December 2019 - Journal of Electronics and Informatics
Latest Publications


TOTAL DOCUMENTS

54
(FIVE YEARS 54)

H-INDEX

3
(FIVE YEARS 3)

Published By Inventive Research Organization

2582-3825
Updated Monday, 12 July 2021

2021 ◽  
Vol 3 (2) ◽  
pp. 138-149
Author(s):  
B Vivekanandam

One of the most crucial roles of the cognitive radio (CR) is detection of spectrum ‘holes’. The ‘no a-priori knowledge required’ prospective of blind detection techniques has attracted the attention of researchers and industries, using simple Eigen values. Over the years, a number of study and research has been carried out to determine the impact of thermal noise in the performance of the detector. However, there has not been much work on the impact of man-made noise, which also hinders the performance of the detector. As a result, both man-made impulse noise and thermal Gaussian noise are examined in this proposed study to determine the performance of blind Eigen value-based spectrum sensing. Many studies have been conducted over long sample length by oversampling or increasing the duration of sensing. As a result, a research progress has been made on shorter sample lengths by using a novel algorithm. The proposed system utilizes three algorithms; they are contra-harmonic-mean minimum Eigen value, contra-harmonic mean Maximum Eigen value and maximum Eigenvalue harmonic mean. For smaller sample lengths, there is a substantial rise in the number of cooperative secondary users, as well as a low signal-to-noise ratio when employing the maximum Eigen value Harmonic mean. The experimental analysis of the proposed work with respect to impulse noise and Gaussian signal using Nakagami-m fading channel is observed and the results identified are tabulated.


2021 ◽  
Vol 3 (2) ◽  
pp. 114-125
Author(s):  
Subarna Shakya

By contributing to the system enhancement, the integration of Nano systems for nanosensors with biomaterials proves to be a unique element in the development of novel innovative systems. The techniques by which manipulation, handling, and preparation of the device are accomplished with respect to industrial use are a critical component that must be considered before the system is developed. The approach must be able to be used in a scanning electron microscope (SEM), resistant to environmental changes, and designed to be automated. Based on this deduction, the main objective of this research work is to develop a novel design of Nano electronic parts, which address the issue of packaging at a nanoscale. The proposed research work has used wood fibres and DNA as the bio material to develop nanoscale packaging. The use of a certain atomic force microscope (ATM) for handling DNA in dry circumstances is demonstrated with SCM wood fibrils/fibers manipulation in a scanning electron microscope (SEM).Keywords: Nano electronics, bioelectronics, scanning electron microscope (SEM), packaging, atomic force microscope (ATM)


2021 ◽  
Vol 3 (2) ◽  
pp. 99-113
Author(s):  
Karuppusamy P.

In several industrial applications, rotating machinery is widely utilized in various forms. A growing amount of study, in the academic and industrial fields, as a potential sector for the confidentiality of modern industrial labor systems, has been drawing early fault diagnosis (EFD) techniques. However, EFD plays an essential role in providing sufficient information for performing maintenance activities, preventing and reducing financial loss and disastrous defaults. Many of the existing techniques for identifying rotations were ineffective. For the identification of spinning machine faults, many in-depth learning methods have recently been developed. This research report has included and analysed a number of research publications that have higher precision than standard algorithms for detecting early failures in rotating machinery. In addition to the artificial intelligence monitoring (AIM) model, detecting the defects in rotating machine was also realized through the simulation output. AIM framework model is also testing the rotating machinery in three different stages, which is based on the vibration signal obtained from the bearing system and further it has been trained with the neural network preceding. Compared to other traditional algorithms, the AIM model has achieved greater precision and also the other performance measures are tabulated in the result and discussion section.


Author(s):  
Karuppusamy P.

In several industrial applications, rotating machinery is widely utilized in various forms. A growing amount of study, in the academic and industrial fields, as a potential sector for the confidentiality of modern industrial labor systems, has been drawing early fault diagnosis (EFD) techniques. However, EFD plays an essential role in providing sufficient information for performing maintenance activities, preventing and reducing financial loss and disastrous defaults. Many of the existing techniques for identifying rotations were ineffective. For the identification of spinning machine faults, many in-depth learning methods have recently been developed. This research report has included and analysed a number of research publications that have higher precision than standard algorithms for detecting early failures in rotating machinery. In addition to the artificial intelligence monitoring (AIM) model, detecting the defects in rotating machine was also realized through the simulation output. AIM framework model is also testing the rotating machinery in three different stages, which is based on the vibration signal obtained from the bearing system and further it has been trained with the neural network preceding. Compared to other traditional algorithms, the AIM model has achieved greater precision and also the other performance measures are tabulated in the result and discussion section.


2021 ◽  
Vol 3 (2) ◽  
pp. 126-137
Author(s):  
Karthigaikumar P.

