Bearing incipient fault diagnosis based upon maximal spectral kurtosis TQWT and group sparsity total variation denoising approach

Localized faults in rolling bearing tend to result in periodic shocks and thus arouse periodic responses in the vibration signal. In this paper, a novel fault diagnosis method based on maximal spectral kurtosis tunable Q-factor wavelet transformation (TQWT) and group sparsity total variation denoising (GS-TVD) is proposed to address the issue of bearing incipient failure. Firstly, the range of Q-factor was pre-selected according to the spectral distribution of impulse component, and bearing vibration signal was transformed by the TQWT method. Then, the spectral kurtosis of each scale transform coefficients was calculated, and the optimal Q-factor and decomposition scale can be selected according to the kurtosis maximum principle. In order to remove the interference components and high-frequency noise from the reconstructed vibration signal generated by inverse TQWT, the GS-TVD approach is employed, thus the cyclic periodicity characteristic and transient impulses can be detected obviously. The two cases experimental results indicate that the proposed technique is more effective and applicable for bearing incipient fault diagnosis compared with traditional method

Plastic deformation depth modeling on grinding of gamma Titanium Aluminides

This work reports on the subsurface plastic deformation depth (PDD) as a result of grinding of γ -TiAl, where the effects of grit size and shape, workpiece speed, and wheel depth of cut were studied. A grinding model based on a stochastic distribution of the chip thickness was used to estimate the expected maximum normal force per grit (Fn_max), which was correlated to the PDD. It was found that the PDD shows a linear correlation with Fn_max^0.5. The results suggest that the indentation model is still valid for grinding if Fn_max^0.5 is used as a PDD predictor variable instead of the total grinding force.Fil: Murtagian, Gregorio R.. The George W. Woodruff School Of Mechanical Engineering Georgia Institute of Technology; Estados UnidosFil: Hecker, Rogelio Lorenzo. Universidad Nacional de La Pampa; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Confluencia; ArgentinaFil: Liang, Steven Y.. The George W. Woodruff School Of Mechanical Engineering Georgia Institute of Technology; Estados UnidosFil: Danyluk, Steven. The George W. Woodruff School Of Mechanical Engineering Georgia Institute of Technology; Estados Unido

Temperature Effects on Grinding Residual Stress

AbstractResidual stress is a key factor that influences the reliability, precision, and life of final products. Earlier studies have alluded to the fact that the grinding process is usually the source of a tensile residual stress on the part surface, while there exists a temperature level commonly referred to as the onset tensile temperature beyond which the tensile profile of residual stresses starts to be generated. In this paper, a physics-based model is proposed to predict the onset temperature as a function of residual stress on an analytical and quantitative basis. The predictive model is based on the temperature distribution function using a moving heat source approach. Then, the thermal stresses are calculated analytically using Timoshenko thermal stress theory [1] followed by an elastic-plastic relaxation condition imposed on these stresses, thus leading to the resulting residual stresses. The model-predicted results have been experimentally validated using data of the grinding of AISI52100 hardened steel with subsequent X-ray and Neutron diffraction measurements. The model was shown to predict the residual stress profile under given process conditions and material properties, therefore providing an analytical tool for grinding process planning and optimization based on the understanding of onset tensile temperature for control of tensile residual stresses

Quantum Logic between Remote Quantum Registers

We analyze two approaches to quantum state transfer in solid-state spin systems. First, we consider unpolarized spin-chains and extend previous analysis to various experimentally relevant imperfections, including quenched disorder, dynamical decoherence, and uncompensated long range coupling. In finite-length chains, the interplay between disorder-induced localization and decoherence yields a natural optimal channel fidelity, which we calculate. Long-range dipolar couplings induce a finite intrinsic lifetime for the mediating eigenmode; extensive numerical simulations of dipolar chains of lengths up to L=12 show remarkably high fidelity despite these decay processes. We further consider the extension of the protocol to bosonic systems of coupled oscillators. Second, we introduce a quantum mirror based architecture for universal quantum computing which exploits all of the spins in the system as potential qubits. While this dramatically increases the number of qubits available, the composite operations required to manipulate "dark" spin qubits significantly raise the error threshold for robust operation. Finally, as an example, we demonstrate that eigenmode-mediated state transfer can enable robust long-range logic between spatially separated Nitrogen-Vacancy registers in diamond; numerical simulations confirm that high fidelity gates are achievable even in the presence of moderate disorder.Comment: 15 pages, 10 figure

Analysis of the Scale Effect for Microscale Machine Tools

ABSTRACT Miniaturization of conventional machine tools has been initiated due to inherent technical and economical advantages. To support further development in this area, a systematic design scheme must be developed on a quantitative basis to reduce the subjective design of miniaturized machine tools. The present work is the size optimization of the miniaturized milling machine on the basis of the proposed design strategy. This design strategy includes individual mathematical computations of key parameters such as volumetric error, machine working space, static, thermal, and dynamic stiffness. This mathematical modeling is established by using analytical methods followed by experimental validation. Individual computations based on the mathematical modeling are carried out to produce the penalty function of the miniaturized milling machine which is then used to find out the optimal dimension. In addition to this, the sensitivity of weighing factors is discussed to find out which weighing factor is more effective to an optimal solution. This study will eventually contribute to the development of more precise miniaturized machine tools

