中文说明：
针对滚动轴承早期故障特征提取困难的问题，提出一种基于参数优化变分模态分解的轴承早期故障诊断方法。首先利用粒子群优化算法对变分模态分解算法的最佳影响参数组合进行搜索，搜索结束后根据所得结果设定变分模态分解算法的惩罚参数和分量个数，并利用参数优化变分模态分解算法对故障信号进行处理。
English Description：
Aiming at the difficulty of feature extraction for early fault of rolling bearing, a method of bearing early fault diagnosis based on parameter optimization variational mode decomposition is proposed. Firstly, the particle swarm optimization algorithm is used to search the best combination of influence parameters of the variational mode decomposition algorithm. After the search, the penalty parameters and the number of components of the variational mode decomposition algorithm are set according to the results, and the fault signal is processed by the parameter optimization variational mode decomposition algorithm