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Material analysis of the fatigue mechanism of rollers in tapered roller bearings

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Science China(Technological Sciences) 2018年第7期61卷 1003-1011页

作者： GUO Wei CAO HongRui zi yanyang HE ZhengJia State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University

Rolling contact fatigue is the main failure mechanism of tapered roller bearings. This study investigated the fatigue mechanism of rollers in a tapered roller bearing that failed in a run-to-failure test. Roller microstructure and crack morphology were investigated through scanning electron microscopy. A microhardness test was performed to investigate the strain hardening of the roller material induced by rolling contact fatigue. Results showed that microcavities and holes are important influential factors of crack initiation and propagation. Crack propagation angle affects crack morphology and propagation mode. Material strain hardening accelerates crack growth. Furthermore, roller misalignment causes uneven hardenability and severe damage to roller ends.

关键词： rolling contact fatigue mechanism crack propagation material microstructure roller misalignment

A 3D nonlinear finite element method for the dynamic analysis of rotating rotor with a transverse crack

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Science China(Technological Sciences) 2017年第2期60卷 219-231页

作者： WANG Shuai zi yanyang WANG Yu HE ZhengJia State Key Laboratory for Manufacturing and Systems Engineering School of Mechanical Engineering Xi'an Jiaotong University Xi'an 710049 China

A general and efficient method is presented in this paper for studying the effects of unbalance on the breathing mechanism of *** on 3D finite element models combined with a nonlinear contact approach for crack modeling, the method is free from theassumption of weight-dominance and can be used to gain deep insights into the breathing mechanism of crack. In order to greatlyreduce the computational time, a complex free-interface component mode synthesis (CMS) method is employed to reduce theorder of the model. Based on the proposed method, the effects of unbalance on the breathing mechanism of crack are *** results show that the unbalance can lead to significant changes in the breathing of crack, even when the unbalance force is about an order of magnitude smaller than the self-weight. Moreover, the level and orientation of the unbalance have also remarkable effects on the breathing behaviors of crack. Besides, a new universal non-steady breathing phenomenon of crack is firstly found in this paper, which denotes that the breathing speed of a crack is fluctuated over one revolution when there exists residual unbalance in the cracked rotor.

关键词： cracked rotor breathing mechanism of crack unbalance 3D finite element model model order reduction

A novel vibration modeling method for a rotating blade with breathing cracks

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Science China(Technological Sciences) 2019年第2期62卷 333-348页

作者： XIE JingSong zi yanyang ZHANG MingQuan LUO QinYuan State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University

This paper proposes a vibration modeling method for a rotating blade with breathing cracks, considering the coupling of the centrifugal effects, the breathing effects and the crack effects. Firstly, considering the combined effects of the centrifugal stress and the bending stress, a crack breathing model for the rotating blade is proposed. Since the crack surface cannot provide the spanwise centrifugal tensile stress, an additional bending moment will be generated at the crack surface in the rotating ***, an additional bending moment caused by the centrifugal stress is then constructed. In addition, due to the discontinuity of the crack cross section, the additional stiffness caused by the centrifugal effects of the cracked blade will be smaller than that of the normal blade. Therefore, a correction coefficient of the centrifugal stiffness is built. Furthermore, based on the Lagrange equation and the assumed modal method, the vibration equation of the rotating blade with a breathing crack is established(RBC model), and a strategy is constructed for solving this vibration equation. Finally, taking the finite element model(FEM) as a reference, the vibration responses of the RBC model, the open crack model(OC) and the bilinear crack model(BC) are compared. The necessity of the RBC model is illustrated, and the accuracy of the RBC model is verified. The RBC model is a computationally efficient alternative to the finite element analysis for the rotating cracked blade. It can provide an important tool for the vibration modeling and the vibration analysis of the rotating shaft-disk-blade system with cracked blades.

