Displaying publications 21 - 40 of 115 in total

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  1. Fulltext Expanded DEMATEL for determining cause and effect group in bidirectional relations
    Falatoonitoosi E, Ahmed S, Sorooshian S
    ScientificWorldJournal, 2014;2014:103846.
    PMID: 24693224 DOI: 10.1155/2014/103846
    Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology has been proposed to solve complex and intertwined problem groups in many situations such as developing the capabilities, complex group decision making, security problems, marketing approaches, global managers, and control systems. DEMATEL is able to realize casual relationships by dividing important issues into cause and effect group as well as making it possible to visualize the casual relationships of subcriteria and systems in the course of casual diagram that it may demonstrate communication network or a little control relationships between individuals. Despite of its ability to visualize cause and effect inside a network, the original DEMATEL has not been able to find the cause and effect group between different networks. Therefore, the aim of this study is proposing the expanded DEMATEL to cover this deficiency by new formulations to determine cause and effect factors between separate networks that have bidirectional direct impact on each other. At the end, the feasibility of new extra formulations is validated by case study in three numerical examples of green supply chain networks for an automotive company.
    Matched MeSH terms: Fuzzy Logic*
  2. Fuzzy time-optimal controller (FTOC) for second order nonlinear systems
    Nagi F, Ahmed SK, Zularnain AT, Nagi J
    ISA Trans, 2011 Jul;50(3):364-75.
    PMID: 21353218 DOI: 10.1016/j.isatra.2011.01.014
    The motivation behind this paper is to seek alternative techniques to achieve a near optimal controller for non-linear systems without solving the analytical problem. In classical optimal control systems, the system states and optimization co-state parameters generate a two-point boundary value problem (TPBVP) using Pontryagin's minimum principle (PMP). The paper contributes a new fuzzy time-optimal controller to the existing fuzzy controllers which has two regular inputs and one bang-bang output. The proposed controller closely approximates the output of the classical time-optimal controller. Further, input membership function are tuned on-line to improve the time-optimal output. The new controller exhibits optimal behaviour for second order non-linear systems. The rules are selected to satisfy the stability and optimality conditions of the new fuzzy time-optimal controller. The paper describes a systematic procedure to design the controller and how to achieve the desired result. To benchmark the new controller performance, a sliding mode controller is used for guidance and comparison purpose. Simulation of three non-linear examples shows promising results. The work described here is expected to incite researcher's interest in fuzzy time-optimal controller design.
    Matched MeSH terms: Fuzzy Logic*
  3. Intelligent classification of electrocardiogram (ECG) signal using extended Kalman Filter (EKF) based neuro fuzzy system
    Meau YP, Ibrahim F, Narainasamy SA, Omar R
    Comput Methods Programs Biomed, 2006 May;82(2):157-68.
    PMID: 16638620
    This study presents the development of a hybrid system consisting of an ensemble of Extended Kalman Filter (EKF) based Multi Layer Perceptron Network (MLPN) and a one-pass learning Fuzzy Inference System using Look-up Table Scheme for the recognition of electrocardiogram (ECG) signals. This system can distinguish various types of abnormal ECG signals such as Ventricular Premature Cycle (VPC), T wave inversion (TINV), ST segment depression (STDP), and Supraventricular Tachycardia (SVT) from normal sinus rhythm (NSR) ECG signal.
    Matched MeSH terms: Fuzzy Logic*
  4. Fulltext An Integrated MCDM Model for Conveyor Equipment Evaluation and Selection in an FMC Based on a Fuzzy AHP and Fuzzy ARAS in the Presence of Vagueness
    Nguyen HT, Dawal SZ, Nukman Y, Rifai AP, Aoyama H
    PLoS One, 2016;11(4):e0153222.
    PMID: 27070543 DOI: 10.1371/journal.pone.0153222
    The conveyor system plays a vital role in improving the performance of flexible manufacturing cells (FMCs). The conveyor selection problem involves the evaluation of a set of potential alternatives based on qualitative and quantitative criteria. This paper presents an integrated multi-criteria decision making (MCDM) model of a fuzzy AHP (analytic hierarchy process) and fuzzy ARAS (additive ratio assessment) for conveyor evaluation and selection. In this model, linguistic terms represented as triangular fuzzy numbers are used to quantify experts' uncertain assessments of alternatives with respect to the criteria. The fuzzy set is then integrated into the AHP to determine the weights of the criteria. Finally, a fuzzy ARAS is used to calculate the weights of the alternatives. To demonstrate the effectiveness of the proposed model, a case study is performed of a practical example, and the results obtained demonstrate practical potential for the implementation of FMCs.
