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research-article

Nonlinear Squeezing Time-Frequency Transform and Application in Rotor Rub-Impact Fault Diagnosis

[+] Author and Article Information
Shibin Wang

State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, P.R. China
wangshibin2008@gmail.com

Laihao Yang

State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, P.R. China
yanglaihao2016@163.com

Xuefeng Chen

State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, P.R. China
chenxf@mail.xjtu.edu.cn

Chaowei Tong

State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, P.R. China
tongchaowei@foxmail.com

Baoqing Ding

State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, P.R. China
dbq.900127@stu.xjtu.edu.cn

Jiawei Xiang

Zhejiang Provincial Key Laboratory of Laser Processing Robot/Key Laboratory of Laser Precision Processing & Detection, Wenzhou, Zhejiang, P.R. China
wxw8627@163.com

1Corresponding author.

ASME doi:10.1115/1.4036993 History: Received January 12, 2017; Revised May 07, 2017

Abstract

Vibration signal analysis has been proved as an effective tool for condition monitoring and fault diagnosis for rotating machines in the manufacturing process. The presence of the rub-impact fault in rotor systems results in vibration signals with fast oscillating periodic instantaneous frequency (IF). In this paper, a novel method for rotor rub-impact fault diagnosis based on nonlinear squeezing time-frequency transform (NSquTFT) is proposed. Firstly, a dynamic model of rub-impact rotor system is investigated to quantitatively reveal the periodic oscillation behavior of the IF of vibration signals. Secondly, the theoretical analysis for the NSquTFT is conducted to prove that the NSquTFT is suitable for signals with fast varying IF, and the method for rotor rub-impact fault diagnosis based on the NSquTFT is presented. Through a dynamic simulation signal, the effectiveness of the NSquTFT in extracting the fast oscillating periodic IF is verified. The proposed method is then applied to analyze an experimental vibration signal collected from a test rig and a practical vibration signal collected from a dual-rotor turbofan engine for rotor rub-impact fault diagnosis. Comparisons are throughout conducted to evaluate the effectiveness of the proposed method by using Hilbert-Huang transform, wavelet-based synchrosqueezing transform, and other methods. The application and comparison results show that the fast oscillating periodic IF of the vibration signals caused by rotor rub-impact faults can be better extracted by the proposed method.

Copyright (c) 2017 by ASME
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