Cantilever beam structure multi-objective optimization method based on Hall effect type tension sensor

The invention relates to the technical field of tension detection, and discloses a GPR-NSGA-II-based Hall effect tension sensor cantilever beam structure multi-objective optimization method, which comprises the following steps of: establishing a finite element model, constructing the finite element model according to a part material and specific structure parameters of a tension sensor cantilever beam structure, calculating a model numerical value, and calculating the tension sensor cantilever beam structure according to the model numerical value. And carrying out grid division on the established finite element model. According to the GPR-NSGA-II-based multi-objective optimization method for the cantilever beam structure of the Hall effect type tension sensor, sample points are selected through an optimal Latin hypercube sampling method, and compared with common Latin hypercube sampling, the sample points can be uniformly distributed in a sample space, so that the performance of a trained GPR model is ensured