Smart Electromagnetic Sensor for Buried Conductive Targets Identification

In this paper, the authors introduce the evolution of an eddy current sensor based on the induction balance principle. Its objective is to localize and identify the various types of buried pipelines like gas and water without excavation. Starting from an analogical version of the sensor, they use modeling to increase its sensitivity. The modeling is realized using a distributed point source method, which gives us rather interesting results. Based on these, the authors describe the hardware and the different electronic parts which composes the detector. They present the second generation of the sensor and the different changes added to improve its performances. Two coding systems are associated to the sensor. It gives an important number of targets (tags) necessary to the application. Each kind of pipe type is associated with a characteristic tag integrating conductive elements. The identification of the tag allows the recognition of the corresponding pipe. The response of the buried tag can be disrupted by the presence of metallic objects in the neighborhood. To eliminate their effects, they use blind-source-separation algorithms. This represents the preprocessing step followed by signal processing software. There are many algorithms used to recognize buried tags. These are based on different principles like neural networks, fuzzy logic, or structural recognition. The multiplicity of the number of algorithms is necessary to surpass the difficult identification and drives us to use an original method of the combination of results, trying to increase the reliability of the final decision. Finally, the authors focus on the sensor evaluation and considered prospects