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Journal of Chongqing University 2017年第1期16卷 1-10页

作者：郭少霞 PEI Qiang The R&D Center of Civil Engineering Technology Dalian University Dalian 116622 P. R. China

The high-rise frame structure has become more and more widespread, like its damage from the complication of the environment. The traditional method of damage detection, which is only suitable for the stationary signal, does not apply to a high-rise frame structure because its damage signal is non-stationary. Thus, this paper presents an application of the short-time fourier transform(STFT) to damage detection of high-rise frame structures. Compared with the fast fourier transform, STFT is found to be able to express the frequency spectrum property of the time interval using the signal within this interval. Application of STFT to analyzing a Matlab model and the shaking table test with a twelve-story frame-structure model reveals that there is a positive correlation between the slope of the frequency versus time and the damage level. If the slope is equal to or greater than zero, the structure is not damaged. If the slope is smaller than zero, the structure is damaged, and the less the slope is, the more serious the damage is. The damage results from calculation based on the Matlab model are consistent with those from the shaking table test, demonstrating that STFT can be a reliable tool for the damage detection of high-rise frame structures.

关键词： short-time fourier transform fast fourier transform damage identification shaking table test time-frequency analysis

FLOW NOISE MEASUREMENT OF SURFACE SHIP WITH TOWED MODEL

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Journal of Hydrodynamics 2008年第6期20卷 784-789页

作者： GAO Xiao-peng BI Yi MIAO Guo-ping School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai 200030 China College of Naval Architecture and Power Naval University of Engineering Wuhan 430033 China

In this article, a new acoustic test technique using towed model was introduced to study flow noise caused by a surface ship. The project of model test was be properly designed for acoustic signal collecting and with the help of appropriate data processing method different kinds of acoustic sources could be successfully identified. A lot of work about fuid noise could be carried on with the towed model, and the noise corresponding to low frequency which is especially interested for its long distance radiating with small attenuation could also be studied in this way.

关键词： acoustic test surface ship towed model flow noise short-time fourier transform

time-extracting S-transform algorithm and its application in rolling bearing fault diagnosis

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Science China(Technological Sciences) 2022年第4期65卷 932-942页

作者： XU YongGang WANG Liang HU AiJun YU Gang Beijing Engineering Research Center of Precision Measurement Technology and Instruments Faculty of Materials and ManufacturingBeijing University of TechnologyBeijing 100124China Department of Mechanical Engineering North China Electric Power UniversityBaoding 071003China School of Electrical Engineering University of JinanJinan 250022China

time-frequency(TF)analysis(TFA)is one of the effective methods to deal with non-stationary *** to their advantages,many experts and scholars have recently developed post-processing algorithms based on traditional *** them,shorttime fourier transform(STFT)based post-processing algorithms have developed the ***,these methods rely heavily on the window length selected in STFT,which has great influence on the post-processing *** this paper,a postprocessing algorithm for effectively processing pulse signals was proposed and called time-extracting S-transform(TEST).The time-domain extraction method based on S-transform avoids the influence of uncertain *** comparing the performance of various TFA methods when processing analog signals,the proposed TEST can clearly show the pulse occurrence time under the premise of ensuring high TF *** actual signal proves that the method can be used for fault diagnosis of rolling bearings.

关键词： time-extracting S-transform time-frequency analysis pulse signal fault diagnosis short-time fourier transform

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Rolling bearing fault diagnostics based on improved data augmentation and ConvNet

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Journal of Systems Engineering and Electronics 2023年第4期34卷 1074-1084页

作者： KULEVOME Delanyo Kwame Bensah WANG Hong WANG Xuegang School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou 313001China