A genome-wide study of blood pressure in African Americans accounting for gene-smoking interaction

Cigarette smoking has been shown to be a health hazard. In addition to being considered a negative lifestyle behavior, studies have shown that cigarette smoking has been linked to genetic underpinnings of hypertension. Because African Americans have the highest incidence and prevalence of hypertension, we examined the joint effect of genetics and cigarette smoking on health among this understudied population. The sample included African Americans from the genome wide association studies of HyperGEN (N = 1083, discovery sample) and GENOA (N = 1427, replication sample), both part of the FBPP. Results suggested that 2 SNPs located on chromosomes 14 (NEDD8; rs11158609; raw p = 9.80 × 10(−9), genomic control-adjusted p = 2.09 × 10(−7)) and 17 (TTYH2; rs8078051; raw p = 6.28 × 10(−8), genomic control-adjusted p = 9.65 × 10(−7)) were associated with SBP including the genetic interaction with cigarette smoking. These two SNPs were not associated with SBP in a main genetic effect only model. This study advances knowledge in the area of main and joint effects of genetics and cigarette smoking on hypertension among African Americans and offers a model to the reader for assessing these risks. More research is required to determine how these genes play a role in expression of hypertension

Structural insights into inhibitor regulation of the DNA repair protein DNA-PKcs.

The DNA-dependent protein kinase catalytic subunit (DNA-PKcs) has a central role in non-homologous end joining, one of the two main pathways that detect and repair DNA double-strand breaks (DSBs) in humans1,2. DNA-PKcs is of great importance in repairing pathological DSBs, making DNA-PKcs inhibitors attractive therapeutic agents for cancer in combination with DSB-inducing radiotherapy and chemotherapy3. Many of the selective inhibitors of DNA-PKcs that have been developed exhibit potential as treatment for various cancers4. Here we report cryo-electron microscopy (cryo-EM) structures of human DNA-PKcs natively purified from HeLa cell nuclear extracts, in complex with adenosine-5'-(γ-thio)-triphosphate (ATPγS) and four inhibitors (wortmannin, NU7441, AZD7648 and M3814), including drug candidates undergoing clinical trials. The structures reveal molecular details of ATP binding at the active site before catalysis and provide insights into the modes of action and specificities of the competitive inhibitors. Of note, binding of the ligands causes movement of the PIKK regulatory domain (PRD), revealing a connection between the p-loop and PRD conformations. Electrophoretic mobility shift assay and cryo-EM studies on the DNA-dependent protein kinase holoenzyme further show that ligand binding does not have a negative allosteric or inhibitory effect on assembly of the holoenzyme complex and that inhibitors function through direct competition with ATP. Overall, the structures described in this study should greatly assist future efforts in rational drug design targeting DNA-PKcs, demonstrating the potential of cryo-EM in structure-guided drug development for large and challenging targets

Molecular Analysis of Serum and Bronchoalveolar Lavage in a Mouse Model of Influenza Reveals Markers of Disease Severity That Can Be Clinically Useful in Humans

Background: Management of influenza, a major contributor to the worldwide disease burden, is complicated by lack of reliable methods for early identification of susceptible individuals. Identification of molecular markers that can augment existing diagnostic tools for prediction of severity can be expected to greatly improve disease management capabilities. Methodology/Principal Findings: We have analyzed cytokines, proteome flux and protein adducts in bronchoalveolar lavage (BAL) and sera from mice infected with influenza A virus (PR8 strain) using a previously established non-lethal model of influenza infection. Through detailed cytokine and protein adduct measurements of murine BAL, we first established the temporal profile of innate and adaptive responses as well as macrophage and neutrophil activities in response to influenza infection. A similar analysis was also performed with sera from a longitudinal cohort of influenza patients. We then used an iTRAQ-based, comparative serum proteome analysis to catalog the proteome flux in the murine BAL during the stages correlating with “peak viremia,” “inflammatory damage,” as well as the “recovery phase.” In addition to activation of acute phase responses, a distinct class of lung proteins including surfactant proteins was found to be depleted from the BAL coincident with their “appearance” in the serum, presumably due to leakage of the protein following loss of the integrity of the lung/epithelial barrier. Serum levels of at least two of these proteins were elevated in influenza patients during the febrile phase of infection compared to healthy controls or to the same patients at convalescence. Conclusions/Significance: The findings from this study provide a molecular description of disease progression in a mouse model of influenza and demonstrate its potential for translation into a novel class of markers for measurement of acute lung injury and improved case management.Singapore. National Research FoundationSingapore-MIT Alliance for Research and Technology (ID-IRG research program