A novel method to aging state recognition of viscoelastic sandwich structures

ZhouSuo Zhang,Jinxiu Qu,Xue Luo,Bing Li,Jinpeng Wen 국제구조공학회 2016 Steel and Composite Structures, An International J Vol.21 No.6

Viscoelastic sandwich structures (VSSs) are widely used in mechanical equipment, but in the service process, they always suffer from aging which affect the whole performance of equipment. Therefore, aging state recognition of VSSs is significant to monitor structural state and ensure the reliability of equipment. However, nonstationary vibration response signals and weak state change characteristics make this task challenging. This paper proposes a novel method for this task based on adaptive second generation wavelet packet transform (ASGWPT) and multiwavelet support vector machine (MWSVM). For obtaining sensitive feature parameters to different structural aging states, the ASGWPT, its wavelet function can adaptively match the frequency spectrum characteristics of inspected vibration response signal, is developed to process the vibration response signals for energy feature extraction. With the aim to improve the classification performance of SVM, based on the kernel method of SVM and multiwavelet theory, multiwavelet kernel functions are constructed, and then MWSVM is developed to classify the different aging states. In order to demonstrate the effectiveness of the proposed method, different aging states of a VSS are created through the hot oxygen accelerated aging of viscoelastic material. The application results show that the proposed method can accurately and automatically recognize the different structural aging states and act as a promising approach to aging state recognition of VSSs. Furthermore, the capability of ASGWPT in processing the vibration response signals for feature extraction is validated by the comparisons with conventional second generation wavelet packet transform, and the performance of MWSVM in classifying the structural aging states is validated by the comparisons with traditional wavelet support vector machine.

Early bolt looseness state identification via generalized variational mode decomposition and similarity index

Yanfei Guo,ZhouSuo Zhang,Wenzhan Yang,Jianbin Cao,Teng Gong 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.3

A novel method for early looseness state identification of bolted joint beams is proposed in this paper based on generalized variational mode decomposition (GVMD) and a similarity index. In the proposed method vibration signals are decomposed by GVMD, which has the property of the multiscale and fixed-frequency decomposition. To effectively extract the desired modes, the frequency band allocation is designed through flexibly defining scale parameters and prior center frequencies according to the characteristics of the signal itself and real needs. A new similarity index is formed based on the centroid frequency ratio of sensitive vibration modes to reliably identify early looseness state. The effectiveness of the proposed method is verified by impulse experiments of bolted joint transverse beam and bolted joint vertical beam. The results indicate that compared with other methods, the proposed method can effectively identify the early looseness state of the bolted joint beams, and has a good repeatability.

State detection of explosive welding structure by dual-tree complex wavelet transform based permutation entropy

Yue Si,ZhouSuo Zhang,Wei Cheng,FeiChen Yuan 국제구조공학회 2015 Steel and Composite Structures, An International J Vol.19 No.3

Recent years, explosive welding structures have been widely used in many engineering fields. The bonding state detection of explosive welding structures is significant to prevent unscheduled failures and even catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, a new method called dual-tree complex wavelet transform based permutation entropy (DTCWT-PE) is proposed to detect bonding state of such structures. Benefiting from the complex analytical wavelet function, the dual-tree complex wavelet transform (DTCWT) has better shift invariance and reduced spectral aliasing compared with the traditional wavelet transform. All those characters are good for characterizing the vibration response signals. Furthermore, as a statistical measure, permutation entropy (PE) quantifies the complexity of non-stationary signals through phase space reconstruction, and thus it can be used as a viable tool to detect the change of bonding state. In order to more accurate identification and detection of bonding state, PE values derived from DTCWT coefficients are proposed to extract the state information from the vibration response signal of explosive welding structure, and then the extracted PE values serve as input vectors of support vector machine (SVM) to identify the bonding state of the structure. The experiments on bonding state detection of explosive welding pipes are presented to illustrate the feasibility and effectiveness of the proposed method.

Investigations of denoising source separation technique and its application to source separation and identification of mechanical vibration signals

Cheng, Wei,Zhang, Zhousuo,Lee, Seungchul,He, Zhengjia SAGE Publications 2014 Journal of vibration and control Vol.20 No.14

<P>A novel vibration source separation and identification method using the denoising source separation (DSS) technique is proposed for the mixed mechanical vibration signals from engines in ships. Denoising source separation enables us to extract the source signals from the mixed signals without prior knowledge of sources and their mixing mode, and thus the important source information extracted by DSS can be used to monitor or actively control engine noises. Different denoising functions such as energy, skew, kurtosis, and tangential functions in DSS are applied to both simulation studies and experimental data to evaluate their separating performances. The tangential function provides the best outperformance with both numerical study and engineering application. In addition, the effectiveness of the proposed DSS method is validated by correlation analysis and the frequency marker tracking method.</P>

