Exploring the Use of Cold Atmospheric Plasma for Sound and Vibration Generation.

In this study, we investigate the potential of cold atmospheric plasma (CAP) as a non-contact excitation device, comparing its performance with an ultrasound transmitter. Utilizing a scanning Laser Doppler Vibrometer (LDV), we visualize the acoustic wavefront generated by a CAP probe and an ultrasound sensor within a designated 50 mm × 50 mm area in front of each probe. Our focus lies in assessing the applicability of a CAP probe for exciting a small polymethyl methacrylate (PMMA) sample. By adjusting the dimensions of the sample to resonate at the excitation frequency of the probe, we can achieve high vibrational velocities, enabling further mechanical analysis. In contrast with traditional vibration excitation techniques such as electrodynamical shakers and hammer impact excitation, a plasma probe can offer distinct advantages without altering the structure's dynamics since it is contactless. Furthermore, in comparison with laser excitation, plasma excitation provides a higher power level. Additionally, while pressurized air systems are applicable for limited low frequencies, plasma probes can perform at higher frequencies. Our findings in this study suggest that CAP is comparable with acoustic excitation, indicating its potential as an effective mechanical excitation method.

On the Angular Control of Rotating Lasers by Means of Line Calculus on Hyperboloids.

We propose a new paradigm for modelling and calibrating laser scanners with rotation symmetry, as is the case for lidars or for galvanometric laser systems with one or two rotating mirrors. Instead of bothering about the intrinsic parameters of a physical model, we use the geometric properties of the device to model it as a specific configuration of lines, which can be recovered by a line-data-driven procedure. Compared to universal data-driven methods that train general line models, our algebraic-geometric approach only requires a few measurements. We elaborate the case of a galvanometric laser scanner with two mirrors, that we model as a grid of hyperboloids represented by a grid of 3×3 lines. This provides a new type of look-up table, containing not more than nine elements, lines rather than points, where we replace the approximating interpolation with exact affine combinations of lines. The proposed method is validated in a realistic virtual setting. As a collateral contribution, we present a robust algorithm for fitting ruled surfaces of revolution on noisy line measurements.

Design and Metrological Analysis of a Backlit Vision System for Surface Roughness Measurements of Turned Parts.

The focus of this study is to design a backlit vision instrument capable of measuring surface roughness and to discuss its metrological performance compared to traditional measurement instruments. The instrument is a non-contact high-magnification imaging system characterized by short inspection time which opens the perspective of in-line implementation. We combined the use of the modulation transfer function to evaluate the imaging conditions of an electrically tunable lens to obtain an optimally focused image. We prepared a set of turned steel samples with different roughness in the range Ra 2.4 µm to 15.1 µm. The layout of the instrument is presented, including a discussion on how optimal imaging conditions were obtained. The paper describes the comparison performed on measurements collected with the vision system designed in this work and state-of-the-art instruments. A comparison of the results of the backlit system depends on the values of surface roughness considered; while at larger values of roughness the offset increases, the results are compatible with the ones of the stylus at lower values of roughness. In fact, the error bands are superimposed by at least 58% based on the cases analyzed.

Seaweed Growth Monitoring with a Low-Cost Vision-Based System.

In this paper, we introduce a method for automated seaweed growth monitoring by combining a low-cost RGB and stereo vision camera. While current vision-based seaweed growth monitoring techniques focus on laboratory measurements or above-ground seaweed, we investigate the feasibility of the underwater imaging of a vertical seaweed farm. We use deep learning-based image segmentation (DeeplabV3+) to determine the size of the seaweed in pixels from recorded RGB images. We convert this pixel size to meters squared by using the distance information from the stereo camera. We demonstrate the performance of our monitoring system using measurements in a seaweed farm in the River Scheldt estuary (in The Netherlands). Notwithstanding the poor visibility of the seaweed in the images, we are able to segment the seaweed with an intersection of the union (IoU) of 0.9, and we reach a repeatability of 6% and a precision of the seaweed size of 18%.

A Continuous Motion Shape-from-Focus Method for Geometry Measurement during 3D Printing.