    Matched MeSH terms: Fuzzy Logic*
  5. On fuzzy semantic similarity measure for DNA coding
    Ahmad M, Jung LT, Bhuiyan MA
    Comput Biol Med, 2016 Feb 1;69:144-51.
    PMID: 26773936 DOI: 10.1016/j.compbiomed.2015.12.017
    A coding measure scheme numerically translates the DNA sequence to a time domain signal for protein coding regions identification. A number of coding measure schemes based on numerology, geometry, fixed mapping, statistical characteristics and chemical attributes of nucleotides have been proposed in recent decades. Such coding measure schemes lack the biologically meaningful aspects of nucleotide data and hence do not significantly discriminate coding regions from non-coding regions. This paper presents a novel fuzzy semantic similarity measure (FSSM) coding scheme centering on FSSM codons׳ clustering and genetic code context of nucleotides. Certain natural characteristics of nucleotides i.e. appearance as a unique combination of triplets, preserving special structure and occurrence, and ability to own and share density distributions in codons have been exploited in FSSM. The nucleotides׳ fuzzy behaviors, semantic similarities and defuzzification based on the center of gravity of nucleotides revealed a strong correlation between nucleotides in codons. The proposed FSSM coding scheme attains a significant enhancement in coding regions identification i.e. 36-133% as compared to other existing coding measure schemes tested over more than 250 benchmarked and randomly taken DNA datasets of different organisms.
    Matched MeSH terms: Fuzzy Logic*
  6. A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process
    Tavana M, Khosrojerdi G, Mina H, Rahman A
    Eval Program Plann, 2019 12;77:101703.
    PMID: 31442587 DOI: 10.1016/j.evalprogplan.2019.101703
    The primary goal in project portfolio management is to select and manage the optimal set of projects that contribute the maximum in business value. However, selecting Information Technology (IT) projects is a difficult task due to the complexities and uncertainties inherent in the strategic-operational nature of the process, and the existence of both quantitative and qualitative criteria. We propose a two-stage process to select an optimal project portfolio with the aim of maximizing project benefits and minimizing project risks. We construct a two-stage hybrid mathematical programming model by integrating Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Inference System (FIS). This hybrid framework provides the ability to consider both the quantitative and qualitative criteria while considering budget constraints and project risks. We also present a real-world case study in the cybersecurity industry to exhibit the applicability and demonstrate the efficacy of our proposed method.
    Matched MeSH terms: Fuzzy Logic*
  7. A new hyperbox selection rule and a pruning strategy for the enhanced fuzzy min-max neural network
    Mohammed MF, Lim CP
    Neural Netw, 2017 Feb;86:69-79.
    PMID: 27890606 DOI: 10.1016/j.neunet.2016.10.012
    In this paper, we extend our previous work on the Enhanced Fuzzy Min-Max (EFMM) neural network by introducing a new hyperbox selection rule and a pruning strategy to reduce network complexity and improve classification performance. Specifically, a new k-nearest hyperbox expansion rule (for selection of a new winning hyperbox) is first introduced to reduce the network complexity by avoiding the creation of too many small hyperboxes within the vicinity of the winning hyperbox. A pruning strategy is then deployed to further reduce the network complexity in the presence of noisy data. The effectiveness of the proposed network is evaluated using a number of benchmark data sets. The results compare favorably with those from other related models. The findings indicate that the newly introduced hyperbox winner selection rule coupled with the pruning strategy are useful for undertaking pattern classification problems.
    Matched MeSH terms: Fuzzy Logic*
  8. Assessing the quality of sardine based on biogenic amines using a fuzzy logic model
    Zare D, Ghazali HM
    Food Chem, 2017 Apr 15;221:936-943.
    PMID: 27979297 DOI: 10.1016/j.foodchem.2016.11.071
    There is an increasing concern about the quality and quality assessment procedures of seafood. In the present study, a model to assess fish quality based on biogenic amine contents using fuzzy logic model (FLM) is proposed. The fish used was sardine (Sardinella sp.) where the production of eight biogenic amines was monitored over fifteen days of storage at 0, 3 and 10°C. Based on the results, histamine, putrescine and cadaverine were selected as input variables and twelve quality grades were considered for quality of fish as output variables for the FLM. Input data were processed by rules established in the model and were then defuzzified according to defined output variables. Finally, the quality of fish was evaluated using the designed model and Pearson correlation between storage times with quality of fish showed r=0.97, 0.95 and 1 for fish stored at 0, 3 and 10°C, respectively.
