The size-of-source effect (SSE) is a major source of uncertainty in radiation thermometers and thermal imaging cameras. This effect is considered a systematic error and is typically evaluated by measuring changes in the detected signal as the size of the radiant source is varied using a set of circular apertures of different diameters. The accurate characterization of the SSE requires measurements over a wide range of object sizes with well-distributed sample points, which is both time-consuming and labor-intensive. This paper proposes a new approach in which the aperture of an iris diaphragm is continuously adjusted to vary the size of the radiant source. An experimental study was conducted to compare the results obtained with individual fixed apertures and to assess whether the camera frame rate and the iris-driving period influence the measured temperature. The proposed approach reproduced the SSE with the same accuracy as measurements made with individual apertures while providing a significantly larger number of measurement points and a notable reduction in the measurement time. Furthermore, the method showed no significant sensitivity to the driving speed of the iris or the camera's frame rate within the investigated range. However, temporal effects arising from the optical components were found to disturb the measurement.
High-precision analysis of the stable isotopic composition of atmospheric methane (CH4) is essential for attributing its sources and sinks and for a more precise understanding of the global methane cycle. Although conventional isotope ratio mass spectrometry (IRMS) provides high accuracy, it lacks in situ capabilities and provides only low data rates. Tunable laser spectrometers offer higher acquisition rates and high sensitivity. In accordance with the Beer–Lambert law, the absorption signal increases proportionally with the optical path length, requiring kilometer-scale paths for atmospheric CH4δ13C) of the stable isotopologues 12CH413CH4cm−1r=0.999893), resulting in a theoretically effective path length of 22.53 km, which is integrated into an Invar cell with active temperature and pressure stabilization. Allan deviation analysis of the temperature regulation shows a minimum of σ=8.85 µK
This paper addresses the application of artificial intelligence in metallography. The aim is to determine the phase fractions of ferrite and austenite in the weld zone of duplex stainless steel based on the evaluation of metallographic microscopic micrographs. The idea arose from the motivation to technically replicate the functionality of the biological eye–brain system, thereby combining the properties of the highly effective human vision (or its simulation) with the significantly faster technical image-processing system. Since the distribution of pixel amplitudes in the metallographic images is irregular, the use of artificial intelligence is a suitable alternative to algorithm-based or gray-value statistical methods. Butt-welded sheet metal strips, which were cut in the weld zone, were used as sample material. The cut surfaces were polished and color-etched. Microscopic images were taken of the prepared samples. In the subsequent image analysis, both simple perceptron variants and deep convolutional neural networks (CNNs) were used. These were designed using appropriate tools and (subsequently) implemented programmatically. To obtain a sufficient amount of training data, the use of synthetic data derived from original data was investigated and implemented for training the networks in addition to using polished samples from real specimens. Training and test runs were conducted with various datasets and network variants, and performance parameters were determined. The results obtained met expectations regarding both the use of synthetic data and the classification error rates of 2 %–3 %. Significant performance differences were observed in processing speed. Here, the convolutional neural networks performed considerably better than the perceptrons.
Emission measurement of on-road vehicles in traffic is an important step for air pollution control and, thus, the reduction of negative effects on public health. Remote emission sensing (RES) is a state-of-the-art technology to detect high emitters by monitoring thousands of vehicles in traffic continuously. State-of-the-art (SOTA) RES systems use optical techniques to measure the ratio of specific pollutants to CO22
In this study, a non-contact, optical methodology based on laser-Doppler vibrometry (LDV) is presented to directly determine the piezoelectric constant d3333d33The presented approach employs freely vibrating LiTaO3d33−1The LDV technique demonstrated here provides (i) non-contact measurement virtually free of clamping effects, (ii) access to high-temperature operation limited only by the furnace, (iii) the ability to map surface distribution, and (iv) the detection of resonances, thereby enabling off-resonant frequency ranges to be determined and to compare with literature values obtained by indirect or contact methods. While this study focuses on LiTaO3, the method is applicable to systems that exhibit displacements down to a few picometers.
