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i-manager's Journal on Circuits and Systems (JCIR)

Current Issue Vol. 12 Issue 1

Dynamic Simulation and Sensitivity Analysis of Steam Generation Solar Power Plant
Unified Power Quality Conditioner (UPQC) Research Study on Steady - State Power Flow
Photovoltaic Module Failure Detection using Machine Vision and Lazy Learning Technique
Design and Implementation of Wallace Tree Multiplier and Its Applications in FIR Filter
Review on Obstacle Detection in Solar Panel Cleaning Applications

Most Cited

Volume 6 Issue 4 September - November 2018

Research Paper

Trioengineering: The Procedures that Use Trioinformatics Neuroengineering Neuromathematics Notation to Express, Build, Define, and Inform the Application of the Trichotomous–Based Inquiry in Digital Research Design

James Edward Osler II*

Professor, School of Education, North Carolina Central University, USA.

Osler, J. E., II. (2018). Trioengineering: The Procedures that Use Trio informatics Neuro engineering Neuromathematics Notation to Express, Build, Define, and Inform the Application of the Trichotomous–Based Inquiry in Digital Research Design, i-manager's Journal on Circuits and Systems, 6(4), 1-15. https://doi.org/10.26634/jcir.6.4.15093

Abstract

This discourse provides a deeper epistemological rational for the novel discipline of “Trioinformatics” through the use of “Trioengineering”. Trioengineering uses of the novel mathematical “Ambitation” or “Neuromathematical Neuroengineering Notation”. This specialized operation that is the Trioinformatics article appeared in the March–May imanager’s Journal on Circuits and Systems. Trioengineering use of the neuromathematics “Ambitation” is the holistic, collaborative, and comprehensive expression of Trioinformatics as a sequential sequence of inquiry into a precise research analysis methodology. Neuroengineering is an innovative way of explaining the transition from trichotomous logic (Osler, 2015) into trichotomous Triple–I (Osler, 2013d) research questions and associated instrumentation [first introduced in the i-manager’s Journal on Mathematics as a part of the Tri–Squared Test (Osler, 2012a)].Trioinformatics is an in–depth way of symbolically illustrating the law of trichotomy and a mathematically–grounded rational technique for explaining the ternary nature of electronic circuitry (Osler, 2015). The use of the Trioinformatics also adds value to investigative inquiry through the efficacy of digital instruments and tools via eduscientifically–engineered (Osler, 2013a) research designs (Osler, 2015).

References

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[23]. Osler, J. E. (2010). Visualus™ © Visioneering Volumetrically: The Mathematics of the Innovative Problem–Solving Model of Inventive Instructional Design (First Edition). Lulu Publishing, Morrisville NC.

[24]. Osler, J. E. (2012a). Trichotomy–Squared – A novel mixed methods test and research procedure designed to analyze, transform, and compare qualitative and quantitative data for education scientists who are administrators, practitioners, teachers, and technologists. i-manager's Journal on Mathematics, 1(3), pp. 23-31. https://doi.org/10.26634/jmat.1.3.1948

[25]. Osler, J. E. & Waden, C. (2012b). Using innovative technical solutions as an intervention for at risk students: A meta–cognitive statistical analysis to determine the impact of ninth grade freshman academies, centers, and center models upon minority student retention and achievement. i-manager's Journal on School Educational Technology, 8(2), pp.11-23. https://doi.org/ 10.26634/jsch.8.2.2023

[26]. Osler, J. E. (2013a). The psychometrics of educational science: Designing trichotomous inventive investigative instruments for qualitative and quantitative for inquiry. i-manager's Journal on School Education Technology, 8(3), 15-22. https://doi.org/10.26634/jsch. 8.3.2123.

