摘要
针对涡桨发动机复杂、非线性的工作环境,利用层次分析(AHP)法提取发动机工作状态特征参数,考虑各特征参数对工作状态识别的影响,以特征参数加权的改进蚁群算法为基础,进行发动机同一工作状态识别、聚类,并采用Mann-Kendall法开展发动机性能预测分析。利用多台涡桨发动机性能参数飞参数据进行验证,结果表明:该方法能准确识别发动机起飞、额定工作状态,巡航以下工作状态识别准确率达84%以上;此外,发动机性能预测效率提升了近50%,而预测错误率小于10%,可以满足航空兵部队维修保障工作的实际需要。
For the complex nonlinear environment of turboprop engine, the AHP(analytic hierarchy process)method was used to extract the operating condition characteristic parameters.To solve the same operating condition recognition and performance prediction problem,the influence of each characteristic parameter on the operating condition recognition was also considered,the improved ant colony algorithm for the weighted characteristic parameters was developed with the use of Mann-Kendall method. The verification results of performance parameter flight data of some turboprop engines showed that the method accurately identified the take-off and rated condition,with the identification accuracy for the operating condition below cruise amounting to more than 84%;the predicted performance efficiency boosted over some 50% as the predicted error rate was under 10%. In this sense, the method can be used as maintenance support for the air force.
作者
王佳
王博
WANG Jia;WANG Bo(Unit 95580,People's Liberation Army,Guiyang 550031,China)
出处
《航空动力学报》
EI
CAS
CSCD
北大核心
2022年第6期1306-1313,共8页
Journal of Aerospace Power
