A study of bispectral analysis in gearbox condition monitoring is presented.The theory of bispectrum and quadratic phase coupling (QPC) is first introduced, and then equationsfor computing bispectrum slices are obtain...A study of bispectral analysis in gearbox condition monitoring is presented.The theory of bispectrum and quadratic phase coupling (QPC) is first introduced, and then equationsfor computing bispectrum slices are obtained. To meet the needs of online monitoring, a simplifiedmethod of computing bispectrum diagonal slice is adopted. Industrial gearbox vibration signalsmeasured from normal and tooth cracked conditions are analyzed using the above method. Experimentsresults indicate that bispectrum can effectively suppress the additive Gaussian noise andchracterize the QPC phenomenon. It is also shown that the 1-D bispectrum diagonal slice can capturethe non-Gaussian and nonlinear feature of gearbox vibration when crack occurred, hence, this methodcan be employed to gearbox real time monitoring and early diagnosis.展开更多
During the condition monitoring of a planetary gearbox, features are extracted from raw data for a fault diagnosis.However, different features have different sensitivity for identifying different fault types, and thus...During the condition monitoring of a planetary gearbox, features are extracted from raw data for a fault diagnosis.However, different features have different sensitivity for identifying different fault types, and thus, the selection of a sensitive feature subset from an entire feature set and retaining as much of the class discriminatory information as possible has a directly effect on the accuracy of the classification results. In this paper, an improved hybrid feature selection technique(IHFST) that combines a distance evaluation technique(DET), Pearson’s correlation analysis, and an ad hoc technique is proposed. In IHFST, a temporary feature subset without irrelevant features is first selected according to the distance evaluation criterion of DET, and the Pearson’s correlation analysis and ad hoc technique are then employed to find and remove redundant features in the temporary feature subset, respectively, and hence,a sensitive feature subset without irrelevant or redundant features is selected from the entire feature set. Further, the k-means clustering method is applied to classify the different kinds of health conditions. The effectiveness of the proposed method was validated through several experiments carried out on a planetary gearbox with incipient cracks seeded in the tooth root of the sun gear, planet gear, and ring gear. The results show that the proposed method can successfully distinguish the different health conditions of a planetary gearbox, and achieves a better classification performance than other methods. This study proposes a sensitive feature subset selection method that achieves an obvious improvement in terms of the accuracy of the fault classification.展开更多
The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre- sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy...The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre- sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy to the gear mesh signal and the background noise.This paper presents a new comprehensive demodulation method which combined with amplitude envelop demodulation and phase demodulation to extract gear crack early fault.A mathematical model of gear vibration signal contain crack fault is put forward.Simulation results based on this model show that the new comprehensive demodulation method is more effective in finding fault and judging fault level then conventional single amplitude demodulation at present.展开更多
综合运用振动信号分析、内窥镜检查、宏观观察、金相分析、扫描电镜(Scanning Electron Microscopy,SEM)分析、能谱仪分析(Energy Dispersive Spectroscopy,EDS)和力学性能试验等多种技术手段,针对某型号风电齿轮箱出现的沿齿槽径向开...综合运用振动信号分析、内窥镜检查、宏观观察、金相分析、扫描电镜(Scanning Electron Microscopy,SEM)分析、能谱仪分析(Energy Dispersive Spectroscopy,EDS)和力学性能试验等多种技术手段,针对某型号风电齿轮箱出现的沿齿槽径向开裂现象进行了故障诊断与原因分析。通过振动信号分析发现异常振动,并通过频谱分析和时域特征提取了确定异常振动的特征;通过内窥镜检查确认故障位置,拆解后利用SEM检测确认裂纹源存在一块大尺寸夹杂物,并通过EDS明确了夹杂物的成分;进一步分析确定齿轮贯穿性开裂的整个过程,通过综合分析确定了故障原因和位置,为设备维护提供了科学依据,并为提高生产效率、延长设备寿命、降低故障损失和维修成本提供了参考。展开更多
基金This project is supported by 95 Pan Deng Program of China (No.PD952l908) National Key Basic Research Special Foundation of China (No.Gl998020320)Provincial Natural Science Foundation of Hubei, China (No.2000J125)
文摘A study of bispectral analysis in gearbox condition monitoring is presented.The theory of bispectrum and quadratic phase coupling (QPC) is first introduced, and then equationsfor computing bispectrum slices are obtained. To meet the needs of online monitoring, a simplifiedmethod of computing bispectrum diagonal slice is adopted. Industrial gearbox vibration signalsmeasured from normal and tooth cracked conditions are analyzed using the above method. Experimentsresults indicate that bispectrum can effectively suppress the additive Gaussian noise andchracterize the QPC phenomenon. It is also shown that the 1-D bispectrum diagonal slice can capturethe non-Gaussian and nonlinear feature of gearbox vibration when crack occurred, hence, this methodcan be employed to gearbox real time monitoring and early diagnosis.
基金Supported by National Natural Science Foundation of China(Grant No.51475053)
文摘During the condition monitoring of a planetary gearbox, features are extracted from raw data for a fault diagnosis.However, different features have different sensitivity for identifying different fault types, and thus, the selection of a sensitive feature subset from an entire feature set and retaining as much of the class discriminatory information as possible has a directly effect on the accuracy of the classification results. In this paper, an improved hybrid feature selection technique(IHFST) that combines a distance evaluation technique(DET), Pearson’s correlation analysis, and an ad hoc technique is proposed. In IHFST, a temporary feature subset without irrelevant features is first selected according to the distance evaluation criterion of DET, and the Pearson’s correlation analysis and ad hoc technique are then employed to find and remove redundant features in the temporary feature subset, respectively, and hence,a sensitive feature subset without irrelevant or redundant features is selected from the entire feature set. Further, the k-means clustering method is applied to classify the different kinds of health conditions. The effectiveness of the proposed method was validated through several experiments carried out on a planetary gearbox with incipient cracks seeded in the tooth root of the sun gear, planet gear, and ring gear. The results show that the proposed method can successfully distinguish the different health conditions of a planetary gearbox, and achieves a better classification performance than other methods. This study proposes a sensitive feature subset selection method that achieves an obvious improvement in terms of the accuracy of the fault classification.
文摘The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre- sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy to the gear mesh signal and the background noise.This paper presents a new comprehensive demodulation method which combined with amplitude envelop demodulation and phase demodulation to extract gear crack early fault.A mathematical model of gear vibration signal contain crack fault is put forward.Simulation results based on this model show that the new comprehensive demodulation method is more effective in finding fault and judging fault level then conventional single amplitude demodulation at present.
文摘综合运用振动信号分析、内窥镜检查、宏观观察、金相分析、扫描电镜(Scanning Electron Microscopy,SEM)分析、能谱仪分析(Energy Dispersive Spectroscopy,EDS)和力学性能试验等多种技术手段,针对某型号风电齿轮箱出现的沿齿槽径向开裂现象进行了故障诊断与原因分析。通过振动信号分析发现异常振动,并通过频谱分析和时域特征提取了确定异常振动的特征;通过内窥镜检查确认故障位置,拆解后利用SEM检测确认裂纹源存在一块大尺寸夹杂物,并通过EDS明确了夹杂物的成分;进一步分析确定齿轮贯穿性开裂的整个过程,通过综合分析确定了故障原因和位置,为设备维护提供了科学依据,并为提高生产效率、延长设备寿命、降低故障损失和维修成本提供了参考。
