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Magneto-electric encoders have been widely used in industry and military applications because of their good shock resistance, small volume, and convenient data processing. However, the characteristics of a magneto-electric encoder’s signal generator and hall sensor changes minimally with temperature variation. These changes cause an angle drift. The main purpose of this study is to construct the compensation system of a neural network and constantly update weight coefficients of temperature correction by finite iteration calculation so that the angle value modified can approach the angle value at the target temperature. This approach is used in adaptive correction of the angle value.

Study on the Temperature Drift Adaptive Compensation Algorithm of a Magneto-Electric Encoder Based on a Simple Neuron