A note on the center of the super Yangian YM∣N(s)Y_{M|N}(\mathfrak{s})

Let $Y_{M|N}(\mathfrak{s})$ be the super Yangian associated with an arbitrary fixed $0^M1^N$-sequence $\mathfrak{s}$. In the present paper, we give a new formula for the quantum Berezinian by using the parabolic generators, which generalizes the usual expression in terms of RTT generators or Drinfeld generators.Comment: final version, to appear in J. Algebr

Design System Construction of Teachers’ on-Job Education and Representation Analysis on Effectiveness

Design system construction of teachers’ on-job education is based on system theory and subjectivity theory, pays attention to four-dimensional design system of “purpose design—curriculum design—mode design—review design”, and is representation of effectiveness for “four-dimensional” design system with pertinence, applicableness, integrity and dynamics

Application of EMD-AR and MTS for hydraulic pump fault diagnosis

A real-time diagnosis of hydraulic pumps is very crucial for the reliable operation of hydraulic systems. The main purpose of this study is to propose a fault diagnosis approach for hydraulic systems based on the empirical mode decomposition (EMD), autoregressive (AR) model, singular value decomposition (SVD), and Mahalanobis–Taguchi system (MTS). The AR model effectively extracts the fault feature of vibration signals. However, it can only be applied to stationary signals; the fault vibration signals of hydraulic pumps are non-stationary. To address this problem, the EMD method is used as a pretreatment step to decompose the non-stationary vibration signals of hydraulic pumps. First, the vibration signals of hydraulic pumps are decomposed into a finite number of stationary intrinsic mode functions (IMF). The AR model of each IMF component is established. The AR parameters and the remnant’s variance are regarded as the initial feature vector matrices. Third, the singular values are obtained by applying the SVD to the initial feature vector matrices. Finally, these values serve as the fault feature vectors to be entered to the MTS, thereby classifying the fault pattern of the hydraulic pumps. The Taguchi methods are employed to reduce the redundant features and extract the principal components. Experimental analysis results indicate that this method can effectively accomplish the fault diagnosis of hydraulic pumps

Rolling Bearing Fault Diagnosis Based on EMD-TEO and Mahalanobis Distance

A intelligent rolling bearing fault diagnosis method is proposed on Empirical Mode Decomposition (EMD) – Teager Energy Operator (TEO) and Mahalanobis distance. EMD can adaptively decompose vibration signal into a series of Intrinsic Mode Functions (IMFs), that is, zero mean mono-component AM-FM signal. TEO can estimate the total mechanical energy required to generate signals, so it has good time resolution and self-adaptive ability to the transient of the signal, which shows the advantage to detect the signal impact characteristics. With regards to the impulse feature of the bearing fault vibration signals, TEO can be used to detect cyclical impulse characteristic caused by bearing failure, gain the instantaneous amplitude spectrum of each IMF component, then identify the characteristic frequency of the interesting and single IMF component in bearing faults by means of Teager energy spectrum. The amplitude of the Teager energy spectrum in inner race fault frequency, outer fault frequency and the ratio of the energy of the resonance frequency to the total energy were extracted as the feature vectors, which were used as training samples and test samples separately for fault diagnosis. Then the Mahalanobis distances between the real measure and different type overalls of fault sample are calculated to classify the real condition of rolling bearing. Experimental results was concluded that this method can accurately identify and diagnose different fault types of rolling bearing