Fractional transformation-based decentralized robust control of a coupled-tank system for industrial applications

Petrochemical and dairy industries, waste management, and paper manufacturing fall under the category of process industries where flow and liquid control are essential. Even when liquids are mixed or chemically treated in interconnected tanks, the fluid and flow should constantly be observed and controlled, especially when dealing with nonlinearity and imperfect plant models. In this study, we propose a nonlinear dynamic multiple-input multiple-output (MIMO) plant model. This model is then transformed through linearization, a technique frequently utilized in the analysis and modeling of fractional processes, and decoupling for decentralized fixed-structure H-infinity robust control design. Simulation tests based on MATLAB and SIMULINK are subsequently executed. Numerous assessments are conducted to evaluate tracking performance, external disturbance re jection, and plant parameter fluctuations to gauge the effectiveness of the proposed model. The objective of this work is to provide a framework that anticipates potential outcomes, paving the way for implementing a reliable controller synthesis for MIMO-connected tanks in real-world scenarios.This research was partially funded by FONDECYT grant number 1200525 (V.L.) from the National Agency for Research and Development (ANID) of the Chilean government under the Ministry of Science, Technology, Knowledge, and Innovation; and by Portuguese funds through the CMAT—Research Centre of Mathematics of University of Minho—within projects UIDB/00013/2020 and UIDP/00013/2020 (C.C.)

Experimental study on impact of high voltage power transmission lines on silicon photovoltaics using artificial neural network

The recent trend of renewable energy has positioned solar cells as an excellent choice for energy production in today’s world. However, the performance of silicon photovoltaic (PV) panels can be influenced by various environmental factors such as humidity, light, rusting, temperature fluctuations and rain, etc. This study aims to investigate the potential impact of high voltage power transmission lines (HVTL) on the performance of solar cells at different distances from two high voltage levels (220 and 500 KV). In fact, HVTLs generate electromagnetic (EM) waves which may affect the power production and photocurrent density of solar cells. To analyze this impact, a real-time experimental setup of PV panel is developed (using both monocrystalline and polycrystalline solar cells), located in the vicinity of 220 and 500 KV HVTLs. In order to conduct this study systematically, the impact of HVTL on solar panel is being measured by varying the distance between the HVTL and the solar panels. However, it is important to understand that the obtained experimental values alone are insufficient for comprehensive verification under various conditions. To address this limitation, an Artificial Neural Network (ANN) is employed to generate HVTL impact curves for PV panels (particularly of voltage and current values) which are impractical to obtain experimentally. The inclusion of ANN approach enhances the understanding of the HVTL impact on solar cell performance across a wide range of conditions. Overall, this work presents the impact study of HVTL on two different types of solar cells at different distances from HVTL for two HV levels (i.e., 220 and 500 KV) and the comparison study of HVTL impact on both monocrystalline and polycrystalline solar cells

An Efficient Fault Detection Method for Induction Motors Using Thermal Imaging and Machine Vision

Induction motors (IMs) are the backbone of industry, and play a vital role in daily life as well. However, induction motors face various faults during their operation, which may cause overheating, energy losses, and failure in the motors. Keeping in mind the severity of the issues associated with fault occurrence, this paper proposes a novel method of fault detection in induction motors by using “Machine Vision (MV)” along with “Infrared Thermography (IRT)”. It is worth mentioning that the timely prevention of faults in the IM ensures the motor’s safety from failures, and provides longer service life. In this work, a dataset of thermal images of an induction motor under different conditions (i.e., normal operation, overloaded, and fault) was developed using an infrared camera without disturbing the working condition of the motor. Then, the extracted thermal images were effectively used for the feature extraction and training by local octa pattern (LOP) and support-vector machine (SVM) classifiers, respectively. In order to enhance the quality of feature extraction from images, the LOP was implemented along with a genetic algorithm (GA). Finally, the proposed methodology was implemented and validated by detecting the faults introduced in an induction motor in real time. In addition to that, a comparative study of the suggested methodology with existing methods also verified the supremacy and effectiveness of the proposed method in comparison to the previous techniques

An Efficient Fault Detection Method for Induction Motors Using Thermal Imaging and Machine Vision

