航空发动机转子不平衡量突增的自动识别

为实现在航空发动机振动信号分析时因封严胶条脱落发生的转子不平衡量突增的自动识别，采用多傅里叶变换（FFT）滤波技术获得转速跟踪滤波后的基频振动时域信号，提出了振幅突增和突增后振幅稳定的转子不平衡量突增的2种特征，通过应用案例对振动信号的程序化进行处理，得到转速跟踪滤波后的基频振动时域信号及转子不平衡量突增的识别参数，数据结果中振幅增大比例系数达到3.75，且突增后振幅稳定。结果表明：采用FFT滤波技术，实现了转子不平衡突增的自动识别，并验证了识别方法的有效性。转子不平衡量突增的识别技术应用于在线监测系统时，能及时识别故障并发出报警信息，保证设备运转的安全；应用于离线振动信号分析系统时，缩短了人工数据分析时间，提高了工作效率。

Automatic Recognition for Aeroengine Rotor Unbalance Surge

In order to realize automatic identification of rotor unbalance surge in the aeroengine, firstly, multiple FFT filtering technol? ogy was used to obtain the time-domain signal of fundamental frequency vibration after speed tracking filtering; secondly, two characteristics of rotor unbalance surge were proposed: amplitude surge and amplitude stabilized after the surge, and the vibration signals were processed through programming. In the application case, by using the time-domain signal of fundamental frequency vibration and the identification parameters of rotor unbalance surge, it was found that the amplitude scaling coefficient reached 3.75 at a certain time, then stabilized after the surge, by which the unbalance surge event was identified. The results show that the method can realize automatic identification of rotor unbalance surge by using multiple FFT filtering technology and the programmed characteristic parameter identifica? tion, and its effectiveness is verified. When the identification technology of rotor unbalance surge is applied to the online monitoring system, it can timely identify faults and send out alarm messages to ensure the safety of equipment operation; when applied to off-line vibra? tion signal analysis systems, it can shorten manual data analysis time and improve work efficiency.