NONLINEAR TIME TRANSFORMATION METHOD FOR STRONG NONLINEAR OSCILLATION SYSTEMS

In this paper,a nonlinear time transformation method is presented for the analysis of strong nonlinear oscillation systems.This method can be used to study the limit cycle behavior of the autonomous systems and to analyze the forced vibration of a strong nonlinear system.

Output only modal identification and structural damage detection using time frequency & wavelet techniques

The primary objective of this paper is to develop output only modal identification and structural damage detection. Identification of multi-degree of freedom （MDOF） linear time invariant （LTI） and linear time variant （LTV--due to damage） systems based on Time-frequency （TF） techniques--such as short-time Fourier transform （STFT）, empirical mode decomposition （EMD）, and wavelets--is proposed. STFT, EMD, and wavelet methods developed to date are reviewed in detail. In addition a Hilbert transform （HT） approach to determine frequency and damping is also presented. In this paper, STFT, EMD, HT and wavelet techniques are developed for decomposition of free vibration response of MDOF systems into their modal components. Once the modal components are obtained, each one is processed using Hilbert transform to obtain the modal frequency and damping ratios. In addition, the ratio of modal components at different degrees of freedom facilitate determination of mode shape. In cases with output only modal identification using ambient/random response, the random decrement technique is used to obtain free vibration response. The advantage of TF techniques is that they arc signal based; hence, can be used for output only modal identification. A three degree of freedom 1：10 scale model test structure is used to validate the proposed output only modal identification techniques based on STFT, EMD, HT, wavelets. Both measured free vibration and forced vibration （white noise） response are considered. The secondary objective of this paper is to show the relative ease with which the TF techniques can be used for modal identification and their potential for real world applications where output only identification is essential. Recorded ambient vibration data processed using techniques such as the random decrement technique can be used to obtain the free vibration response, so that further processing using TF based modal identification can be performed.

Anti-aliasing nonstationary signals detecion algorithm based on interpolation in the frequency domain using the short time Fourier transform

To eliminate the aliasing that appeared during the measurement of multi-components nonstationary signals, a novel kind of anti-aliasing algorithm based on the short time Fourier transform （STFT） is brought forward. First the physical essence of aliasing that occurs is analyzed; second the interpolation algorithm model is setup based on the Hamming window; then the fast implementation of the algorithm using the Newton iteration method is given. Using the numerical simulation the feasibility of algorithm is validated. Finally, the electrical circuit experiment shows the practicality of the algorithm in the electrical engineering.

A novel sparse filtering approach based on time-frequency feature extraction and softmax regression for intelligent fault diagnosis under different speeds

Modern agricultural mechanization has put forward higher requirements for the intelligent defect diagnosis.However,the fault features are usually learned and classified under all speeds without considering the effects of speed fluctuation.To overcome this deficiency,a novel intelligent defect detection framework based on time-frequency transformation is presented in this work.In the framework,the samples under one speed are employed for training sparse filtering model,and the remaining samples under different speeds are adopted for testing the effectiveness.Our proposed approach contains two stages:1)the time-frequency domain signals are acquired from the mechanical raw vibration data by the short time Fourier transform algorithm,and then the defect features are extracted from time-frequency domain signals by sparse filtering algorithm;2)different defect types are classified by the softmax regression using the defect features.The proposed approach can be employed to mine available fault characteristics adaptively and is an effective intelligent method for fault detection of agricultural equipment.The fault detection performances confirm that our approach not only owns strong ability for fault classification under different speeds,but also obtains higher identification accuracy than the other methods.

