The invention discloses a complex industrial process fault monitoring method based on OICA, The invention is used for improving the accuracy of industrial process fault monitoring and has important significance in improving the safety of a production process to ensure the safety of production equipment and production personnel and improving the product quality. The method comprises two stages of off-line modeling and on-line monitoring. The step of off-line modeling comprises the following steps: preprocessing original data; extracting independent main components and residual errors of the data by adopting OICA; and calculating a control limit through kernel density estimation in the independent component space and the residual space respectively. The step of on-line monitoring comprises the following steps: preprocessing data at the current sampling moment; and calculating the statistics of the data at the current moment, and comparing the statistics with the control limit to judge whether the fermentation process runs normally. The method does not need to assume that data obeys Gaussian distribution, is low in calculation complexity, and is not limited by a hybrid matrix form, sothat the fault monitoring effect is better.