Rub-Impact Fault Diagnosis of Rotating Machinery Based on 1-D Convolutional Neural Networks

Wu, Xinya; Peng, Zhike; Jishun, Ren; Cheng, Changming; Wang, Dong

doi:10.1109/jsen.2019.2944157

Cited by 45 publications

(21 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ma et al [23] proposed a multi-objective optimization method to analyze the vibration attenuation effects of the squeeze film damper parameters on the dynamic response of the system. It was found that in the misalignmentrubbing coupling fault, the amplitude of the fundamental frequency reduced by 7.4%, the amplitude of 2× the fundamental frequency dropped by 51.5%, and the amplitude of 3× the fundamental frequency reduced by 16.8%. Their study provided a theoretical reference for vibration control and the optimal design of rotating machinery.…”

Section: Introductionmentioning

confidence: 99%

“…Researchers have strived to understand the rub-impact fault, for example, exploring the fault mechanism [8][9][10], the fault feature extraction method [11][12][13], source localization [14,15], and intelligent fault diagnosis [16,17], etc. These studies contributed to the development of rub-impact fault diagnosis and to practical applications.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Study on a Fault Mitigation Scheme for Rub-Impact of an Aero-Engine Based on NiTi Wires

Pan

Liu³

et al. 2022

Sensors

View full text Add to dashboard Cite

The aim of this study was to solve the frequently occurring rotor-stator rub-impact fault in aero-engines without causing a significant reduction in efficiency. We proposed a fault mitigation scheme, using shape memory alloy (SMA) wire, whereby the tip clearance between the rotor and the stator is adjusted. In this scheme, an acoustic emission (AE) sensor is utilized to monitor the rub-impact fault. An active control actuator is designed with pre-strained two-way SMA wires, driven by an electric current via an Arduino control board, to mitigate the rub-impact fault once it occurs. In order to investigate the feasibility of the proposed scheme, a series of tests on the material properties of NiTi wires, including heating response rate, ultimate strain, free recovery rate, and restoring force, were carried out. A prototype of the actuator was designed, manufactured, and tested under various conditions. The experimental result verifies that the proposed scheme has the potential to mitigate or eliminate the rotor-stator rub-impact fault in aero-engines.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Study on a Fault Mitigation Scheme for Rub-Impact of an Aero-Engine Based on NiTi Wires

Pan

Liu³

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…e steam turbine rotor plays an important role in transforming thermal energy into mechanical energy. In a highspeed rotating working station, any defect on the rotor will affect the safe running and even cause serious accidents [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Study on Intelligent Diagnosis of Rotor Fault Causes with the PSO-XGBoost Algorithm

Gu¹,

Wang

Qian

et al. 2021

Mathematical Problems in Engineering

View full text Add to dashboard Cite

On basis of fault categories detection, the diagnosis of rotor fault causes is proposed, which has great contributions to the field of intelligent operation and maintenance. To improve the diagnostic accuracy and practical efficiency, a hybrid model based on the particle swarm optimization-extreme gradient boosting algorithm, namely, PSO-XGBoost is designed. XGBoost is used as a classifier to diagnose rotor fault causes, having good performance due to the second-order Taylor expansion and the explicit regularization term. PSO is used to automatically optimize the process of adjusting the XGBoost’s parameters, which overcomes the shortcomings when using the empirical method or the trial-and-error method to adjust parameters of the XGBoost model. The hybrid model combines the advantages of the two algorithms and can diagnose nine rotor fault causes accurately. Following diagnostic results, maintenance measures referring to the corresponding knowledge base are provided intelligently. Finally, the proposed PSO-XGBoost model is compared with five state-of-the-art intelligent classification methods. The experimental results demonstrate that the proposed method has higher diagnostic accuracy and practical efficiency in diagnosing rotor fault causes.

show abstract

“…19 Studies have also been carried out to see the vibration response under single-point rubbing 20 and multiple-point rubbing. 21 Wu et al 22 applied the one-dimensional (1D) convolutional neural network (CNN) for finding rub defect of turbine rotor. From the study, it has been found that rotor rubbing excites harmonics of rotor speed and natural frequency.…”

Section: Introductionmentioning

confidence: 99%

A novel health indicator developed using filter-based feature selection algorithm for the identification of rotor defects

Kumar

Gandhi

Liu

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

View full text Add to dashboard Cite

In this work, a novel health indicator is developed for the identification of rotor defects. The indicator is developed by extracting features from vibration data acquired from horizontal and vertical directions of rotors. A total of 38 features were initially extracted from time-domain signal, frequency-domain signal, and time–frequency representation. Out of many features, six most important features were selected using filter-based feature selection process. Thereafter, important features were fused together using manifold learning to develop health indicator. The developed indicator is used to identify misalignments (angular misalignment and parallel misalignment), rub, and unbalance. The major benefit of the proposed method is that it not only indicates the presence of defect in the rotor but also indicates the severity of defect. The experimental study presented in this article justifies that the proposed method is sensitive to the increasing levels of horizontal and angular misalignment and unbalance. The developed indicator is sensitive enough to indicate the presence of rub.

show abstract

Rub-Impact Fault Diagnosis of Rotating Machinery Based on 1-D Convolutional Neural Networks

Cited by 45 publications

References 33 publications

Study on a Fault Mitigation Scheme for Rub-Impact of an Aero-Engine Based on NiTi Wires

Study on a Fault Mitigation Scheme for Rub-Impact of an Aero-Engine Based on NiTi Wires

Study on Intelligent Diagnosis of Rotor Fault Causes with the PSO-XGBoost Algorithm

A novel health indicator developed using filter-based feature selection algorithm for the identification of rotor defects

Contact Info

Product

Resources

About