Calibration study of force-balanced micro accelerometer based on least squared method and genetic algorithm

The force-balanced micro accelerometer is selected to study the calibration in MEMS sensors. The fabrication and test of accelerometer are presented, the test data is calibrated by least squared method and genetic algorithm in cubic function, and the results are compared to study characteristics of calibration on different methods. The advantage of least squared method is the distribution of residual error is relative uniform and the sum of errors is relative small, and drawback is this type of calibration can't be carried out on special demands; and the genetic algorithm can be carried out under any requirements, but its calibration time is longer than least squared method, and its precision depends on the iterative generations.