In 3D printing, as in other manufacturing processes, there is a push for zero-defect manufacturing, mainly to avoid waste. To evaluate the quality of the printed parts during the printing process, an accurate 3D measurement method is required. By scanning the part during the buildup, potential nonconformities to tolerances can be detected early on and the printing process could be adjusted to avoid scrapping the part. Out of many, shape-from-focus, is an accurate method for recovering 3D shapes from objects. However, the state-of-the-art implementation of the method requires the object to be stationary during a measurement. This does not reconcile with the nature of 3D printing, where continuous motion is required for the manufacturing process. This research presents a novel methodology that allows shape-from-focus to be used in a continuous scanning motion, thus making it possible to apply it to the 3D manufacturing process. By controlling the camera trigger and a tunable lens with synchronous signals, a stack of images can be created while the camera or the object is in motion. These images can be re-aligned and then used to create a 3D depth image. The impact on the quality of the 3D measurement was tested by analytically comparing the quality of a scan using the traditional stationary method and of the proposed method to a known reference. The results demonstrate a 1.22% degradation in the measurement error.

Accuracy Assessment of Joint Angles Estimated from 2D and 3D Camera Measurements.

To automatically evaluate the ergonomics of workers, 3D skeletons are needed. Most ergonomic assessment methods, like REBA, are based on the different 3D joint angles. Thanks to the huge amount of training data, 2D skeleton detectors have become very accurate. In this work, we test three methods to calculate 3D skeletons from 2D detections: using the depth from a single RealSense range camera, triangulating the joints using multiple cameras, and combining the triangulation of multiple camera pairs. We tested the methods using recordings of a person doing different assembly tasks. We compared the resulting joint angles to the ground truth of a VICON marker-based tracking system. The resulting RMS angle error for the triangulation methods is between 12° and 16°, showing that they are accurate enough to calculate a useful ergonomic score from.

Identification of Corrosion Minerals Using Shortwave Infrared Hyperspectral Imaging.

In this study, we propose a new method to identify corrosion minerals in carbon steel using hyperspectral imaging (HSI) in the shortwave infrared range (900-1700 nm). Seven samples were artificially corroded using a neutral salt spray test and examined using a hyperspectral camera. A normalized cross-correlation algorithm is used to identify four different corrosion minerals (goethite, magnetite, lepidocrocite and hematite), using reference spectra. A Fourier Transform Infrared spectrometer (FTIR) analysis of the scraped corrosion powders was used as a ground truth to validate the results obtained by the hyperspectral camera. This comparison shows that the HSI technique effectively detects the dominant mineral present in the samples. In addition, HSI can also accurately predict the changes in mineral composition that occur over time.

Cold Atmospheric Plasma Does Not Affect Stellate Cells Phenotype in Pancreatic Cancer Tissue in Ovo.

Pancreatic ductal adenocarcinoma (PDAC) is a challenging neoplastic disease, mainly due to the development of resistance to radio- and chemotherapy. Cold atmospheric plasma (CAP) is an alternative technology that can eliminate cancer cells through oxidative damage, as shown in vitro, in ovo, and in vivo. However, how CAP affects the pancreatic stellate cells (PSCs), key players in the invasion and metastasis of PDAC, is poorly understood. This study aims to determine the effect of an anti-PDAC CAP treatment on PSCs tissue developed in ovo using mono- and co-cultures of RLT-PSC (PSCs) and Mia PaCa-2 cells (PDAC). We measured tissue reduction upon CAP treatment and mRNA expression of PSC activation markers and extracellular matrix (ECM) remodelling factors via qRT-PCR. Protein expression of selected markers was confirmed via immunohistochemistry. CAP inhibited growth in Mia PaCa-2 and co-cultured tissue, but its effectiveness was reduced in the latter, which correlates with reduced ki67 levels. CAP did not alter the mRNA expression of PSC activation and ECM remodelling markers. No changes in MMP2 and MMP9 expression were observed in RLT-PSCs, but small changes were observed in Mia PaCa-2 cells. Our findings support the ability of CAP to eliminate PDAC cells, without altering the PSCs.

