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| 1 | Tunable Q-factor wavelet transform denoising with neighboring coefficients and its application to rotating machinery fault diagnosis显示文摘Fault diagnosis of rotating machinery is of great importance to the high quality products and long-term safe operation.However,the useful weak features are usually corrupted by strong background noise,thus increasing the difficulty of the feature extraction.Thereby,a novel denoising method based on the tunable Q-factor wavelet transform(TQWT)using neighboring coefficients is proposed in this article.The 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 signal.Meanwhile,neighboring coefficients denoising is adopted to avoid the overkill of conventional term-by-term thresholding techniques.Because of having the combined advantages of the two methods,the presented denoising method is more practical and effective than other methods.The 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 case.The 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. | HE WangPeng ZI YanYang CHEN BinQiang WANG Shuai HE ZhengJia | 2013 | Science China(Technological Sciences)2013，56，8： | 27 |
| 2 | A pseudo wavelet system-based vibration signature extracting method for rotating machinery fault detection显示文摘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 components.Although they can be collected via vibration measurements,the critical fault signatures are always masked by overwhelming interfering contents,therefore difficult to be identified.Moreover,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 environments.In order to address the deficiencies of DWTs,a pseudo wavelet system(PWS) is proposed based on the filter constructing strategies of wavelet tight frames.The presented PWS is implemented via a specially devised shift-invariant filterbank structure,which generates non-dyadic wavelet subbands as well as dyadic ones.The PWS offers a finer partition of the vibration signal into the frequency-scale plane.In 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 forward.SSEK is used for selecting the optimal analyzing parameters among the decomposed wavelet subbands so that the masked critical fault signatures can be explicitly recognized.The proposed method has been applied to engineering fault diagnosis cases,in which the processing results showed its effectiveness and superiority to some existing methods. | CHEN BinQiang ZHANG ZhouSuo ZI YanYang YANG ZhiBo HE ZhengJia | 2013 | Science China(Technological Sciences)2013，56，5： | 13 |
| 3 | A novel vibration modeling method for a rotating blade with breathing cracks显示文摘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 state.Therefore, 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. | XIE JingSong ZI YanYang ZHANG MingQuan LUO QinYuan | 2019 | Science China(Technological Sciences)2019，62，2： | 10 |
| 4 | A data-driven threshold for wavelet sliding window denoising in mechanical fault detection显示文摘Wavelet denoising is an effective approach to extract fault features from strong background noise.It has been widely used in mechanical fault detection and shown excellent performance.However,traditional thresholds are not suitable for nonstationary signal denoising because they set universal thresholds for different wavelet coefficients.Therefore,a data-driven threshold strategy is proposed in this paper.First,the signal is decomposed into different subbands by wavelet transformation.Then a data-driven threshold is derived by estimating the noise power spectral density in different subbands.Since the data-driven threshold is dependent on the noise estimation and adapted to data,it is more robust and accurate for denoising than traditional thresholds.Meanwhile,sliding window method is adopted to set a flexible local threshold.When this method was applied to simulation signal and an inner race fault diagnostic case of dedusting fan bearing,the proposed method has good result and provides valuable advantages over traditional methods in the fault detection of rotating machines. | CHEN YiMin ZI YanYang CAO HongRui HE ZhengJia SUN HaiLiang | 2014 | Science China(Technological Sciences)2014，57，3： | 9 |
