提出了基于核函数主元分析的齿轮故障诊断方法。
An approach to gear fault diagnosis is presented, which bases on kernel principal component analysis (KPCA).
因此，齿轮故障诊断技术的应用研究是非常重要的。
Therefore, the gear fault diagnosis technology research is very important.
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.
提出一种新的自适应时变滤波器设计方法，并将其应用于变速齿轮箱齿轮故障诊断中。
A new method for adaptive time-varying filter design and its application in gearbox fault diagnosis is proposed.
在研究蚁群优化神经网络训练算法的基础上，建立了矿井提升机减速器齿轮故障诊断模型。
On the basis of researching the optimization of neural network through ant colony algorithm, the mine hoist reducer gear failure diagnosis model is established.
本文从选择诊断特征指标出发，探讨了利用散度指标建立齿轮故障诊断模糊判据的理论与方法。
The fuzzy threshold of gear faults for diagnosis is discussed in the paper based on mathematics. An example of creating the threshold using actual vibration signal is given for demonstration.
介绍了希尔伯特黄变换算法的原理及流程，利用由希尔伯特谱反映出的丰富的物理信息来对齿轮进行故障诊断。
This paper explains the theory and algorithm of the HHT. It employs the plenty of information of gear embodied in Hilbert spectrum for fault diagnosis.
这就为齿轮的早期故障诊断带来了很大困难。
This brought great difficulties to diagnose the early fault of gear.
准确地提取各种典型故障的特征是进行齿轮箱故障诊断的关键。
Extracting precisely the vibration characteristics of typical gearbox faults is a key to its diagnosis.
稀疏信号分解；阶比分析；齿轮；故障诊断；
Sparse signal decomposition Order analysis Gear Fault diagnosis;
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.
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.
提出了一种基于多分类支持向量机的齿轮箱故障诊断方法。
A gearbox fault diagnosis method based on multi-class support vector machine was proposed in this paper.
汽车变速器齿轮制造缺陷声频特征的提取，是汽车变速器噪声故障诊断专家系统准确诊断齿轮制造缺陷的关键。
Extracting the sound frequency features is vital for the noise diagnosis expert system to detect the gear processing error in a transmission.
对齿轮箱做振动测试和分析，通过模式识别找到齿轮箱损坏时呈现的特性，为齿轮箱故障诊断提供依据。
Vibration data acquisition and signal processing has been done for gear box, by criterion of fault model, we find the characteristic of fault gear box and make contribution to fault diagnosis for it.
齿轮作为一种重要的机械传动设备，对其进行故障诊断具有重要意义。
Gear as an important mechanical transmission equipment, its fault diagnosis has important significance.
该方法应用于LC5T 81变速箱齿轮的故障诊断中，能够比较准确地识别与诊断出变速箱齿轮的走合运行状态、磨损运行状态和故障运行状态，具有一定的实用价值。
This method was used to diagnose normal working state, wear working state and fault working state of LC5T81 transmission gear. The results show that this method is effective and practical.
与谱分析诊断结论比较后，得出了神经网络应用于齿轮传动装置故障诊断的可行性。
After comparing these conclusions with those obtained from the genealogy analysis, the availability of applying the BP to fault diagnosis was shown.
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.
由于地铁齿轮传动装置安装隐蔽、结构复杂、难于拆卸，故障类型多而复杂，加之测试条件的限制，故障诊断难度相当大。
Due to concealment installation, complicated structure, difficult to remove, complex fault and limit test conditions, the fault diagnosis of gear transmission is extremely difficult.
齿轮箱是机械设备的重要传动部件，其故障诊断得到了广泛的重视。
Gearbox is the important transmission component in the mechanical equipments, so much attention has been given to the fault diagnosis technology for it.
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.
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.
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.
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