利用倒谱包络方法解决液压泵轴承故障特征提取和故障诊断的问题。
The cepstrum envelope analysis is applied to solve the problem of the diagnosis of bearing failure to hydraulic pump.
针对感应电动机轴承故障特征提取的不足，提出了瞬时功率小波包分解的方法。
To solve the problem in obtaining bearing fault characteristics of induction motors, a method based on instantaneous power decomposition via wavelet packet is put forward.
结果表明：该方法可以有效提取滚动轴承故障特征频率，提高了轴承故障诊断的准确性。
The results indicate that this method is able to extract effectively the rolling bearing fault feature frequency and improve the veracity of rolling bearing fault diagnosis.
对滚动轴承的内圈、外圈故障信号的分析结果表明本文方法可以有效地提取滚动轴承故障特征。
The analysis results from roller bearing signals with inner-race or out-race faults show that the diagnosis approach could extract fault characteristics effectively.
在数值仿真和轴承故障特征选择中，采用新方法在保证诊断精度的同时，可以节省大量选择时间。
The composite method saves more computing time than the wrapper method with holding the classification accuracy in data simulation and experiment on bearing fault feature selection.
试验结果表明，这种方法能有效地提取滚动轴承的故障特征，诊断其故障。
The experiment shows that the method can extract effectively the fault characteristics of rolling bearing and detect its failure.
反映滚动轴承故障的特征周期信号处于较低频带内，容易被噪声淹没，难以检测。
The fault characteristic periodic signals of the rolling bearing are in low frequency band and often buried in the noise.
滚动轴承的振动信号是非平稳信号，用常规方法难以从振动信号中提取有效故障特征信息。
The fault feature information can not be obtained availably by regular methods to extract the features of nonstationary vibration signals produced by fault rolling bearings.
为了提取机车滚动轴承早期损伤类故障特征，本文提出了一种双重小波平均谱方法，并通过诊断实例验证了方法的有效性。
To extract early fatigue feature of engine bearings, the paper presents an average spectrum method with double-wavelet and the diagnosis examples are used to show the validity of the method.
运用此方法对内燃机主轴承不同间隙下的噪声信号进行分析，结果表明，此方法能有效地提取故障的特征，实现状态监测。
Applying the order bi-spectrum in the analysis of engine noise signals shows that it can extract the fault characteristics and realize the state monitoring.
采用多重分形改进算法提取往复压缩机振动信号的多重分形特征，得到了轴承故障的广义维数谱。
The multifractal features are extracted from the vibration signals of different spots on reciprocating compressor using the improving arithmetic, the general dimension spectrum of bearing.
已知试验轴承的故障特征参数与非故障特征参数，采用何种方法对采自实际应用场合的轴承信号进行判断和处理是问题的关键。
How to diagnose and deal with bearing signal which is gathered on-the-spot is the key problem based on the known of bearing trouble feature parameter and non-trouble one.
提出曲元分析(CCA)和自组织特征映射(SOFM)相结合的方法用于轴承的故障诊断特征提取。
The combination of curvilinear component analysis (CCA) and self-organizing feature map (SOFM) were applied to a diagnosis for fault feature extraction of bearing.
分析了电磁轴承多传感器故障的基本特征，提出了电磁轴承多传感器故障诊断方法——基于序列变量的多值逻辑代数方法。
It was analyzed in detail about the way of fault diagnosis of the sensors of magnetic bearings in guidance with the multi-valued logic algebra.
首先总结了轴位移故障的特征和导致故障的直接原因，将它们和可倾瓦止推轴承的性能相结合，组成一故障诊断专家系统。
First, an expert system of fault diagnosis is set up by summarizing symptoms and their direct reasons for axial displacement fault and by combining them to the tilting pad thrust bearing performance.
本文总结分析了滚动轴承典型故障的故障机理及其振动特征，详细介绍了滚动轴承振动信号分析与故障诊断的方法。
The fault principle and the fault vibration property were analyzed in this paper. The means of vibration signal analysis and fault diagnosis of the rolling bearing were also introduced.
与传统的轴承故障检测技木相比，其优越性在于可以提取振动信号的高频能量中的低频调制信号，从而大大提高了故障特征信号的信噪比。
Compared with traditional bearing fault diagnosis method, the approach proposed in this paper can detect the low frequency modulated components from high frequency band.
提出基于小波尺度图重分配的信号瞬态特征检测方法和瞬时能量估计方法，并应用于轴承在多种轻微故障状况下的振动非平稳特征的检测与表示。
The singal transient feature detection represent method, and a transient energy evaluation method are used based on the reassigned scalogram for the vibration non-stationary feature representation.
在曲柄轴承磨损故障机理的研究基础上，论文对其故障特征信息提取及故障识别方法开展了进一步的研究。
Based on the research of crank bearing wear fault mechanics, the fault feature extraction and fault diagnosis method are further studied.
滚动轴承故障诊断的关键是对振动信号进行分析和处理，并提取滚动轴承的故障特征。
The key to fault diagnosis of rolling bearing is the analysis and processing of vibration signals, and extract fault features of rolling bearing.
提出了基于小波包分解频带能量监测法，对滚动轴承的几种典型故障进行了诊断，并且提取特征向量，为后续的神经网络识别作准备。
Propose wavelet packet decomposition frequency-band monitoring method, diagnose typical failures of rolling bearing, and extract eigenvector to prepare follow-up Neural network identification.
在故障诊断中的滚子轴承的旋转频率的重要性进行了分析，根据故障特征频率的计算公式。
The importance of rotating frequency in fault diagnosis of roller bearings is analyzed based on formula of fault characteristic frequency.
本文以滚动轴承为研究对象，应用新理论，提出轴承故障信号特征提取的新方法。
This paper goes on the rolling bearing as the research object, researching the new theories and methods of bearing fault signal feature extraction.
针对当前的诊断方法没有充分利用其故障特征频带的问题，提出了基于混沌振子的滚动轴承故障的非线性诊断方法。
The characteristic frequency band is not fully used in some diagnosis methods. A non-linear method based on chaotic oscillator is presented.
本发明提供一种车辆轴承故障检测仪，利用轴承故障时的声音特征来进行判断。
The invention provides a fault detector for a vehicle bearing, which judges by utilization of sound features of the bearing under the condition of fault.
结果表明，重分配的小波尺度图能够以较高的时频分辨率表示轴承振动中的非平稳特征，反映轴承的多种故障，瞬时能量估计可以作为分析轴承状态的依据。
Results show that the reassigned scalogram has the signal feature in the time-scale plane with the high resolution, the transient energy evaluation has the transient feature in a more distinct as…
结果表明，重分配的小波尺度图能够以较高的时频分辨率表示轴承振动中的非平稳特征，反映轴承的多种故障，瞬时能量估计可以作为分析轴承状态的依据。
Results show that the reassigned scalogram has the signal feature in the time-scale plane with the high resolution, the transient energy evaluation has the transient feature in a more distinct as…
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