累积和检测方法是根据声呐目标信号出现与消失时概率密度函数(Probability Distribution Function,PDF)的变化进行有效的瞬态信号检测。以非高斯模型t分布假设替代传统的高斯分布方差变化假设作为描述瞬态信号的PDF形式,推导了累积和检...累积和检测方法是根据声呐目标信号出现与消失时概率密度函数(Probability Distribution Function,PDF)的变化进行有效的瞬态信号检测。以非高斯模型t分布假设替代传统的高斯分布方差变化假设作为描述瞬态信号的PDF形式,推导了累积和检验统计量的表达、更新量PDF求取的数值方法,利用快速傅里叶变换法计算了门限和自由度等检测参数。利用仿真的落水信号、船体加速信号和消声水池实验数据进行检验。结果表明,基于t分布假设的累积和方法对瞬态脉冲信号的检测效果优于常规累积和方法,能更快地响应信号变化,更好地抑制背景干扰。展开更多
Vibration signal is an important prerequisite for mechanical fault detection. However, early stage defect of rotating machiner- ies is difficult to identify because their incipient energy is interfered with background...Vibration signal is an important prerequisite for mechanical fault detection. However, early stage defect of rotating machiner- ies is difficult to identify because their incipient energy is interfered with background noises. Multiwavelet is a powerful tool used to conduct non-stationary fault feature extraction. However, the existing predetermined multiwavelet bases are independ- ent of the dynamic response signals. In this paper, a constructing technique of vibration data-driven maximal-overlap adaptive multiwavelet （MOAMW） is proposed for enhancing the extracting performance of fault symptom. It is able to derive an opti- mal multiwavelet basis that best matches the critical non-stationary and transient fault signatures via genetic algorithm. In this technique, two-scale similarity transform （TST） and symmetric lifting （SymLift） scheme are combined to gain high designing freedom for matching the critical faulty vibration contents in vibration signals based on the maximal fitness objective. TST and SymLift can add modifications to the initial multiwavelet by changing the approximation order and vanishing moment of mul- tiwavelet, respectively. Moreover, the beneficial feature of the MOAWM lies in that the maximal-overlap filterbank structure can enhance the periodic and transient characteristics of the sensor signals and preserve the time and frequency analyzing res- olution during the decomposition process. The effectiveness of the proposed technique is validated via a numerical simulation as well as a rolling element beating with an outer race scrape and a gearbox with rub fault.展开更多
文摘累积和检测方法是根据声呐目标信号出现与消失时概率密度函数(Probability Distribution Function,PDF)的变化进行有效的瞬态信号检测。以非高斯模型t分布假设替代传统的高斯分布方差变化假设作为描述瞬态信号的PDF形式,推导了累积和检验统计量的表达、更新量PDF求取的数值方法,利用快速傅里叶变换法计算了门限和自由度等检测参数。利用仿真的落水信号、船体加速信号和消声水池实验数据进行检验。结果表明,基于t分布假设的累积和方法对瞬态脉冲信号的检测效果优于常规累积和方法,能更快地响应信号变化,更好地抑制背景干扰。
基金supported by the National Natural Science Foundation of China(Grant No.51275384)the Key Project of National Natural Science Foundation of China(Grant No.51035007)+1 种基金the National Basic Research Program of China(Grant No.2009CB724405)the Specialized Research Fund for the Doctoral Program of Higher Education(Grant No.20110201130001)
文摘Vibration signal is an important prerequisite for mechanical fault detection. However, early stage defect of rotating machiner- ies is difficult to identify because their incipient energy is interfered with background noises. Multiwavelet is a powerful tool used to conduct non-stationary fault feature extraction. However, the existing predetermined multiwavelet bases are independ- ent of the dynamic response signals. In this paper, a constructing technique of vibration data-driven maximal-overlap adaptive multiwavelet （MOAMW） is proposed for enhancing the extracting performance of fault symptom. It is able to derive an opti- mal multiwavelet basis that best matches the critical non-stationary and transient fault signatures via genetic algorithm. In this technique, two-scale similarity transform （TST） and symmetric lifting （SymLift） scheme are combined to gain high designing freedom for matching the critical faulty vibration contents in vibration signals based on the maximal fitness objective. TST and SymLift can add modifications to the initial multiwavelet by changing the approximation order and vanishing moment of mul- tiwavelet, respectively. Moreover, the beneficial feature of the MOAWM lies in that the maximal-overlap filterbank structure can enhance the periodic and transient characteristics of the sensor signals and preserve the time and frequency analyzing res- olution during the decomposition process. The effectiveness of the proposed technique is validated via a numerical simulation as well as a rolling element beating with an outer race scrape and a gearbox with rub fault.