A Fast Shape-from-Focus-Based Surface Topography Measurement Method.

Shape from focus is an accurate, but relatively time-consuming, 3D profilometry technique (compared to e.g., laser triangulation or fringe projection). This is the case because a large amount of data that needs to be captured and processed to obtain 3D measurements. In this paper, we propose a two-step shape-from-focus measurement approach that can improve the speed with 40%. By using a faster profilometry technique to create a coarse measurement of an unknown target, this coarse measurement can be used to limit the data capture to only the required frames. This method can significantly improve the measurement and processing speed. The method was tested on a 40 mm by 40 mm custom target and resulted in an overall 46% reduction of measurement time. The accuracy of the proposed method was compared against the conventional shape from focus method by comparing both methods with a more accurate reference.

Extrinsic Camera Calibration with Line-Laser Projection.

Knowledge of precise camera poses is vital for multi-camera setups. Camera intrinsics can be obtained for each camera separately in lab conditions. For fixed multi-camera setups, the extrinsic calibration can only be done in situ. Usually, some markers are used, like checkerboards, requiring some level of overlap between cameras. In this work, we propose a method for cases with little or no overlap. Laser lines are projected on a plane (e.g., floor or wall) using a laser line projector. The pose of the plane and cameras is then optimized using bundle adjustment to match the lines seen by the cameras. To find the extrinsic calibration, only a partial overlap between the laser lines and the field of view of the cameras is needed. Real-world experiments were conducted both with and without overlapping fields of view, resulting in rotation errors below 0.5°. We show that the accuracy is comparable to other state-of-the-art methods while offering a more practical procedure. The method can also be used in large-scale applications and can be fully automated.

Structural intensity assessment on shells via a finite element approximation.

Structural intensity on plates or shells can provide insights on how the vibrational energy is transmitted throughout a sample. Its assessment via experimental deflections are widely documented in the case of plates, which just requires the computation of spatial derivatives of out-of-plane displacements or velocities and a knowledge of the sample's material properties. However, if the structural intensity is to be assessed on arbitrary shells, a more elaborate data processing is required. The in-plane displacements become relevant terms and the spatial derivatives along a predefined local coordinate system need to be computed. Here, a method from which experimental data is interpolated on a finite element mesh is proposed. First, the global displacements and shape of a sample's outer-surface are measured. These data are then projected on a quadratic mesh, where the Kirchhoff plate theory is invoked for the individual elements. The data differentiation is computed via quadratic shape functions, from which the strains and structural intensity are estimated. Through the obtained vibrational energy results on the basis of measured displacement and shape data and by validating the method via a numerical simulation, the proposed work has shown to be a reliable tool to assess energy transmission on irregular shells.

Interactive Camera Network Design Using a Virtual Reality Interface.

The traditional literature on camera network design focuses on constructing automated algorithms. These require problem-specific input from experts in order to produce their output. The nature of the required input is highly unintuitive, leading to an impractical workflow for human operators. In this work we focus on developing a virtual reality user interface allowing human operators to manually design camera networks in an intuitive manner. From real world practical examples we conclude that the camera networks designed using this interface are highly competitive with, or sometimes even superior to, those generated by automated algorithms, but the associated workflow is more intuitive and simple. The competitiveness of the human-generated camera networks is remarkable because the structure of the optimization problem is a well known combinatorial NP-hard problem. These results indicate that human operators can be used in challenging geometrical combinatorial optimization problems, given an intuitive visualization of the problem.

Camera Calibration Using Gray Code.

In order to determine camera parameters, a calibration procedure involving the camera recordings of a checkerboard is usually performed. In this paper, we propose an alternative approach that uses Gray-code patterns displayed on an LCD screen. Gray-code patterns allow us to decode 3D location information of points of the LCD screen at every pixel in the camera image. This is in contrast to checkerboard patterns where the number of corresponding locations is limited to the number of checkerboard corners. We show that, for the case of a UEye CMOS camera, the precision of focal-length estimation is 1.5 times more precise than when using a standard calibration with a checkerboard pattern.

The interaction effect between vibrations and temperature simulating truck transport on the flavor stability of beer.

