Development of a multiprobe electrical resistivity tomography prototype system and robust underground clustering

Development of a multiprobe electrical resistivity tomography prototype system and robust underground clustering

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Article ID: iaor20172022
Volume: 34
Issue: 3
Publication Date: Jun 2017
Journal: Expert Systems
Authors: ,
Keywords: Turkey, sensor networks, tomography, sensors, electrical engineering, fuzzy clustering, geology
Abstract:

This study reports a 24‐probe electrical resistivity tomography (ERT) prototype system and its empirical evaluation in a case study setting. The system was designed using the Wenner soil resistivity measurement method. The performance and outputs of the approach and the developed prototype system were assessed and approved by the General Directorate of Mineral Research and Exploration of Turkey. This study is also supported by the Republic of Turkey Ministry of Science, Industry and Technology through the project ‘Distinguishing of Metallic Targets (code number is 1064.STZ.2011‐2).’ The state of the art of this study is multiprobe ERT, which has a touchscreen for ease of use and improved measurement accuracy for minimizing RMS (root mean square) error using a 16‐bit ADC. Similar to other ERT systems, the prototype system that we have developed allows the user to change the current and probe interval via the touchscreen user interface. In addition to this system, a new fuzzy clustering algorithm named robust colored image fuzzy C‐mean was developed in this study. The robust colored image fuzzy C‐mean performs underground clustering in RGB colors, which provides improved clustering results compared to those of the conventional fuzzy C‐mean clustering algorithm.

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