流体机械2024，Vol.52Issue(4)：87-94,8.DOI:10.3969/j.issn.1005-0329.2024.04.013
基于灰色关联机理组合模型的压缩机电功率预测
Prediction of compressor electric power based on gray relational mechanism combination model
摘要
Abstract
In order to accurately obtain the compressor electric power,the GRM(1,m)-Mechanism combination prediction model was established using Matlab language through the experimental bench for the variable frequency rolling rotor refrigeration system according to the characteristics of the(GRM(1,m))prediction model such as low sample demand for gray correlation,high prediction accuracy and its ability to reflect the system essential characteristics.The compressor electric power was predicted by these three models respectively.The results show that the GRM(1,m)-Mechanism combination prediction model has better prediction accuracy and applicability than two other models.Its maximum relative error and average relative error were 4.05%and 1.71%respectively,which were 1.29%and 1.09%lower than that of the Mechanism model,and 1.02%and 2.19%lower than that of the gray correlation(GRM(1,m))prediction model.Finally,the average relative error of combination prediction model was verified to be within 1.9%by the compressor variable speed experiments,which further proved the accuracy and applicability of the GRM(1,m)-Mechanism model.关键词
变频滚动转子/电功率/灰色关联/机理/预测Key words
variable frequency rolling rotor/electrical power/gray relational/mechanism/prediction分类
机械制造引用本文复制引用
程哲铭,陶乐仁,黄理浩,章轻歌..基于灰色关联机理组合模型的压缩机电功率预测[J].流体机械,2024,52(4):87-94,8.基金项目
国家高科技研究发展计划项目(2008AA05Z204) （2008AA05Z204）
上海市动力工程多相流动与传热重点实验室开放基金项目(13DZ2260900) （13DZ2260900）
