Wastewater lifting pumps are the key equipment of municipal wastewater treatment plants, the normal operation of which directly affects the economic benefit. In order to ensure the normal operation of municipal wastewater treatment plants, how to realize the accurate early warning of wastewater lifting pumps is a difficult problem. Aiming at this problem, an intelligent early warning method based on a fuzzy neural network model and a current time series model is proposed in this paper. Firstly, by selecting the feature data related to the early warning, the fuzzy neural network model is constructed. Then, the isolated fault probability of the wastewater lifting pumps for each data point is obtained; Secondly, the current time series model of wastewater lifting pumps is established based on the changing rate of the feature parameters. Then, the time series fault probability of each data point is obtained; Thirdly, the final fault probability is obtained through the weighted fusion of the two types of fault probability predicted by FNN and current time series model, and then the fault warning of wastewater lift pumps is carried out. Finally, the proposed method is applied to the early warning of wastewater lifting pumps with different flow rates in municipal wastewater treatment plants. The experimental results show that the proposed method can realize accurate early warning, and the accuracy performance is higher than those of the comparison algorithms.