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

We present a new algorithm for manifold learning and nonlinear dimensionality reduction. Based on a set of unorganized da-ta points sampled with noise from a parameterized manifold, the local geometry of the manifold is learned by constructing an approxi-mation for the tangent space at each point, and those tangent spaces are then aligned to give the global coordinates of the data pointswith respect to the underlying manifold. We also present an error analysis of our algorithm showing that reconstruction errors can bequite small in some cases. We illustrate our algorithm using curves and surfaces both in 2D/3D Euclidean spaces and higher dimension-al Euclidean spaces. We also address several theoretical and algorithmic issues for further research and improvements.

Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment

https://escholarship.org/content/qt4999765n/qt4999765n.pdf?t=psy2c4

Multi-Layer domain adaptation method for rolling bearing fault diagnosis

A review of stochastic resonance in rotating machine fault detection

Fault diagnosis of single-phase induction motor based on acoustic signals

Investigation on Potential Barrier of Terminal Pinned Schottky Junction

Optimal Design of PMSLM Based on Extremum Robust Domain Characteristic

To improve the bandwidth and thrust performance of permanent magnet synchronous linear motor (PMSLM), from the perspective of motor structure design, this article proposes a high-accuracy and fast-calculation inductance model of centralized winding based on analytic kernel-embedded elastic-net regression (AKER) to establish a comprehensive analytical model of PMSLM performance. A stochastic fractal search (SFS) algorithm is introduced to optimize the comprehensive performances of PMSLM. First, Neumann's formula of integral is used to establish the equivalent inductance analytical model (EIAM) for the three-phase winding of PMSLM, and the analytic kernel is constructed based on the EIAM. In combination with the finite element simulation samples of inductance, the analytical kernel is embedded into the elastic-net regression to establish the inductance model of high efficiency, namely AKER, and compared with the finite element mode (FEM), EIAM and other advanced methods, the superiority of AKER is verified from the accuracy and time cost. Then, based on the proposed AKER inductance model, the current and voltage equations of PMSLM are decoupled in the two-phase rotating coordinate system to establish the comprehensive analysis model of the PMSLM performance. Based on the comprehensive model, the optimization function of PMSLM is constructed, and the SFS algorithm is introduced to solve the function iteratively. Finally, the effectiveness of the proposed modeling and optimization method is verified by FEM-based control simulation and prototype experiment, respectively.

Thrust Bandwidth Modeling and Optimization of PMSLM Based on Analytic Kernel-Embedded Elastic-Net Regression

Diamond Single Crystal-Polycrystalline Hybrid Microchannel Heat Sink Strategy for Directional Heat Dissipation of Hot Spots in Power Devices

The paper presents a rapid and accurate mover position detection method for permanent magnet synchronous linear motors (PMSLMs). Based on sinusoidal fringe pattern and machine visual method, a mover position detection system is established, and sequence of 2D fringe images with the information of mover position are recorded by a high-speed camera instantaneously. The 2D fringes images are converted into 1D curves with integer fringe periods to reduce the time delay and suppress the spectral leakage of Fourier transform. Fourier phase analysis is used to retrieve the phase evolution and the displacement can be calculated according to the fringe width and system calibration. Finally, simulations and experiments validate the superiority and reliability of the method.

Jiwen Zhao

Papers

Investigation on Potential Barrier of Terminal Pinned Schottky Junction

Optimal Design of PMSLM Based on Extremum Robust Domain Characteristic

Thrust Bandwidth Modeling and Optimization of PMSLM Based on Analytic Kernel-Embedded Elastic-Net Regression

Diamond Single Crystal-Polycrystalline Hybrid Microchannel Heat Sink Strategy for Directional Heat Dissipation of Hot Spots in Power Devices

Mover Position Detection for PMSLM Based on Sinusoidal Fringe Pattern and Fourier Phase Analysis