文章摘要
张亮,吴闯,唐希浪,冯少林.航空发动机故障实体识别方法及应用[J].空军工程大学学报:自然科学版,2022,23(2):1-6
航空发动机故障实体识别方法及应用
A Method of Recognizing Aero Engine Fault Entity and Its Application
  
DOI:
中文关键词: 航空发动机  智能故障诊断  实体识别  知识图谱
英文关键词: aero-engine  intelligent fault diagnosis  entity recognition  knowledge map
基金项目:中国博士后科学基金(2021M693941)
作者单位
张亮,吴闯,唐希浪,冯少林 1.空军工程大学装备管理与无人机工程学院西安710051 2.95478部队重庆401329 
摘要点击次数: 140
全文下载次数: 177
中文摘要:
      故障实体识别是自主获取航空发动机故障知识的基础,对实现航空发动机故障智能诊断起到至关重要的作用。为准确快速搭建航空发动机大规模故障知识库,在定义了“单元”“故障状态”“表征信号”“检查方法”和“解决措施”5种航空发动机故障实体类型的基础上,初步构建了一种以Bert BiLSTM CRF模型为基础的航空发动机故障实体识别方法。基于某型航空发动机大规模数据集分析抽取了故障实体,搭建了滑油压力异常故障知识图谱,验证了该方法识别航空发动机多源异构故障数据的有效性。
英文摘要:
      Fault entity recognition is a basis of obtaining the knowledge of aero engine fault autonomously, which plays an important role in realizing the intelligent fault diagnosis of aero engine. For building up fleetly accurately aero engine fault knowledge base, on the basis of the five kinds of aero engine fault entity type defined, i.e. “unit”, “state failure”, “characterization of signals”, “inspection methods” and “solution”, a kind of Bert BiLSTM CRF model of aero engine fault entity recognition method preliminary is constructed. Based on the large scale data set analysis of an aero engine, fault entities are extracted and fault knowledge map of abnormal oil pressure is constructed, verifying the effectiveness of the proposed method in identifying heterogeneous fault data of aero engine
查看全文   查看/发表评论  下载PDF阅读器
关闭