Numerical analysis of an infrared gas sensor utilizing an indium-tin-oxide-based plasmonic slot waveguide

Plasmonic waveguides have attracted much attention owing to the associated high field intensity at the metal–dielectric interface and their ability to confine the modes at the nanometer scale. At the same time, they suffer from relatively high propagation loss, which is due to the presence of metal. Several alternative materials have been introduced to replace noble metals, such as transparent conductive oxides (TCOs). A particularly popular TCO is indium tin oxide (ITO), which is compatible with standard microelectromechanical systems (MEMS) technology. In this work, the feasibility of ITO as an alternative plasmonic material is investigated for infrared absorption sensing applications: we numerically design and optimize an ITO-based plasmonic slot waveguide for a wavelength of 4.26 µm, which is the absorption line of CO2. Our optimization is based on a figure of merit (FOM), which is defined as the confinement factor divided by the imaginary part of the effective mode index (i.e., the intrinsic damping of the mode). The obtained optimal FOM is 3.2, which corresponds to 9 µm and 49 % for the propagation length (characterizing the intrinsic damping) and the confinement factor, respectively.

Smart in-cylinder pressure sensor for closed-loop combustion control

Our approach of a closed-loop combustion control is built on an intensively evaluated robust cylinder pressure sensor with integrated smart electronics and an openly programmed engine control unit. The presented pressure sensor consists of a steel membrane and a highly strain-sensitive thin film with laser-welded electrical contacts. All components are optimized for reliable operation at high temperatures. The sensor setup safely converts the in-cylinder pressure of a combustion engine at temperatures of up to 200 ∘C into the desired electrical values. Furthermore, the embedded smart electronics provides a fast analogue to digital conversion and subsequently computes significant combustion parameters in real time, based on implemented thermodynamic equations, namely the 50 % mass fraction burned, the indicated mean effective pressure, the maximum pressure and a digital value, which represents the intensity of knocking. Only these aggregated parameters – not the running pressure values – are sent to the engine control unit. The data communication between the smart sensor and the engine control unit is based on the controller area network bus system, which is widely spread in the automotive industry and allows a robust data transfer minimizing electrical interferences. The established closed-loop combustion control is able to control the ignition angle in accordance with the 50 % mass fraction burned at a certain crankshaft angle. With this loop, the combustion engine is controlled and run efficiently even if the ignition angle is intentionally incorrectly adjusted. The controlled and automatic correction of simulated ageing effects is demonstrated as well as the self-adjustment of an efficient operation when different fuels are used. In addition, our approach saves the computing capacity of the engine control unit by outsourcing the data processing to the sensor system.

Validation of SI-based digital data of measurement using the TraCIM system

The digital transformation in the field of sensors and sensor systems fosters an increasing exchange and interoperation of measurement data by machines. The data of measurement need to be uniformly structured based on The International System of Units (SI) with appropriate information on measurement uncertainty. This work presents a concept for an online validation system that can be used by humans and software to efficiently classify the agreement of XML-structured data with relevant recommendations for measurement data. The system is within the TraCIM (Traceability for Computationally-Intensive Metrology) validation platform which was developed for software validation in metrology where high standards of quality management must be met.

Monitor and control test room for investigating thermal performance of panels incorporating phase-change material

This article aims to present equipment designed and developed to study the effective thermal conductivity of composite panels. The composite panel used is a rigid polyurethane foam covered with a layer of aluminum on both sides. The panel is mounted in the test chamber equipped with several sensors and actuators connected via an Arduino platform. Tests have been carried out by applying heat to impose various interior temperatures. Sensors at different locations are used to monitor and record temperatures in and around the composite panel during heating and natural cooling. A model, based on the Fourier equations of thermal conduction and natural convection heat transfer for the steady state, was developed to assess the effective thermal conductivity. The performance of the system was confirmed using temperature signals through the panels for thermal characterization of composite materials. The determined effective thermal conductivity obtained was in agreement with the experimental values reported in the technical data sheets with relative deviations of less than 10 %.

High-temperature behavior of housed piezoelectric resonators based on CTGS

A temperature sensor based on piezoelectric single crystals allowing stable operation in harsh environments such as extreme temperatures and highly reducing or oxidizing atmospheres is presented. The temperature dependence of the mechanical stiffness of thickness shear mode resonators is used to determine temperature changes. The sensor is based on catangasite (Ca3TaGa3Si2O14 – CTGS), a member of a langasite crystal family. CTGS exhibits an ordered crystal structure and low acoustic losses, even at 1000 ∘C. The resonance frequency and quality factor of unhoused and of housed CTGS resonators are measured up to about 1030 ∘C. A temperature coefficient of the resonance frequency of about 200 Hz K−1 for a 5 MHz device is found and enables determination of temperature changes as small as 0.04 K. Housed CTGS resonators do not show any significant change in the resonance behavior during a 30 d, long-term test at 711 ∘C.

