Simulation Research on Exploiting Electrostatic Potential Difference Sensing for Shaft Centerline Orbit Reconstruction

To realize the non-contact measurement of the rotational shaft centerline orbit, a shaft centerline orbit reconstruction method using a specifically designed electrostatic sensor in conjunction with the neural network approximator is proposed in this paper. The sensing principle of the designed electrostatic sensor is based on the partial capacitance theory. The proposed sensor consists of one electrostatic field excitation electrode, two sensing electrodes, and a cylindrical metal shield covering the three electrodes. It directly establishes the map from the sensor output (voltages between sensing electrodes and shield) to shaft center position through the neural network approximator so that the shaft centerline orbit can be reconstructed. The CAE software COMSOL Multiphysics is used for sensor modeling and simulation analysis. The simulation reconstruction experiment is carried out to test the performance of the proposed sensor and to obtain training data for the neural network. The experiment result shows that the RMS error of the proposed sensor is within 0.4 μm, which has proved the feasibility of the novel sensor combined with the neural network fitting algorithm for industrial applications.