| 5 | Construction of adaptive redundant multiwavelet packet and its application to compound faults detection of rotating machinery显示文摘It is significant to detect the fault type and assess the fault level as early as possible for avoiding catastrophic accidents.Due to diversity and complexity,the compound faults detection of rotating machinery under non-stationary operation turns to be a challenging task.Multiwavelet with two or more base functions may match two or more features of compound faults,which may supply a possible solution to compound faults detection.However,the fixed basis functions of multiwavelet transform,which are not related with the vibration signal,may reduce the accuracy of compound faults detection.Moreover,the decomposition results of multiwavelet transform not being own time-invariant is harmful to extract the features of periodical impulses.Furthermore,multiwavelet transform only focuses on the multi-resolution analysis in the low frequency band,and may leave out the useful features of compound faults.To overcome these shortcomings,a novel method called adaptive redundant multiwavelet packet(ARMP) is proposed based on the two-scale similarity transforms.Besides,the relative energy ratio at the characteristic frequency of the concerned component is computed to select the sensitive frequency bands of multiwavelet packet coefficients.The proposed method was used to analyze the compound faults of rolling element bearing.The results showed that the proposed method could enhance the ability of compound faults detection of rotating machinery. | CHEN JingLong ZI YanYang HE ZhengJia WANG XiaoDong | 2012 | Science China(Technological Sciences)2012，55，8： | 7 |
| 6 | Gearbox fault diagnosis of rolling mills using multiwavelet sliding window neighboring coefficient denoising and optimal blind deconvolution显示文摘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. | YUAN Jing HE ZhengJia ZI YanYang LIU Han | 2009 | Science China(Technological Sciences)2009，52，10： | 7 |
| 7 | The principle of second generation wavelet for milling cutter breakage detection显示文摘Performance degradation or failure of manufacturing equipment will badly influence machining quality.Because of discontinuousness of the milling process,dynamic signals produced in the milling process become non-stationary.This 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 functions.Namely,by means of the inner product operation of a signal with basis functions containing scale function and wavelet function,signal decomposition and reconstruction are obtained.Acoustic 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 support.The 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. | HE ZhengJia CAO HongRui LI Zhen ZI YanYang CHEN XueFeng | 2009 | Science China(Technological Sciences)2009，52，5： | 5 |
| 8 | Study of frequency-shifted and re-scaling stochastic resonance and its application to fault diagnosis显示文摘 | Jiyong Tan Xuefeng Chen Junying Wang Huaxin Chen Hongrui Cao Yanyang Zi Zhengjia He | 2008 | Mechanical Systems and Signal Processing2008，，3： | 3 |
| 9 | Material analysis of the fatigue mechanism of rollers in tapered roller bearings显示文摘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. | GUO Wei CAO HongRui ZI YanYang HE ZhengJia | 2018 | Science China(Technological Sciences)2018，61，7： | 2 |
| 10 | Reprogrammable 3D Mesostructures Through Compressive Buckling of Thin Films with Prestrained Shape Memory Polymer显示文摘 | Xiaogang Guo Zheng Xu Fan Zhang Xueju Wang Yanyang Zi John A. Rogers Yonggang Huang Yihui Zhang | 2018 | Acta Mechanica Solida Sinica2018，31，5： | 2 |
| 11 | Application of the EEMD method to rotor fault diagnosis of rotating machinery显示文摘 | Yaguo Lei Zhengjia He Yanyang Zi | 2008 | Mechanical Systems and Signal Processing2008，，4： | 2 |
| 12 | Application of the EEMD method to rotor fault diagnosis of rotating machinery显示文摘 | Lei Yaguo He Zhengjia Zi Yanyang | 2009 | Mechanical Systems and Signal Pro- cessing2009，23，： | 1 |
| 13 | Enhance- ment of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree com- plex wavelet transform 显示文摘 | Wang Yanxue He Zhengjia Zi Yanyang | 2010 | Mechanical Systems and Signal Processing2010，24，1： | 1 |
| 14 | Enhancement of signal denoising and multiple fault signatures detecting in rotating machinery using dual-tree complex wavelet transform显示文摘 | WANG Yanxue HE Zhengjia ZI Yanyang | 2010 | Mechanical Systems and Signal Processing2010，24，1： | 1 |
| 15 | Application of the EEMD method to rotor fault diagnosis of rotating ma- chinery显示文摘 | Lei Yaguo He Zhengjia Zi Yanyang | 2009 | Mechanical Systems and Signal Processing2009，23，4： | 1 |
| 16 | EEMD method and WNN for fault diagnosis of locomotive roller bear- ings 显示文摘 | Lei Yaguo He Zhengjia Zi Yanyang | 2011 | Expert Systems with Applications2011，3，6： | 1 |
| 17 | Rotating machinery fauh diagnosis using signal-adapted lifting scheme 显示文摘 | Zhen Li Zhengjia He Yanyang Zi | 2008 | Mechanical Systems and Signal Processing2008，22，3： | 1 |
| 18 | Multiwa-velet construction via an adaptive symmetric lifting scheme and its applications for rotating machinery fault diagnosis显示文摘 | WANG Xiaodong ZI Yanyang HE Zhengjia | 2009 | Measurement Science and Technology2009，20，04： | 1 |
| 19 | Gear fault detection using customized multiwavelet lifting schemes显示文摘 | YUAN Jing HE Zhengjia ZI Yanyang | 2010 | Mechanical Systems and Signal Processing2010，24，5： | 1 |
| 20 | Gear fault de- tection using customized muhiwavelet lifting schemes 显示文摘 | Yuan Jing He Zhengjia Zi Yanyang | 2010 | Mechanical Systems and Signal Processing2010，24，5： | 1 |
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