摘要
阶次跟踪是一种有效的解决变转速故障诊断问题的方法,其关键前提是存在转速信号作为参考。然而,由于强背景噪声和弱谐波关系的影响,现有转速估计方法的准确性和自适应性有待进一步提高。因此,提出一种融合多传感器信号的改进多阶概率方法(MOPA)用以估计瞬时转速。首先,依据不同传感器信号的基频统一性和主导分量差异性,通过时频图瞬时切片归一化融合的方式,构建具有强谐波关系的时频图;其次,为消除时变工况下时频图中横纵方向上的间歇恒频和短时宽频背景噪声,提出滑动消噪方法;最后,基于处理后的时频图执行MOPA,实现瞬时转速自动估计,结合阶次跟踪解决风电齿轮箱变转速故障诊断问题。经实测数据验证,改进MOPA估计的瞬时频率的准确性和自适应性均优于对方法,平均绝对百分比误差为0.56%,均小于对比方法的15.73%、13.99%和1.21%。结合阶次分析诊断了变转速下风电齿轮箱异常。
The order tracking is an effective method to solve the problem of variable speed fault diagnosis.The key premise is that there is a speed signal as a reference.However,due to the influence of strong background noise and weak harmonic relations,the accuracy and adaptability of the existing speed estimation methods need to be further improved.Therefore,an improved multi-order probability approach(MOPA)based on multi-sensor signals is proposed to estimate the instantaneous speed.Firstly,according to the unity of fundamental frequency and the difference of dominant component of different sensor signals,the time-frequency diagram with a strong harmonic relationship is constructed through the normalization and fusion of instantaneous slices of the time-frequency diagram.Secondly,to eliminate the intermittent constant frequency and short-time broadband background noise in the transverse and longitudinal direction of the time-frequency diagram under time-varying conditions,a sliding noise reduction method is proposed.Finally,MOPA is implemented based on the processed time-frequency diagram to realize automatic estimation of instantaneous speed,and the fault diagnosis problem under variable speed of wind power gearbox is solved by combining the order tracking method.The measured data evaluate that the accuracy and adaptability of the instantaneous frequency estimated by the improved MOPA are better than those of the opposite methods.The mean absolute percentage error is 0.56%,which is lower than 15.73%,13.99%,and 1.21%of the comparison methods.Combined with the order analysis,the abnormality of the wind turbine gearbox under variable speed is diagnosed.
作者
刘长良
刘少康
李洋
刘帅
武英杰
Liu Changliang;Liu Shaokang;Li Yang;Liu Shuai;Wu Yingjie(School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China;Baoding Key Laboratory of State Detection and Optimization of Integrated Energy System,Baoding 071003,China;School of Automation Engineering,Northeast Electric Power University,Jilin 132012,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2024年第5期208-217,共10页
Chinese Journal of Scientific Instrument
基金
中央高校基本科研业务费专项资金(2023JG005,2023JC010)
河北省高等学校科学技术研究项目(CXY2023001)资助。
关键词
变转速
故障诊断
风电齿轮箱
瞬时频率
阶次跟踪
variable speed
fault diagnosis
wind turbine gearbox
instantaneous frequency
order tracking
