Abstract Fracture healing is a complicated process, research shows that the stress environment of traumatic section is one of the main factors that affect the quality and speed of fracture healing. In order to guarantee the quality and speed of fracture healing, it is necessary to predict the stress and its variation tendency dynamically and accurately in the course of fracture healing, so that the applied force from fracture treatment device on traumatic section can be immediately adjusted. In allusion to the low predictive precision problem of existing stress predictive methods, this paper proposed a dynamic method for predicting fracture healing stress based on weakening buffer operator and equal-dimension-new-information GM (1,1) model. This method in first step used the role of weakening buffer operator for actual measured stress data, and then built the predictive model of weakening processed stress data sequence by using GM (1,1) equaldimension-new-information model. Testing experiments were conducted in goat fracture models, and the daily average stress on trauma section in the course of fracture healing was obtained. Experimental results showed that the predictive precision was 40 times of that obtained from the method based on GM (1,1) equal-dimension-new-information model.
