scholarly journals A Soft Computing Approach to Crack Detection and Impact Source Identification with Field-Programmable Gate Array Implementation

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Arati M. Dixit ◽  
Harpreet Singh
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Inference System ◽  
Source Identification ◽  
Field Programmable Gate Array ◽  
Crack Detection ◽  
Fuzzy Inference ◽  
Inference System ◽  
Field Programmable ◽  
Computing Approach

The real-time nondestructive testing (NDT) for crack detection and impact source identification (CDISI) has attracted the researchers from diverse areas. This is apparent from the current work in the literature. CDISI has usually been performed by visual assessment of waveforms generated by a standard data acquisition system. In this paper we suggest an automation of CDISI for metal armor plates using a soft computing approach by developing a fuzzy inference system to effectively deal with this problem. It is also advantageous to develop a chip that can contribute towards real time CDISI. The objective of this paper is to report on efforts to develop an automated CDISI procedure and to formulate a technique such that the proposed method can be easily implemented on a chip. The CDISI fuzzy inference system is developed using MATLAB’s fuzzy logic toolbox. A VLSI circuit for CDISI is developed on basis of fuzzy logic model using Verilog, a hardware description language (HDL). The Xilinx ISE WebPACK9.1i is used for design, synthesis, implementation, and verification. The CDISI field-programmable gate array (FPGA) implementation is done using Xilinx’s Spartan 3 FPGA. SynaptiCAD’s Verilog Simulators—VeriLogger PRO and ModelSim—are used as the software simulation and debug environment.

scholarly journals A Fuzzy Logic Based System for Secure Scrum

2019 ◽  
Vol 8 (4) ◽  
pp. 8961-8964
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
System Performance ◽  
Fuzzy Inference ◽  
System Model ◽  
Basic System ◽  
Inference System ◽  
General Functioning ◽  
Software Engineers

Software is a basic system that acts as a major key part in general functioning system like securing the need of performance and scope of the system. Here the security is given to unauthorized user as unauthorized client that casually gets the change or modification within the system by effecting the efficiency and functionality of the system. So in order to overcome this issue new improved software is taken that improves the system performance and security. the paper represents a new fuzzy logic based system for handling secured attribute and assessment in software. Based on this reason we propose PC1 and bugs dataset for fuzzy inference system can be used. This secured system model helps software engineers to select secured and safety software for the performance and ambiguity.

EKSTRAKSI FITUR PEMBULUH DARAH CITRA FUNDUS RETINA MENGGUNAKAN FUZZY LOGIC

2021 ◽  
Vol 26 (2) ◽  
pp. 163-175
Author(s):  
Asyaroh Ramadona Nilawati ◽  
Taufik Hidayat
Keyword(s):  
Fuzzy Logic ◽  
Optic Disc ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Median Filtering ◽  
Inference System

Ekstraksi pola pembuluh darah retina dapat dimanfaatkan dalam sistem biometrik sebagai otentikasi keamanan. Citra hasil ekstraksi pola pembuluh darah retina dapat dimasukkan ke dalam fitur untuk identifikasi sistem biometrik. Salah satu metode yang dapat dilakukan untuk melakukan segmentasi pembuluh darah retina adalah metode fuzzy logic. Pada penelitian ini, dilakukan ekstraksi pembuluh darah citra fundus retina menggunakan implementasi fuzzy logic. Peneliti menggunakan sejumlah 20 citra fundus yang diperoleh dari dataset DRIVE berformat .tif. Proses segmentasi dimulai dengan tahap preprocessing yang berisikan konversi citra menjadi grayscale, median filtering, perataan histogram CLAHE, dan eliminasi optic disc, kemudian dilanjutkan dengan pembuatan fuzzy inference system. Tahapan preprocessing yang digunakan merupakan hasil dari rangkaian uji coba peneliti dengan melihat hasil dari setiap uji coba yang dilakukan, sehingga mendapatkan citra yang menonjolkan fitur pembuluh darah dan menghilangkan noise atau fitur retina yang tidak diperlukan seperti optic disc. Uji coba segmentasi dilakukan pada Polyspace R2020a sebagai media untuk menjalankan program mulai dari preprocessing hingga segmentasi menggunakan fuzzy logic. Keluaran dari segmentasi ini berupa citra segmentasi hasil dari metode fuzzy logic dan crisp value. Metode fuzzy logic berhasil diterapkan untuk melakukan ekstraksi pembuluh darah retina dan menghasilkan crisp value. Hasil penelitian ini diharapkan dapat digunakan sebagai salah satu fitur sistem identifikasi biometrik retina.