[27]. Osler, J. E. (2013b). The psychological efficacy of education as a science through personal, professional, and contextual inquiry of the affective learning domain. i-manager's Journal on Educational Psychology, 6(4), pp. 36-41. https://doi.org/10.26634/jpsy.6.4.2186

[28]. Osler, J. E. (2013c). Proximal positive parallel notation: A novel method of expressing mathematical complements, collaborations, and combinations. i-manager's Journal on Mathematics, 2(4), 21-32. https://doi.org/10.26634/jmat.2.4.2612

[29]. Osler, J. E. (2013d). Transformational research engineering: Research design metrics for in–depth and empowering K–12 teacher professional development. i-manager's Journal on School Educational Technology, 9(1), 43-60. https://doi.org/10.26634/jsch.9.1.2526

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Research Paper

Early, Demagnetization Assessment of PMSM Machine by Discrete Wavelet Transform

Khadim Moin Siddiqui* , S. Chatterji**

* Associate Professor and Head, Department of Electrical Engineering, Guru Nanak Institute of Engineering & Management, Hoshiarpur, Punjab, India.

** Group Director, Shri Guru Nanak Dev Education Trust, Dalewal, Hoshiarpur, Punjab, India.

Siddiqui, K. M., Chatterji, S. (2018). Early, Demagnetization Assessment of PMSM Machine by Discrete Wavelet Transform, i-manager's Journal on Circuits and Systems, 6(4), 16-25. https://doi.org/10.26634/jcir.6.4.15214

Abstract

Nowadays, in many applications, the Permanent Magnet Synchronous Motor (PMSM) has become an alternative to induction machines due to its reliability and excellent dynamic performance. Therefore, the PMSM are being used in the large variety of applications, especially in automotive or high power traction systems. In this motor, the diagnosis of magnetic status has become a challenging task for many researchers since a decade. Therefore, in this research paper an attempt has been made to solve the above problem and trying to diagnose magnetic demagnetization in the early stage precisely. The magnetic demagnetization of the PMSM has been diagnosed with the help of a proposed simulation model. In the simulation model, various stages of magnetic demagnetizations have been created by varying some physical parameters and have been diagnosed in the early stages by applying advanced wavelet transform technique. For diagnosis of magnetic demagnetization, two approaches have been used; first is the time domain technique and second is the time-frequency domain technique.

References

[1]. Demetriades, G. D., De La Parra, H. Z., Andersson, E., & Olsson, H. (2010). A real-time thermal model of a permanent-magnet synchronous motor. IEEE Transactions on Power Electronics, 25(2), 463-474.

[2]. Ding, X., Bhattacharya, M., & Mi, C. (2010). Simplified thermal model of PM motors in hybrid vehicle applications taking into account eddy current loss in magnets. Journal of Asian Electric Vehicles, 8(1), 1337- 1343.

[3]. El-Refaie, A. M., Harris, N. C., Jahns, T. M., & Rahman, K. M. (2004). Thermal analysis of multibarrier interior PM synchronous machine using lumped parameter model. IEEE Transactions on Energy Conversion, 19(2), 303-309.

[4]. Feng, G., Lai, C., & Kar, N. C. (2017). Particle-filter-based magnet flux linkage estimation for PMSM magnet condition monitoring using harmonics in machine speed. IEEE Transactions on Industrial Informatics, 13(3), 1280- 1290.

[5]. Feng, G., Lai, C., Tjong, J., & Kar, N. (2018). Non-invasive Kalman Filter based Permanent Magnet Temperature Estimation for Permanent Magnet Synchronous Machines. IEEE Transactions on Power Electronics, 33(12), 10673-10682.

[6]. Fu, W. N., & Ho, S. L. (2010). Dynamic demagnetization computation of permanent magnet motors using finite element method with normal magnetization curves. IEEE Transactions on Applied Superconductivity, 20(3), 851-855.

[7]. Lai, C., Iyer, K. L. V., Mukherjee, K., & Kar, N. C. (2015). Analysis of electromagnetic torque and effective winding inductance in a surface-mounted PMSM during integrated battery charging operation. IEEE Transactions on Magnetics, 51(11), 1-4.

[8]. Liu, K., & Zhu, Z. Q. (2015). Mechanical parameter estimation of permanent-magnet synchronous machines with aiding from estimation of rotor PM flux linkage. IEEE Transactions on Industry Applications, 51(4), 3115-3125.