关键词： vibration modeling rotating blade crack breathing model centrifugal effects

Construction of adaptive redundant multiwavelet packet and its application to compound faults detection of rotating machinery

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Science China(Technological Sciences) 2012年第8期55卷 2083-2090页

作者： CHEN JingLong zi yanyang HE ZhengJia WANG XiaoDong State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong UniversityXi'an 710049China Technology Center CNPC Logging Co.Xi'an 710077China

It is significant to detect the fault type and assess the fault level as early as possible for avoiding catastrophic *** to diversity and complexity,the compound faults detection of rotating machinery under non-stationary operation turns to be a challenging *** with two or more base functions may match two or more features of compound faults,which may supply a possible solution to compound faults ***,the fixed basis functions of multiwavelet transform,which are not related with the vibration signal,may reduce the accuracy of compound faults ***,the decomposition results of multiwavelet transform not being own time-invariant is harmful to extract the features of periodical ***,multiwavelet transform only focuses on the multi-resolution analysis in the low frequency band,and may leave out the useful features of compound *** overcome these shortcomings,a novel method called adaptive redundant multiwavelet packet(ARMP) is proposed based on the two-scale similarity ***,the relative energy ratio at the characteristic frequency of the concerned component is computed to select the sensitive frequency bands of multiwavelet packet *** proposed method was used to analyze the compound faults of rolling element *** results showed that the proposed method could enhance the ability of compound faults detection of rotating machinery.

关键词： adaptive redundant multiwavelet packet compound faults detection feature extraction rolling element bearing

Gearbox fault diagnosis of rolling mills using multiwavelet sliding window neighboring coefficient denoising and optimal blind deconvolution

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Science China(Technological Sciences) 2009年第10期52卷 2801-2809页

作者： YUAN Jing HE ZhengJia zi yanyang LIU Han State Key Laboratory for Manufacturing Systems Engineering School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China Shanghai Baosteel Industry Inspection Corporation Baosteel Group CorporationShanghai 200122China

Fault diagnosis of rolling mills, especially the main drive gearbox, is of great importance to the high quality products and long-term safe operation. However, the useful fault information is usually submerged in heavy background noise under the severe condition. Thereby, a novel method based on multiwavelet sliding window neighboring coefficient denoising and optimal blind deconvolution is proposed for gearbox fault diagnosis in rolling mills. The emerging multiwavelets can seize the important signal processing properties simultaneously. Owing to the multiple scaling and wavelet basis functions, they have the supreme possibility of matching various features. Due to the periodicity of gearbox signals, sliding window is recommended to conduct local threshold denoising, so as to avoid the "overkill" of conventional universal thresholding techniques. Meanwhile, neighboring coefficient denoising, considering the correlation of the coefficients, is introduced to effectively process the noisy signals in every sliding window. Thus, multiwavelet sliding window neighboring coefficient denoising not only can perform excellent fault extraction, but also accords with the essence of gearbox fault features. On the other hand, optimal blind deconvolution is carried out to highlight the denoised features for operators' easy identification. The filter length is vital for the effective and meaningful results. Hence, the foremost filter length selection based on the kurtosis is discussed in order to full benefits of this technique. The new method is applied to two gearbox fault diagnostic cases of hot strip finishing mills, compared with multiwavelet and scalar wavelet methods with/without optimal blind deconvolution. The results show that it could enhance the ability of fault detection for the main drive gearboxes.

关键词： multiwavelet denoising blind deconvolution gearbox fault diagnosis rolling mill

Sparse Autoencoder-based Multi-head Deep Neural Networks for Machinery Fault Diagnostics with Detection of Novelties

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Chinese Journal of Mechanical Engineering 2021年第3期34卷 146-157页

作者： Zhe Yang Dejan Gjorgjevikj Jianyu Long yanyang zi Shaohui Zhang Chuan Li School of Mechanical Engineering Dongguan University of TechnologyDongguan 523808China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China Faculty of Computer Science and Engineering Ss.Cyril and Methodius UniversitySkopjeMacedonia

Supervised fault diagnosis typically assumes that all the types of machinery failures are ***,in practice unknown types of defect,i.e.,novelties,may occur,whose detection is a challenging *** this paper,a novel fault diagnostic method is developed for both diagnostics and detection of *** this end,a sparse autoencoder-based multi-head Deep Neural Network(DNN)is presented to jointly learn a shared encoding representation for both unsupervised reconstruction and supervised classification of the monitoring *** detection of novelties is based on the reconstruction ***,the computational burden is reduced by directly training the multi-head DNN with rectified linear unit activation function,instead of performing the pre-training and fine-tuning phases required for classical *** addressed method is applied to a benchmark bearing case study and to experimental data acquired from a delta 3D *** results show that its performance is satisfactory both in detection of novelties and fault diagnosis,outperforming other state-of-the-art *** research proposes a novel fault diagnostics method which can not only diagnose the known type of defect,but also detect unknown types of defects.

