To address the issue of interdimensional coupling interference in three-dimensional vibration acceleration sensors, this paper focuses on the spatial layered structure fiber bragg grating (FBG) three-dimensional vibration acceleration sensor. It outlines the basic principle of three-dimensional vibration acceleration sensing. An experimental platform for dynamic calibration of the vibration acceleration is constructed, and the structural coupling characteristics of the sensor are analyzed. A neural network model based on the whale optimization algorithm and extreme learning machine (WOA-ELM) is proposed for non-linear decoupling experiments. The results show that the average measurement errors in the x, y, and z axes are reduced to 1. 58% , 1. 17% , and 0. 17% , respectively. Additionally, the maximum values of the average class I and class II errors are reduced to 0. 73% and 0. 37% , respectively. The decoupling effect of the WOA-ELM is compared with other algorithms, and the results demonstrate that WOA-ELM is more effective in reducing inter-dimensional coupling interference in the three-dimensional vibration accelerometer sensor, thereby improving measurement accuracy.