Automated parameter extraction of ScAlN MEMS devices using an extended Euler-Bernoulli beam theory

Magnetoelectric sensors provide the ability to measure magnetic fields down to the pico tesla range and are currently the subject of intense research. Such sensors usually combine a piezoelectric and a magnetostrictive material, so that magnetically induced stresses can be measured electrically. Scandium aluminium nitride gained a lot of attraction in the last few years due to its enhanced piezoelectric properties. Its usage as resonantly driven microelectromechanical system (MEMS) in such sensors is accompanied by a manifold of influences from crystal growth leading to impacts on the electrical and mechanical parameters. Usual investigations via nanoindentation allow a fast determination of mechanical properties with the disadvantage of lacking the access to the anisotropy of specific properties. Such anisotropy effects are investigated in this work in terms of the Young’s modulus and the strain on basis of a MEMS structures through a newly developed fully automated procedure of eigenfrequency fitting based on a new non-Lorentzian fit function and subsequent analysis using an extended Euler–Bernoulli theory. The introduced procedure is able to increase the resolution of the derived parameters compared to the common nanoindentation technique and hence allows detailed investigations of the behavior of magnetoelectric sensors, especially of the magnetic field dependent Young‘s modulus of the magnetostrictive layer

Indoor localization: novel RSSI approach based on analytical solution and two receivers

Indoor localization based on trilateration method uses at least three receivers for an accurate localization in 2-D. We performed indoor localization in 2-D using only two receivers, combining algebraic equations for signal strengths into one quadratic equation with transmitter position as unknown and using a specific receiver placement at the two adjacent corners of the room. This receiver arrangement assures unique coordinates of the transmitter position inside a room, rejecting automatically the other solution which appears outside the room volume. The accuracy of the method is numerically tested in a room with dimensions of 9.7 m × 4.7 m × 3 m and shows a mean reconstruction error of 3.4 cm

Comparison of defect detection limits in Lorentz force eddy current testing and classical eddy current testing

Lorentz force eddy current testing (LET) is a motion-induced eddy current testing method in the framework of nondestructive testing. In this study, we address the question of how this method is classified in comparison with a commercial eddy current testing (ECT) measurement device ELOTEST N300 in combination with the probe PKA48 from Rohmann GmbH. Therefore, measurements using both methods are performed and evaluated. Based on the measurement results, the corresponding defect detection limits, i.e., up to which depth the defect can be detected, are determined and discussed. For that reason, the excitation frequency spectrum of the induced eddy currents in the case of LET is considered

Scanning method for indoor localization using the RSSI approach

This paper presents a scanning method for indoor mobile robot localization using the received signal strength indicator (RSSI) approach. The method eliminates the main drawback of the conventional fingerprint, whose database construction is time-consuming and which needs to be rebuilt every time a change in indoor environment occurs. It directly compares the column vectors of a kernel matrix and signal strength vector using the Euclidean distance as a metric. The highest resolution available in localization using a fingerprint is restricted by a resolution of a set of measurements performed prior to localization. In contrast, resolution using the scanning method can be easily changed using a denser grid of potential sources. Although slightly slower than the trilateration method, the scanning method outperforms it in terms of accuracy, and yields a reconstruction error of only 0. 08 m averaged over 1600 considered source points in a room with dimensions 9.7 m × 4.7 m × 3 m. Its localization time of 0. 39 s makes this method suitable for real-time localization and tracking