A Machine-Learning-Based Robust Classification Method for PV Panel Faults.

Renewable energy resources have gained considerable attention in recent years due to their efficiency and economic benefits. Their proportion of total energy use continues to grow over time. Photovoltaic (PV) cell and wind energy generation are the least-expensive new energy sources in most countries. Renewable energy technologies significantly contribute to climate mitigation and provide economic benefits. Apart from these advantages, renewable energy sources, particularly solar energy, have drawbacks, for instance restricted energy supply, reliance on weather conditions, and being affected by several kinds of faults, which cause a high power loss. Usually, the local PV plants are small in size, and it is easy to trace any fault and defect; however, there are many PV cells in the grid-connected PV system where it is difficult to find a fault. Keeping in view the aforedescribed facts, this paper presents an intelligent model to detect faults in the PV panels. The proposed model utilizes the Convolutional Neural Network (CNN), which is trained on historic data. The dataset was preprocessed before being fed to the CNN. The dataset contained different parameters, such as current, voltage, temperature, and irradiance, for five different classes. The simulation results showed that the proposed CNN model achieved a training accuracy of 97.64% and a testing accuracy of 95.20%, which are much better than the previous research performed on this dataset.

Modified Smoothing Algorithm for Tracking Multiple Maneuvering Targets in Clutter.

This research work extends the fixed interval smoothing based on the joint integrated track splitting (FIsJITS) filter in the multi-maneuvering-targets (MMT) tracking environment. We contribute to tackling unknown dynamics of the multi-maneuvering-targets (MMT) using the standard kinematic model. This work is referred to as smoothing MMT using the JITS (MMT-sJITS). The existing FIsJITS algorithm is computationally more complex to solve for the MMT situation because it enumerates a substantial number of measurement-to-track assignments and calculates their posteriori probabilities globally. The MMT-sJITS updates a current target track by assuming the joint (common) measurements detected by neighbor tracks are modified clutters (or pretended spurious measurements). Thus, target measurement concealed by a joint measurement is optimally estimated based on measurement density of the modified clutter. This reduces computational complexity and provides improved tracking performance. The MMT-sJITS generates forward tracks and backward tracks using the measurements collected by a sensor such as a radar. The forward and backward multi-tracks state predictions are fused to obtain priori smoothing multi-track state prediction, as well as their component existence probabilities. This calculates the smoothing estimate required to compute the forward JITS state estimate, which reinforces the MMT tracking efficiently. Monte Carlo simulation is used to verify best false-track discrimination (FTD) analysis in comparison with existing multi-targets tracking algorithms.

Thickness dependences of acoustic bandgaps with different generation mechanisms in phononic crystals immersed in water.

The thickness dependences of acoustic bandgaps were theoretically and experimentally investigated in two-dimensional phononic crystals (PCs) immersed in water. The acoustic pressure transmission coefficients were measured as a function of the PC thickness in order to understand the characteristics of the transmission loss through the PCs. The acoustic bandgaps can be classified into two types of generation mechanisms from the perspective of acoustic diffraction modes: Bragg bandgap and non-zeroth order diffraction (NZOD) bandgap. The NZOD bandgaps show larger transmission losses and shorter decay lengths with increasing PC thickness than the Bragg bandgaps.

Zeroth-order resonance phenomenon in an acoustic composite right/left-handed metamaterial resonator.

This study proposes an acoustic theory that describes the resonance phenomena in a resonator made of acoustic composite right/left-handed (CRLH) metamaterials, and verifies it through numerical simulation. The established theory for a microwave CRLH metamaterial resonator is adapted to explain the resonance phenomena in an acoustic CRLH metamaterial resonator. In particular, attention is focused on the zeroth-order resonance phenomenon which has several interesting properties. When a resonator is composed of a CRLH metamaterial, a resonance with a flat acoustic field distribution may occur at one of the frequencies where the wavenumber becomes zero. This resonance is called zeroth-order resonance. Through numerical simulation, such unusual resonance phenomenon in acoustics is observed in more detail and the proposed theory is verified. The results of the theory and the numerical simulation clearly show that zeroth-order resonance can exist at those frequencies where the acoustic field distribution is flat due to infinite wavelength. It is also shown that the resonance frequency and the Q factor of this resonance depend on the boundary condition at both ends of the resonator, and they basically do not change even when the number of units is reduced or increased.

Direct exfoliation and dispersion of two-dimensional materials in pure water via temperature control.

The high-volume synthesis of two-dimensional (2D) materials in the form of platelets is desirable for various applications. While water is considered an ideal dispersion medium, due to its abundance and low cost, the hydrophobicity of platelet surfaces has prohibited its widespread use. Here we exfoliate 2D materials directly in pure water without using any chemicals or surfactants. In order to exfoliate and disperse the materials in water, we elevate the temperature of the sonication bath, and introduce energy via the dissipation of sonic waves. Storage stability greater than one month is achieved through the maintenance of high temperatures, and through atomic and molecular level simulations, we further discover that good solubility in water is maintained due to the presence of platelet surface charges as a result of edge functionalization or intrinsic polarity. Finally, we demonstrate inkjet printing on hard and flexible substrates as a potential application of water-dispersed 2D materials.