[9]. Liu, S., Mohammed, O. A., & Liu, Z. (2007). An improved FE-based phase variable model of PM synchronous machines including dynamic core losses. IEEE Transactions on Magnetics, 43(4), 1801-1804.

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[13]. Sarikhani, A., & Mohammed, O. (2012, September). Real-time demagnetization assessment of PM synchronous machine. In Electrical Machines (ICEM), 2012 XX^th International Conference on (pp. 2418-2424). IEEE.

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[15]. Siddiqui, K. M., Upadhyay, S. K., Singh, S., Srivastava, R. K., & Babu, R. (2017a). Performance and Analysis of PWM Inverter Fed 3-Phase Pmsm Drive. i-manager's Journal on Electronics Engineering, 8(1), 9- 18.

[16]. Siddiqui, K.M., Sahay, K., and Giri, V.K. (2017). Modeling and open phase fault analysis in three and five phase permanent magnet synchronous motor machine. i-manager's Journal on Instrumentation and Control Engineering, 5(4), 32-40.

[17]. Simani, S., Farsoni, S., & Castaldi, P. (2015). Fault diagnosis of a wind turbine benchmark via identified fuzzy models. IEEE Transactions on Industrial Electronics, 62(6), 3775-3782.

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Research Paper

Design of Area Efficient Encoder and Decoder using Quantum DOT Cellular Automata

Mrunalini M. Kamble* , Deepti S. Khurge**

* P.G. Student, Department of Electronic & Telecommunication, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

** Assistant Professor, Department of Electronic & Telecommunication, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

Kamble, M., Khurge,D. S. (2018). Design of Area Efficient Encoder and Decoder using Quantum Dot Cellular Automata, i-manager's Journal on Circuits and Systems, 6(4), 26-30. https://doi.org/10.26634/jcir.6.4.14942

Abstract

As an alternative to CMOS-VLSI, researchers have proposed new technologies like FINFET, CNTFET, MTJ to reduce the scalability of the device. A new computing paradigm with quantum dots called Quantum dot Cellular Automata (QCA) is a polarization based digital logic architecture. QCA cell is the basic unit to build logic gates and devices in quantum domain. It proposes an effective design of logic gates and arithmetic circuit using QCA. Here the half and full adder is designed using minimum number of QCA cells with no crossover and compared with previous results. So these designs can be used to construct complex circuits. The simulations of the present work have been carried out by means of QCA designer tools. The simulation results help to implement large digital circuits in nanoscalerange.

References

[1]. Ahmad, F., Bhat, G. M., & Ahmad, P. Z. (2014). Novel adder circuits based on quantum-dot cellular automata (QCA). Circuits and Systems, 5(06), 142-152.

[2]. Balakrishnan, L., Godhavari, T., & Kesavan, S. (2015, August). Effective design of logic gates and circuit using Quantum Cellular Automata (QCA). In Advances in Computing, Communications and Informatics (ICACCI), 2015 International Conference on (pp. 457-462). IEEE.

[3]. Nano-Arch Online. Quantum-dot Cellular Automata (QCA), Copyright © 2012 University of Erlangen-Nürnberg. All rights reserved, pages 1-11. Retrieved from http://www.cs3.tf.uni-erlangen.de/Research/KOMINA/ QCA_slides.pdf

[4]. Porod, W., Lent, C., Bernstein, G. H., Orlov, A. O., Hamlani, I., Snider, G. L., & Merz, J. L. (1999). Quantum-dot Cellular Automata: Computing with coupled quantum dots. International Journal of Electronics, 86(5), 549-590.

[5]. Rani, T. S., Karmakar, S., Metri, A. A., & Sharan, P. (2015). Comparative study of half adder and subtractor circuits based on Quantum-dot Cellular Automata (QCA). In International Conference on Advances in Computer & Communication Engineering (Vol. 3, No. 3, pp. 61-67).

[6]. Sinha, S. K., & Chaudhury, S. (2014). Comparative study of leakage power in CNTFET over MOSFET device. Journal of Semiconductors, 35(11), 114002.

