Design and development of 3-stage determination of damage location using Mamdani-adaptive genetic-Sugeno model

Sahu, Sasmita; Kumar, Priyadarshi Biplab; Parhi, Dayal R.

doi:10.15632/jtam-pl.55.4.1325

Cited by 6 publications

(2 citation statements)

References 13 publications

(7 reference statements)

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“…They made analysis by using finite element methods and fuzzy logic techniques. Sahu et al [10] proposed a method like Fuzzy logic technique and Adaptive Genetic Algorithm for structural damage detection in an unhealthy cantilever aluminum alloy beam. Afterwards, the results obtained both from the experimental analysis and the proposed methods are verified.…”

Section: Introductionmentioning

confidence: 99%

Numerical and Theoretical Analysis of Free Vibration of a Multi- Cracked Cantilever Beam with Rectangular Cross Section

2019

JSTR

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Structures used in the application must perform their duties undamaged during the time they are used. Cracks often affect the dynamic properties of the structural elements and can cause severe durability problems. The crack detection in the structural elements and vibration analysis are vital in engineering applications and so far has been the subject of many researches. In present study, free vibration analysis of the un-cracked and cracked cantilever beam was performed and the first three natural frequencies were determined as theoretically and numerically. After verifying the results, the beams were modeled using CATIA software and analyzed using the finite element method with ANSYS software in order to get quick results. The effect of the location of the crack, the depth of the crack, the width of the crack and the number of cracks on the first three natural frequencies was investigated by performing a parametric study. The results are given in tables and graphs.

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Section: Introductionmentioning

confidence: 99%

Numerical and Theoretical Analysis of Free Vibration of a Multi- Cracked Cantilever Beam with Rectangular Cross Section

2019

JSTR

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“…There are various applicable controller methods that can be divided in to different branches such as model-base or none modelbase [11][12][13][14][15][16][17][18][19][20][21]; (Figure 1 & 2), adaptive [22][23][24][25][26][27][28], and intelligence [29][30][31][32][33][34][35][36] methods. Tuning the parameters of a controller method which contains a high number of tunable parameters, is very crucial and can be very cumbersome.…”

Section: Introductionmentioning

confidence: 99%

Control of a SCARA Robot Using Feedback Linearization and Kalman Filter Observer

Nazari

2019

EME

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In this paper an efficient controller is presented for controlling SCARA robot in present of undesirable noises in variable states. To do so, feedback linearization is considered as the main controller and kalman filter estimator is utilized to estimate the state variables from the noisy output signals. In order to evaluate the performance of the purposed method, a simulation test is performed to apply this controller on the SCARA robot. The simulation is done for both noisy and not noisy signals. The results show that the kalman filter observer has accomplished a good state estimation and feedback lineation controller has tracked the desired signals perfectly as well.

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Navigational Control Analysis of Mobile Robot in Cluttered Unknown Environment Using Novel Neural-GSA Technique

Das¹,

Mohanty²,

Behera

et al. 2020

Lecture Notes in Mechanical Engineering

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Design and development of 3-stage determination of damage location using Mamdani-adaptive genetic-Sugeno model

Cited by 6 publications

References 13 publications

Numerical and Theoretical Analysis of Free Vibration of a Multi- Cracked Cantilever Beam with Rectangular Cross Section

Numerical and Theoretical Analysis of Free Vibration of a Multi- Cracked Cantilever Beam with Rectangular Cross Section

Control of a SCARA Robot Using Feedback Linearization and Kalman Filter Observer

Navigational Control Analysis of Mobile Robot in Cluttered Unknown Environment Using Novel Neural-GSA Technique

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