介绍了一种基于振动信号隐马尔可夫模型(HMM)的新的齿轮故障检测和诊断方案。
A new gear fault detection and diagnosis scheme based on Hidden Markov Model (HMM) of vibration signals is introduced.
研究表明，齿轮运动信号分解能够有效检测齿轮的各类故障，高阶加速度信号对齿轮某些类型的早期故障更加敏感。
Experimental results show that gear vibration signal decomposition can detect different faults, and high-order acceleration signals are more sensitive to certain type of fault.
利用双正交小波基将齿轮的故障振动信号分解到时频域，并提取出齿轮的故障特征。
This paper mainly introduces that the fault vibrating signal of gears was decomposed into time-frequency domains by double-orthogonal wavelet analysis and the fault feature of gears was picked up.
通过数字模拟实验与齿轮箱故障信号检测，验证了新的双线性时间-频率分布对复杂信号中瞬时分量的探测效果。
By digital simulation and detection of gearbox fault signal the detection effect of the novel bilinear time-frequency transform is validated for the transient components in complex signal.
分析了齿轮典型故障的故障机理及其振动特征，阐述了齿轮振动信号分析与故障诊断的方法。
In this paper, typical fault mechanisms and vibration characters are analyzed; the methods of analyzing gear vibration signal and diagnosing fault are described.
本发明公开了一种基于多尺度线调频基稀疏信号分解的齿轮故障诊断方法。
The invention discloses a gear fault diagnosis method based on multiscale linear frequency modulation-based sparse signal decomposition.
振动信号分析是进行齿轮箱状态监测与故障诊断的重要手段。
Vibration signal analysis is widely used in the state monitoring and failure diagnosis of the gear and rolling bearing.
振动信号能量在局域波时频分布中的变化，是局域波法诊断齿轮磨损故障的特征。
The energy variation of vibration signals is the features of gearbox-case fault diagnosis.
齿轮故障实验信号的研究结果表明：该方法能有效地识别齿轮的齿根裂纹故障。
The experimental results show that this method based on EMD can(effectively) recognize the faults of gear crack.
通过对齿轮齿根裂纹故障实验信号的分析，表明该方法能有效地诊断齿轮的裂纹故障。
The experimental results show that order tracking analysis and Angle domain average technique can effectively diagnose the faults of the gear crack.
为了诊断单级传动齿轮副故障，本文提出信号周期分段处理的方法。
This thesis presented a technique for diagnosing gear pairs faults and introduced the procedure in detail.
结合实验对齿轮箱信号进行时间序列分析，对比各种工况下的模型曲线，识别齿轮箱的运行故障。
Through experiment this paper analyses the signals of the gear box, then comparing with the model curve of the different conditions in order to distinguish the operating trouble of the gear box.
该方法是通过对测取齿轮工况下的振动信号进行频谱分析，从而找出齿轮产生故障的原因。
By use of the method, the vibration signal in working state is measured and the spectrum analysis of the gear can be taken, so that the cause of the gear breakdown is found out.
介绍了齿轮箱故障振动信号传统的时域、频域分析方法，并列举了一些不同故障所应用的分析方法。
The traditional time and frequency domain methods of vibration signals of gear box fault are introduced in this paper. And meanwhile this paper lists different applied fault analysis means.
提出了基于线调频基稀疏信号分解的包络阶次谱方法，并将其应用于变速齿轮箱故障诊断之中。
An envelope order spectrum based on multi-scale chirplet and sparse signal decomposition was proposed and applied to the fault diagnosis of gearboxes with rotating speed fluctuation.
针对齿轮箱升降速过程中振动信号非平稳的特点，将常规的阶次分析与双谱分析技术相结合，提出了基于阶次双谱的齿轮箱故障诊断方法。
In order to process the non-stationary vibration signals such as speed up or speed down signals effectively, the order bispectrum technique was presented.
建议了一种基于复解析小波变换的瞬时频率分析齿轮故障振动信号的方法。 该方法将希尔伯特变换与小波变换相结合，具有自适应分析能力。
A method using transient frequency based on complex-analytical- wavelet-transform, which combines Hilbert transform with wavelet transform and possesses adaptive analytical ability, is proposed.
针对齿轮箱升降速过程中振动信号非平稳的特点，将阶次跟踪、角域平均和幅值、相位解调分析技术相结合，提出了基于幅值和相位解调分析的齿轮箱故障诊断方法。
In order to process the non-stationary vibration signals such as speed up or speed down signals effectively, the order tracking technique and Angle domain average technique were presented.
将分形几何引入齿轮振动信号的故障分析中 ，用关联维数来刻画振动信号的故障特征。
Application to fault diagnosis of reciprocating compressor based on emprical mode decomposition and correlation dimension;
将分形几何引入齿轮振动信号的故障分析中 ，用关联维数来刻画振动信号的故障特征。
Application to fault diagnosis of reciprocating compressor based on emprical mode decomposition and correlation dimension;
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