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

Enhanced conversion efficiency of vacancy-related color centers in diamonds grown on a patterned metal surface by chemical vapor deposition

To solve the problem that both analytical model (AM) and finite element model are difficult to give consideration to the calculation accuracy and efficiency at the same time in motor optimization work, a novel Lasso regression with the embedded AM, called EAM-LR, is proposed to quickly and accurately calculate the thrust performance of the permanent magnet synchronous linear motor (PMSLM) in this article. First, the thrust performances of PMSLM are analyzed by the AM to determine the variation range of structural design parameters. Based on the variation range, a finite-element sample database is established. Then, combined with the finite-element sample database, the analytical mapping functions derived from AM, are integrated into Lasso regression to establish EAM-LR. The accuracy of EAM-LR was verified by comparison with AM, traditional lasso regression, and well-known extreme learning machine. Finally, combined with the EAM-LR, the chaotic golden section algorithm is introduced to search the optimal structure parameters of PMSLM, and the control simulation and prototype experiment prove the effectiveness of the proposed method.

Thrust Performance Improvement of PMSLM Based on Lasso Regression With Embedded Analytical Model

Reduction of the spatial harmonics of back electromotive force(EMF) is a useful way to reduce thrust ripple of permanent magnet linear synchronous motor (PMLSM). In this study, a method of v-skewing in the coils is proposed to reduce the harmonics to suppress thrust ripple in the PMLSM. The thrust and the harmonic are generated in a double-sided PMLSM model. The 3-D finite element method (FEM) is used to build the PMLSM model in consideration of the effect of the v-skewing. Motor platform and testing platform are also built to conduct experimental verification. Simulation results are compared with experiment values. The results indicate that the proposed method is effective for reduction of thrust ripple in double secondary PMSLM.

Thrust ripple reduction according to coil arrangement in PMLSM with double secondary side

Polymer-based thermally conductive materials are preferred for heat dissipation owing to their low density, flexibility, low cost, and easy processing. Researchers have been trying to develop a polymer-based composite film with excellent thermal conductivity (TC), mechanical strength, thermal stability, and electrical properties. However, synergistically achieving these properties in a single material is still a challenge. To address the above requirements, we prepared poly(diallyldimethylammonium chloride)-functionalized nanodiamond (ND@PDDA)/aramid nanofiber (ANF) composite films using a self-assembly strategy. Owing to a strong interfacial interaction arising from electrostatic attraction, ND particles attract strongly along the ANF axis to form ANF/ND "core-sheath" arrangements. These assemblies self-construct three-dimensional thermally conductive networks through ANF gelation precipitation, which was analyzed as the key parameter for the realization of high thermal performances. The as-prepared ND@PDDA/ANF composite films exhibited high in-plane and through-plane TCs up to 30.99 and 6.34 W/m·K, respectively, at a 50 wt % functionalized ND loading, representing the optimal values among all previously reported polymer-based electrical insulating composite films. Furthermore, the nanocomposites also achieved other properties necessary for realistic applications, such as outstanding mechanical properties, excellent thermal stability, ultra-low thermal expansion coefficient, excellent electrical insulation, low dielectric constant, low dielectric loss, and outstanding flame retardancy. Thus, this excellent comprehensive performance enables the ND@PDDA/ANF composite films to be used as advanced multifunctional nanocomposites in thermal management, flexible electronics, and intelligent wearable equipment.

Fabrication of High Thermal Conductivity Nanodiamond/Aramid Nanofiber Composite Films with Superior Multifunctional Properties.

Self-powered solar-blind UV detectors were fabricated using high-quality Ru/diamond Schottky diodes. Photocurrents of 1 nA and 1.3 nA were obtained for detector Semi and Mesh under the condition of zero bias and 220 nm UV light irradiation, while the dark currents of these two detectors were 0.53 pA and 0.007 pA at 0 V, respectively. Photosensitive areas of detector Semi and Mesh were 1 mm2 and 0.74 mm2, respectively. Rectification ratios as high as 1.5 × 107 and 5.7 × 108 at ±5 V for Semi and Mesh were obtained, showing good rectifying characteristics for the vertical Schottky diodes. Responsivities at 0 V of Semi and Mesh were 10.3 mA/W and 16.2 mA/W, respectively. High detectivities of 3.8 × 1012 Jones and 5.2 × 1013 Jones for detector Semi and Mesh indicate excellent self-powered detection performance. To make a comprehensive comparison of the performance of diamond solar-blind UV detectors, a log(Iph) versus log(Idark) graph was proposed, and the detector in this work showed an ultrahigh SNR of 2 × 105. A high linear dynamic range of 105.9 dB was achieved for the self-powered detector Mesh. 

Self-Powered Solar-Blind UV Detectors Based on O-Terminated Vertical Diamond Schottky Diode with Low Dark Current, High Detectivity, and High Signal-to-Noise Ratio

Jiwen Zhao

Papers

Enhanced conversion efficiency of vacancy-related color centers in diamonds grown on a patterned metal surface by chemical vapor deposition

Thrust Performance Improvement of PMSLM Based on Lasso Regression With Embedded Analytical Model

Thrust ripple reduction according to coil arrangement in PMLSM with double secondary side

Fabrication of High Thermal Conductivity Nanodiamond/Aramid Nanofiber Composite Films with Superior Multifunctional Properties.

Self-Powered Solar-Blind UV Detectors Based on O-Terminated Vertical Diamond Schottky Diode with Low Dark Current, High Detectivity, and High Signal-to-Noise Ratio