BACKGROUND: Beer flavor stability is important to brewers as a result of the increased global demand for beer. Increasing export leads to prolonged periods of transportation and storage and causes fresh flavor deterioration. Therefore, the present study examined the effect of different temperatures in combination with vibrations on beer quality. Beer was exposed to vibrations (50 Hz, 15 m s-2 , simulating transport) at 5, 30 and 45 °C for 22, 38 and 90 h and (for half the samples) aged for 60 days at 30 °C. RESULTS: The results obtained indicated decreased oxygen concentrations as a result of an elevated temperature and vibrations. There was no effect (P > 0.05) on color and a limited effect of temperature and vibrations on iso-α-acids. The parameters temperature and vibrations have a significant influence (P < 0.05) on aldehyde concentrations, namely total aldehydes, and especially '2-methylpropanal', '2-methylbutanal' and 'furfural'. CONCLUSION: The impact of vibrations on the aldehydes concentrations was substantial when subjected to an elevated temperature. Furthermore, a forced aging test of shorter duration than traditional methods might be developed. © 2018 Society of Chemical Industry.

Extrinsic Calibration of a Laser Galvanometric Setup and a Range Camera.

Currently, galvanometric scanning systems (like the one used in a scanning laser Doppler vibrometer) rely on a planar calibration procedure between a two-dimensional (2D) camera and the laser galvanometric scanning system to automatically aim a laser beam at a particular point on an object. In the case of nonplanar or moving objects, this calibration is not sufficiently accurate anymore. In this work, a three-dimensional (3D) calibration procedure that uses a 3D range sensor is proposed. The 3D calibration is valid for all types of objects and retains its accuracy when objects are moved between subsequent measurement campaigns. The proposed 3D calibration uses a Non-Perspective-n-Point (NPnP) problem solution. The 3D range sensor is used to calculate the position of the object under test relative to the laser galvanometric system. With this extrinsic calibration, the laser galvanometric scanning system can automatically aim a laser beam to this object. In experiments, the mean accuracy of aiming the laser beam on an object is below 10 mm for 95% of the measurements. This achieved accuracy is mainly determined by the accuracy and resolution of the 3D range sensor. The new calibration method is significantly better than the original 2D calibration method, which in our setup achieves errors below 68 mm for 95% of the measurements.

Detection, Localization and Quantification of Impact Events on a Stiffened Composite Panel with Embedded Fiber Bragg Grating Sensor Networks.

Nowadays, it is possible to manufacture smart composite materials with embedded fiber optic sensors. These sensors can be exploited during the composites' operating life to identify occurring damages such as delaminations. For composite materials adopted in the aviation and wind energy sector, delaminations are most often caused by impacts with external objects. The detection, localization and quantification of such impacts are therefore crucial for the prevention of catastrophic events. In this paper, we demonstrate the feasibility to perform impact identification in smart composite structures with embedded fiber optic sensors. For our analyses, we manufactured a carbon fiber reinforced plate in which we embedded a distributed network of fiber Bragg grating (FBG) sensors. We impacted the plate with a modal hammer and we identified the impacts by processing the FBG data with an improved fast phase correlation (FPC) algorithm in combination with a variable selective least squares (VS-LS) inverse solver approach. A total of 164 impacts distributed on 41 possible impact locations were analyzed. We compared our methodology with the traditional P-Inv based approach. In terms of impact localization, our methodology performed better in 70.7% of the cases. An improvement on the impact time domain reconstruction was achieved in 95 . 1 % of the cases.

RTM Production Monitoring of the A380 Hinge Arm Droop Nose Mechanism: A Multi-Sensor Approach.

