Löchte, Andre A1 - Rojas Ruiz, Ignacio A1 - Glösekötter, Peter T1 - Battery State Estimation with ANN and SVR Evaluating Electrochemical Impedance Spectra Generalizing DC Currents JF - Applied Sciences N2 - The demand for energy storage is increasing massively due to the electrification of transport and the expansion of renewable energies. Current battery technologies cannot satisfy this growing demand as they are difficult to recycle, as the necessary raw materials are mined under precarious conditions, and as the energy density is insufficient. Metal–air batteries offer a high energy density as there is only one active mass inside the cell and the cathodic reaction uses the ambient air. Various metals can be used, but zinc is very promising due to its disposability and non-toxic behavior, and as operation as a secondary cell is possible. Typical characteristics of zinc–air batteries are flat charge and discharge curves. On the one hand, this is an advantage for the subsequent power electronics, which can be optimized for smaller and constant voltage ranges. On the other hand, the state determination of the system becomes more complex, as the voltage level is not sufficient to determine the state of the battery. In this context, electrochemical impedance spectroscopy is a promising candidate as the resulting impedance spectra depend on the state of charge, working point, state of aging, and temperature. Previous approaches require a fixed operating state of the cell while impedance measurements are being performed. In this publication, electrochemical impedance spectroscopy is therefore combined with various machine learning techniques to also determine successfully the state of charge during charging of the cell at non-fixed charging currents. Keywords: electrochemical impedance spectroscopy; artificial neural networks; support vector regression; zinc-air battery; state estimation; state of charge KW - Battery State Estimation Y1 - 2021 SN - 978-84-1117-173-1 U6 - http://dx.doi.org/10.3390/app12010274 VL - 12 IS - 1 SP - 275 ER - TY - JOUR A1 - Staacke, Robert A1 - John, Roger A1 - Wunderlich, Ralf A1 - Horsthemke, Ludwig A1 - Knolle, Wolfgang A1 - Laube, Christian A1 - Glösekötter, Peter A1 - Burchard, Bernd A1 - Abel, Bernd A1 - Meijer, Jan T1 - Isotropic Scalar Quantum Sensing of Magnetic Fields for Industrial Application JF - Advanced Quantum Technologies N2 - Magnetic field sensors based on quantum mechanic effects are often susceptible to misalignments of the magnetic field or need advanced procedures to compensate for these. Also, the record breaking sensitivities reported for superconducting quantum interference devices and alkali vapor magnetometers come along with large and complex experimental setups. The nitrogen vacancy center in diamond can be used to design a simple, small, and robust sensor without employing microwave radiation. By using compressed nanodiamond particles, it is possible to eliminate the need of an alignment of the magnetic field and still obtain the absolute magnetic flux density in a single measurement. In order to demonstrate the capabilities of this approach, a centimeter-sized modified automotive demo board is employed as a complete sensor with a sensitivity of 78 µT/Wurzel Hz. KW - Isotropic Scalar Y1 - 2020 U6 - http://dx.doi.org/10.1002/qute.202000037 SP - 1 EP - 8 PB - Wiley-Vch Verlag CY - Weinheim ER - TY - CHAP A1 - Horsthemke, Ludwig A1 - Staake, Robert A1 - Burchard, Bernd A1 - Meijer, Jan A1 - Bischoff, Christian A1 - Glösekötter, Peter T1 - Highly Sensitive Compact Room Temperature Quantum Scalar Magnetormeter T2 - SMSI 2020 N2 - Magnetometry with nitrogen–vacancy (NV) defects in diamond has been extensively stud-ied in the past [1]. While most approaches in-clude the use of microwaves (MW) for the de-tection of electron spin resonance, only few investigate the sensitivity of the photolumines-cence (PL) from NV centers to an external magnetic field without MW [2, 3, 4]. This work aims to utilize this effect to build a highly sensi-tive and compact room temperature magne-tometer. The avoidance of MW serves the re-duction of production costs and allows a com-mercialization at the current patent situation. KW - Highly Sensitive Y1 - 2020 U6 - http://dx.doi.org/10.5162/SMSI2020/A1.4 SP - 47 EP - 48 ER - TY - JOUR A1 - Löchte, Andre A1 - Thranow, Jan-Ole A1 - Gebing, Marcel A1 - Horsthemke, Ludwig A1 - Glösekötter, Peter T1 - Forschungsprojekt Zink-Luft-Akkumulator an der FH Münster JF - VDI Ingenieur forum N2 - Die wachsenden Anteile fluktuierender rege­nerativer Energien in der Energieversorgung (bis 2020 sollen 30 % und 2050 sogar So % des Stroms aus regenerativen Energiequellen stammen) sowie die Steigerung der Elektro­mobilität machen deutlich: Das Thema der Zwischenspeicherung elektrischer Energie ist von höchster gesellschaftlicher Relevanz und verlangt zwingend nach einer Lösung. Neue Technologien, die umweltfreundlich, sicher, leistungsfähig und bezahlbar zugleich sind, müssen deshalb entwickelt werden. KW - Zink-Luft-Akkumulator Y1 - 2020 VL - H 45620 IS - 2/2020 SP - 50 EP - 51 ER -