The invention relates to a chemical system multi-working-condition fault detection method based on local adaptive standardization and belongs to the technical field of chemical process monitoring, industrial data processing and process system engineering. According to the method, a local adaptive standardization method is provided, the variational automatic encoder technology of the deep neural network is applied, an average value of the data in the local moving window is calculated to serve as an average value parameter of local adaptive standardization, different average values are used fordifferent data, and the adaptive capacity is achieved. The method is advantaged in that local adaptive standardization processing is utilized, and fault detection is carried out by detecting whether the data in a local moving window deviates or not, and the method can be suitable for any working condition, has higher accuracy and stronger generalization ability, can meet the requirement of real-time detection, and avoids chemical accidents or reduces the harm caused by accidents through early warning of faults.