Based on an assessment of production capabilities, manufacturing sectors' core competency is increased. The importance of product quality in this aspect cannot be overstated. Several academics have introduced Deming's 14 principles, Shewhart cycle, total quality management, and other approaches to decrease the external failure costs and enhance product yield rates. Analysis of industrial data and process monitoring is becoming increasingly important as a part of the Industry 4.0 paradigm. In order to reduce the internal failure cost and inspection overhead, quality control (QC) schemes are utilized by industries. The final product quality has an interactive and cumulative effect of various parameters like operators and equipment in multistage manufacturing processes (MMP). In other cases, the final product is inspected in a single workstation with QC. It's challenging to do a cause analysis in MMP whenever a failure occurs. Several industries are looking for the optimal quality prediction model in order to achieve flawless production. The majority of current approaches solely handles single-stage manufacturing and is inadequate in dealing with MMP quality concerns. To overcome this issue, this paper proposes an industrial quality prediction system with a combination of multiple Program Component Analysis (PCA) and Decision Stump (DS) algorithm for MMP quality prediction. A SECOM (SEmiCOnductor Manufacturing) dataset is used for verification and validation of the proposed model. Based on the findings, it is clear that this model is capable of performing accurate classification and prediction in the field of industrial quality.


2021 ◽  
Vol 3 (2) ◽  
pp. 89-98
Author(s):  
Abul Bashar ◽  
Smys S

The hybrid system configuration is used for meeting the thermal and electrical load demands of an off-grid network simultaneously with the model proposed in this paper. Li-ion battery, Micro Gas Turbine (MGT), wind turbine and solar photovoltaic configurations are analyzed. Hybrid Optimization of Multiple Electric Renewables (HOMER) software is used for estimating utilization of various strategies for power management, recovered waste heat and excess energy in the model. The heating demand is met and examined by the thermal load controller with and without the options of waste heat recovery. The hybrid system hardware components are sized, compared and analyzed based on cyclic charging (CC) and load following (LF) dispatch strategies. Various electrical to thermal load ratio are considered for examining the system performance. Various uncertainties and their effects are reported on comparison of grid-connected and stand-alone options. The hardware components are reduced in size thereby appreciable cost benefits are observed in the results. In the optimized hybrid system, the renewable energy fraction is increased causing high renewable penetrations and the CO2 emission is reduced by a large value. For all the configurations analyzed, several environmental and cost benefits are offered by the CC strategy.


2021 ◽  
Vol 3 (2) ◽  
pp. 77-88
Author(s):  
Malti Bansal ◽  
Harmandeep Singh ◽  
Gaurav Sharma

This research paper reviews and briefly discusses about the multiplexers and demultiplexers. This research paper aims to explore the history of multiplexers, types of multiplexers, applications and the real-time use cases of multiplexers. Furthermore, it also includes a brief introduction on the different multiplexing techniques employed in analog and digital electronics, ongoing research studies and future research scope for multiplexers.


2021 ◽  
Vol 3 (1) ◽  
pp. 61-76
Author(s):  
Thomas Amanuel ◽  
Amanuel Ghirmay ◽  
Huruy Ghebremeskel ◽  
Robel Ghebrehiwet ◽  
Weldekidan Bahlibi

Signal processing is considered as an efficient technique to detect the faults in three-phase induction motors. Detection of different varieties of faults in the rotor of the motor are widely studied at the industrial level. To extend further, this research article presents the analysis on various signal processing techniques for fault detection in three-phase induction motor due to the damages in rotor bar. Usually, Fast Fourier Transform (FFT) and STFT are used to analyze the healthy and faulty motor conditions based on the signal characteristics. The proposed study covers the advantages and limitations of the proposed wavelet transform (WT) and each technique for detecting the broken bar of induction motors. The good frequency information can be collected from FFT techniques for handling multiple faults identification in three-phase induction motor. Despite the hype, the detection accuracy gets reduced during the dynamic condition of the machine because the frequency information on sudden time changes cannot be employed by FFT. The WT method signal analysis is compared with FFT to propose fault detection method for induction motor. The WT method is proving better accuracy when compared to all existing methods for signal information analysis. The proposed research work has simulated the proposed method with MATLAB / SIMULINK and it helps to effectively detect the healthy and faulty conditions of the motor.


2021 ◽  
Vol 3 (1) ◽  
pp. 49-60
Author(s):  
Hadish Habte Tesfamikael ◽  
Adam Fray ◽  
Israel Mengsteab ◽  
Adonay Semere ◽  
Zebib Amanuel

Low-level and medium-level leg injury patients can be operated wheelchair independently in the clinical region. The construction of an electric wheelchair is one of the solutions to operate electric wheelchair by the patients themselves. The motor is an essential part of an electrical wheelchair for driving from one place to another place. The response of the system is very important for the optimization of the system. The existing methods fail in gradual sensitivity during motion and lack of response time to the user. This article is consist of a design for optimizing the existing DC motor transfer function for the smart wheelchair. The perfect angular tuning of the derivative controller provides a better executing time for our proposed model. The smoother responses from the smart wheelchair are obtaining by the dynamic response of closed-loop control. The design of DC motors is to drive smart wheelchair as per the needs. Besides, the construction of a mathematical model for proposing a system involves the DC motor drive to the smart wheelchair arrangement. The proposed model gives independent mobility of smart wheelchair with less response time and better sensitivity. Here, the mathematical model provides the details of immediate response to the user and less execution time of the complex system process. Finally, the authors discussed future improvements to the current DC motor design in the proposed system.


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