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Fault diagnosis of rotor systems with breathing slant cracks based on nonlinear output frequency response functions

JOURNAL OF VIBRATION AND CONTROL 2024年第21-22期30卷 4752-4763页

作者： Li, Zhi-nong Li, Yun-long Xia, Heng-heng Chen, Shi-yao Wang, Fei Nanchang Hangkong Univ Key Lab Nondestruct Testing Minist Educ Nanchang Peoples R China Guangxi Univ Sch Mech Engn Nanning Peoples R China Nanchang Hangkong Univ Key Lab Nondestruct Testing Minist Educ 696 Fenghe South Ave Nanchang 330063 Jiangxi Peoples R China

When it comes to practical engineering, there is a high likelihood of shafts developing slant cracks due to torque transmission. These cracks exhibit breathing characteristics, repeatedly opening and closing under gravity and radial forces. To diagnose rotor systems with breathing slant cracks, the nonlinear output frequency response functions (NOFRFs) method is introduced. Firstly, a dynamic model of rotor systems with breathing slant cracks is established, and the system's frequency spectra are obtained by solving the model with different crack angles, depths, and positions. Secondly, the NOFRFs values at different orders are derived based on the NOFRFs theory. The simulation results display increased nonlinear characteristics with crack angle and depth. The system's nonlinear characteristics are stronger when cracks are closer to the disk. The <(G(3)(j omega(F)))over bar> value for the first-order is sensitive to crack angles, the <(G(4)(j4 omega(F)))over bar> value for the second-order is sensitive to crack depths, and the <(G4(j4 omega(F)))over bar> value for the fourth-order is sensitive to crack positions. As a result, the NOFRFs response at different orders can detect variations in angles, depths, and positions of the breathing slant crack. Finally, experiments are conducted on a rotor system with breathing slant cracks, and the results match those of the simulation, indicating that the NOFRFs method is feasible for identifying breathing slant cracks.

关键词： Slant crack nonlinear output frequency response functions fault diagnosis rotor system dynamics model

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Tool Condition Monitoring Based on nonlinear output frequency response functions and Multivariate Control Chart

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Journal of Dynamics, Monitoring and Diagnostics 2023年第4期2卷 243-251页

作者： Yufei Gui Ziqiang Lang Zepeng Liu Hatim Laalej Department of Automatic Control and Systems Engineering University of SheffieldSheffield S102TNUK Advanced Manufacturing Research Centre University of SheffieldSheffield S102TNUK

Tool condition monitoring(TCM)is a key technology for intelligent *** objective is to monitor the tool operation status and detect tool breakage so that the tool can be changed in time to avoid significant damage to workpieces and reduce manufacturing ***,an innovative TCM approach based on sensor data modelling and model frequency analysis has been *** from traditional signal feature-based monitoring,the data from sensors are utilized to build a dynamic process ***,the nonlinear output frequency response functions,a concept which extends the linear system frequency response function to the nonlinear case,over the frequency range of the tooth passing frequency of the machining process are extracted to reveal tool health *** order to extend the novel sensor data modelling and model frequency analysis to unsupervised condition monitoring of cutting tools,in the present study,a multivariate control chart is proposed for TCM based on the frequency domain properties of machining processes derived from the innovative sensor data modelling and model frequency *** feature dimension is reduced by principal component analysis *** the moving average strategy is exploited to generate monitoring variables and overcome the effects of *** milling experiments of titanium alloys are conducted to verify the effectiveness of the proposed approach in detecting excessive flank wear of solid carbide end *** results demonstrate the advantages of the new approach over conventional TCM techniques and its potential in industrial applications.

关键词： intelligent manufacturing multivariate control chart nonlinear Autoregressive with eXogenous Input modelling nonlinear output frequency response functions tool condition monitoring

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The analysis of nonlinear systems in the frequency domain using nonlinear output frequency response functions

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AUTOMATICA 2018年 94卷 452-457页

作者： Bayma, Rafael Suzuki Zhu, Yunpeng Lang, Zi-Qiang Univ Sheffield Dept Automat Control & Syst Engn Mappin St Sheffield S1 3JD S Yorkshire England Univ Fed Para CAMTUC Fac Elect Engn Belem Para Brazil

The nonlinear output frequency response functions (NOFRFs) are a concept which provides a new extension of the well-known concept of the frequency response Function (FRF) of linear systems to the nonlinear case. The present study introduces a NOFRFs based approach for the analysis of nonlinear systems in the frequency domain. It is well known that a nonlinear system can, under rather general conditions, be represented by a polynomial type nonlinear Auto Regressive with eXogenous input (NARX) model. From the NARX model of a nonlinear system under study, the NOFRFs based approach for the frequency analysis of nonlinear systems involves solving a set of linear difference equations known as the Associated Linear Equations (ALEs) to determine the system nonlinear output responses and then the NOFRFs of the system up to an arbitrary order of nonlinearity of interests. The results enable a representation of the frequency domain characteristics of nonlinear systems by means of a series of Bode diagram like plots that can be used for nonlinear system frequency analyses for various purposes including, for example, condition monitoring, fault diagnosis, and nonlinear modal analysis. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Volterra series Associated Linear Equations nonlinear output frequency response functions frequency domain analysis

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Feasibility study of bonding state detection of explosive composite structure based on nonlinear output frequency response functions

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STEEL AND COMPOSITE STRUCTURES 2017年第4期24卷 391-397页

作者： Si, Yue Zhang, Zhou-Suo Wang, Hong-fang Yuan, Fei-Chen Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Shaanxi Peoples R China

With the increasing application of explosive composite structure in many engineering fields, its interface bonding state detection is more and more significant to avoid catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, the concept of nonlinear output frequency response functions (NOFRFs) is introduced to detect the bonding state of explosive composite structure. The NOFRFs can describe the nonlinear characteristics of nonlinear vibrating system. Because of the presence of the bonding interface, explosive composite structure itself is a nonlinear system;when bonding interface of the structure is damaged, its dynamic characteristics show enhanced nonlinear characteristic. Therefore, the NOFRFs-based detection index is proposed as indicator to detect the bonding state of explosive composite pipes. The experimental results verify the effectiveness of the detection approach.