    Matched MeSH terms: Fuzzy Logic*
  9. Fulltext Hybrid PSO-FLC for dynamic global peak extraction of the partially shaded photovoltaic system
    Farh HMH, Eltamaly AM, Othman MF
    PLoS One, 2018;13(11):e0206171.
    PMID: 30388119 DOI: 10.1371/journal.pone.0206171
    Particle Swarm Optimization (PSO) is widely used in maximum power point tracking (MPPT) of photovoltaic (PV) energy systems. Nevertheless, this technique suffers from two main problems in the case of partial shading conditions (PSCs). The first problem is that PSO is a time invariant optimization technique that cannot follow the dynamic global peak (GP) under time variant shading patterns (SPs) and sticks to the first GP that occurs at the beginning. This problem can be solved by dispersing the PSO particles using two new techniques introduced in this paper. The two new proposed PSO re-initialization techniques are to disperse the particles upon the SP changes and the other one is upon a predefined time (PDT). The second problem is regarding the high oscillations around steady state, which can be solved by using fuzzy logic controller (FLC) to fine-tune the output power and voltage from the PV system. The new contribution of this paper is the hybrid PSO-FLC with two PSO particles dispersing techniques that is able to solve the two previous mentioned problems effectively and improve the performance of the PV system in both normal and PSCs. A detailed list of comparisons between hybrid PSO-FLC and original PSO using the two proposed methodologies are achieved. The results prove the superior performance of hybrid PSO-FLC compared to PSO in terms of efficiency, accuracy, oscillations reduction around steady state and soft tuning of the GP tracked.
    Matched MeSH terms: Fuzzy Logic*
  10. Comparative study of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS) and multiple linear regression (MLR) for modeling of Cu (II) adsorption from aqueous solution using biochar derived from rambutan (Nephelium lappaceum) peel
    Wong YJ, Arumugasamy SK, Chung CH, Selvarajoo A, Sethu V
    Environ Monit Assess, 2020 Jun 17;192(7):439.
    PMID: 32556670 DOI: 10.1007/s10661-020-08268-4
    Presence of copper within water bodies deteriorates human health and degrades natural environment. This heavy metal in water is treated using a promising biochar derived from rambutan (Nephelium lappaceum) peel through slow pyrolysis. This research compares the efficacies of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models and evaluates their capability in estimating the adsorption efficiency of biochar for the removal of Cu (II) ions based on 480 experimental sets obtained in a laboratory batch study. The effects of operational parameters such as contact time, operating temperature, biochar dosage, and initial Cu (II) ion concentration on removing Cu (II) ions were investigated. Eleven different training algorithms in ANN and 8 different membership functions in ANFIS were compared statistically and evaluated in terms of estimation errors, which are root mean squared error (RMSE), mean absolute error (MAE), and accuracy. The effects of number of hidden neuron in ANN model and fuzzy set combination in ANFIS were studied. In this study, ANFIS model with Gaussian membership function and fuzzy set combination of [4 5 2 3] was found to be the best method, with accuracy of 90.24% and 87.06% for training and testing dataset, respectively. Contribution of this study is that ANN, ANFIS, and MLR modeling techniques were used for the first time to study the adsorption of Cu (II) ions from aqueous solutions using rambutan peel biochar.
    Matched MeSH terms: Fuzzy Logic*
  11. Recent Advancements in Fuzzy C-means Based Techniques for Brain MRI Segmentation
    Latif G, Alghazo J, Sibai FN, Iskandar DNFA, Khan AH
    Curr Med Imaging, 2021;17(8):917-930.
    PMID: 33397241 DOI: 10.2174/1573405616666210104111218
    BACKGROUND: Variations of image segmentation techniques, particularly those used for Brain MRI segmentation, vary in complexity from basic standard Fuzzy C-means (FCM) to more complex and enhanced FCM techniques.

    OBJECTIVE: In this paper, a comprehensive review is presented on all thirteen variations of FCM segmentation techniques. In the review process, the concentration is on the use of FCM segmentation techniques for brain tumors. Brain tumor segmentation is a vital step in the process of automatically diagnosing brain tumors. Unlike segmentation of other types of images, brain tumor segmentation is a very challenging task due to the variations in brain anatomy. The low contrast of brain images further complicates this process. Early diagnosis of brain tumors is indeed beneficial to patients, doctors, and medical providers.

