重叠共振补偿:一种复合故障检测方法

IF 8.9 1区 工程技术 Q1 ENGINEERING, MECHANICAL
Haiyang Pan , Zhangping Wu , Jian Cheng , Jinde Zheng , Shuchao Deng , Jinyu Tong , Long Zhang
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引用次数: 0

摘要

复合断层的各种状态特征所对应的频带具有叠加、混叠和非线性特征。传统的频带分割方法往往会破坏共振频带,从而影响复合故障特征的准确提取和分离。为了克服这一局限性,本文提出了一种基于邻域可拓因子(NEF)的邻域可拓Ramanujan分解(NERD)方法。首先,它通过NEF实现频段交叉分割,代表了一种允许相邻频段之间重叠边界的软分割方法。该方法可以在保持频带完整性的同时更准确地捕获局部特征,实现共振频带重叠的补偿。其次,NEF以信号的能量分布为参考框架,通过宏观变化率和微观稳定性指标量化重叠区域的隶属度。这种双视角方法可以更好地跨频带边界传输耦合复合故障信息,同时最大限度地减少有效信号分量的损失。此外,该方法还定义了广义Ramanujan周期聚合指数(GRPA),将故障信息可视化地呈现在过滤后的分量中,从而能够精确地提取复合故障特征。采用模拟轴承故障信号和实验数据集进行综合验证,证实了NERD方法的有效性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Overlapping resonance compensation: A composite fault detection methodology
The frequency bands corresponding to various state characteristics of composite faults typically exhibit superposition, mixing, and nonlinear characteristics. Conventional frequency band segmentation methods frequently disrupt resonant frequency bands, thereby hindering accurate extraction and separation of composite fault features. To overcome this limitation, this paper proposes a novel neighborhood extension Ramanujan decomposition (NERD) method guided by the neighborhood extension factor (NEF). Firstly, it implements frequency band cross-segmentation through NEF, representing a soft-segmentation approach that permits overlapping boundaries between adjacent frequency bands. This method can capture local features more accurately while maintaining the integrity of the frequency band and achieve compensation for overlapping resonant frequency bands. Secondly, the NEF employs the signal’s energy distribution as a reference framework, quantifying the membership degree of overlapping regions through both macroscopic rate of change and microscopic stability metrics. This dual perspective approach facilitates better transmission of coupled composite fault information across frequency band boundaries while minimizing the loss of effective signal components. Furthermore, the method defines the generalized Ramanujan periodic aggregation index (GRPA), which visualizes fault information within filtered components, thereby enabling precise extraction of composite fault features. Comprehensive validation using both simulated bearing fault signals and experimental datasets confirms the efficacy and superiority of the NERD method.
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来源期刊
Mechanical Systems and Signal Processing
Mechanical Systems and Signal Processing 工程技术-工程:机械
CiteScore
14.80
自引率
13.10%
发文量
1183
审稿时长
5.4 months
期刊介绍: Journal Name: Mechanical Systems and Signal Processing (MSSP) Interdisciplinary Focus: Mechanical, Aerospace, and Civil Engineering Purpose:Reporting scientific advancements of the highest quality Arising from new techniques in sensing, instrumentation, signal processing, modelling, and control of dynamic systems
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