Induction motors (IMs) are the backbone of industry, and play a vital role in daily life as well. However, induction motors face various faults during their operation, which may cause overheating, energy losses, and failure in the motors. Keeping in mind the severity of the issues associated with fault occurrence, this paper proposes a novel method of fault detection in induction motors by using “Machine Vision (MV)” along with “Infrared Thermography (IRT)”. It is worth mentioning that the timely prevention of faults in the IM ensures the motor’s safety from failures, and provides longer service life. In this work, a dataset of thermal images of an induction motor under different conditions (i.e., normal operation, overloaded, and fault) was developed using an infrared camera without disturbing the working condition of the motor. Then, the extracted thermal images were effectively used for the feature extraction and training by local octa pattern (LOP) and support-vector machine (SVM) classifiers, respectively. In order to enhance the quality of feature extraction from images, the LOP was implemented along with a genetic algorithm (GA). Finally, the proposed methodology was implemented and validated by detecting the faults introduced in an induction motor in real time. In addition to that, a comparative study of the suggested methodology with existing methods also verified the supremacy and effectiveness of the proposed method in comparison to the previous techniques

Fabrication of CuFe₂O₄/α‑Fe₂O₃ Composite Thin Films on FTO Coated Glass and 3‑D Nanospike Structures for Efficient Photoelectrochemical Water Splitting

Recently, photoelectrochemical conversion (PEC) of water into fuel is attracting great attention of researchers due to its outstanding benefits. Herein, a systematic study on PEC of water using CuFe₂O₄/ α–Fe₂O₃ composite thin films is presented. CuFe₂O₄/ α–Fe₂O₃ composite thin films were deposited on two different substrates; (1) planner FTO glass and (2) 3-dimensional nanospike (NSP). The films on both substrates were characterized and tested as anode material for photoelectrochemical water splitting reaction. During PEC studies, it was observed that the ratio between two components of composite is crucial and highest PEC activity results were achieved by 1:1 component ratio (CF-1) of CuFe₂O₄ and α–Fe₂O₃. The CF-1 ratio sample deposited on planar FTO substrate provided a photocurrent density of 1.22 mA/cm² at 1.23 <i>V</i>_RHE which is 1.9 times higher than bare α–Fe₂O₃ sample. A significant PEC activity outperformance was observed when CF-1 ratio composite thin films were deposited on 3D NSP. The highest photocurrent density of 2.26 mA/cm² at 1.23 <i>V</i>_RHE was achieved for 3D NSP sample which is around 3.6 times higher than photocurrent density generated by α–Fe₂O₃ thin film only. The higher photocurrent densities of 3D nanostructured devices compared to planar one are attributed to the enhanced light trapping and increased surface area for photoelectrochemical water oxidation on the surface. The difference between valence and conduction bands of CuFe₂O₄ and α–Fe₂O₃ allows better separation of photogenerated electrons and holes at the CuFe₂O₄/ α–Fe₂O₃ interface which makes it more active for photoelectrochemical water splitting

Spray Pyrolysis Deposition of ZnFe₂O₄/Fe₂O₃ Composite Thin Films on Hierarchical 3‑D Nanospikes for Efficient Photoelectrochemical Oxidation of Water

In this work, we study the role of nanotextured ZnFe₂O₄/Fe₂O₃composite thin films fabricated by ultrasonic spray pyrolysis (USP) on the photoelectrochemical water oxidation reactions. The ZnFe₂O₄/Fe₂O₃ composites with different molar ratios are deposited on three-dimensional nanospikes (NSP) substrate, and the results are compared with those for planar devices. It is observed that optical absorption and charge separation due to larger surface area is significantly enhanced in nanotextured photoactive ZnFe₂O₄/Fe₂O₃ films. After characterization of ZnFe₂O₄/Fe₂O₃ composite films with different molar ratios (ZF1, ZF2, and ZF3), we find that the nanotextured ZF1 composite with a molar ratio of 1:1 has the highest activity with photocurrent density of 2.19 mA/cm² in photoelectrochemical oxidation of water. This photocurrent density is 3.4 and 2.73 times higher than the photocurrent density values of pure hematite on planar fluorine-doped tin oxide (FTO) coated glass and the highest reported value of ZnFe₂O₄/Fe₂O₃ composite, respectively. In addition, the results of electrochemical impedance spectroscopy (EIS) and photoluminescence (PL) tests indicate lower charge transfer resistance and faster charge extraction for the nanotextured ZnFe₂O₄/Fe₂O₃ composite (ZF1). Overall, our new fabrication process for the ZnFe₂O₄/Fe₂O₃ composite together with the effect of nanostructured substrate shows a better charge separation and enhanced optical absorption, resulting in a highly efficient photoelectrochemical water-splitting device

Nanotextured Spikes of α‑Fe₂O₃/NiFe₂O₄ Composite for Efficient Photoelectrochemical Oxidation of Water