We present an eight-channel evaluation board that enables fast data acquisition for ultrasound sonography (USG) and photoacoustic imaging (PAI). High frame rates enable averaging, resulting in an improved signal-to-noise ratio (SNR). A high SNR is becoming increasingly important in photoacoustic imaging, as the trend in the development of new systems is shifting from powerful solid-state lasers (pulse repetition frequency ≈ 10–100 Hz, pulse energy ≈ 10–100 mJ) to integrated compact pulsed laser diodes (PLDs) offering higher pulse repetition frequencies (≈ 1–10 kHz) at reduced pulse energies (≈ 1 µJ–2 mJ). The board is designed for processing high data rates and a robust analog signal chain. It integrates a programmable preamplifier (preamp) with adjustable gain followed by an integrated circuit comprising low-noise amplification, low-pass filtering, and 12-bit analog-to-digital (ADC) conversion. An AMD Zynq system-on-chip (SoC) handles processing on the board. The ADC is readout with low-voltage differential signal (LVDS) and the captured data are transmitted via Ethernet. Evaluation and image processing is done on a PC. The scientific contribution is the quantitative characterization of gain distribution and its effect on SNR in a multichannel photoacoustic receive chain. A sustained acquisition rate of 540 frames per second is demonstrated, validating frame averaging as an effective method to compensate for reduced pulse energy of compact pulsed laser diodes.
The implementation of automation in the metrological traceability of measurements has been demonstrated to possess considerable potential for enhancing the effectiveness of quality management. This enhancement is achieved by decreasing the necessity for human interaction and reducing the risks associated with manual data processing. For this purpose, it is imperative that all metrological and administrative information in quality certificates be provided in a fully machine-readable and machine-interpretable form. The transition from paper-based calibration certificates to Digital Calibration Certificates (DCCs), which meet these requirements, enables a fully automatic process conformity monitoring system. A demonstrator that monitors the temperature of a process has been developed as an example to illustrate the potential for automation that accompanies the use of DCCs, including in security. The programming code is also published to give a starting point for the reader's own implementation.
membrane, is made, we matched it better with the materials used to capture target chemicals. This makes the sensor easier to build and more reliable. Our work shows how choosing the right membrane material can greatly improve performance, opening the way for broader applications in detecting pollutants.
The recent bridged EGFET (extended-gate field effect transistor) sensor design is the most user-friendly potentiometric transducer concept to date. Manufacturing of the sensor, the introduction of a sensitised phase transfer membrane by in situ casting, and transduction of the electric potential resulting from analyte–sensitiser binding are remarkably simple. However, so far, the immobilisation of the sensitiser has only been demonstrated within an agar hydrogel phase transfer membrane, the same material used for the so-called bridge that defines the concept. Here, we demonstrate in situ casting of a plasticised polyvinyl chloride (PVC) membrane onto the agar bridge as an alternative. We compare the performance of different types of sensitisers – an organic dye and an ion-exchanging clay – for the same target analyte, Cr(VI) oxyanions, when the sensitiser is immobilised in either an agar hydrogel or a plasticised PVC membrane. We find superior performance, as quantified by sensor response at the Cr(VI) maximum contaminant limit, when the membrane and processing solvent match the solubility of the sensitiser. We unite the simplicity of the bridged EGFET, the convenience of in situ membrane casting, and the performance advantage of organic-solvent-processed phase transfer membranes for organic sensitisers.
The first choice in science and industry to image surfaces down to the sub-nm range are scanning electron microscopy (SEM) and atomic force microscopy (AFM). Both techniques have specific disadvantages which can be compensated by the other method. Therefore, the implementation of AFM inside an SEM vacuum chamber provides the user with the best of both worlds. When operated under vacuum, AFM cantilevers have larger Q factors than in air and thus a lower scanning speed. In this work, an electrical circuit and a piezoelectrically driven micro-electromechanical system (MEMS) cantilever is developed to tune the Q factor of the cantilever using a feedback system, with the goal of replacing air damping. In doing so, it is demonstrated that AFM measurements in vacuum with scanning speeds as under ambient air pressure are feasible. The cantilever features an electrically driven integrated piezoelectric transducer, which is used to excite the oscillation while the piezoelectric current serves as a feedback signal for a closed-loop feedback approach. In vacuum, the Q factor is reduced by a factor of 4. Hence, the cantilever oscillation and step response show a damping behaviour equivalent to an operation in air.
An algorithm for adaptive accuracy enhancement of lateral position sensing based on quadrature spatio-temporal modulation is presented, and its application in a prototype micropower optical position sensor with simultaneously firing infrared emitters is reported. Substantial (4×) improvement in measurement accuracy over a basic detection method has been observed using an automated test stand where partial incapacity on one of the emitter channels has been simulated.
