scholarly journals Novel Features Extraction for Fault Detection Using Thermography Characteristics and IV Measurements of CIGS Thin-Film Module

2020 ◽  
Vol 19 (5) ◽  
pp. 311-325
Author(s):  
Reham A. Eltuhamy ◽  
Mohamed Rady ◽  
Khaled H. Ibrahim ◽  
Haitham A. Mahmoud
Keyword(s):  
Thin Film ◽  
Fault Detection ◽  
Fault Detection And Diagnosis ◽  
Pv Module ◽  
Cigs Thin Film ◽  
Copper Indium ◽  
Pv Modules ◽  
Detection And Diagnosis ◽  
Types Of Faults ◽  
Copper Indium Gallium

Regarding the fault diagnosis of Copper Indium Gallium Selenide (CIGS) PV modules, previously published articles focused on employing statistical analysis of thermography images. This approach failed in many cases to distinguish among fault types. This article presents a novel methodology to diagnose and predict faults of thin-film CIGS PV modules using infrared thermography analysis combined with measurements of I-V characteristics. The proposed methodology encompasses a comprehensive site work to capture images that cover many fault types of the PV module under study. The novelty of the technique depends on utilizing processing and analysis of the captured images using new proposed mathematical parameters to extract different faults’ features. Using I-V measurements combined with thermography analysis, the differences between different types of faults are detected. Then, a general classification matrix of CIGS fault detection and diagnosis, using features based on mathematical parameters and IV measurements has been established. Results show that the analysis of the temperature distribution is proved to be insufficient to identify specific modes of different faults. In addition, the proposed procedure for fault detection and classification, which depends on the pattern of faults, can be used for any type of PV module. This results in more reliance on the proposed technique to increase the confidence level of fault detection.

scholarly journals Fault Detection and Diagnosis Using Combined Autoencoder and Long Short-Term Memory Network

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4612 ◽  
Author(s):  
Pangun Park ◽  
Piergiuseppe Di Marco ◽  
Hyejeon Shin ◽  
Junseong Bang
Keyword(s):  
Time Series ◽  
Fault Detection ◽  
Short Term Memory ◽  
Fault Detection And Diagnosis ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory ◽  
Detection And Diagnosis ◽  
Lstm Network ◽  
Types Of Faults

Fault detection and diagnosis is one of the most critical components of preventing accidents and ensuring the system safety of industrial processes. In this paper, we propose an integrated learning approach for jointly achieving fault detection and fault diagnosis of rare events in multivariate time series data. The proposed approach combines an autoencoder to detect a rare fault event and a long short-term memory (LSTM) network to classify different types of faults. The autoencoder is trained with offline normal data, which is then used as the anomaly detection. The predicted faulty data, captured by autoencoder, are put into the LSTM network to identify the types of faults. It basically combines the strong low-dimensional nonlinear representations of the autoencoder for the rare event detection and the strong time series learning ability of LSTM for the fault diagnosis. The proposed approach is compared with a deep convolutional neural network approach for fault detection and identification on the Tennessee Eastman process. Experimental results show that the combined approach accurately detects deviations from normal behaviour and identifies the types of faults within the useful time.

Bondability of ultrasonic Aluminum bonds on the molybdenum (de)selenide and molybdenum of back contact layer of copper indium gallium (de)selenide CIGS thin film photovoltaic solar panel

Solar Energy ◽  
2021 ◽  
Vol 228 ◽  
pp. 516-522
Author(s):  
Hassan Basher ◽  
Muhammad Nubli Zulkifli ◽  
Mohd Khairil Rahmat ◽  
Muhammad Ghazali Abdul Rahman ◽  
Azman Jalar ◽  
...  
Keyword(s):  
Thin Film ◽  
Contact Layer ◽  
Solar Panel ◽  
Back Contact ◽  
Cigs Thin Film ◽  
Copper Indium ◽  
Indium Gallium ◽  
Copper Indium Gallium

scholarly journals Fault Detection and Diagnosis in Multi-Robot Systems: A Survey

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4019 ◽  
Author(s):  
Eliahu Khalastchi ◽  
Meir Kalech
Keyword(s):  
Fault Detection ◽  
Fault Detection And Diagnosis ◽  
Research Opportunities ◽  
The World ◽  
Different Types ◽  
Robot Systems ◽  
Detection And Diagnosis ◽  
Types Of Faults ◽  
Multi Robot

The use of robots has increased significantly in the recent years; rapidly expending to numerous applications. These sophisticated machines are susceptible to different types of faults that might endanger the robot or its surroundings. These faults must be detected and diagnosed in time to allow continual operation. The field of Fault Detection and Diagnosis (FDD) has been studied for many years. This research has given birth to many approaches that are applicable to different types of physical machines. However, the domain of robotics poses unique requirements that challenge traditional FDD approaches. The study of FDD for robotics is relatively new; only few surveys were presented. These surveys have focused on the single robot scenario. To the best of our knowledge, there is no survey that focuses on FDD for Multi-Robot Systems (MRS). In this paper we set out to fill this gap. This paper provides detailed insights to the world of FDD for MRS. We first describe how different attributes of MRS pose different challenges for FDD. With respect to these challenges, we survey different FDD approaches applicable for MRS. We conclude with a description of research opportunities in this field. With these contributions it is the authors’ intention to provide detailed insights to the world of FDD for MRS.