We demonstrate for the first time the application of p-NiFe₂O₄/n-Fe₂O₃ composite thin films as anode materials for light-assisted electrolysis of water. The p-NiFe₂O₄/n-Fe₂O₃ composite thin films were deposited on planar fluorinated tin oxide (FTO)-coated glass as well as on 3D array of nanospike (NSP) substrates. The effect of substrate (planar FTO and 3D-NSP) and percentage change of each component (i.e., NiFe₂O₄ and Fe₂O₃) of composite was studied on photoelectrochemical (PEC) water oxidation reaction. This work also includes the performance comparison of p-NiFe₂O₄/n-Fe₂O₃ composite (planar and NSP) devices with pure hematite for PEC water oxidation. Overall, the nanostructured p-NiFe₂O₄/n-Fe₂O₃ device with equal molar 1:1 ratio of NiFe₂O₄ and Fe₂O₃ was found to be highly efficient for PEC water oxidation as compared with pure hematite, 1:2 and 1:3 molar ratios of composite. The photocurrent density of 1:1 composite thin film on planar substrate was equal to 1.07 mA/cm² at 1.23 V_RHE, which was 1.7 times higher current density as compared with pure hematite device (0.63 mA/cm² at 1.23 V_RHE). The performance of p-NiFe₂O₄/n-Fe₂O₃ composites in PEC water oxidation was further enhanced by their deposition over 3D-NSP substrate. The highest photocurrent density of 2.1 mA/cm² at 1.23 V_RHE was obtained for the 1:1 molar ratio p-NiFe₂O₄/n-Fe₂O₃ composite on NSP (NF1-NSP), which was 3.3 times more photocurrent density than pure hematite. The measured applied bias photon-to-current efficiency (ABPE) value of NF1-NSP (0.206%) was found to be 1.87 times higher than that of NF1-P (0.11%) and 4.7 times higher than that of pure hematite deposited on FTO-coated glass (0.044%). The higher PEC water oxidation activity of p-NiFe₂O₄/n-Fe₂O₃ composite thin film as compared with pure hematite is attributed to the Z-path scheme and better separation of electrons and holes. The increased surface area and greater light absorption capabilities of 3D-NSP devices result in further improvement in catalytic activities

All Inorganic Cesium Lead Iodide Perovskite Nanowires with Stabilized Cubic Phase at Room Temperature and Nanowire Array-Based Photodetectors

Alluring optical and electronic properties have made organometallic halide perovskites attractive candidates for optoelectronics. Among all perovskite materials, inorganic CsPbX₃ (X is halide) in black cubic phase has triggered enormous attention recently owing to its comparable photovoltaic performance and high stability as compared to organic and hybrid perovskites. However, cubic phase stabilization at room temperature for CsPbI₃ still survives as a challenge. Herein we report all inorganic three-dimensional vertical CsPbI₃ perovskite nanowires (NWs) synthesized inside anodic alumina membrane (AAM) by chemical vapor deposition (CVD) method. It was discovered that the as-grown NWs have stable cubic phase at room temperature. This significant improvement on phase stability can be attributed to the effective encapsulation of NWs by AAM and large specific area of these NWs. To demonstrate device application of these NWs, photodetectors based on these high density CsPbI₃ NWs were fabricated demonstrating decent performance. Our discovery suggests a novel and practical approach to stabilize the cubic phase of CsPbI₃ material, which will have broad applications for optoelectronics in the visible wavelength range

Lead-Free Perovskite Nanowire Array Photodetectors with Drastically Improved Stability in Nanoengineering Templates

Organometal halide perovskite materials have triggered enormous attention for a wide range of high-performance optoelectronic devices. However, their stability and toxicity are major bottleneck challenges for practical applications. Substituting toxic heavy metal, that is, lead (Pb), with other environmentally benign elements, for example, tin (Sn), could be a potential solution to address the toxicity issue. Nevertheless, even worse stability of Sn-based perovskite material than Pb-based perovskite poses a great challenge for further device fabrication. In this work, for the first time, three-dimensional CH₃NH₃SnI₃ perovskite nanowire arrays were fabricated in nanoengineering templates, which can address nanowire integration and stability issues at the same time. Also, nanowire photodetectors have been fabricated and characterized. Intriguingly, it was discovered that as the nanowires are embedded in mechanically and chemically robust templates, the material decay process has been dramatically slowed down by up to 840 times, as compared with a planar thin film. This significant improvement on stability can be attributed to the effective blockage of diffusion of water and oxygen molecules within the templates. These results clearly demonstrate a new and alternative strategy to address the stability issue of perovskite materials, which is the major roadblock for high-performance optoelectronics