    RESULTS: FCM segmentation works on images obtained from magnetic resonance imaging (MRI) scanners, requiring minor modifications to hospital operations to early diagnose tumors as most, if not all, hospitals rely on MRI machines for brain imaging.

    CONCLUSION: In this paper, we critically review and summarize FCM based techniques for brain MRI segmentation.

    Matched MeSH terms: Fuzzy Logic*
  12. Fulltext Dynamics of fractional order nonlinear system: A realistic perception with neutrosophic fuzzy number and Allee effect
    Alam Khan N, Abdul Razzaq O, Riaz F, Ahmadian A, Senu N
    J Adv Res, 2021 09;32:109-118.
    PMID: 34484830 DOI: 10.1016/j.jare.2020.11.015
    Introduction: The fusion of fractional order differential equations and fuzzy numbers has been widely used in modelling different engineering and applied sciences problems. In addition to these, the Allee effect, which is of high importance in field of biology and ecology, has also shown great contribution among other fields of sciences to study the correlation between density and the mean fitness of the subject.

    Objectives: The present paper is intended to measure uncertain dynamics of an economy by restructuring the Cobb-Douglas paradigm of the renowned Solow-Swan model. The purpose of study is further boosted innovatively by subsuming the perception of logistic growth with Allee effect in the dynamics of physical capital and labor force.

    Methods: Fractional order derivative and neutrosophic fuzzy (NF) theory are applied on the parameters of the Cobb-Douglas equation. Distinctively, cogitating fractional order derivative to study the change at each fractional stage; single-valued triangular neutrosophic fuzzy numbers (SVTNFN) to cope the uncertain situations; logistic growth function with Allee effect to analyze the factors in natural way, are the significant and novel features of this endeavor.

    Results: The incorporation of the aforementioned theories and effects in the Cobb-Douglas equation, resulted in producing maximum sustainable capital investment and maximum capacity of labor force. The solutions in intervals located different possible solutions for different membership degrees, which accumulated the uncertain circumstances of a country.

    Conclusion: Explicitly, these notions add new facts and figures not only in the dynamical study of capital and labor, which has been overlooked in classical models, but also left the door open for discussion and implementation on classical models of different fields.

    Matched MeSH terms: Fuzzy Logic*
  13. Fulltext FuGeF: A Resource Bound Secure Forwarding Protocol for Wireless Sensor Networks
    Umar IA, Mohd Hanapi Z, Sali A, Zulkarnain ZA
    Sensors (Basel), 2016 Jun 22;16(6).
    PMID: 27338411 DOI: 10.3390/s16060943
    Resource bound security solutions have facilitated the mitigation of spatio-temporal attacks by altering protocol semantics to provide minimal security while maintaining an acceptable level of performance. The Dynamic Window Secured Implicit Geographic Forwarding (DWSIGF) routing protocol for Wireless Sensor Network (WSN) has been proposed to achieve a minimal selection of malicious nodes by introducing a dynamic collection window period to the protocol's semantics. However, its selection scheme suffers substantial packet losses due to the utilization of a single distance based parameter for node selection. In this paper, we propose a Fuzzy-based Geographic Forwarding protocol (FuGeF) to minimize packet loss, while maintaining performance. The FuGeF utilizes a new form of dynamism and introduces three selection parameters: remaining energy, connectivity cost, and progressive distance, as well as a Fuzzy Logic System (FLS) for node selection. These introduced mechanisms ensure the appropriate selection of a non-malicious node. Extensive simulation experiments have been conducted to evaluate the performance of the proposed FuGeF protocol as compared to DWSIGF variants. The simulation results show that the proposed FuGeF outperforms the two DWSIGF variants (DWSIGF-P and DWSIGF-R) in terms of packet delivery.
    Matched MeSH terms: Fuzzy Logic
  14. Fulltext Design and Implementation of Fuzzy Compensation Scheme for Temperature and Solar Irradiance Wireless Sensor Network (WSN) on Solar Photovoltaic (PV) System
    Pazikadin AR, Rifai D, Ali K, Mamat NH, Khamsah N
    Sensors (Basel), 2020 Nov 25;20(23).