Comparative Study of the Second Generation a-Si:H, CdTe, and CIGS Thin-Film Solar Cells

2019 ◽  
Vol 1154 ◽  
pp. 102-111 ◽  
Author(s):  
Md. Mahabub Alam Moon ◽  
Md. Ferdous Rahman ◽  
Jaker Hossain ◽  
Abu Bakar Md. Ismail
Keyword(s):  
Thin Film ◽  
Solar Cells ◽  
Second Generation ◽  
Operating Temperature ◽  
Thin Film Solar Cells ◽  
Cigs Thin Film ◽  
Copper Indium ◽  
Indium Gallium ◽  
Hydrogenated Amorphous ◽  
Copper Indium Gallium

In this article, simulation results of novel and facilitated heterostructures of the Second Generation (2G) Thin-film Solar Cells (TFSCs): hydrogenated amorphous Silicon (a-Si:H), Cadmium Telluride (CdTe), and Copper Indium Gallium di-Selenide (Cu(In,Ga)Se2or CIGS) have been presented to compare their performances. The solar cells have been modeled and analyzed for investigating optimized structure with higher stabilized efficiency. Entire simulations have been accomplished using Analysis of Microelectronic and Photonic Structures – 1 Dimensional (AMPS-1D) device simulator. The thickness of the absorber layer was varied from 50 nm to 1400 nm for a-Si:H and from 50 nm to 3 μm for both CdTe and CIGS cells to realize its impact on cell performance. The utmost efficiency, η of 9.134%, 20.776%, and 23.03% were achieved at AM 1.5 (1000 W/m2) for a-Si:H, CdTe, and CIGS material cells, respectively. Lastly, the operating temperature of the three cells was varied from 280°K to 328°K to realize its effect on the cell PV performances.

scholarly journals In-field monitoring of eight photovoltaic plants: degradation rate along seven years of continuous operation

ACTA IMEKO ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 75 ◽  
Author(s):  
Alessio Carullo ◽  
Antonella Castellana ◽  
Alberto Vallan ◽  
Alessandro Ciocia ◽  
Filippo Spertino
Keyword(s):  
Thin Film ◽  
Degradation Rate ◽  
Crystalline Silicon ◽  
Electrical Characterization ◽  
Cigs Thin Film ◽  
Copper Indium ◽  
Degradation Rates ◽  
Pv Modules ◽  
Photovoltaic Plants ◽  
Silicon Based

<p class="Abstract">The results of more than seven years (October 2010-December 2017) of continuous monitoring are presented in this paper. Eight outdoor photovoltaic (PV) plants were monitored. The monitored plants use different technologies: mono-crystalline silicon (m-Si), poli-crystalline silicon (p-Si), string ribbon silicon, copper indium gallium selenide (CIGS), thin film, and cadmium telluride (CdTe) thin film. The thin-film and m-Si modules are used both in fixed installations and on x-y tracking systems. The results are expressed in terms of the degradation rate of the efficiency of each PV plant, which is estimated using the measurements provided by a multi-channel data acquisition system that senses both electrical and environmental quantities. A comparison with the electrical characterization of each plant obtained by means of the transient charge of a capacitive load is also made. In addition, three of the monitored plants are characterized at module level, and the estimated degradation rates are compared to the values obtained with the monitoring system. The main outcome of this work can be summarized as the higher degradation rate of thin-film based PV modules with respect to silicon-based PV modules.</p>

scholarly journals Research on Copper Indium Gallium Selenide (CIGS) Thin-Film Solar Cells

2021 ◽  
Vol 267 ◽  
pp. 02031
Author(s):  
Jixiang Zhou ◽  
Changyu Li
Keyword(s):  
Thin Film ◽  
Solar Cells ◽  
Solar Cell ◽  
Thin Film Solar Cells ◽  
Gallium Selenide ◽  
Copper Indium Gallium Selenide ◽  
Cigs Thin Film ◽  
Copper Indium ◽  
Indium Gallium ◽  
Copper Indium Gallium

As a new-style solar cell, copper indium gallium selenide (CIGS) thin-film solar cell owns excellent characteristics of solar energy absorption, and it is one of the widely used thin-film solar cells. This paper mainly focuses on the research progress of this type of solar cell. Firstly, its theoretical principles are briefly described. Then, its cell materials, configuration and fabrication procedure are introduced. Subsequently, the remarkable research work about CIGS solar cell are reviewed. Finally, its commercial status is illustrated, followed by the critical issues and future perspectives.

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