Fault Diagnosis of Train Axle Box Bearing Based on Multifeature Parameters

Failure of the train axle box bearing will cause great loss. Now, condition-based maintenance of train axle box bearing has been a research hotspot around the world. Vibration signals generated by train axle box bearing have nonlinear and nonstationary characteristics. The methods used in traditional bearing fault diagnosis do not work well with the train axle box. To solve this problem, an effective method of axle box bearing fault diagnosis based on multifeature parameters is presented in this paper. This method can be divided into three parts, namely, weak fault signal extraction, feature extraction, and fault recognition. In the first part, a db4 wavelet is employed for denoising the original signals from the vibration sensors. In the second part, five time-domain parameters, five IMF energy-torque features, and two amplitude-ratio features are extracted. The latter seven frequency domain features are calculated based on the empirical mode decomposition and envelope spectrum analysis. In the third part, a fault classifier based on BP neural network is designed for automatic fault pattern recognition. A series of tests are carried out to verify the proposed method, which show that the accuracy is above 90%

Smart Substation Network Fault Classification Based on a Hybrid Optimization Algorithm

Accurate network fault diagnosis in smart substations is key to strengthening grid security. To solve fault classification problems and enhance classification accuracy, we propose a hybrid optimization algorithm consisting of three parts: anti-noise processing (ANP), an improved separation interval method (ISIM), and a genetic algorithm-particle swarm optimization (GA-PSO) method. ANP cleans out the outliers and noise in the dataset. ISIM uses a support vector machine (SVM) architecture to optimize SVM kernel parameters. Finally, we propose the GA-PSO algorithm, which combines the advantages of both genetic and particle swarm optimization algorithms to optimize the penalty parameter. The experimental results show that our proposed hybrid optimization algorithm enhances the classification accuracy of smart substation network faults and shows stronger performance compared with existing methods

Review on Pulling Force of Agricultural Labor and Its Effectiveness in China

This essay details a 3D simulation of a number of control methods used for maneuvering of teleoperated USAR robots. The implementation was produced in the Unity3D engine. The simulation implemented different variations on field-ofview angle, turning algorithms, and camera view perspectives. An evaluation using volunteer test operators was conducted and discussed. The sample size was too small to draw any definitive conclusions. Further testing is advised.Denna uppsats behandlar en 3D-simulering samt användartester av flera olika kontrollmetoder som används vid fjärrstyrning av obemannade räddningsrobotar. Implementationen skapades med Unity3D-plattformen. De styrmetoder som testades var olika stora synfältsvinklar på kameran, olika algoritmer för att styra robotens svängning, samt olika kameraperspektiv. Användartester med frivilliga testförare genomfördes och diskuteras. Provstorleken var för liten för att kunna dra några definitiva slutsatser. Ytterligare tester rekommenderas

Slicing-free Inverse Regression in High-dimensional Sufficient Dimension Reduction

Sliced inverse regression (SIR, Li 1991) is a pioneering work and the most recognized method in sufficient dimension reduction. While promising progress has been made in theory and methods of high-dimensional SIR, two remaining challenges are still nagging high-dimensional multivariate applications. First, choosing the number of slices in SIR is a difficult problem, and it depends on the sample size, the distribution of variables, and other practical considerations. Second, the extension of SIR from univariate response to multivariate is not trivial. Targeting at the same dimension reduction subspace as SIR, we propose a new slicing-free method that provides a unified solution to sufficient dimension reduction with high-dimensional covariates and univariate or multivariate response. We achieve this by adopting the recently developed martingale difference divergence matrix (MDDM, Lee & Shao 2018) and penalized eigen-decomposition algorithms. To establish the consistency of our method with a high-dimensional predictor and a multivariate response, we develop a new concentration inequality for sample MDDM around its population counterpart using theories for U-statistics, which may be of independent interest. Simulations and real data analysis demonstrate the favorable finite sample performance of the proposed method

Phages Bearing Affinity Peptides to Bovine Rotavirus Differentiate the Virus from Other Viruses

The aim of this study was to identify potential ligands and develop a novel diagnostic test to pathogenic bovine rotavirus (BRV) using phage display technology. The viruses were used as an immobilized target followed by incubation with a 12-mer phage display random peptide library. After five rounds of biopanning, phages had a specific binding activity to BRV were isolated. DNA sequencing indicated that phage displayed peptides HVHPPLRPHSDK, HATNHLPTPHNR or YPTHHAHTTPVR were potential ligands to BRV. Using the specific peptide-expressing phages, we developed a phage-based ELISA to differentiate BRV from other viruses. Compared with quantitative real-time PCR (qPCR), the phage-mediated ELISA was more suitable for the capture of BRV and the detection limitation of this approach was 0.1 µg/ml of samples. The high sensitivity, specificity and low cross-reactivity for the phage-based ELISA were confirmed in receiver operating characteristics (ROC) analysis

Optical observations of a SN 2002cx-like peculiar supernova SN 2013en in UGC 11369

We present optical observations of a SN 2002cx-like supernova SN 2013en in UGC 11369, spanning from a phase near maximum light (t= +1 d) to t= +60 d with respect to the R-band maximum. Adopting a distance modulus of mu=34.11 +/- 0.15 mag and a total extinction (host galaxy+Milky Way) of $A_V \sim1.5$ mag, we found that SN 2013en peaked at $M(R)\sim -18.6$ mag, which is underluminous compared to the normal SNe Ia. The near maximum spectra show lines of Si II, Fe II, Fe III, Cr II, Ca II and other intermediate-mass and iron group elements which all have lower expansion velocities (i.e., ~ 6000 km/s). The photometric and spectroscopic evolution of SN 2013en is remarkably similar to those of SN 2002cx and SN 2005hk, suggesting that they are likely to be generated from a similar progenitor scenario or explosion mechanism.Comment: 8 pages, 8 figures, 3 tables, accepted for publication in MNRA

Revealing the Signal of QCD Phase Transition in Heavy-Ion Collisions

We propose a novel method to construct the Landau thermodynamic potential directly from the fluctuations measured in heavy-ion collisions. The potential is capable of revealing the signal of the critical end-point (CEP) and the first order phase transition (FOPT) of QCD in the system even away from the phase transition region. With the available experimental data, we show that the criterion of the FOPT is negative for most of the collision energies which indicates no signal of FOPT. The data at $\sqrt{s_\mathrm{NN}}=7.7$ GeV with 0-5% centrality shows a different behavior and the mean value of the data satisfies the criterion. However, the uncertainty is still too large to make a certain conclusion. The higher order fluctuations are also required for confirming the signal. We emphasize therefore that new measurements with higher precision for the $C_{1,...,6}$ within 0-5% centrality in the vicinity of $\sqrt{s_\mathrm{NN}}=7.7$ GeV are in demand which may finally reveal the signal of QCD phase transition.Comment: 7 pages, 4 figure