| 齿轮箱振动与输入能量信号的频域相干分析与关系识别 |
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| 引用本文： | 李怀俊,刘越琪,谢小鹏.齿轮箱振动与输入能量信号的频域相干分析与关系识别[J].农业工程学报,2015,31(4):175-182. |
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| 作者姓名： | 李怀俊 刘越琪 谢小鹏 |
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| 作者单位： | 1. 广东交通职业技术学院车辆安全工程技术中心，广州 510650,1. 广东交通职业技术学院车辆安全工程技术中心，广州 510650,2. 华南理工大学摩擦学与故障诊断研究所，广州 510640 |
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| 基金项目： | 广东省自然科学基金（S2011010002118）；广东省高校优秀青年教师培养项目（Yq2013178） |
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| 摘 要： | 为了提高旋转设备诊断效率、发展基于设备输入能量信号分析的故障诊断技术,该文提出并论述了输入能量信号分析方法在设备故障诊断技术研究中的有效性。首先从齿轮箱振动机理角度分析了传动能量与振动信号之间的关系,指出轴系扭矩及输入功率是齿轮静态传递误差的激励,进而导致振动信号的产生;其次通过建立齿轮传动能量与振动关系模型,利用相干函数以概率统计的形式揭示了输入能量与振动信号响应之间的关系;最后通过正常与断齿齿轮的对比试验,验证了功率信号的频谱特征与传统的齿轮故障振动频谱相一致,亦具有表征齿轮箱工况的明显作用,同时分析了振动和功率信号的自功率谱和互功率谱,利用相干分析方法,从经典控制理论角度验证了二者所呈现出的强相关性。该文为以能量信号分析为核心的旋转设备故障诊断技术的研究提供参考。
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| 关 键 词： | 振动 故障检测 信号分析 输入能量信号 相干分析 互功率谱 |
| 收稿时间： | 2014/8/14 0:00:00 |
| 修稿时间： | 2/4/2015 12:00:00 AM |
Frequency domain coherence analysis and relationship recognition between gearbox vibration and input energy signal |
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| Li Huaijun,Liu Yueqi and Xie Xiaopeng.Frequency domain coherence analysis and relationship recognition between gearbox vibration and input energy signal[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(4):175-182. |
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| Authors: | Li Huaijun Liu Yueqi and Xie Xiaopeng |
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| Institution: | 1. Vehicle Safety Engineering Technology Center, Guangdong Communication Polytechnic, Guangdong 510650, China,1. Vehicle Safety Engineering Technology Center, Guangdong Communication Polytechnic, Guangdong 510650, China and 2. Tribology and Fault Diagnosis Institute, South China University of Technology, Guangdong 510640, China |
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| Abstract: | Abstract: From the perspective of energy, vibration of gearbox and other rotating equipment actually is the energy propagation process. Although vibration signal analysis is the most popular technology to realize fault diagnosis for such equipment, but to broaden the horizons of rotating equipment fault diagnosis technology, the validity of energy signal analysis method was proposed and discussed in this paper. How to shed some further light on the issue through theoretical and experimental study is a prospective research work in this field. Firstly, the relationship between the gearbox transmission energy and vibration signal was analyzed based on the vibration mechanism which revealed that the torque and input power generate gear static transmission error, and then produce the vibration signal. Meanwhile, a general formula was given for calculating the input power of the transmission system, which was used to establish the theory basis for the pre-processing of the original energy data. Secondly, the model of gear transmission energy interact with vibration was proposed to analyze the stable I/O relationship between the input energy and vibration signal response using correlation function based on the probability statistics form. Results showed that the larger of correlation value in the key frequency point, the more obvious of vibration energy dissipation. Finally, the normal and fault gear contrast experiment was carried out in the energy monitoring experimental platform of gear transmission system. Analysis of the experimental power signal spectrum found it is similar to vibration signal that the side band also appeared with the rotating frequency as modulation frequency on the both side of the fault gear's meshing frequencyand typical frequency point distribution with larger amplitude accords with the traditional gear fault characteristic spectrum. Thus the spectrum features of power signal was confirmed consistent with traditional gear fault vibration spectrum, which all could reflect rich frequency information. So, condition of gearbox could also be revealed obviously by using power signal spectrum Meanwhile, auto power spectrum and cross power spectrum of vibration and power signal were all analyzed by using coherent analysis method, and the forecast that they correlate highly was verified based on classical control theory. In conclusion, vibration excitation originated from in gear vibration mechanism analysis filed, and energy had a close relationship with vibration signal. The paper lays an effective foundation for the fault diagnosis technology based on energy signal analysis. |
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| Keywords: | vibrations fault detection signal analysis input energy signal coherence analysis cross power spectrum |
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