Suppression to the cross-channel interference based on the short time Fourier transform

A new cross-channel interference suppression method is proposed to decrease the cross-channel interference in beat signals based on the short time Fourier transform （STY3＂） and the inverse short time Fourier transform （ISTFT） when the dual-orthogonal polarimetric frequency-modulated continu- ous wave （FMCW） radar adopts the opposite-slope linear frequency modulation signal pair in the simultaneous measurement mode. The STFT is applied only on the signals in the cross-interference intervals in the four polarimetric channels to decrease the computation complexity. A mask matrix for suppressing the interference is constructed using the constant false alarm ratio （CFAR） detection on the spectrograms by the STFY. The simulative results show that the cross-channel interference is effi- ciently suppressed by the proposed method. The comparison between the proposed method and the rejection method verifies the improved performance of the proposed method.

Time to Transform

ON April 22, world leaders met in New York to sign the major agreement on unitedly combating climate change they had reached in Paris in December 2015, The signing ceremony set into action the global implementation of a long-term goal： achieving zero carbon emission.

A Water Level Forecast of Pattani River in the Southern of Thailand by Deep Learning

Nowadays, the deep learning methods are widely applied to analyze and predict the trend of various disaster events and offer the alternatives to make the appropriate decisions. These support the water resource management and the short-term planning. In this paper, the water levels of the Pattani River in the Southern of Thailand have been predicted every hour of 7 days forecast. Time Series Transformer and Linear Regression were applied in this work. The results of both were the water levels forecast that had the high accuracy. Moreover, the water levels forecasting dashboard was developed for using to monitor the water levels at the Pattani River as well.

Underdetermined Blind Source Separation of Adjacent Satellite Interference Based on Sparseness

The problem of underdetermined blind source separation of adjacent satellite interference is proposed in this paper. Density Clustering algorithm(DC-algorithm) presented in this article is different from traditional methods. Sparseness representation has been applied in underdetermined blind signal source separation. However, some difficulties have not been considered, such as the number of sources is unknown or the mixed matrix is ill-conditioned. In order to find out the number of the mixed signals, Short Time Fourier Transform(STFT) is employed to segment received mixtures. Then, we formulate the blind source signal as cluster problem. Furthermore, we construct Cost Function Pair and Decision Coordinate System by using density clustering. At the end of this paper, we discuss the performance of the proposed method and verify the novel method based on several simulations. We verify the proposed method on numerical experiments with real signal transmission, which demonstrates the validity of the proposed method.

A Multi-Gap Multi-Channel Gas Switch for the Linear Transformer Driver

A multi-gap and multi-channel gas switch with convexo-convex discal planet electrodes was designed and investigated. Eight gaps are formed in series by a trigger electrode, six intermediate electrodes and two high voltage electrodes with a uniform gap length of 5 ram. The self breakdown and triggered breakdown performance of the switch are reported. Both the delay time and jitter decrease with the increase in the trigger voltage, switching coefficient and the decrease in the trigger isolating resistor. The delay time of the switch is about 40 ns, and the jitter is less than 2 ns when charged with 4-85 kV and triggered by a voltage pule of -75 kV. The inductance of the switch is about 30 nH.

OPTIMAL PROPORTIONAL REINSURANCE WITH CONSTANT DIVIDEND BARRIER

In this article, we consider an optimal proportional reinsurance with constant dividend barrier. First, we derive the Hamilton-Jacobi-Bellman equation satisfied by the expected discounted dividend payment, and then get the optimal stochastic control and the optimal constant barrier. Secondly, under the optimal constant dividend barrier strategy, we consider the moments of the discounted dividend payment and their explicit expressions are given. Finally, we discuss the Laplace transform of the time of ruin and its explicit expression is also given.

SOME COMPARISONS BETWEEN GENERALIZED ORDER STATISTICS

Some stochastic comparisons of generalized order statistics under the right spread order, the location independent riskier order and the total time transform order are investigated in this paper. The underlying distributions and parameters on which generalized order statistics are based are also surveyed to obtain the conditions for increasing the expectations of spacings between the first two generalized order statistics and between the last two generalized order statistics.