Convolutional neural networks(CNNs)are well suited to bearing fault classification due to their ability to learn discriminative spectro-temporal ***,gathering sufficient cases of faulty conditions in real-world engineering scenarios to train an intelligent diagnosis system is *** paper proposes a fault diagnosis method combining several augmentation schemes to alleviate the problem of limited fault *** begin by identifying relevant parameters that influence the construction of a *** leverage the uncertainty principle in processing time-frequency domain signals,making it impossible to simultaneously achieve good time and frequency resolutions.A key determinant of this phenomenon is the window function's choice and length used in implementing the shorttime fourier *** Gaussian,Kaiser,and rectangular windows are selected in the experimentation due to their diverse *** overlap parameter's size also influences the outcome and resolution of the spectrogram.A 50%overlap is used in the original data transformation,and±25%is used in implementing an effective augmentation policy to which two-stage regular CNN can be applied to achieve improved *** best model reaches an accuracy of 99.98%and a cross-domain accuracy of 92.54%.When combined with data augmentation,the proposed model yields cutting-edge results.

关键词： bearing failure short-time fourier transform prognostics and health management data augmentation fault diagnosis

Enhancing non-profiled side-channel attacks by time-frequency analysis

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Cybersecurity 2023年第4期6卷 50-75页

作者： Chengbin Jin Yongbin Zhou Institute of Information Engineering Chinese Academy of SciencesBeijingChina School of Cyber Security University of Chinese Academy of SciencesBeijingChina School of Cyber Science and Engineering Nanjing University of Science and TechnologyNanjingChina

Side-channel analysis(SCA)has become an increasing important method to assess the physical security of cryptographic *** the process of SCA,the number of attack data directly determines the performance of *** sufficient attack data,the adversary can achieve a successful ***,in reality,the cryptographic device may be protected with some countermeasures to limit the number of encryptions using the same *** this case,the adversary cannot use casual numbers of data to perform *** performance of SCA will be severely dropped if the attack traces are *** this paper,we introduce wavelet scatter transform(WST)and short-time fourier transform(STFT)to non-profiled side-channel analysis domains,to improve the performance of side-channel attacks in the context of insufficient *** design a practical framework to provide suitable parameters for WST/STFT-based *** the proposed method,the WST/STFT-based SCA method can significantly enhance the performance and robustness of non-profiled *** practical attacks against four public datasets show that the proposed method is able to achieve more robust *** with the original correlation power analysis(CPA),the number of attack data can be reduced by 50–95%.

关键词： Correlation power analysis Side-channel analysis Proposed attack framework Wavelet scatter transform short-time fourier transform

Split vector quantization for sinusoidal amplitude and frequency

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Journal of Zhejiang University-Science C(Computers and Electronics) 2011年第2期12卷 140-154页

作者： Pejman MOWLAEE Abolghasem SAYADIAN Hamid SHEIKHZADEH Department of Electronic Engineering Amirkabir University of Technology

In this paper, we suggest applying tree structure on the sinusoidal parameters. The suggested sinusoidal coder is targeted to find the coded sinusoidal parameters obtained by minimizing a likelihood function in a least square (LS) sense. From a rate-distortion standpoint, we address the problem of how to allocate available bits among different frequency bands to code sinusoids at each frame. For further analyzing the quantization behavior of the proposed method, we assess the quantization performance with respect to other methods: the short-time fourier transform (STFT) based coder commonly used for speech enhancement or separation, and the line spectral frequency (LSF) coder used in speech coding. Through extensive simulations, we show that the proposed quantizer leads to less spectral distortion as well as higher perceived quality for the re-synthesized signals based on the coded parameters in a model-based approach with respect to previous STFT-based methods. The proposed method lowers the complexity, and, due to its tree-structure, leads to a rapid search capability. It provides flexibility for use in many speaker-independent applications by finding the most likely frequency vectors selected from a list of frequency candidates. Therefore, the proposed quantizer can be considered an attractive candidate for model-based speech applications in both speaker-dependent and speaker-independent scenarios.

