The Ripple Effect and Nonlinear Error Comprehensive Correction of the Hall Voltage Sensor
Ran Xu · Chuangan jishu xuebao · 2008
Some of Hall voltage mutual inductors have serious error caused by ripple effect etc when DC voltage with HF harmonic is measured. In the face of this question, a sort of error comprehensive correcting method which is based on information fusion technology of the neural network is presented. On this way , the ripple voltage character parameter is picked-up directly from output signal of voltage sensor and the added sensor is not need. Regarding the ripple voltage as no-target parameter and input voltage as target parameter and ideal output as target value, an artificial neural network (ANN) is structured and trained. The weights and offsets of each layer are obtained after training the ANN. The simulating experimental results demonstrate that ANN can approach to a correcting plane and solve preferably the error -correction question of the Hall voltage sensor.