Deterioration Assessment of Infrastructure Using Fuzzy Logic and Image Processing Algorithm

2018 ◽  
Vol 32 (2) ◽  
pp. 04018009 ◽  
Author(s):  
Haran Pragalath ◽  
Sankarasrinivasan Seshathiri ◽  
Harsh Rathod ◽  
Balasubramanian Esakki ◽  
Rishi Gupta
2019 ◽  
Vol 52 (9-10) ◽  
pp. 1517-1531 ◽  
Author(s):  
Faisal Mehmood ◽  
Zeeshan Haider ◽  
Umar Farooq ◽  
Yin Baoqun

Most of the research studies nowadays are trying to bring automation to biomedical engineering and Lab on a Chip which is fast growing interdisciplinary field and has attracted researchers from various fields. The objective of this paper is to present an overall system to control droplet movement inside microfluidic channel using fuzzy logic controller, image processing algorithm, and microvalves installed within microfluidic channel. A state space model has been derived from circuit analogy approach to describe the microfluidic network. Furthermore, a COMSOL-based study is primed for device structure by means of droplet generation and controlling the droplet through fitted valves. Moreover, an image processing algorithm based on active contours has been proposed in this research to track the movement of the droplet through the channel. This droplet controlling method is utterly based on fuzzy controller as well as camera images to move the droplet at desired position by controlling flow rates inside the fluidic channel using valves installed inside the microfluidic device. The results indicate that the fuzzy logic controller performs much better in terms of stability and faster response as compared to conventional proportional–integral–derivative controller.


2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Soo Hyun Park ◽  
Sang Ha Noh ◽  
Michael J. McCarthy ◽  
Seong Min Kim

AbstractThis study was carried out to develop a prediction model for soluble solid content (SSC) of intact chestnut and to detect internal defects using nuclear magnetic resonance (NMR) relaxometry and magnetic resonance imaging (MRI). Inversion recovery and Carr–Purcell–Meiboom–Gill (CPMG) pulse sequences used to determine the longitudinal (T1) and transverse (T2) relaxation times, respectively. Partial least squares regression (PLSR) was adopted to predict SSCs of chestnuts with NMR data and histograms from MR images. The coefficient of determination (R2), root mean square error of prediction (RMSEP), ratio of prediction to deviation (RPD), and the ratio of error range (RER) of the optimized model to predict SSC were 0.77, 1.41 °Brix, 1.86, and 11.31 with a validation set. Furthermore, an image-processing algorithm has been developed to detect internal defects such as decay, mold, and cavity using MR images. The classification applied with the developed image processing algorithm was over 94% accurate to classify. Based on the results obtained, it was determined that the NMR signal could be applied for grading several levels by SSC, and MRI could be used to evaluate the internal qualities of chestnuts.


1995 ◽  
Vol 11 (5) ◽  
pp. 751-757 ◽  
Author(s):  
J. A. Throop ◽  
D. J. Aneshansley ◽  
B. L. Upchurch

2011 ◽  
Vol 36 (1) ◽  
pp. 48-57 ◽  
Author(s):  
Kwang-Wook Seo ◽  
Hyeon-Tae Kim ◽  
Dae-Weon Lee ◽  
Yong-Cheol Yoon ◽  
Dong-Yoon Choi

2017 ◽  
Vol 5 (1) ◽  
pp. 28-42 ◽  
Author(s):  
Iryna Borshchova ◽  
Siu O’Young

Purpose The purpose of this paper is to develop a method for a vision-based automatic landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving platform. The landing system must be highly accurate and meet the size, weigh, and power restrictions of a small UAV. Design/methodology/approach The vision-based landing system consists of a pattern of red markers placed on a moving target, an image processing algorithm for pattern detection, and a servo-control for tracking. The suggested approach uses a color-based object detection and image-based visual servoing. Findings The developed prototype system has demonstrated the capability of landing within 25 cm of the desired point of touchdown. This auto-landing system is small (100×100 mm), light-weight (100 g), and consumes little power (under 2 W). Originality/value The novelty and the main contribution of the suggested approach are a creative combination of work in two fields: image processing and controls as applied to the UAV landing. The developed image processing algorithm has low complexity as compared to other known methods, which allows its implementation on general-purpose low-cost hardware. The theoretical design has been verified systematically via simulations and then outdoors field tests.


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