工程船舶机械运行状态监测及故障诊断
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摘要
工程船舶机械运行状态的信号具有非平稳性,传统方法无法准确提取信号中的特征,使得工程船舶机械运行状态监测不准确,故障诊断错误率高,为此提出了基于Hilbert变换的工程船舶机械运行状态监测和故障诊断方法。首先提取工程船舶机械运行状态信号,然后采用Hilbert变换对工程船舶机械运行状态信号进行分解,提取特征,最后根据特征向量建立工程船舶机械运行状态识别模型,实验结果表明,本文方法可以较好描述工程船舶机械运行状态,获得了较高正确率的工程船舶机械故障诊断结果。
The signal of the operating state of the engineering ship is nonstationary. The traditional method can not accurately extract the characteristics of the signal, which makes the monitoring of the operating state of the ship machinery inaccurate and the error rate of fault diagnosis high. Therefore, a method of monitoring and fault diagnosis of the engineering ship machinery based on Hilbert transformation is proposed. First, the state signal of the engineering ship's mechanical operation is extracted. Then the Hilbert transformation is used to decompose the state signal of the engineering ship's mechanical operation state, and the characteristics are extracted. Finally, according to the characteristic vector, the state recognition model of the engineering ship machinery operation state is set up. The experimental results show that the method of this paper can describe the operation of the engineering ship mechanically better. The results of mechanical fault diagnosis for engineering ships are obtained.
The signal of the operating state of the engineering ship is nonstationary. The traditional method can not accurately extract the characteristics of the signal, which makes the monitoring of the operating state of the ship machinery inaccurate and the error rate of fault diagnosis high. Therefore, a method of monitoring and fault diagnosis of the engineering ship machinery based on Hilbert transformation is proposed. First, the state signal of the engineering ship's mechanical operation is extracted. Then the Hilbert transformation is used to decompose the state signal of the engineering ship's mechanical operation state, and the characteristics are extracted. Finally, according to the characteristic vector, the state recognition model of the engineering ship machinery operation state is set up. The experimental results show that the method of this paper can describe the operation of the engineering ship mechanically better. The results of mechanical fault diagnosis for engineering ships are obtained.
引文
[1]董磊,任章,李清东.基于模型和案例推理的混合故障诊断方法[J].系统工程与电子技术,2012,34(11):2339-2343.
[2]曹辉,张均东.现代船舶轮机模拟器的应用与发展[J].航海教育研究,2012,12(1):33-36.
[3]李军伟,韩捷,李志农.小波变换域双谱分析及其在滚动轴承故障诊断中的应用[J].振动与冲击,2005,25(5):92-96.
[4]伶俐,郭建英,蒋凤林.小波分析与Hilbert分析在滚动轴承故障诊断中的应用[J].哈尔滨理工大学学报,2008,13(2):82-85.
[5]陈永会,姜旭,郭山国,等.基于小波分析和Hilbert变换的滚动轴承故障诊断[J].机械设计,2010,27(8):91-94.
[2]曹辉,张均东.现代船舶轮机模拟器的应用与发展[J].航海教育研究,2012,12(1):33-36.
[3]李军伟,韩捷,李志农.小波变换域双谱分析及其在滚动轴承故障诊断中的应用[J].振动与冲击,2005,25(5):92-96.
[4]伶俐,郭建英,蒋凤林.小波分析与Hilbert分析在滚动轴承故障诊断中的应用[J].哈尔滨理工大学学报,2008,13(2):82-85.
[5]陈永会,姜旭,郭山国,等.基于小波分析和Hilbert变换的滚动轴承故障诊断[J].机械设计,2010,27(8):91-94.