Dioxin emission prediction for municipal solid waste incineration process with multi-window combination detection
Dioxin(DXN)is a highly toxic pollutant emitted from municipal solid waste incineration(MSWI),which is difficult to be detected in real time.The time-varying characteristics of the MSWI process leads to a decrease in the online prediction performance of the soft-sensor model.Aiming at the above problems,this paper proposes a method of DXN emission prediction with multi-window combination detection.Firstly,combined the data standardization window and the online prediction window enables DXN emission prediction for new samples,and the outlier detection window,the feature detection space window and the output space detection window are combined to realize the identification of drifting samples.Then,the detected drift samples are combined and removed duplicates,and whether the number of drift sample sets reaches the pre-set threshold is judged.If it reaches,the new models are constructed,otherwise the historical model is to be used continuously.Finally,the real industrial process data are used to verify the effectiveness of the proposed method.
municipal solid waste incineration(MSWI)dioxin(DXN)emission predictionmulti-window detectionconcept driftmodel update
万方数据
维普
