Research on efficiency prediction method of reciprocating air compressor based on digital twin technology
The method for compressor efficiency prediction and parameter optimization by establishing the reciprocating air compressor digital twin model has the advantage of flexibility,low cost,and good versa-tility.However,the traditional twin model based on the BP neural network(BPNN)has lots of shortcom-ings,such as longer training time to establish a module,easily falling into the local optimal solution,and difficulty in achieving the global optimal solution.To solve these problems,a novel digital twin model based on the CIWOA-BPNN algorithm is put forward to determine the key indexes by the principal compo-nent analysis method,in which a CIWOA algorithm is introduced to improve the BPNN's performance.The results show that the new CIWOA-BPNN twin model effectively avoids falling the local optimal prob-lem.The relative error of CIWOA-BPNN is less than 0.6％,and the coefficient of determination is 0.997 75,which greatly improves the prediction accuracy compared with the traditional model.
reciprocating air compressorefficiencyBP neural networkimproved whale optimization al-gorithm
万方数据
维普