Smoothing the output power of a wind energy conversion system using a hybrid nonlinear pitch angle controller

2021 ◽  
pp. 014459872110417
Author(s):  
Ya-Jun Fan ◽  
Hai-tong Xu ◽  
Zhao-Yu He
Keyword(s):  
Fuzzy Logic ◽  
Wind Energy ◽  
Output Power ◽  
Wind Turbines ◽  
Fuzzy Inference System ◽  
Pitch Angle ◽  
Fuzzy Inference ◽  
Hybrid Control ◽  
Inference System ◽  
Neuro Fuzzy

Wind energy has been developed and is widely used as a clean and renewable form of energy. Among the existing variety of wind turbines, variable-speed variable-pitch wind turbines have become popular owing to their variable output power capability. In this study, a hybrid control strategy is proposed to implement pitch angle control. A new nonlinear hybrid control approach based on the Adaptive Neuro-Fuzzy Inference System and fuzzy logic control is proposed to regulate the pitch angle and maintain the captured mechanical energy at the rated value. In the controller, the reference value of the pitch angle is predicted by the Adaptive Neuro-Fuzzy Inference System according to the wind speed and the blade tip speed ratio. A proposed fuzzy logic controller provides feedback based on the captured power to modify the pitch angle in real time. The effectiveness of the proposed hybrid pitch angle control method was verified on a 5 MW offshore wind turbine under two different wind conditions using MATLAB/Simulink. The simulation results showed that fluctuations in rotor speed were dramatically mitigated, and the captured mechanical power was always near the rated value as compared with the performance when using the Adaptive Neuro-Fuzzy Inference System alone. The variation rate of power was 0.18% when the proposed controller was employed, whereas it was 2.93% when only an Adaptive Neuro-Fuzzy Inference System was used.

Fuzzy Logic-Based Inference Systems

2015 ◽  
pp. 209-239
Keyword(s):  
Fuzzy Logic ◽  
Knowledge Representation ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Mathematical Formulation ◽  
Cognitive Map ◽  
Fuzzy Cognitive Map ◽  
Adaptive Networks ◽  
Inference System ◽  
Inference Systems

This chapter presents the mathematical formulation of the fuzzy logic-based inference systems, used as means to infer about the response of ill-conditioned systems, based on the field knowledge representation in the fuzzy world. Particular approaches are explored, e.g., Fuzzy Inference System (FIS), Adaptive Networks-based FIS (ANFIS), Intuitionistic FIS (IFIS) and Fuzzy Cognitive Map (FCM), surfacing their potentialities in modeling applications, such as those in the field of learning, examined in the chapters of Part III that follow.

Dynamic Behaviour and Crack Detection of a Multi Cracked Rotating Shaft using Adaptive Neuro-Fuzzy-Inference System

2016 ◽  
Vol 6 (4) ◽  
pp. 1-10 ◽  
Author(s):  
Rajeev Ranjan
Keyword(s):  
Finite Element ◽  
Fuzzy Inference System ◽  
Crack Detection ◽  
Fuzzy Inference ◽  
Crack Depth ◽  
Multiple Cracks ◽  
Rotating Shaft ◽  
Element Analysis ◽  
Inference System ◽  
Neuro Fuzzy

The presence of crack changes the physical characteristics of a structure which in turn alter its dynamic response characteristics. So it is important to understand dynamics of cracked structures. Crack depth and location are the main parameters influencing the vibration characteristics of the rotating shaft. In the present study, a technique based on the measurement of change of natural frequencies has been employed to detect the multiple cracks in rotating shaft. The model of shaft was generated using Finite Element Method. In Finite Element Analysis, the natural frequency of the shaft was calculated by modal analysis using the software ANSYS. The Numerical data were obtained from FEA, then used to train through Adaptive Neuro-Fuzzy-Inference System. Then simulations were carried out to test the performance and accuracy of the trained networks. The simulation results show that the proposed ANFIS estimate the locations and depth of cracks precisely.

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