关键词： bonding state detection explosive composite structure nonlinear output frequency response functions

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Machinery fault diagnosis-oriented regularization for nonlinear system identification: Framework and applications

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APPLIED ACOUSTICS 2025年 231卷

作者： Zhao, Yulai Liu, Zepeng Yang, Zhiwei Han, Qingkai Ma, Hui Northeastern Univ Sch Mech Engn & Automat Shenyang 110819 Liaoning Peoples R China Newcastle Univ Sch Engn Newcastle NE1 7RU England

In this article, we propose a novel framework for machinery fault diagnosis based on nonlinear system identification, called Identification for Fault Diagnosis (I4FD) The focus and necessity of the framework is that it can mitigate the effects of external environmental changes and enhance diagnostic accuracy. The framework integrates regularized data-driven modeling and frequency analysis. During the modeling process, prior physical knowledge about the diagnostic target is incorporated through a penalty parameter, leading to fault diagnosisoriented regularization (FDoR). FDoR tailors the model specifically for fault diagnosis (FD) applications, offering new insights into FD-oriented system identification. The regularized NARX modeling in this paper does not end when a model is built by using information in a period of time, but uses the updated data for continuous dynamic modeling. After the model is identified, frequency analysis is then used to extract model-based features, which change significantly when faults occur. The effectiveness of the I4FD framework is demonstrated through simulations and real cases, highlighting its advantages over traditional methods and its industrial potential.

关键词： nonlinear system identification Regularization nonlinear output frequency response functions (NOFRFs) Fault diagnosis (FD)

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On-line condition monitoring for rotor systems based on nonlinear data-driven modelling and model frequency analysis

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nonlinear DYNAMICS 2024年第7期112卷 5439-5451页

作者： Zhao, Yulai Liu, Zepeng Zhang, Hongxu Han, Qingkai Liu, Yang Wang, Xuefei Northeastern Univ Sch Mech Engn & Automat Shenyang 110819 Liaoning Peoples R China Univ Sheffield Dept Automat Control & Syst Engn Sheffield S1 3JD England Univ Manchester Sch Engn Manchester M13 9PL England

This paper proposes a novel on-line rotor system condition monitoring approach using nonlinear data-driven modelling and model frequency analysis. First, the dynamic process model of the vibration transmission path between the vibration measurement points of two fulcrum structures is established by utilizing nonlinear data-driven modelling. Then, the unique frequency properties are extracted from the established model to reveal, in real time, the health condition of the rotor system. Finally, using the frequency properties as features, the unsupervised learning technology is applied to the on-line monitoring of the rotor system. Compared to conventional condition monitoring methods, the proposed approach can output an early warning 26 min before a shaft fracture occurs, without generating false alarms. Consequently, this approach can greatly enhance diagnostic accuracy, demonstrating its potential to contribute to the advancement of rotor system condition monitoring techniques.

关键词： Rotor systems nonlinear output frequency response functions Dynamic process model Condition monitoring

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A novel analysis method for fault diagnosis of hydro-turbine governing system

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY 2017年第2期231卷 164-171页

作者： Xia, Xin Ni, Wei Sang, Yingjun Huaiyin Inst Technol Coll Automat Huaian 223003 Jiangsu Peoples R China

The fault diagnosis of hydro-turbine governing system is important to the operation of the hydropower station and the stability of the power grid. In order to improve the diagnostic accuracy and efficiency, a novel fault diagnosis method based on nonlinear output frequency response functions and a novel identification method of nonlinear output frequency response functions have been proposed and applied to the problem of hydro-turbine governing system fault diagnostics. First, the nonlinear model of hydro-turbine governing system is built. And the fault diagnosis principles based on nonlinear output frequency response functions are also introduced. Then, the disadvantages of the traditional identification method are discussed, and a novel identification method is proposed for nonlinear output frequency response functions according to the operation characteristic of hydro-turbine governing system. Finally, simulation verification and experimental studies have been presented to demonstrate the accuracy and efficiency of the proposed fault diagnosis method. The results indicate that the proposed method is simple and practical for fault diagnosis of hydro-turbine governing system.

关键词： Hydro-turbine governing system fault diagnosis nonlinear output frequency response functions Volterra series system identification

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A novel failure analysis and diagnosis method for hydraulic-turbine generator unit

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JOURNAL OF VIBROENGINEERING 2016年第6期18卷 3568-3580页

作者： Xia, Xin Ni, Wei Huaiyin Inst Technol Coll Automat Huaian Peoples R China

The failure analysis and diagnosis of hydraulic-turbine generator unit (HGU) is important to protect the safety and stability of the electric system. But failure analysis and diagnosis for HGU is lacking of fault data, and most of the failure analysis and diagnosis methods are proposed without considering the characteristic of HGU. In this paper, a vibration dynamic modeling method for HGU is proposed by using the finite element method, and further the vibration data in different states are getting through numerical simulation. Then, the failure feature is extracted based on the nonlinear output frequency response functions (NOFRFs). Finally, a diagnosis system with Support Vector Machine (SVM) is proposed and employed for diagnosis of the HGU. The experimental results indicate that the feature which extracted from NOFRFs has a strong effect, and demonstrates that the proposed method is feasible and helpful for fault diagnosis in HGU.

关键词： hydraulic-turbine generator unit fault diagnosis finite element nonlinear output frequency response functions

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