    PMID: 33255797 DOI: 10.3390/s20236744
    Photovoltaic (PV) systems need measurements of incident solar irradiance and PV surface temperature for performance analysis and monitoring purposes. Ground-based network sensor measurement is preferred in many near real-time operations such as forecasting and photovoltaic (PV) performance evaluation on the ground. Hence, this study proposed a Fuzzy compensation scheme for temperature and solar irradiance wireless sensor network (WSN) measurement on stand-alone solar photovoltaic (PV) system to improve the sensor measurement. The WSN installation through an Internet of Things (IoT) platform for solar irradiance and PV surface temperature measurement was fabricated. The simulation for the solar irradiance Fuzzy Logic compensation (SIFLC) scheme and Temperature Fuzzy Logic compensation (TFLC) scheme was conducted using Matlab/Simulink. The simulation result identified that the scheme was used to compensate for the error temperature and solar irradiance sensor measurements over a variation temperature and solar irradiance range from 20 to 60 °C and from zero up to 2000 W/m2. The experimental results show that the Fuzzy Logic compensation scheme can reduce the sensor measurement error up to 17% and 20% for solar irradiance and PV temperature measurement.
    Matched MeSH terms: Fuzzy Logic
  15. Fulltext Autonomous Road Roundabout Detection and Navigation System for Smart Vehicles and Cities Using Laser Simulator-Fuzzy Logic Algorithms and Sensor Fusion
    Ali MAH, Mailah M, Jabbar WA, Moiduddin K, Ameen W, Alkhalefah H
    Sensors (Basel), 2020 Jul 01;20(13).
    PMID: 32630340 DOI: 10.3390/s20133694
    A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator-fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. A wheeled mobile robot (WMR) is supposed to navigate autonomously on the road in real-time and reach a predefined goal while discovering and detecting the road roundabout. A complete modeling and path planning of the road's roundabout intersection was derived to enable the WMR to navigate autonomously in indoor and outdoor terrains. A new algorithm, called Laser Simulator, has been introduced to detect various entities in a road roundabout setting, which is later integrated with fuzzy logic algorithm for making the right decision about the existence of the roundabout. The sensor fusion process involving the use of a Wi-Fi camera, laser range finder, and odometry was implemented to generate the robot's path planning and localization within the road environment. The local maps were built using the extracted data from the camera and laser range finder to estimate the road parameters such as road width, side curbs, and roundabout center, all in two-dimensional space. The path generation algorithm was fully derived within the local maps and tested with a WMR platform in real-time.
    Matched MeSH terms: Fuzzy Logic
  16. Fulltext Robust H∞-Fuzzy Logic Control for Enhanced Tracking Performance of a Wheeled Mobile Robot in the Presence of Uncertain Nonlinear Perturbations
    Ahmad NS
    Sensors (Basel), 2020 Jun 30;20(13).
    PMID: 32630046 DOI: 10.3390/s20133673
    Motion control involving DC motors requires a closed-loop system with a suitable compensator if tracking performance with high precision is desired. In the case where structural model errors of the motors are more dominating than the effects from noise disturbances, accurate system modelling will be a considerable aid in synthesizing the compensator. The focus of this paper is on enhancing the tracking performance of a wheeled mobile robot (WMR), which is driven by two DC motors that are subject to model parametric uncertainties and uncertain deadzones. For the system at hand, the uncertain nonlinear perturbations are greatly induced by the time-varying power supply, followed by behaviour of motion and speed. In this work, the system is firstly modelled, where correlations between the model parameters and different input datasets as well as voltage supply are obtained via polynomial regressions. A robust H ∞ -fuzzy logic approach is then proposed to treat the issues due to the aforementioned perturbations. Via the proposed strategy, the H ∞ controller and the fuzzy logic (FL) compensator work in tandem to ensure the control law is robust against the model uncertainties. The proposed technique was validated via several real-time experiments, which showed that the speed and path tracking performance can be considerably enhanced when compared with the results via the H ∞ controller alone, and the H ∞ with the FL compensator, but without the presence of the robust control law.
    Matched MeSH terms: Fuzzy Logic
  17. Fulltext Development of closed-loop supply chain network in terms of corporate social responsibility
    Pedram A, Pedram P, Yusoff NB, Sorooshian S
    PLoS One, 2017;12(4):e0174951.
    PMID: 28384250 DOI: 10.1371/journal.pone.0174951
    Due to the rise in awareness of environmental issues and the depletion of virgin resources, many firms have attempted to increase the sustainability of their activities. One efficient way to elevate sustainability is the consideration of corporate social responsibility (CSR) by designing a closed loop supply chain (CLSC). This paper has developed a mathematical model to increase corporate social responsibility in terms of job creation. Moreover the model, in addition to increasing total CLSC profit, provides a range of strategic decision solutions for decision makers to select a best action plan for a CLSC. A proposed multi-objective mixed-integer linear programming (MILP) model was solved with non-dominated sorting genetic algorithm II (NSGA-II). Fuzzy set theory was employed to select the best compromise solution from the Pareto-optimal solutions. A numerical example was used to validate the potential application of the proposed model. The results highlight the effect of CSR in the design of CLSC.
