The 14th IMEKO TC10 Workshop on Technical Diagnostics

Despite continuous technological enhancements of metal Additive Manufacturing (AM) systems, the lack of process repeatability and stability still represents a barrier for the industrial breakthrough. The most relevant metal AM applications currently involve industrial sectors (e.g. aerospace and bio-medical) where defects avoidance is fundamental. Because of this, there is the need to develop novel in situ monitoring tools able to keep under control the stability of the process on a layer-by-layer basis, and to detect the onset of defects as soon as possible. On the one hand, AM systems must be equipped with in situ sensing devices able to measure relevant quantities during the process, a.k.a. process signatures. On the other hand, in-process data analytics and statistical monitoring techniques are required to detect and localize the defects in an automated way. This paper reviews the literature and the commercial tools for in situ monitoring of powder bed fusion (PBF) processes. It explores the different categories of defects and their main causes, the most relevant process signatures and the in situ sensing approaches proposed so far. Particular attention is devoted to the development of automated defect detection rules and the study of process control strategies, which represent two critical fields for the development of future smart PBF systems.

In this paper, we present and evaluate a new approach to communicate with inter-integrated circuit (I2C) enabled circuits such as sensors over near field communication (NFC). The NFC-to-I2C interface was designed using a non-standard NFC command to control the I2C bus directly from a smartphone, which was controlling both, the read and write operations on the I2C bus. The NFC-to-I2C interface was reporting back the data bytes on the bus to the smartphone when the transaction was completed successfully. The proposed system was tested experimentally, both, with write and read requests to a commercial microcontroller featuring a hardware I2C port, as well as reading a commercial I2C enabled humidity and temperature sensor. We present experimental results of the system which show that our approach enables an easy interface between smartphones and external sensors. Interfacing external sensors is useful and beneficial for smartphone users, especially, if certain types of sensors are not available on smartphones.

In this paper, a full featured MATLAB framework for Measurement System Analysis, fully compliant with the ISO 5725 Repeatability and Reproducibility (R&R) assessment is presented. While preserving the operations prescribed in the ISO standard, the software presents distinct improvements.

First of all, all computations are made using exact closed-form formulae (instead of statistical tables) allowing a consistent analysis without limitations on the number of participating laboratories and measurements, and using custom significance levels of statistical tests. Second, a double threshold decision system for each test step has been implemented, helping the statistician to decide on the elimination of outliers/stragglers. Third, ANOVA analysis has been included.

The software therefore, besides producing quickly and efficiently all the graphical and numerical results required in an inter-laboratory experiment, provide guidelines for properly updating the ISO 5725 standard.

The mode of primary oscillations of a micromechanical gyroscope (MMG) sensor is provided by an electrostatic comb-drive actuator in which the interaction between the micromechanical structures and electronics occurs by means of a single or differential capacitive sensor. Two pairs of capacitive sensors are traditionally used for frequency stabilization of MMG primary oscillations. The first pair of capacitive sensors excites primary oscillations, while the second measures the amplitude of primary oscillations. The stabilization system provides a continuous frequency tuning of primary oscillations that increases the duration of transition processes, the time of operational readiness, and the instability of the output signal from the secondary oscillation channel of the MMGs. This paper presents a new approach to the primary oscillation control system of the two-component MMG. The method of calculating the natural resonant frequency is based on measurements of the total current passing through the comb-driver actuator capacitances, and a lock-in detection is suggested. This paper consists of the results of the numerical analysis, the description of the proposed approach to the frequency control of the primary MMG oscillations, and the Simulink model of the behaviour of the MMG stabilization system, depending on its mechanical-and-physical properties with regard to a 2% shift of the natural resonant frequency. The frequency control of the primary oscillations at 2% frequency detuning is performed within 0.11 s.

Vision-based measurement techniques are often applied in experimental activities because of the possibility to obtain full-field dense measurement without any loading effect. Many different vision-based techniques are available in literature to measure a plurality of mechanical quantities. Digital image correlation (DIC) and pattern matching are very popular image processing techniques used in 2D and 3D measurement, in particular to estimate displacement and strain. Both these techniques show a systematic effect in displacement measurement. This paper proposed a novel method to compensate for the systematic effect in pattern matching and DIC. The basic idea is to shift the reference image backward and forward of an amount equal to 0.25 px using a Fourier-based technique, and then run the DIC analysis (or pattern matching analysis) two times, using each time one of the two new reference images. The final displacement is estimated by averaging the results of the two analyses. This approach allows significantly reducing the systematic effect in the results, as shown in the numerical and experimental validation. The numerical validation for different types of pattern and different noise levels is conducted for both DIC and pattern matching analysis. Moreover, the influence of the size of the pattern is discussed for pattern matching analysis. Finally the proposed technique is validated with an experimental test. To this purpose, a coordinate measuring machine (CMM) is used to impose subpixel displacement to a target and estimating the displacements with a pattern matching analysis on images acquired by a digital camera. The results of numerical validation and experimental validation demonstrate that the proposed compensation method allows reducing the systematic effect significantly.

Modal analysis is commonly considered as an effective tool to obtain the intrinsic characteristics of structures including natural frequencies, modal damping ratios, and mode shapes, which are significant indicators for monitoring the health status of engineering structures. The complex mode indicator function (CMIF) can be regarded as an effective numerical tool to perform modal analysis. In this paper, experimental strain modal analysis based on the CMIF has been introduced. Moreover, a distributed fiber-optic sensor, as a dense measuring device, has been applied to acquire strain data along a beam surface. Thanks to the dense spatial resolution of the distributed fiber optics, more detailed mode shapes could be obtained. In order to test the effectiveness of the method, a mass lump—considered as a linear damage component—has been attached to the surface of the beam, and damage detection based on strain mode shape has been carried out. The results manifest that strain modal parameters can be estimated effectively by utilizing the CMIF based on the corresponding simulations and experiments. Furthermore, damage detection based on strain mode shapes benefits from the accuracy of strain mode shape recognition and the excellent performance of the distributed fiber optics.

The effects of assumptions about bunch properties on the accuracy of the measurement method of the bunch length based on radio frequency deflectors (RFDs) in electron linear accelerators (LINACs) are investigated. In particular, when the electron bunch at the RFD has a non-negligible energy chirp (i.e. a correlation between the longitudinal positions and energies of the particle), the measurement is affected by a deterministic intrinsic error, which is directly related to the RFD phase offset. A case study on this effect in the electron LINAC of a gamma beam source at the Extreme Light Infrastructure-Nuclear Physics (ELI-NP) is reported. The relative error is estimated by using an electron generation and tracking (ELEGANT) code to define the reference measurements of the bunch length. The relative error is proved to increase linearly with the RFD phase offset. In particular, for an offset of ${{7}^{\circ}}$, corresponding to a vertical centroid offset at a screen of about 1 mm, the relative error is 4.5%.

Comprehensive analysis of the angular and linear accelerations of moving elements (shafts, gears) allows an increase in the quality of the condition monitoring of mechanisms. However, existing tools and methods measure either linear or angular acceleration with postprocessing. This paper suggests a new construction design of an angular acceleration sensor for moving elements. The sensor is mounted on a moving element and, among other things, the data transfer and electric power supply are carried out wirelessly. In addition, the authors introduce a method for processing the received information which makes it possible to divide the measured acceleration into the angular and linear components. The design has been validated by the results of laboratory tests of an experimental model of the sensor. The study has shown that this method provides a definite separation of the measured acceleration into linear and angular components, even in noise. This research contributes an advance in the range of methods and tools for condition monitoring of mechanisms.