[7]. Sridharan, K., & Pudi, V. (2015). Design of Arithmetic Circuits in Quantum Dot Cellular Automata Nanotechnology (Vol. 599). Springer.

[8]. Walus, K., Dysart, T. J., Jullien, G. A., & Budiman, R. A. (2004). QCA Designer: A rapid design and simulation tool for Quantum-dot Cellular Automata. IEEE Transactions on Nanotechnology, 3(1), 26-31.

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Research Paper

Detection of Rotor Broken Bar of an Induction Motor using S-Transform

Sudhir Agrawal* , V. K. Giri , A. N. Tiwari*

* PhD Scholar, Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, Uttar Pradesh, India.

Director, Rajkiya Engineering College, Sonbhadra, Uttar Pradesh, India.

* Professor, Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, Gorakhpur, Uttar Pradesh, India.

Agrawal, S., Giri, V. K., Tiwari, A. N. (2018). Detection of Rotor Broken Bar of an Induction Motor using S-Transform, i-manager's Journal on Circuits and Systems, 6(4), 31-37. https://doi.org/10.26634/jcir.6.4.15113

Abstract

Induction motors are the one of the most important production machines of any industry around the world. Therefore, the condition monitoring of induction motors is very important for successful and profitable running of an industry. Broken rotor bars are one of the critical health problems of any induction motor. To tackle this, application of Stockwell- Transform (ST) is presented in this paper. ST has been applied on the simulated signal of rotor broken bar and the results are compared with the Fast Fourier Transform method, which is a frequency domain analysis method. Normally, frequency domain analysis fails to detect the broken bar of the rotor if the severity of damage is low. The results obtained by applying ST confirms that the ST transform is able to detect the breakage of rotor bar better if the damage level is small.

References

[1]. Abellan-Nebot, J. V., & Subirón, F. R. (2010). A review of machining monitoring systems based on artificial intelligence process models. The International Journal of Advanced Manufacturing Technology, 47(1-4), 237-257.

[2]. Ahamed, S. K., Karmakar, S., Mitra, M., & Sengupta, S. (2010). Diagnosis of induction motor faults due to broken rotor bar and rotor mass unbalance through discrete wavelet transform of starting current at no-load. Journal of Electrical Systems, 6(3), 442-456.

[3]. Dias, C. G., & Pereira, F. H. (2018). Broken rotor bars detection in induction motors running at very low slip using a hall effect sensor. IEEE Sensors Journal, 18(11), 4602- 4613.

[4]. Gaeid, K. S., Ping, H. W., Khalid, M., & Salih, A. L. (2011). Fault diagnosis of induction motor using MCSA and FFT. Electrical and Electronic Engineering, 1(2), 85- 92.

[5]. Guedidi, S., Zouzou, S. E., Laala, W., Yahia, K., & Sahraoui, M. (2013). Induction motors broken rotor bars detection using MCSA and neural network: Experimental research. International Journal of System Assurance Engineering and Management, 4(2), 173-181.

[6]. Guldemir, H., & Bradley, K. J. (2003). An improved approach to the prediction of line current spectrum in induction machines. Electrical Engineering, 86(1), 17-24.

[7]. Hassan, O. E., Amer, M., Abdelsalam, A. K., & Williams, B. W. (2018). Induction motor broken rotor bar fault detection techniques based on fault signature analysis–a review. IET Electric Power Applications, 12(7), 895-907.

[8]. Jardine, A. K., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7), 1483-1510.

[9]. Kurek, J., & Osowski, S. (2010). Support vector machine for fault diagnosis of the broken rotor bars of squirrel-cage induction motor. Neural Computing and Applications, 19(4), 557-564.

[10]. Mehala, N., & Dahiya, R. (2008, December). A comparative study of FFT, STFT, and wavelet techniques for induction machine fault diagnostic analysis. In Proceedings of the 7^thWSEAS International Conference on Computational Intelligence, Man-Machine Systems and Cybernetics (Vol.2931).

[11]. Mehala, N., & Dahiya, R. (2009). Condition monitoring methods, failure identification and analysis for Induction machines. International Journal of Circuits, Systems and Signal Processing, 3(1), 10-17.