关键词： Deep learning Fault diagnostics Novelty detection Multi-head deep neural network Sparse autoencoder

Tunable Q-factor wavelet transform denoising with neighboring coefficients and its application to rotating machinery fault diagnosis

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Science China(Technological Sciences) 2013年第8期56卷 1956-1965页

作者： HE WangPeng zi yanyang CHEN BinQiang WANG Shuai HE ZhengJia School of Mechanical Engineering Xi'an Jiaotong University State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University

Fault diagnosis of rotating machinery is of great importance to the high quality products and long-term safe ***,the useful weak features are usually corrupted by strong background noise,thus increasing the difficulty of the feature ***,a novel denoising method based on the tunable Q-factor wavelet transform(TQWT)using neighboring coefficients is proposed in this *** emerging TQWT possesses excellent properties compared with the conventional constant-Q wavelet transforms,which can tune Q-factor according to the oscillatory behavior of the ***,neighboring coefficients denoising is adopted to avoid the overkill of conventional term-by-term thresholding *** of having the combined advantages of the two methods,the presented denoising method is more practical and effective than other *** proposed method is applied to a simulated signal,a rolling element bearing with an outer race defect from antenna transmission chain and a gearbox fault detection *** processing results demonstrate that the proposed method can successfully identify the fault features,showing that this method is more effective than the conventional wavelet thresholding denoising methods,term-by-term TQWT denoising schemes and spectral kurtosis.

关键词： tunable Q-factor wavelet transform(TQWT) signal denoising neighboring coefficients fault diagnosis

A pseudo wavelet system-based vibration signature extracting method for rotating machinery fault detection

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Science China(Technological Sciences) 2013年第5期56卷 1294-1306页

作者： CHEN BinQiang ZHANG ZhouSuo zi yanyang YANG ZhiBo HE ZhengJia School of Mechanical Engineering Xi'an Jiaotong University State Key Laboratory for Manufacturing and System Engineering Xi'an Jiaotong University

The rotating machinery,as a typical example of large and complex mechanical systems,is prone to diversified sorts of mechanical faults,especially on their rotating *** they can be collected via vibration measurements,the critical fault signatures are always masked by overwhelming interfering contents,therefore difficult to be ***,owing to the distinguished time-frequency characteristics of the machinery fault signatures,classical dyadic wavelet transforms(DWTs) are not perfect for detecting them in noisy *** order to address the deficiencies of DWTs,a pseudo wavelet system(PWS) is proposed based on the filter constructing strategies of wavelet tight *** presented PWS is implemented via a specially devised shift-invariant filterbank structure,which generates non-dyadic wavelet subbands as well as dyadic *** PWS offers a finer partition of the vibration signal into the frequency-scale *** addition,in order to correctly identify the essential transient signatures produced by the faulty mechanical components,a new signal impulsiveness measure,named spatial spectral ensemble kurtosis(SSEK),is put *** is used for selecting the optimal analyzing parameters among the decomposed wavelet subbands so that the masked critical fault signatures can be explicitly *** proposed method has been applied to engineering fault diagnosis cases,in which the processing results showed its effectiveness and superiority to some existing methods.

关键词： rotating machinery shift-invariant non-dyadic decomposition vibration measurement signal impulsiveness

The principle of second generation wavelet for milling cutter breakage detection

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Science China(Technological Sciences) 2009年第5期52卷 1312-1322页

作者： HE ZhengJia CAO HongRui LI Zhen zi yanyang CHEN XueFeng State Key Laboratory for Manufacturing Systems Engineering School of Mechanical EngineeringXi’an Jiaotong UniversityXi’an 710049China

Performance degradation or failure of manufacturing equipment will badly influence machining *** of discontinuousness of the milling process,dynamic signals produced in the milling process become *** paper indicates that the essence of SGW(second generation wavelet) transform in non-stationary signal processing is the mathematics principle of inner product transform of a dynamic signal with basis ***,by means of the inner product operation of a signal with basis functions containing scale function and wavelet function,signal decomposition and reconstruction are *** emission signals generated in the milling processes of a CNC machine were analyzed by using the basis functions of SGW which are oscillation,decay and compact *** features of end milling cutter breakage have been extracted,and the influences on machining surface quality have been identified effectively,which provide scientific bases for fault diagnosis,error tracing and quality control.

关键词： SGW inner product algorithm cutter breakage machining quality