This research presents a case study of production monitoring on an aerospace composite component: the hinge arm of the droop nose mechanism on the Airbus A380 wing leading edge. A sensor network composed of Fibre Bragg Gratings, capacitive sensors for cure monitoring and thermocouples was embedded in its fibre reinforced lay-up and measurements were acquired throughout its Resin Transfer Moulding production process. Two main challenges had to be overcome: first, the integration of the sensor lines in the existing Resin Transfer Moulding mould without modifying it; second, the demoulding of the component without damaging the sensor lines. The proposed embedding solution has proved successful. The wavelength shifts of the Fibre Bragg Gratings were observed from the initial production stages, over the resin injection, the complete curing of the resin and the cooling-down prior to demoulding. The sensors proved to be sensitive to detecting the resin flow front, vacuum and pressure increase into the mould and the temperature increase caused by the resin curing. Measurements were also acquired during the post-curing cycle. Residual strains during all steps of the process were derived from the sensors' wavelength shift, showing values up to 0.2% in compression. Moreover, the capacitive sensors were able to follow-up the curing degree during the production process. The sensors proved able to detect the resin flow front, whereas thermocouples could not measure an appreciable increase of temperature due to the fact that the resin had the same temperature as the mould.

Vibration Monitoring Using Fiber Optic Sensors in a Lead-Bismuth Eutectic Cooled Nuclear Fuel Assembly.

Excessive fuel assembly vibrations in nuclear reactor cores should be avoided in order not to compromise the lifetime of the assembly and in order to prevent the occurrence of safety hazards. This issue is particularly relevant to new reactor designs that use liquid metal coolants, such as, for example, a molten lead-bismuth eutectic. The flow of molten heavy metal around and through the fuel assembly may cause the latter to vibrate and hence suffer degradation as a result of, for example, fretting wear or mechanical fatigue. In this paper, we demonstrate the use of optical fiber sensors to measure the fuel assembly vibration in a lead-bismuth eutectic cooled installation which can be used as input to assess vibration-related safety hazards. We show that the vibration characteristics of the fuel pins in the fuel assembly can be experimentally determined with minimal intrusiveness and with high precision owing to the small dimensions and properties of the sensors. In particular, we were able to record local strain level differences of about 0.2 µÏµ allowing us to reliably estimate the vibration amplitudes and modal parameters of the fuel assembly based on optical fiber sensor readings during different stages of the operation of the facility, including the onset of the coolant circulation and steady-state operation.

Underwater Acoustic Wavefront Visualization by Scanning Laser Doppler Vibrometer for the Characterization of Focused Ultrasonic Transducers.

The analysis of acoustic wave fields is important for a large number of engineering designs, communication and health-related reasons. The visualization of wavefronts gives valuable information about the type of transducers and excitation signals more suitable for the test itself. This article is dedicated to the development of a fast procedure for acoustic fields visualization in underwater conditions, by means of laser Doppler vibrometer measurements. The ultrasonic probe is a focused transducer excited by a chirp signal. The scope of this work is to evaluate experimentally the properties of the sound beam in order to get reliable information about the transducer itself to be used in many kinds of engineering tests and transducer design.

Dynamic Strain Measurements on Automotive and Aeronautic Composite Components by Means of Embedded Fiber Bragg Grating Sensors.

The measurement of the internal deformations occurring in real-life composite components is a very challenging task, especially for those components that are rather difficult to access. Optical fiber sensors can overcome such a problem, since they can be embedded in the composite materials and serve as in situ sensors. In this article, embedded optical fiber Bragg grating (FBG) sensors are used to analyze the vibration characteristics of two real-life composite components. The first component is a carbon fiber-reinforced polymer automotive control arm; the second is a glass fiber-reinforced polymer aeronautic hinge arm. The modal parameters of both components were estimated by processing the FBG signals with two interrogation techniques: the maximum detection and fast phase correlation algorithms were employed for the demodulation of the FBG signals; the Peak-Picking and PolyMax techniques were instead used for the parameter estimation. To validate the FBG outcomes, reference measurements were performed by means of a laser Doppler vibrometer. Sensors 2015, 15 27175 The analysis of the results showed that the FBG sensing capabilities were enhanced when the recently-introduced fast phase correlation algorithm was combined with the state-of-the-art PolyMax estimator curve fitting method. In this case, the FBGs provided the most accurate results, i.e. it was possible to fully characterize the vibration behavior of both composite components. When using more traditional interrogation algorithms (maximum detection) and modal parameter estimation techniques (Peak-Picking), some of the modes were not successfully identified.