[12]. Prieto, M. D., Cirrincione, G., Espinosa, A. G., Ortega, J. A., & Henao, H. (2013). Bearing fault detection by a novel condition-monitoring scheme based on statistical-time features and neural networks. IEEE Transactions on Industrial Electronics, 60(8), 3398-3407.

[13]. Rai, V. K., & Mohanty, A. R. (2007). Bearing fault diagnosis using FFT of intrinsic mode functions in Hilbert–Huang transform. Mechanical Systems and Signal Processing, 21(6), 2607-2615.

[14]. Rodríguez, P. V. J., Negrea, M., & Arkkio, A. (2008). A simplified scheme for induction motor condition monitoring. Mechanical Systems and Signal Processing, 22(5), 1216-1236.

[15]. Stockwell, R. G., Mansinha, L., & Lowe, R. P. (1996). Localization of the complex spectrum: the S transform. IEEE Transactions on Signal Processing, 44(4), 998-1001.

[16]. Trachi, Y., Elbouchikhi, E., Choqueuse, V., & Benbouzid, M. (2015, November). Stator current analysis by subspace methods for fault detection in induction machines. In Industrial Electronics Society, IECON 2015- 41^st Annual Conference of the IEEE (pp.3479-3484). IEEE.

[17]. Wang, D., Peter, W. T., & Tsui, K. L. (2013). An enhanced Kurtogram method for fault diagnosis of rolling element bearings. Mechanical Systems and Signal Processing, 35(1-2), 176-199.

[18]. Wang, J., Gao, R. X., & Yan, R. (2011). Broken-rotor-bar diagnosis for induction motors. In Journal of Physics: Conference Series (Vol. 305, No. 1, p. 012026). IOP Publishing.

[19]. Widodo, A., Kim, E. Y., Son, J. D., Yang, B. S., Tan, A. C., Gu, D. S., ... & Mathew, J. (2009). Fault diagnosis of low speed bearing based on relevance vector machine and support vector machine. Expert Systems with Applications, 36(3), 7252-7261.

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Research Paper

Design and Verification of 16-Bit RISC Processor using SystemVerilog

S. M. Bhagat* , S. U. Bhandari**

* PG Scholar, Department of Electronic and Telecommunication from Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

** Professor, Department of Electronic and Telecommunication from Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

Bhagat, S. M., Bhandari, S. U. (2018). Design and Verification of 16-Bit RISC Processor using System Verilog, i-manager's Journal on Circuits and Systems, 6(4), 38-41. https://doi.org/10.26634/jcir.6.4.14864

Abstract

The regularly increasing complexity and size of the designs faces various issues with traditional verification methods. To address this issue a reuse-oriented, verification methodology should be adopted which is built on the rich semantic support of a standard language. This paper presents a design of a 16 bit RISC processor with 15 instructions. The design is described in each module and the performance of the design is also presented in convenient manner. Although the design cycle takes time, but more time is required for verification. To perform verification process, verification environment is built for few modules of this RISC processor using SystemVerilog. Among various verification methodologies here a simple approach of verification is presented.

References

[1]. Balpande, V. V., Pande, A. B., Walke, M. J., Choudhari, B. D., Bagade, K. R. (2015). Design and Implementation of 16 Bit Processor on FPGA. International Journal of Advanced Research in Computer Science and Software Engineering, 5 (1),704-708.

[2]. Bhagat, S. M., & Bhandari, S. U. (2018). Design and Analysis of 16-bit RISC processor. Fourth International Conference on Computing, Communication, Control & Automation.

[3]. Jung, S. P., Xu, J., Lee, D., Park, J. S., Kim, K. J., & Cho, K. S. (2008, November). Design & verification of 16 bit RISC processor. In SoC Design Conference, 2008. ISOCC'08. International (Vol. 3, pp. 13-14). IEEE.

[4]. Parihar, R. K. S., & Reddy, S (2006). A report on Designing of 16-bit RISC Processor. Birla Institute of Technology and Science, Pilani.

