Reduction in the Sensor Effect on Acoustic Emission Data to Create a Generalizable Library by Data Merging.

The aim of this paper is to discuss the effect of the sensor on the acoustic emission (AE) signature and to develop a methodology to reduce the sensor effect. Pencil leads are broken on PMMA plates at different source-sensor distances, and the resulting waves are detected with different sensors. Several transducers, commonly used for acoustic emission measurements, are compared with regard to their ability to reproduce the characteristic shapes of plate waves. Their consequences for AE descriptors are discussed. Their different responses show why similar test specimens and test conditions can yield disparate results. This sensor effect will furthermore make the classification of different AE sources more difficult. In this context, a specific procedure is proposed to reduce the sensor effect and to propose an efficient selection of descriptors for data merging. Principal Component Analysis has demonstrated that using the Z-score normalized descriptor data in conjunction with the Krustal-Wallis test and identifying the outliers can help reduce the sensor effect. This procedure leads to the selection of a common descriptor set with the same distribution for all sensors. These descriptors can be merged to create a library. This result opens up new outlooks for the generalization of acoustic emission signature libraries. This aspect is a key point for the development of a database for machine learning.

An Impact Localization Solution Using Embedded Intelligence-Methodology and Experimental Verification via a Resource-Constrained IoT Device.

Recent advances both in hardware and software have facilitated the embedded intelligence (EI) research field, and enabled machine learning and decision-making integration in resource-scarce IoT devices and systems, realizing "conscious" and self-explanatory objects (smart objects). In the context of the broad use of WSNs in advanced IoT applications, this is the first work to provide an extreme-edge system, to address structural health monitoring (SHM) on polymethyl methacrylate (PPMA) thin-plate. To the best of our knowledge, state-of-the-art solutions primarily utilize impact positioning methods based on the time of arrival of the stress wave, while in the last decade machine learning data analysis has been performed, by more expensive and resource-abundant equipment than general/development purpose IoT devices, both for the collection and the inference stages of the monitoring system. In contrast to the existing systems, we propose a methodology and a system, implemented by a low-cost device, with the benefit of performing an online and on-device impact localization service from an agnostic perspective, regarding the material and the sensors' location (as none of those attributes are used). Thus, a design of experiments and the corresponding methodology to build an experimental time-series dataset for impact detection and localization is proposed, using ceramic piezoelectric transducers (PZTs). The system is excited with a steel ball, varying the height from which it is released. Based on TinyML technology for embedding intelligence in low-power devices, we implement and validate random forest and shallow neural network models to localize in real-time (less than 400 ms latency) any occurring impacts on the structure, achieving higher than 90% accuracy.

New in vitro SPF Evaluation Method for Hydrophilic Sunscreen Samples.

A new method was developed for the in vitro sun protection factor (SPF) evaluation of sunscreen samples. A new type of substrate, a hydroxyalkyl cellulose-coated plate, was also prepared specifically for hydrophilic samples. This new substrate was required because hydrophilic samples would be unlikely to wet the surface of the standard cosmetic PMMA UV evaluation plate. A super-hydrophilic quartz plate was prepared by corona-discharge treatment before an aqueous solution of hydroxyalkyl cellulose was spread on it. A flat and uniform hydroxyalkyl cellulose film was subsequently formed through the evaporation of water. Special care was taken to inhibit the generation of spatial non-uniformity. Six hydrophilic sunscreen samples with in vivo SPF values of 56, 55, 52, 25, 15, and 4, were then applied to the prepared hydroxyalkyl cellulose-coated plate, as well as a super-hydrophilic quartz plate and a flat hydrophobic PMMA plate. The thicknesses of the applied layers were determined using a wheel-shaped wet film thickness gauge immediately after the application, and UV transmission was measured using an SPF analyzer. The value of in vitro SPF was calculated from the UV absorbance and the thickness of the layer. For two out of the six samples, PMMA plate could not be available, as the samples were unable to wet the PMMA surface. Relatively small differences were observed between the in vitro SPF values when the super-hydrophilic and hydroxyalkyl cellulose-coated plates were used. Samples exhibiting higher in vivo SPF were also associated with higher in vitro SPF values, although a linear relationship was not observed. In contrast to the super-hydrophilic plate whose half-life of the super-hydrophilicity is only approximately five days, the hydrophilicity of the hydroxyalkyl cellulose-coated plate scarcely varied during six months of storage. Finally, a simplified evaluation method was also proposed. The validity of the method was verified through a ring test where three researchers employed this method in different laboratories at three independent organizations.

Preparation of dumbbell manganese dioxide/gelatin composites and their application in the removal of lead and cadmium ions.

The nano-sized sorbents restrict their practical application in flow-through system due to excessive pressure. In this study, dumbbell MnO2/gelatin composites were synthesized based on the protein-assisted synthesis technology. Then they were immobilized on the amino-modified polymethyl methacrylate (PMMA) plate. SEM, TEM, XRD, XPS and FT-IR were employed to study the surface properties and the adsorption mechanism of MnO2/gelatin composites. Adsorption experiments for Pb(II) and Cd(II) ions were performed to study the adsorption isotherms, kinetics, and thermodynamics as well as the influencing factors. The maximum adsorption capacities of Pb(II) and Cd(II) ions were 318.7 mg g-1 and 105.1 mg g-1 respectively. The adsorption process met the pseudo-second-order kinetic model. Subsequently, MnO2/gelatin composites modified plates were used to remove the heavy metal ions in surface water and wastewater samples. The removal efficiencies of Pb(II) ion was changed from 83% (wastewater) to 100% (surface water), when the initial concentration was 10 mg L-1. This device exhibited great application prospect in the removal of heavy metals taking advantage of its high removal efficiency, excellent stability and reusability and ease of operation.