Automatic Adjustment Method for Rotor Dynamic Balance System

This paper aims to develop an automatic adjustment method (AAM) that integrates 3D sensor and dynamic balancing platform using 3D computer vision technology and dynamic balance algorithm to improve the efficiency of rotor dynamic balancing. Active rotor dynamic balancing process relies on technicians to mount washers on particular balance columns based on their experience, therefore uncertainty causes productivity decline. The proposed AAM introduce 3D sensors on active rotor dynamic balance machine to get 3D point cloud of rotor and balance columns. First, by 3D depth data, the background noise can be removed to detect the positions of axis center, key phasor and balance columns of rotor automatically. Second, combine with unbalance vector from dynamic balancing machine, the AAM system calculated the optimal balance configuration by the vector analysis algorithm. Experiments in industrial examples showed that, compared to conventional method, the proposed AAM requires fewer rounds to achieve acceptance. In contrast, the industrial rotor balancing method previously used by operators requires more than three rounds in average. That is, the proposed AAM can accurately analyze the dynamic balance and greatly reduce the redundant dynamic balance operations. In conclusion, compared to the conventional approach, the proposed AAM is superior in terms of efficiency, effectiveness and robustness in online optimization of rotor dynamic balance. Notably, the effectiveness of the AAM has also been confirmed by Taiwan manufacturers that use rotor dynamic balance machines.