Finite element analysis and mathematical characterization of contact pressure distribution in bolted joints

Jianbin Cao,Zhousuo Zhang 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.10

Quantitative characterization of contact pressure distribution in bolted joints directly influences the calculation accuracy of connection stiffness. In this paper, a three-dimensional finite element model of the bolted joints is established using the software ANSYS, and pretension force and contact between the joint components are accommodated in the model. Then, parametric studies are carried out to investigate the effects of the material properties, preloads, bolt sizes, grip lengths and hole clearances on the contact pressure distribution. According to the finite element analysis results, a polynomial equation system is derived for mathematical representation of contact pressure distribution in bolted joints. Furthermore, the conical envelope angle used in the mathematical characterization is identified for the bolted joints with different bolt sizes and grip lengths. Finally, an experimental platform is constructed for the measurement of contact pressure distribution, and then the applicability of mathematical characterization is validated by comparison with a series of experiment results.

Sparsity maximization nonlinear blind deconvolution and its application in identification of satellite microvibration sources

Teng Gong,ZhouSuo Zhang,Xin Luo,Jianbin Cao,Yanfei Guo 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.1

In this study, sparsity maximization nonlinear blind deconvolution (NBD) is proposed to identify the vibration sources of satellite systems from mixed vibration signals. The proposed algorithm decomposes NBD into two independent stages, namely, nonlinear compensation and blind deconvolution. Since nonlinear distortion weakens the sparsity of the observed signals, sparsity maximization is introduced to the nonlinear compensation stage. In the blind deconvolution stage, the blind deconvolution algorithm with reference is used to separate the source signals. The proposed algorithm can improve the accuracy of source signal extraction from nonlinear mixed signals of complex mechanical systems. The effectiveness of the proposed method is verified through simulations. An experimental system of aluminum cabin structure is built based on the satellite’s cabin structure. Results show that the proposed algorithm can successfully realize the identification of source signals.

Non uniform virtual material modeling on contact interface of assembly structure with bolted joints

Jianbin Cao,Zhousuo Zhang,Wenzhan Yang,Yanfei Guo 국제구조공학회 2019 Structural Engineering and Mechanics, An Int'l Jou Vol.72 No.5

Accurate modeling of contact interface in bolted joints is crucial in predicting the dynamic behavior for bolted assemblies under external load. This paper presents a contact pressure distribution based non-uniform virtual material method to describe the joint interface of assembly structure, which is connected by sparsely distributed multi-bolts. Firstly, the contact pressure distribution of bolted joints is obtained by the nonlinear static analysis in the finite element software ANSYS. The contact surface around bolt hole is divided into several sub-layers, and contact pressure in each sub-layer is thought to be evenly. Then, considering multi-asperity contact at the micro perspective, the relationship between contact pressure and interfacial virtual material parameters for each sub-layer is established by using the fractal contact theory. Finally, an experimental platform for the dynamic characteristics testing of a beam lap structure with double-bolted joint is constructed to validate the efficiency of proposed method. It is found that the theoretical results are in good agreement with experimental results by impact response in both time- and frequency-domain, and the relative errors of the first four natural frequencies are less than 1%. Furthermore, the presented model is used to examine the effect of rough contact surface on dynamic characteristics of bolted joint.

Inhomogeneous bonding state modeling for vibration analysis of explosive clad pipe

Jianbin Cao,Zhousuo Zhang,Yanfei Guo,Teng Gong 국제구조공학회 2019 Steel and Composite Structures, An International J Vol.31 No.3

Early detection of damage bonding state such as insufficient bonding strength and interface partial contact defect for the explosive clad pipe is crucial in order to avoid sudden failure and even catastrophic accidents. A generalized and efficient model of the explosive clad pipe can reveal the relationship between bonding state and vibration characteristics, and provide foundations and priory knowledge for bonding state detection by signal processing technique. In this paper, the slender explosive clad pipe is regarded as two parallel elastic beams continuously joined by an elastic layer, and the elastic layer is capable to describe the non-uniform bonding state. By taking the characteristic beam modal functions as the admissible functions, the Rayleigh-Ritz method is employed to derive the dynamic model which enables one to consider inhomogeneous system and any boundary conditions. Then, the proposed model is validated by both numerical results and experiment. Parametric studies are carried out to investigate the effects of bonding strength and the length of partial contact defect on the natural frequency and forced response of the explosive clad pipe. A potential method for identifying the bonding quality of the explosive clad pipe is also discussed in this paper.