一种基于静态分割符号序列的降解特征提取技术
Chunxia Gu1, Juan Bi2, Bing Wang3
1School of Economics & Management, Shanghai Maritime University, Shanghai, China.
Scientific reports
|January 3, 2024
概括
一种新的静态分割符号序列法准确地从码头起重机变速箱振动信号中提取退化特征. 这种技术增强了复杂性表征,并灵敏地描述了性能退化,为健康评估提供了快速的基础.
科学领域:
- 机械工程 机械工程
- 信号处理 信号处理
- 状态监控 状态监控
背景情况:
- 传统方法难以识别由于噪音和冲击部件而导致的码头起重机变速箱振动信号中的降解模式.
- 精确的特征提取对于有效的状态监测和关键机械的预测性维护至关重要.
研究的目的:
- 为码头起重机变速箱振动信号提出一种新的降解特征提取技术.
- 为了提高信号复杂性和噪声存在的性能降低的特征.
主要方法:
- 基于基本尺度的静态分割符号序列技术的开发.
- 统一的符号化标准使用健康状况信号的平方根平均值和比例系数.
- 扩展符号集以改善信息内容和复杂性表征,特别是在高价值地区.
主要成果:
- 拟议的技术准确而灵活地描述了振动信号中的性能下降.
- 使用物流混乱序列和升降机制变速箱寿命信号的分析表明性能降低的敏感描述.
- 该方法有效地描述了非线性时间序列的复杂性.
结论:
- 静态分割符号序列技术为从噪音振动数据中提取退化特征提供了强大的解决方案.
- 该方法在计算上快速,适合实时应用.
- 这种技术为开发码头起重机变速箱先进健康评估方法提供了基础.
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