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The Design and Implementation of an ANN-based Non-linearity Compensator of LVDT Sensor

Linear variable differential transformer (LVDT) sensors are used in engineering applications due to their fine-grained measurements. However, these sensors exhibit non-linear input-output characteristics, which decrease the reliability of the sensing system. The contribution of this article is three-fold. First, it provides an experimental study of the non-linearity problem of the LVDT. Second, it proposes the design of a functional link artificial neural network (FLANN) based non-linearity compensator model for overcoming it. Finally, it validates the feasibility of the solution in simulation, and presents a proof-of-concept hardware implementation on a SPARTAN-II (PQ208)FPGA using VHDL in Xilinx. The model has been mathematically derived, and its simulation study has been presented that achieves nearly 100% linearity range. The result obtained from the FPGA implementation is in good agreement with the simulation result, which establishes its actualization as part of a general manufacturing process for linearity compensated LVDT sensors.

preprint2014arXivOpen access

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