Application of higher order spectral features and support vector machines for bearing faults classification

Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery. This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier. The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals. The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults. The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction. These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions. In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used. Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed. The average of these performance measures is computed to report the overall performance of the support vector machine classifier. In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity. The sensitivity and robustness of the proposed method are explored by running a series of experiments. A receiver operating characteristic (ROC) curve made the results more convincing. The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals.     

Inverted pendulum stabilization: Characterization of codimension-three triple zero bifurcation via multiple delayed proportional gains

The paper considers the problem of stabilization of systems possessing a multiple zero eigenvalue at the origin. The controller that we propose, uses multiple delayed measurements instead of derivative terms. Doing so, we increase the performances of the closed loop in presence of system uncertainties and/or noisy measurements. The problem formulation and the analysis is presented through a classical engineering problem which is the stabilization of an inverted pendulum on a cart moving horizontally. On one hand, we perform a nonlinear analysis of the center dynamics described by a three dimensional system of ordinary differential equations with a codimension-three triple zero bifurcation. On the other hand, we present the complementary stability analysis of the corresponding linear time invariant system with two delays describing the behavior around the equilibrium. The aim of this analysis is to characterize the possible local bifurcations. Finally, the proposed control scheme is numerically illustrated and discussed.     

Theoretical investigation of solvent effects on the selective hydrogenation of furfural over Pt(111)

It was well known that solvent effect plays a very important role in the catalytic reaction. There are many theoretical studies on the solvent effect in homogeneous catalysis while there are few theoretical studies on the solvent effect in the heterogeneous catalytic reaction and there has been no work to investigate the solvent effect on furfural transformation in heterogeneous catalysis. In the present work, both the density functional calculations and the microkinetic analysis were performed to study the selective hydrogenation of furfural over Pt(111) in the presence of methanol as well as toluene and compared with that in the gas condition. The present results indicated that the methanol can enhance the adsorption strength of furfural and other oxygen-containing reaction species due to its relatively strong polarity properties and this can be a main reason for solvent-induced high activity and selectivity. Another reason is that reaction paths study showed that the presence of methanol solvent makes the dehydrogenation of furfural less thermochemical due to the fact that furfural is more stabilized than that of dehydrogenation species, and methanol also has an inhibition effect on the dehydrogenation of furfural in the kinetic aspect, and further energetic span theory proves highest activity and selectivity for hydrogenation in methanol solvent of vapor, methanol and toluene. Moreover, microkinetic model simulation demonstrated that the activity and selectivity of hydrogenation in methanol is both higher than that in vapor and toluene. The much higher activity in methanol is due to the stabilized adsorbed reactants in the surface, which leads to a higher surface coverage of furfural. It might be proposed based on the present work that a solvent with relatively strong polarity may be favorable for the high selective hydrogenation of furfural.     

Recent activities in the field of Nuclear Operational Management and Nuclear Safety Engineering

Recent activities in the field of Nuclear Operational Management and Nuclear Safety Engineering, the studies related to risk analysis methodology, design, and operational management, physical phenomena, and emergency preparedness and nuclear security, have been progressed. Especially, ‘risk analysis methodology’ and ‘design and operational management’ are the main categories of the field, in which more than half of published articles on Journal of Nuclear Science and Technology are related to these categories.     

A precise sensor fault detection technique using statistical techniques for wireless body area networks

One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.     

Finite element analysis of fracture behavior in ceramics: Competition between artificial notch and internal defects under three-point bending

Evaluation of the nonlinear relationship between the surface defect size and fracture strength of ceramics is important for engineering applications. In this study, we aim to predict the apparent nonlinear relationship between the defect size and fracture strength of single-edge notched beams (SENBs) using the finite element method. Specifically, we applied the methodology for predicting fracture strength from microstructure distribution data (relative density, pore size, aspect ratio, and grain size) to a finite element analysis (FEA) model in which the shape and size of the initial defects are defined at notch locations. By reproducing the apparent nonlinearity caused by the competition between the surface and internal defects within the framework of linear elastic fracture mechanics, the effectiveness of the FEA methodology for the evaluation of strength scatter and allowable crack size in ceramics was demonstrated.     

Damage evolution in polymer due to exposure to high-pressure hydrogen gas

The use of hydrogen as a fuel is increasing exponentially, and the most economical way to store and transport hydrogen for fuel use is as a high-pressure gas. Polymers are widely used for hydrogen distribution and storage systems because they are chemically inert towards hydrogen. However, when exposed to high-pressure hydrogen, some hydrogen diffuses through polymers and occupies the preexisting cavities inside the material. Upon depressurization, the hydrogen trapped inside polymer cavities can cause blistering or cracking by expanding these cavities. A continuum mechanics–based deformation model was deployed to predict the stress distribution and damage propagation while the polymer undergoes depressurization after high-pressure hydrogen exposure. The effects of cavity size, cavity location, and pressure inside the cavity on damage initiation and evolution inside the polymer were studied. The stress and damage evolution in the presence of multiple cavities was also studied, because interaction among cavities alters the damage and stress field. It was found that all these factors significantly change the stress state in the polymer, resulting in different paths for damage propagation. The effect of adding carbon black filler particles and plasticizer on the damage was also studied. It was found that damage tolerance of the polymer increases drastically with the addition of carbon black fillers, but decreases with the addition of the plasticizer.     

Event-triggered distributed receding horizon control for tracking and formation of homogeneous multi-agent systems

This paper proposes an event-triggered distributed receding horizon control (DRHC) approach for the formation and tracking problems of homogeneous multi-agent systems. For each agent, an event-triggering condition, based on assumed predictive information of the neighbours, is derived from stability analysis. Considering the uncertain deviation between the assumed and true predictive information, we design a time-varying compatibility constraint for the individual optimization problem. In the event-triggered DRHC algorithm, each agent solves the optimization problem and communicates with its neighbours only when the event-triggering condition is satisfied, so the communication and computation burden are reduced. Moreover, guarantees for the recursive feasibility and asymptotic stability of the overall system are proved. A simulation example is provided to illustrate effectiveness of the proposed approach.     

Sensitization of MCF7 Cells with High Notch1 Activity by Cisplatin and Histone Deacetylase Inhibitors Applied Together

Histone deacetylase inhibitors (HDIs) are promising anti-cancer agents that inhibit proliferation of many types of cancer cells including breast carcinoma (BC) cells. In the present study, we investigated the influence of the Notch1 activity level on the pharmacological interaction between cisplatin (CDDP) and two HDIs, valproic acid (VPA) and suberoylanilide hydroxamic acid (SAHA, vorinostat), in luminal-like BC cells. The type of drug–drug interaction between CDDP and HDIs was determined by isobolographic analysis. MCF7 cells were genetically modified to express differential levels of Notch1 activity. The cytotoxic effect of SAHA or VPA was higher on cells with decreased Notch1 activity and lower for cells with increased Notch1 activity than native BC cells. The isobolographic analysis demonstrated that combinations of CDDP with SAHA or VPA at a fixed ratio of 1:1 exerted additive or additive with tendency toward synergism interactions. Therefore, treatment of CDDP with HDIs could be used to optimize a combined therapy based on CDDP against Notch1-altered luminal BC. In conclusion, the combined therapy of HDIs and CDDP may be a promising therapeutic tool in the treatment of luminal-type BC with altered Notch1 activity.