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首页> 外文会议>Sensors and systems for reliability, safety and affordability >ROTATING MACHINERY DIAGNOSIS USING SYNCHRO-SQUEEZING TRANSFORM BASED FEATURE ANALYSIS
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ROTATING MACHINERY DIAGNOSIS USING SYNCHRO-SQUEEZING TRANSFORM BASED FEATURE ANALYSIS

机译：基于同步压缩变换的特征分析旋转机械诊断

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A powerful signal decomposition tool named Synchro-squeezing transform (SST) has recently emerged in the context of non-stationary signal processing. Founded upon the premise of time-frequency (TF) reassignment, its basic objective is to provide a sharper representation of signals in the TF plane. Additionally it can also extract the individual components of a non-stationary multi-component signal, akin to empirical mode decomposition (EMD). The rich mathematical structure based on continuous wavelet transform (CWT) makes SST attractive for rotating machinery diagnosis, through which multiple amplitude-modulated and frequency-modulated signals embedded in noise can be extracted. This work utilizes the decomposing power of synchro-squeezing transform to extract the IMFs from gear and bearing signals, followed by the application of standard rotating machinery condition indicators. This approach promises improved prognostic power than that can be achieved by applying condition indicators directly to the inherently complex data. The efficacy and the robustness of the algorithm are demonstrated with the aid of practical experimental data obtained from a helicopter gearbox test facility in Trenton, New Jersey, and also from seeded bearing fault tests, called the helicopter integrated diagnostic system (HIDS), carried out using an iron bird test stand (SH - 60) at Naval Air Warfare Center (NAWC) - Trenton, and SH-60B/F flight vehicles at NAWC-patuxent river.
机译：最近在非平稳信号处理的背景下出现了一种功能强大的信号分解工具，称为同步压缩变换（SST）。建立在时频（TF）重新分配的前提下，其基本目标是在TF平面中提供更清晰的信号表示。此外，它还可以提取非平稳多分量信号的各个分量，类似于经验模式分解（EMD）。基于连续小波变换（CWT）的丰富数学结构使SST对旋转机械诊断具有吸引力，通过它可以提取嵌入在噪声中的多个幅度调制和频率调制信号。这项工作利用同步压缩变换的分解能力从齿轮和轴承信号中提取IMF，然后应用标准的旋转机械状态指示器。与通过直接将条件指标应用于固有的复杂数据所获得的方法相比，这种方法有望提高预后能力。借助从新泽西州特伦顿的直升机变速箱测试设施以及从播种的轴承故障测试（称为直升机集成诊断系统（HIDS））获得的实际实验数据，证明了该算法的有效性和鲁棒性。在特伦顿海军空战中心（NAWC）使用铁鸟试验台（SH-60），并在NAWC-patuxent河使用SH-60B / F飞行器。

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