Characterization of specular freeform surfaces from reflected ray directions using experimental ray tracing

The applications of freeform surfaces in optical components and systems are increasing more and more. Therefore, appropriate measurement techniques are needed to measure these freeform surfaces for verification. This task is still a challenge for most measurement techniques. In this paper, we propose a measurement technique for optical and other specular freeform surfaces based on experimental ray tracing. This technique is able to measure form and mid-spatial-frequency deviations simultaneously. The focus will be set on the sensing technique and the measurement uncertainties in the setup. As the measurement technique is described, an estimation of the influence of different uncertainties based on simulations is given. The result from an experimental measurement is evaluated in relation to the influence of the uncertainties. A comparison measurement for evaluation is given.

Referencing of powder bed for in situ detection of lateral layer displacements in additive manufacturing

An increasing number of additive manufacturing (AM) applications leads to rising challenges for the process-accompanying quality assurance. Beside post-processing measurement systems, in situ monitoring systems in particular are currently requested to ensure feedback controlling during AM processes. For data acquisition and subsequent evaluation, a high data quality is of importance. It depends on a high resolution and accuracy of measurement systems, adapted measurement conditions and a reference to the powder bed or component for geometric measurements. Within this scientific study, a new reference system has been implemented into the powder bed to reduce measurement deviations by an abbreviated metrological loop. After data acquisition and image processing layer by layer, the position stability of the reference system has been analysed in relation to the optical measuring system. Based on a contour detection of the reference markers, the evaluation of geometrical process deviations is presented as an essential basis for a closed-loop controlling system. Thermally induced and mechanical drifts within the manufacturing process can be verified by the reference system in the powder bed. As an outlook, two methods are suggested for a process-accompanying referenced detection of the melting pool and resulting contour displacements during additive manufacturing.

Influence of synchronization within a sensor network on machine learning results

Process sensor data allow for not only the control of industrial processes but also an assessment of plant conditions to detect fault conditions and wear by using sensor fusion and machine learning (ML). A fundamental problem is the data quality, which is limited, inter alia, by time synchronization problems. To examine the influence of time synchronization within a distributed sensor system on the prediction performance, a test bed for end-of-line tests, lifetime prediction, and condition monitoring of electromechanical cylinders is considered. The test bed drives the cylinder in a periodic cycle at maximum load, a 1 s period at constant drive speed is used to predict the remaining useful lifetime (RUL). The various sensors for vibration, force, etc. integrated into the test bed are sampled at rates between 10 kHz and 1 MHz. The sensor data are used to train a classification ML model to predict the RUL with a resolution of 1 % based on feature extraction, feature selection, and linear discriminant analysis (LDA) projection. In this contribution, artificial time shifts of up to 50 ms between individual sensors' cycles are introduced, and their influence on the performance of the RUL prediction is investigated. While the ML model achieves good results if no time shifts are introduced, we observed that applying the model trained with unmodified data only to data sets with time shifts results in very poor performance of the RUL prediction even for small time shifts of 0.1 ms. To achieve an acceptable performance also for time-shifted data and thus achieve a more robust model for application, different approaches were investigated. One approach is based on a modified feature extraction approach excluding the phase values after Fourier transformation; a second is based on extending the training data set by including artificially time-shifted data. This latter approach is thus similar to data augmentation used to improve training of neural networks.

Methods and procedure of referenced in situ control of lateral contour displacements in additive manufacturing

Additive manufacturing technologies are further developing from prototype to serial production. This trend requires rising challenges to the process-accompanying quality assurance. Optical in situ quality control approaches show great potential to generate accurate measurement data, which are essential for feedback control. If a reliable referencing concept for the layer-by-layer measured data is guaranteed, contour information can be used during the manufacturing to correct occurring geometrical deviations. Within this scientific study, two methods of optical, referenced in situ control of lateral displacements of additive manufactured contours are presented. In the first approach the 2-D contour of the melting pool is analysed in relation to a position-stable reference system implemented in the powder bed. The second approach uses the translucent contour of deeper layers covered with powder as a reference. Within the image evaluation several pre-processing steps like calibration, undistortion, rectification, illumination correction and low-pass filtering are essential for reliable and correct geometric measurements. The following adapted contour detection and position determination of the referenced melting pool contours are based on an extended edge detection algorithm according to Canny (1986). With the evaluation of further manufacturing layers of already lowered powder bed levels, it is possible to specify the influence of powder application on geometrical displacements separately. This is done by a comparison of the position of the detected powder-covered melting pool contours with the previously applied melted region. Consequently a better understanding of lateral contour displacements within the additive manufacturing process is the goal, which is important for a process-accompanying correction of geometrical deviations.

Iterative feature detection of a coded checkerboard target for the geometric calibration of infrared cameras

The geometric calibration of cameras becomes necessary when images should be undistorted, geometric image information is needed or data from more than one camera have to be fused. This process is often done using a target with a checkerboard or circular pattern and a given geometry. In this work, a coded checkerboard target for thermal imaging cameras and the corresponding image processing algorithm for iterative feature detection are presented. It is shown that, due in particular to the resulting better feature detectability at image borders, lower uncertainties in the estimation of the distortion parameters are achieved.