关键词： short-time fourier transform Split vector quantization Sinusoidal modeling Spectral distortion

SRMD:Sparse Random Mode Decomposition

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Communications on Applied Mathematics and Computation 2024年第2期6卷 879-906页

作者： Nicholas Richardson Hayden Schaeffer Giang Tran University of Waterloo WaterlooONCanada University of British Columbia VancouverBCCanada University of California Los AngelesCAUSA

Signal decomposition and multiscale signal analysis provide many useful tools for timefrequency *** proposed a random feature method for analyzing time-series data by constructing a sparse approximation to the *** randomization is both in the time window locations and the frequency sampling,which lowers the overall sampling and computational *** sparsification of the spectrogram leads to a sharp separation between time-frequency clusters which makes it easier to identify intrinsic modes,and thus leads to a new data-driven mode *** applications include signal representation,outlier removal,and mode *** benchmark tests,we show that our approach outperforms other state-of-the-art decomposition methods.

关键词： Sparse random features Signal decomposition short-time fourier transform

Estimation of structural modal parameters by fourier transform with an optimal window

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Journal of Harbin Institute of Technology(New Series) 2005年第5期12卷 595-598页

作者：朱宏平万信华 School of Civil Engineering &Mechanics Huazhong University of Science &Technology Wuhan 430074 China

An adaptive fourier transform （FT） with an optimal window has been proposed for the time-frequency analysis of nonstationary time series. The method allows for a good estimation of both frequency and amplitude of the spectrum and can be easily applied to the general case of time-varying signals. The evaluation of the proposed approach has been performed on measured time-varying signals from a suspension bridge model and a steel frame model whose data have the typical non-stationary characteristics. The numerical results show that the proposed approach can overcome some of the difficulties encountered in the classic fourier transform technique and can achieve higher computation accuracy.

关键词： short-time fourier transform optimal window length modal parameters engineering structures

A convolutional neural network based approach to sea clutter suppression for small boat detection

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Frontiers of Information Technology & Electronic Engineering 2020年第10期21卷 1504-1520页

作者： Guan-qing LI Zhi-yong SONG Qiang FU National Key Laboratory of Science and Technology on ATR College of Electronic Science and TechnologyNational University of Defense TechnologyChangsha 410073China

Current methods for radar target detection usually work on the basis of high signal-to-clutter *** this paper we propose a novel convolutional neural network based dual-activated clutter suppression algorithm,to solve the problem caused by low signal-to-clutter ratios in actual situations on the sea *** activation has two ***,we multiply the activated weights of the last dense layer with the activated feature maps from the upsample *** this,we can obtain the class activation maps(CAMs),which correspond to the positive region of the sea ***,we obtain the suppression coefficients by mapping the CAM inversely to the sea clutter ***,we obtain the activated range-Doppler maps by multiplying the coefficients with the raw range-Doppler *** addition,we propose a sampling-based data augmentation method and an effective multiclass coding method to improve the prediction *** on real datasets verified the effectiveness of the proposed method.

关键词： Convolutional neural networks Class activation map short-time fourier transform Small target detection Sea clutter suppression

THE WAVELET ANALYSIS METHOD ON THE TRANSIENT SIGNAL

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Journal of Coal Science & Engineering(China) 1996年第1期2卷 90-97页

作者：吴淼

Many dynamic signals of mining machines are transient, such as load signals when roadheader’s cutting head being cut-in or cut-out and response signals produced by these *** these transient signals, the traditional fourier analysis method is quite *** limitations of analysis, resolution by using short-time fourier transform (STFT) on them were discussed in this paper. Because of wavelet transform having the characteristics of flexible window and multiresolution analysis, we try to apply it to analyse these transient signal. In order to give a pratical example,using D18 wavelet and Mallat’s tree algorithm with MATLAB, the discrete wavelet transform was calculated for the simulating response signals of a three-degree-of freedom vibration system when it Was under impulse and random excitations. The results of the wavelet transform made clear its effectiveness and superiority in analysing transient signals of mining machines.

关键词： transient signals short-time fourier transform discrete wavelet transform