The impact resistance of composite materials — a review

Machinery health prognostics: A systematic review from data acquisition to RUL prediction

https://escholarship.org/content/qt5ns8r3fs/qt5ns8r3fs.pdf?t=pihyfp

Remaining useful life estimation in prognostics using deep convolution neural networks

A recurrent neural network based health indicator for remaining useful life prediction of bearings

The detection, diagnostic, and prognostic of bearing degradation play a key role in increasing the reliability and safety of electrical machines, especially in key industrial sectors. This paper presents a new approach that combines the Hilbert-Huang transform (HHT), the support vector machine (SVM), and the support vector regression (SVR) for the monitoring of ball bearings. The proposed approach uses the HHT to extract new heath indicators from stationary/nonstationary vibration signals able to tack the degradation of the critical components of bearings. The degradation states are detected by a supervised classification technique called SVM, and the fault diagnostic is given by analyzing the extracted health indicators. The estimation of the remaining useful life is obtained by a one-step time-series prediction based on SVR. A set of experimental data collected from degraded bearings is used to validate the proposed approach. The experimental results show that the use of the HHT, the SVM, and the SVR is a suitable strategy to improve the detection, diagnostic, and prognostic of bearing degradation.

/pdf/bearing-health-monitoring-based-on-hilbert-huang-transform-3k4ceuhtrh.pdf

Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression

The integrity of machining tools is important to maintain a high level of surface quality. The wear of the tool can lead to poor surface quality of the workpiece and even to damage of the machine. Furthermore, in some applications such as aeronautics and precision engineering, it is preferable to change the tool earlier rather than to loose the workpiece because of its high price compared to the tool's one. Thus, to maintain a high quality of the manufactured pieces, it is necessary to assess and predict the level of wear of the cutting tool. This can be done by using condition monitoring and prognostics. The aim is then to estimate and predict the amount of wear and calculate the remaining useful life (RUL) of the cutting tool. This paper presents a method for tool condition assessment and life prediction. The method is based on nonlinear feature reduction and support vector regression. The number of original features extracted from the monitoring signals is first reduced. These features are then used to learn nonlinear regression models to estimate and predict the level of wear. The method is applied on experimental data taken from a set of cuttings and simulation results are given. These results show that the proposed method is suitable for assessing the wear evolution of the cutting tools and predicting their RUL. This information can then be used by the operators to take appropriate maintenance actions.

/pdf/health-assessment-and-life-prediction-of-cutting-tools-based-474xu8qq7b.pdf

Health assessment and life prediction of cutting tools based on support vector regression

Remaining useful life estimation based on nonlinear feature reduction and support vector regression

Damage prediction in composite plates subjected to low velocity impact

In the present paper, the extended finite element method (X-FEM) is adopted to analyze vibrations of cracked plates. Mindlin’s plate theory taking into account the effects of shear deformation and rotatory inertia is included in the development of the model. First, conventional FEM without any discontinuity is carried out, then the enrichment proposed by Moes et al. (Int J Numer Methods Eng 46, 131–150, 1999) of nodal elements containing cracks is added to the FEM formulation. Numerical implementation of enriched elements by discontinuous functions is performed, and thus dynamic equations (stiffness and mass matrices) are established. A FORTRAN computer code based on the X-FEM formulation is hence developed. Rectangular and square plates containing through-edge and central cracks with different boundary conditions are considered. The subspace iteration method is used to solve the eigenvalue problem. Natural frequencies as well as the corresponding eigenfunctions are consequently calculated as a function of the crack length. The obtained results show that the X-FEM is an efficient method in the dynamic analysis of plates containing discontinuities.

Vibration analysis of cracked plates using the extended finite element method

Adhesive layers were included along the interfaces of a baseline graphite/epoxy [0 5 /90 5 /0 5 ] laminate for impact study. Impacted specimens were sectioned longitudinally and transversely for observation of the damage modes. The existence of adhesive layers resulted in the following effects: delamination was effectively suppressed up to very high impact velocities; matrix cracking in the upper lamina was greatly reduced; and the contact area appreciably increased thereby reducing the stress concentration effect. An apparent disadvantage in using adhesive layers was found; that is, the bending crack in the bottom lamina which could branch out into delamination cracks when adhesive layers Were absent tended to penetrate the middle lamina and break fibers.

Said Rechak

Papers

Health assessment and life prediction of cutting tools based on support vector regression

Remaining useful life estimation based on nonlinear feature reduction and support vector regression

Damage prediction in composite plates subjected to low velocity impact

Vibration analysis of cracked plates using the extended finite element method

Effect of Adhesive Layers on Impact Damage in Composite Laminates