This article investigates methods for sampling volatiles on a compounding extruder to enable the development of a quasi-continuous automated sampling and measurement system for odorous contaminants. A first prototype of a bespoke extraction system was presented in earlier work, comprising four sequential cooling traps and one subsequent sorption trap. This setup allows us to obtain samples from the vacuum degassing port of a Coperion ZSK extruder. Preliminary results indicated that samples contain a plethora of odor-active compounds. This study assesses samples from the processing of post-consumer recycled polypropylene by means of gas chromatography–mass spectrometry/olfactory detection (GC–MS/O), focusing on comparing the composition of condensed and adsorbed samples. The results give an overview of the degassing atmosphere, listing more than 108 volatile compounds including odorants. Qualitative comparison of the sampling techniques indicates significant fractioning between condensates and adsorbates, which is illustrated on an orientation plot for water solubility versus volatility. Based on the results, guidelines for the design of sampling units for automated use in the aspired online monitoring application are proposed to transfer a broad spectrum of relevant contaminants to an attached measurement system.
Wildlife-related traffic accidents represent a persistent hazard on rural roads in Germany and beyond. Current electronic wildlife warning systems typically monitor only very short distances and therefore cannot provide large-area coverage. This paper presents a novel multisensor approach that integrates radar and infrared (IR) technology into existing roadside delineators. Due to regulatory requirements, delineators are placed at intervals of 50 m on German country roads. Integrating sensors into these delineators thus provides a uniform infrastructure that can be utilised. The radial extension of the sensor range allows a monitoring zone to be formed along the road. We evaluate thermal infrared arrays and high-resolution 60 GHz radar sensors for range, resolution and robustness under varying environmental conditions. Field measurements in wildlife parks demonstrate that the system can reliably detect deer at distances of up to 30 m and evaluate their moving speed as well. Challenges such as ambient temperature effects, optical dispersion in IR detection and resolution limits are discussed. The results highlight the potential of multisensor systems to reduce wildlife accidents and improve road safety.
In times of digital transformation, machines are expected to operate exclusively using the International System of Units (SI), something that humans have not yet fully achieved. The same should include sensor systems feeding data to those machines. This requires an internationally authoritative database for converting the non-SI units that humans enter to SI units at the level of the human–machine interface or human–sensor interface.
Power transformers are an integral part of our electric power system. Parasitic direct currents in the alternating-current grid cause inefficient transformer operation and demand mitigation measures to protect the grid’s constituents. In particular, geomagnetically induced currents (GICs) arising from solar activity prove to be an unpredictable risk for grid operators. Within this paper, we present an interferometric fiber-optic current sensor system designed for long-term monitoring of GICs, allowing fully remote sensor control and data access. The developed sensor possesses a noise-limited threshold sensitivity of 2.64 mA 
The fabrication of microelectromechanical systems (MEMS) devices comprises many steps, each of which adds to the tolerance, resulting in device performances that may fall outside the defined limits in the design process. Hence, it is important to know local thin film properties most accurately, directly affecting the performance of the MEMS device. Furthermore, the capability of monitoring and mapping the thin film thickness and stress across a wafer enables device statistics and the strengthening of scientific statements. Within this study, we used standard MEMS structures consisting of a cantilever and a step profile to perform automated and contactless characterization of the local thin film thickness and stress across six 4-inch (100 mm) wafers. For this purpose, we constructed a measurement setup combining white light interferometry (WLI) to measure the static deflection of the cantilevered beams and plates and the thickness of the thin film through a step profile etched into the thin film. Even more, an XYZ-stage positions hundreds of devices below the objective lens of the WLI. This leads to precise maps of the local thin film thickness and to the extraction of a mean stress and a gradient stress from the static deflection of slender beams. The beams are oriented parallel and perpendicular to the wafer flat so that the measurement of orientation-dependent stress values is possible.