[5]. Patil, A. S., & Shivaleelavathi, B. G. (2017). Design and implementation of pipelined 8-Bit RISC processor using Verilog HDL on FPGA. International Research Journal of Engineering and Technology (IRJET), 4(6), 1753-1756.

[6]. Sethulekshmi, R., Jazir, S., Rahiman, R. A., Karthik, R., & Abdulla, M. S. (2016, March). Verification of a RISC processor IP core using System Verilog. In Wireless Communications, Signal Processing and Networking (WiSPNET), International Conference on (pp. 1490-1493). IEEE.

[7]. Uma, R. (2012). Design and Performance analysis of 8 bit RISC Processor Using Xilinx Tool. International Journal of Engineering Research and Application, 2(2), 53-58.

i-manager's Journal on Circuits and Systems (JCIR)

Current Issue Vol. 12 Issue 1

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Volume 6 Issue 4 September - November 2018

Trioengineering: The Procedures that Use Trioinformatics Neuroengineering Neuromathematics Notation to Express, Build, Define, and Inform the Application of the Trichotomous–Based Inquiry in Digital Research Design

James Edward Osler II*

Professor, School of Education, North Carolina Central University, USA.

Abstract

References

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Early, Demagnetization Assessment of PMSM Machine by Discrete Wavelet Transform

Khadim Moin Siddiqui* , S. Chatterji**

* Associate Professor and Head, Department of Electrical Engineering, Guru Nanak Institute of Engineering & Management, Hoshiarpur, Punjab, India. ** Group Director, Shri Guru Nanak Dev Education Trust, Dalewal, Hoshiarpur, Punjab, India.

Siddiqui, K. M., Chatterji, S. (2018). Early, Demagnetization Assessment of PMSM Machine by Discrete Wavelet Transform, i-manager's Journal on Circuits and Systems, 6(4), 16-25. https://doi.org/10.26634/jcir.6.4.15214

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Design of Area Efficient Encoder and Decoder using Quantum DOT Cellular Automata

Mrunalini M. Kamble* , Deepti S. Khurge**

* P.G. Student, Department of Electronic & Telecommunication, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India. ** Assistant Professor, Department of Electronic & Telecommunication, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

Kamble, M., Khurge,D. S. (2018). Design of Area Efficient Encoder and Decoder using Quantum Dot Cellular Automata, i-manager's Journal on Circuits and Systems, 6(4), 26-30. https://doi.org/10.26634/jcir.6.4.14942

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Detection of Rotor Broken Bar of an Induction Motor using S-Transform

Sudhir Agrawal* , V. K. Giri **, A. N. Tiwari***

Agrawal, S., Giri, V. K., Tiwari, A. N. (2018). Detection of Rotor Broken Bar of an Induction Motor using S-Transform, i-manager's Journal on Circuits and Systems, 6(4), 31-37. https://doi.org/10.26634/jcir.6.4.15113

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Design and Verification of 16-Bit RISC Processor using SystemVerilog

S. M. Bhagat* , S. U. Bhandari**

* PG Scholar, Department of Electronic and Telecommunication from Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India. ** Professor, Department of Electronic and Telecommunication from Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

Bhagat, S. M., Bhandari, S. U. (2018). Design and Verification of 16-Bit RISC Processor using System Verilog, i-manager's Journal on Circuits and Systems, 6(4), 38-41. https://doi.org/10.26634/jcir.6.4.14864

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* Associate Professor and Head, Department of Electrical Engineering, Guru Nanak Institute of Engineering & Management, Hoshiarpur, Punjab, India.

** Group Director, Shri Guru Nanak Dev Education Trust, Dalewal, Hoshiarpur, Punjab, India.

* P.G. Student, Department of Electronic & Telecommunication, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

** Assistant Professor, Department of Electronic & Telecommunication, Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

Sudhir Agrawal* , V. K. Giri , A. N. Tiwari*

* PG Scholar, Department of Electronic and Telecommunication from Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.

** Professor, Department of Electronic and Telecommunication from Pimpri Chinchwad College of Engineering, Pune, Maharashtra, India.