    Matched MeSH terms: Fuzzy Logic
  18. Fulltext Design of perfect tracking self-tuning fuzzy PID controller with reference model
    Nur Sakinah Abdul Aziz, Mazidah Tajjudin, Ramli Adnan
    Pertanika Journal of Science & Technology, 2017;25(107):179-188.
    MyJurnal
    Fuzzy Logic is a popular method to tune a PID controller. By using Fuzzy Logic, the PID is tuned automatically based on information of output error, which is better than other tuning rule methods. Fuzzy Logic Control will tune gains of PID controller by using a set of fuzzy rules designed specifically for that. However, specific transient requirements of the process output cannot be assigned to the controller. This research proposes a new method to overcome this problem by using a reference model. Step input from the reference model that contains the desired response information will be compared against the actual output. The reference model can be pre-selected by the user as desired. This study was simulated on a steam temperature process model while few sets of first-order model were used as reference. The results showed that the proposed Fuzzy PID controller with reference model provides better performance with perfect tracking during transient and steady-state.
    Matched MeSH terms: Fuzzy Logic
  19. Fulltext DC-link capacitor voltage regulation with effort-reduction fuzzy logic control for three-level inverter-based shunt active power filter
    Nashiren Farzilah, Mailah, Yap Hoon, Mohd Amran, Mohd Radzi
    Pertanika Journal of Science & Technology, 2017;25(102):11-20.
    MyJurnal
    Shunt active power filter (SAPF) is the most effective solution for current harmonics. In its controller, DC-link capacitor voltage regulation algorithm with either proportional-integral (PI) or fuzzy logic control (FLC) technique has played a significant role in maintaining a constant DC voltage across all the DC-link capacitors. However, PI technique performs poorly with high overshoot and significant time delay under dynamic state conditions, as its parameters are difficult to be tuned without requiring complete knowledge of the designated system. Although FLC technique has been developed to overcome limitations of PI technique, it is mostly developed with high complexity thereby increases computational burden of the designed controller. This paper presents a fuzzy-based DC-link capacitor voltage regulation algorithm with reduced computational efforts to enhance performance of three-phase three-level neutralpoint diode clamped (NPC) inverter-based SAPF in overall DC-link voltage regulation. The proposed method is called effort-reduction FLC technique. The proposed algorithm is developed and evaluated in MATLAB-Simulink. Moreover, conventional algorithm with PI technique is tested for comparison purposes. Simulation results have confirmed improvement achieved by the proposed algorithm in comparison to the conventional algorithm.
    Matched MeSH terms: Fuzzy Logic
  20. Fulltext A Novel Eddy Current Testing Error Compensation Technique Based on Mamdani-Type Fuzzy Coupled Differential and Absolute Probes
    Abdalla AN, Ali K, Paw JKS, Rifai D, Faraj MA
    Sensors (Basel), 2018 Jun 30;18(7).
    PMID: 29966367 DOI: 10.3390/s18072108
    Eddy current testing (ECT) is an accurate, widely used and well-understood inspection technique, particularly in the aircraft and nuclear industries. The coating thickness or lift-off will influence the measurement of defect depth on pipes or plates. It will be an uncertain decision condition whether the defects on a workpiece are cracks or scratches. This problem can lead to the occurrence of pipe leakages, besides causing the degradation of a company’s productivity and most importantly risking the safety of workers. In this paper, a novel eddy current testing error compensation technique based on Mamdani-type fuzzy coupled differential and absolute probes was proposed. The general descriptions of the proposed ECT technique include details of the system design, intelligent fuzzy logic design and Simulink block development design. The detailed description of the proposed probe selection, design and instrumentation of the error compensation of eddy current testing (ECECT) along with the absolute probe and differential probe relevant to the present research work are presented. The ECECT simulation and hardware design are proposed, using the fuzzy logic technique for the development of the new methodology. The depths of the defect coefficients of the probe’s lift-off caused by the coating thickness were measured by using a designed setup. In this result, the ECECT gives an optimum correction for the lift-off, in which the reduction of error is only within 0.1% of its all-out value. Finally, the ECECT is used to measure lift-off in a range of approximately 1 mm to 5 mm, and the performance of the proposed method in non-linear cracks is assessed.
    Matched MeSH terms: Fuzzy Logic
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