In an era of rapid technological advancement, object detection has become essential for enhancing efficiency and safety in various fields. Although significant progress has been made in air-based applications, underwater object detection remains relatively unexplored, especially in shallow aquatic environments such as coastal zones, harbors, and aquaculture facilities, due to its unique challenges. Ultrasonic technology, with its ability to travel long distances underwater and perform well in turbid and low-light conditions, stands out as a promising solution. Recent advances in micro-electromechanical system (MEMS) technology, particularly capacitive micromachined ultrasonic transducers (CMUTs), offer new opportunities for underwater detection. CMUTs are compact and highly sensitive and operate with a wide bandwidth, making them ideal for underwater applications. This research explores the use of CMUTs, fabricated by Fraunhofer ENAS with a resonant frequency of 1.5 MHz, for underwater object detection. Initial experiments confirmed their feasibility for detecting submerged objects of various sizes, shapes, and materials. Further investigations assessed the resolution of CMUTs in detecting minimum object sizes using an automated XYZ stage. Finally, the technology was used to map the topography of test objects, including intricate 3D structures and alphabet shapes, demonstrating its potential for high-resolution mapping. These results highlight the promising capabilities of CMUTs for underwater sensing applications, with substantial potential for further development.
A novel concept of an acoustic flowmeter, based on single-mode waveguides, is proposed, implemented, and analysed in this work. Instead of transmitting a pulse diagonally across the duct's cross-section, this device operates with two ducts that operate simultaneously as pipes and as waveguides. Below the frequency threshold for single-mode propagation, acoustic waves are forced to traverse the waveguides with a plane front, precluding the possibility of beam drifting, inner reflections, and spreading losses. This enables the designer to flexibly increase the sound path and perform a highly sensitive measurement of the flow velocity and speed of sound, even if the excitation frequency is required to be kept below a relatively low value. A device based on this principle was constructed and tested for flow measurements in air. It consists of two waveguides of a circular cross-section (5 mmkHz). Usage of a wideband signal was possible due to the combined frequency response of a special kind of micromachined ultrasound transducer (MUT) and a commercial micro-electromechanical system (MEMS) microphone. The constructed flowmeter was capable of measuring flow velocities up until the transition to turbulent flow at 16 L min−1L min−1, and it also detected changes of less than 0.2 m s−1
This research presents a capacitive displacement sensor concept, designed for integration into a pin array gripper. The sensor employs a plate capacitor structure to measure the displacement of individual pins, with each pin positioned to move between the electrodes. The sensor is designed with sensing, guiding and shielding electrodes to maintain a homogeneous electric field between the capacitor plates and a linear capacitance response. We implemented a shielding strategy with the objective of minimising external interference and reducing mutual interference between individual displacement sensors. This ensures stable operation and reliable measurements, which are crucial for the reliable functioning in dynamic environments. The design is optimised for additive manufacturing, offering advantages in customisation, adaptability to various pin gripping systems and a compact form factor. It also opens up new possibilities for integrating sensing elements directly into the structure of the gripper. A prototype sensor was fabricated using additive manufacturing and tested in an experimental setup to validate its functionality and to enable a comparison of its performance against the results of numerical simulations.
This study demonstrates how integrating silicon mechanical sensors into composite structures enables the detection of internal structural variations and can find applications in process monitoring or structural health monitoring (SHM). It introduces a novel, minimally intrusive process for embedding sensors within composites (substrate-free transfer-printed sensor). Both temperature and strain effects are studied and presented. The silicon strain sensor exhibits high sensitivity due to the piezoresistive effect. The combination of high temperature and strain produces a plastic degradation of the material, linked to the creep phenomenon of the composite's epoxy resin binder. This internal structure modification in the composite is directly detected with the strain gauges in real time.
Wearable biosensors play a crucial role in modern healthcare, providing continuous monitoring of various physiological parameters. However, the reliance on batteries that require replacement introduces interruptions in the data acquisition process and patient discomfort, and for this reason, energy harvesting methods that convert human body energy into electricity have attracted considerable research interest. In this paper, the concept of an innovative hybrid energy harvester that combines piezoelectric and reverse electrowetting-on-dielectric (REWOD) techniques is introduced. The key working principle revolved around the electrical double layer present in the REWOD component and coupling it with a piezoelectric generator via an electret. By harnessing biomechanical vibrations with a piezoelectric material and the REWOD unit, the overall power output of the harvester was enhanced. The proposed design was evaluated through numerical simulations and a series of experimental tests. In the present work, experimental results on the influence of various design parameters on the amount of generated power through the REWOD process are presented, thus contributing to the advancement of self-powered, sustainable, wearable biosensors, enabling seamless and continuous data acquisition without relying on external batteries.