基于贝叶斯诊断理论的航空发动机燃气涡轮机故障原因分析  

Analysis of Malfunction Causes of Aerial Engine Gas Turbine Based on Bayesian Diagnosis Theory

作　　者：王晓钢[1] 刘振岗[1] 邹刚[1] 范兴[1] 刘治国[1] 郭刚[1] 

机构地区：[1]海军航空工程学院青岛校区航空机械系,山东青岛266041

出　　处：《西安航空学院学报》2016年第1期3-6,共4页Journal of Xi’an Aeronautical Institute

摘　　要：将贝叶斯数值理论应用到航空发动机燃气涡轮机的故障诊断过程中,通过建立燃气涡轮机贝叶斯数值诊断理论模型,计算出系统所表现出的故障征兆对故障成因的概率,利用状态识别极限法则,来判定涡轮机系统所处的工作状态。经过长期实践验证,此方法具有良好的故障诊断、识别效果,有效提高了该型燃气涡轮机故障诊断过程中不确定性信息处理的能力及推理的质量。Bayesian numerical theory is applied to the malfunction diagnosis process of aerial starter motor gas turbine in this text .The numerical theory model of Bayesian malfunction diagnosis of gas turbine is es‐tablished .The probability of malfunction foreboding that shows to the cause of system is calculated ,and the status identification extreme rule is utilized to judge the working status of the turbine engine system . The long‐time outfield practice verifies that this method is effective in malfunction diagnosis and identifica‐tion ,and increasing the uncertainly information disposal competence and inferential quality of motor starter gas turbine malfunction diagnose process .

关 键 词：航空发动机 燃气涡轮机 贝叶斯理论 故障诊断 

分 类 号：V263.6[航空宇航科学与技术—航空宇航制造工程]