Comparative Performance of Intelligent Algorithms for System Identification and Control

Madkour, A. A.; Dahal, Keshav; Yu, Hongnian

doi:10.1515/jisys.2008.17.4.313

Cited by 5 publications

(1 citation statement)

References 7 publications

(8 reference statements)

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“…Sekhar and Prabhu [13] have derived a method for crack detection in a cracked shaft using finite element analysis using correct expression for strain energy release rate function. Hossain et al [14] have presented an investigation for comparative performance of intelligent system-like genetic algorithms (GAs) and adaptive neurofuzzy inference system (ANFIS) algorithms for identification of fault in an active vibration control (AVC) system. A comparative performance of the proposed method is presented and discussed through a set of experiments.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Adaptive Fuzzy Technique for Multiple Crack Diagnosis of Faulty Beam Using Vibration Signatures

Dash

2013

Advances in Fuzzy Systems

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This paper discusses the multicrack detection of structure using fuzzy Gaussian technique. The vibration parameters derived from the numerical methods of the cracked cantilever beam are used to set several fuzzy rules for designing the fuzzy controller used to predict the crack location and depth. Relative crack locations and relative crack depths are the output parameters from the fuzzy inference system. The method proposed in the current analysis is used to evaluate the dynamic response of cracked cantilever beam. The results of the proposed method are in good agreement with the results obtained from the developed experimental setup.

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Section: Introductionmentioning

confidence: 99%

Analysis of Adaptive Fuzzy Technique for Multiple Crack Diagnosis of Faulty Beam Using Vibration Signatures

Dash

2013

Advances in Fuzzy Systems

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Effect of Slenderness Ratio on Crack Parameters of Simply Supported Shaft

Nanda

Das

Parhi

2014

Procedia Materials Science

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Transverse crack is a common occurrence present in over simply supported shaft. The development of crack in a shaft is leads to catastrophic failure, which will affect the dynamic behavior such a local stiffness and stress intensity factor of the given shaft. The change in stiffness and stress intensity factor will lead to change in eigenfrequency with their mode shapes at different crack location and depth.In the present study a methodology is applied for detecting multi crack with its location and size due to transverse crack at same angular position along longitudinal direction at different slenderness ratioThe shaft is subjected to both axial and bending load. The behavior of the shaft in presence of two transverse cracks subjected to are observed by taking basic parameters such as non-dimensional depth (b i /D), non-dimensional length (L i /L) and three relative natural frequencies with their relative mode shapes. The compliance matrix is calculated from stress intensity factor for two degrees of freedom. The compliance matrix is a function of crack parameters such as depth and location of crack. The three relative natural frequencies and their mode shapes at different location and depth obtained analytical. In the Present Research, the method of validating results for crack location and depth with its intensity in using Genetic algorithm. At the beginning, theoretical analyses have been outlined for determining crack parameters and feed the same to trend up GA. The proposed theoretical approach has been verified by comparing with the results obtained from GA.

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