Pseudo-Magnetotelluric 2D Inversion Technology of Magnetic-Source Transient Electromagnetics

Based on the fact that it is diffi cult to implement optimum inversion using 2D and 3D forward modeling with magnetic-source transient electromagnetics(TEM),this paper explores a novel approach to the implementation of 2D magnetic-source TEM inversion.In particular,we converted magnetic-source TEM data into magnetotelluric(MT)data and then used a 2D MT inversion method to implement a 2D magnetic-source TEM inversion interpretation.First,we studied the similarity between magnetic-source TEM waves and MT waves and between magnetic-source TEM all-time apparent resistivity and MT Cagniard apparent resistivity.Then,we selected an optimal time-frequency transformation coeffi cient to implement rapid time-frequency transformation of all-time TEM apparent resistivity to MT Cagniard apparent resistivity.Afterward,we conducted 1D pseudo-MT inversions of magnetic-source 1D TEM theoretical models.The 1D inversion results demonstrated that the diff erence between the inversion parameters and model parameters was small,while the MT 1D inversion method could be used to conduct magnetic 1D TEM inversion within a certain margin of error.We further conducted 2D pseudo-MT inversions of 3D magnetic-source TEM theoretical models,and the 2D inversion results indicated that selecting a joint 2D pseudo-MT transverse-electric(TE)and transverse-magnetic(TM)inversion method based on measuring the line above a 3D anomalous body can help to accurately implement a 2D inversion interpretation of the 3D TEM response.

Path Integral Solution for an Angle-Dependent Anharmonic Oscillator

We have given a straightforward method to solve the problem of noncentral anharmonic oscillator in three dimensions. The relative propagator is presented by means of path integrals in spherical coordinates. By making an adequate change of time we are able to separate the angular motion from the radial one. The relative propagator is then exactly calculated. The energy spectrum and the corresponding wave functions are obtained.

Product(α1,α2)-modulation spaces Dedicated to the Memory of Michel Marias

We study fundamental properties of product(α,α)-modulation spaces built by(α,α)-coverings of R× R.Precisely we prove embedding theorems between these spaces with different parameters and other classical spaces.Furthermore,we specify their duals.The characterization of product modulation spaces via the short time Fourier transform is also obtained.Families of tight frames are constructed and discrete representations in terms of corresponding sequence spaces are derived.Fourier multipliers are studied and as applications we extract lifting properties and the identification of our spaces with(fractional) Sobolev spaces with mixed smoothness.

Improvement of signal processing in Coriolis mass flowmeters for gas-liquid two-phase flow

As an increasingly popular flow metering technology,Coriolis mass flowmeter exhibits high measurement accuracy under single-phase flow condition and is widely used in the industry.However,under complex flow conditions,such as two-phase flow,the measurement accuracy is greatly decreased due to various factors including improper signal processing methods.In this study,three digital signal processing methods—the quadrature demodulation(QD)method,Hilbert method,and sliding discrete time Fourier transform method—are analyzed for their applications in processing sensor signals and providing measurement results under gas-liquid two-phase flow condition.Based on the analysis,specific improvements are applied to each method to deal with the signals under two-phase flow condition.For simulation,sensor signals under single-and two-phase flow conditions are established using a random walk model.The phase difference tracking performances of these three methods are evaluated in the simulation.Based on the digital signal processor,a converter program is implemented on its evaluation board.The converter program is tested under single-and two-phase flow conditions.The improved signal processing methods are evaluated in terms of the measurement accuracy and complexity.The QD algorithm has the best performance under the single-phase flow condition.Under the two-phase flow condition,the QD algorithm performs a little better in terms of the indication error and repeatability than the improved Hilbert algorithm at 160,250,and 420 kg/h flow points,whereas the Hilbert algorithm outperforms the QD algorithm at the 600 kg/h flow point.

The Reduction Square Root and Perturbation for a Class of Strongly Continuous Operator Families

We introduce the concept of a times C-second resolvent families and present the rela- tionship between a times C-resolvent families and a times C-second resolvent families. Moreover, the perturbation and square root for a times C-resolvent families are considered in this paper which generalize the counterparts of C-Cosine operator functions.