Displaying all 2 publications

Abstract:
Sort:
  1. Salama A, Malekmohammadi A, Mohanna S, Rajkumar R
    Int J Biomed Imaging, 2017;2017:3589324.
    PMID: 29225613 DOI: 10.1155/2017/3589324
    This paper presents a multitasking electrical impedance tomography (EIT) system designed to improve the flexibility and durability of an existing EIT system. The ability of the present EIT system to detect, locate, and reshape objects was evaluated by four different experiments. The results of the study show that the system can detect and locate an object with a diameter as small as 1.5 mm in a testing tank with a diameter of 134 mm. Moreover, the results demonstrate the ability of the current system to reconstruct an image of several dielectric object shapes. Based on the results of the experiments, the programmable EIT system can adapt the EIT system for different applications without the need to implement a new EIT system, which may help to save time and cost. The setup for all the experiments consisted of a testing tank with an attached 16-electrode array made of titanium alloy grade 2. The titanium alloy electrode was used to enhance EIT system's durability and lifespan.
  2. Akram NA, Isa D, Rajkumar R, Lee LH
    Ultrasonics, 2014 Aug;54(6):1534-44.
    PMID: 24792683 DOI: 10.1016/j.ultras.2014.03.017
    This work proposes a long range ultrasonic transducers technique in conjunction with an active incremental Support Vector Machine (SVM) classification approach that is used for real-time pipeline defects prediction and condition monitoring. Oil and gas pipeline defects are detected using various techniques. One of the most prevalent techniques is the use of "smart pigs" to travel along the pipeline and detect defects using various types of sensors such as magnetic sensors and eddy-current sensors. A critical short coming of "smart pigs" is the inability to monitor continuously and predict the onset of defects. The emergence of permanently installed long range ultrasonics transducers systems enable continuous monitoring to be achieved. The needs for and the challenges of the proposed technique are presented. The experimental results show that the proposed technique achieves comparable classification accuracy as when batch training is used, while the computational time is decreased, using 56 feature data points acquired from a lab-scale pipeline defect generating experimental rig.
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links