Deep learning data prediction method for sintering process of rotary cement kiln

• Main Authors: KONG YAGUANG, BAI JIANJUN, ZHANG RIDONG, REN YANWEI
• Format: Patent
• Language: Chinese; English
• Published: 10.10.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a deep learning data prediction method for the sintering process of a rotary cement kiln. The method comprises the following steps: firstly, collecting data of a sensor in the sintering process of the rotary cement kiln, and preprocessing the data; secondly, constructing a novel prediction network, and predicting the preprocessed data; and then collecting newly obtained process data in the sintering process of the rotary cement kiln. And finally, predicting newly collected data by using the prediction model. According to the method, the defects that a traditional prediction model is complex in modeling process and cannot process nonlinear data are overcome, and the real data tracking capacity of the model is improved. 本发明公开了一种水泥回转窑烧成过程的深度学习数据预测方法。本发明首先采集水泥回转窑烧成过程中传感器的数据，对数据进行预处理。其次构建新型预测网络，对预处理的数据进行预测。然后采集水泥回转窑烧成过程中新得到的过程数据。最后使用预测模型对新采集到的数据进行预测。本发明改善了传统预测模型建模过程复杂，无法处理非线性数据的缺点，提高了模型跟踪真实数据的能力。