Seismic dip estimation based on the twodimensional Hilbert transform and its application in random noise attenuation

In seismic data processing, random noise seriously affects the seismic data quality and subsequently the interpretation. This study aims to increase the signal-to-noise ratio by suppressing random noise and improve the accuracy of seismic data interpretation without losing useful information. Hence, we propose a structure-oriented polynomial fitting filter. At the core of structure-oriented filtering is the characterization of the structural trend and the realization of nonstationary filtering. First, we analyze the relation of the frequency response between two-dimensional（2D） derivatives and the 2D Hilbert transform. Then, we derive the noniterative seismic local dip operator using the 2D Hilbert transform to obtain the structural trend. Second, we select polynomial fitting as the nonstationary filtering method and expand the application range of the nonstationary polynomial fitting. Finally, we apply variableamplitude polynomial fitting along the direction of the dip to improve the adaptive structureoriented filtering. Model and field seismic data show that the proposed method suppresses the seismic noise while protecting structural information.

Ultrasonic transducer array tomography for detecting defect of metal plate based on Hilbert transformation

Hilbert transformation and improved ellipse localization method is applied in ultrasonic transducer array tomography to detect defect of metal plate.By combining the improved ellipse localization method and time-reversal method,the new ultrasonic tomography algorithm employs smooth Hilbert envelope instead of discrete amplitude to reconstruct defect image.An ultrasonic tomography system with six transducers is built to evaluate the effectiveness of the new ultrasonic tomography algorithm.The S0 mode Lamb wave is excited on special condition,and the mode of received signal is identified by Vigner-Wille distribution.The gray value of image area is defined by envelope of the reflected S0 mode Lamb wave signal from defect boundary.Defect image can be reconstructed by summing gray value of all pixels in the image area.The experimentally reconstructed defect image shows that the new tomography algorithm based on Hilbert transformation is efficient for defect detection in metal plate.

Quantum Mechanical Hilbert Transformation for Normally Ordering Coulomb Potential-Type Operators

We show that the technique of integration within an ordered product of operators can be extended to Hilbert transform. In so doing we derive normally ordered expansion of Coulomb potential-type operators directly by using the mathematical Hilbert transform formula.

Condition Evaluation in Steel Truss Bridge with Fused Hilbert Transform,Spectral Kurtosis,and Bandpass Filter

This study is concerned with the diagnosis of discrepancies in a steel truss bridge by identifying dynamic properties from the vibration response signals of the bridges.The vibration response signals collected at bridges under three different vehicular speeds of 10 km/hr,20 km/hr,and 30 km/hr are analyzed using statistical features such as kurtosis,magnitude of peak-to-peak,root mean square,crest factor as well as impulse factor in time domain,and Stockwell transform in the time-frequency domain.The considered statistical features except for kurtosis show uncertain behavior.The Stockwell transform showed low-resolution outcomes when the presence of noise in the recorded vibration responses.The elimination of noise and extraction of meaningful dynamic properties from the vibration responses is done by applying a new method which comes from the fusion of Hilbert transform with Spectral kurtosis and bandpass filtering.The outcomes obtained from Hilbert transform processed residual signals which are further filtered using bandpass filter show more robustness and accuracy in characterizing bridge modal frequencies from the noisy vibration responses.The proposed method produces a high-resolution frequency response which can unveil the joint discrepancy in the bridge structure.

A Method for Incipient Fault Diagnosis of Roller Bearings Based on the Wavelet Transform Correlation Filter and Hilbert Transform

Noise is the biggest obstacle that makes the incipient fault diagnosis results of roller bearings uncorrected; a new method for diagnosing incipient fault of roller bearings based on the Wavelet Transform Correlation Filter and Hilbert Transform was proposed. First, the weak fault information features are picked up from the roller bearings fault vibration signals by use of a de-noising characteristic of the Wavelet Transform Correlation Filter as the preprocessing of the Hilbert Envelope Analysis. Then, in order to get fault features frequency, de-noised wavelet coefficients of high scales which represent high frequency signal were analyzed by Hilbert Envelope Spectrum Analysis. The simulation signals and diagnosing examples analysis results reveal that the proposed method is more effective than the method of direct wavelet coefficients-Hilbert Transform in de-noising and clarifying roller bearing incipient fault.

Phase Error Compensation of Three-Dimensional Reconstruction Combined with Hilbert Transform

Nonlinear response is an important factor affecting the accuracy of three-dimensional image measurement based on the fringe structured light method.A phase compensation algorithm combined with a Hilbert transform is proposed to reduce the phase error caused by the nonlinear response of a digital projector in the three-dimensional measurement system of fringe structured light.According to the analysis of the influence of Gamma distortion on the phase calculation,the algorithm establishes the relationship model between phase error and harmonic coefficient,introduces phase shift to the signal,and keeps the signal amplitude constant while filtering out the DC component.The phase error is converted to the transform domain,and compared with the numeric value in the space domain.The algorithm is combined with a spiral phase function to optimize the Hilbert transform,so as to eliminate external noise,enhance the image quality,and get an accurate phase value.Experimental results show that the proposed method can effectively improve the accuracy and speed of phase measurement.By performing phase error compensation for free-form surface objects,the phase error is reduced by about 26%,and about 27%of the image reconstruction time is saved,which further demonstrates the feasibility and effectiveness of the method.

WEIGHTED HILBERT TRANSFORM AND BαMETRIC

In the paper, the author generalized the Hardy and Littlewood's theorem toBa space, i.e. for all Pm satisfying 1 < α = infpm≤ β≤ suppm < ∞, m = 1, 2,..., and the following inequalityholds if and on1y if.

Oscillatory hyper Hilbert transforms along curves

The hyper Hilbert transform Tnf（x） =∫-1^1 f（x - Γ（t））e^-i｜t｜-β｜t｜^-1-αdt along an appropriate curve Γ（t） on R^n is investigated,where β 〉 α 〉 0.An L^p boundedness theorem of T4 is obtained,which is an extension of some earlier results of n = 2 and n = 3.

Transient Power and Quality Events Analysed Using Hilbert Transforms

This work presents an advanced mathematical tool applicable to the recognition and classification of power system transients and disturbances. Disturbances without a periodic pattern or with a non-linear pattern require a more suitable tool than the Fourier series （Fast Fourier or Windowed Fourier Transforms）. To overcome these drawbacks, other tools have been broadly used, such as the wavelet transform. However, the wavelet transform also has some drawbacks such as the lack of adaptivity or interpretation of nonlinear phenomena that the Hilbert and Hilbert Huang Transform techniques could mitigate. The Hilbert techniques transform a time domain function into a space representation both in time and frequency. In the paper, the technique is applied to analyse several short-term and steady events, like a short circuit, a capacitor-switching transient, or a line energisation, showing the abilities of the Hilbert-based transforms.

Measurement of Moment of Inertia Based on Hilbert Transform

A measurement model based on torsion pendulum was established,in which nonlinear damping and nonlinear restoring force were considered.The calculation method of the moment of inertia was based on Hilbert transform.The motion of torsion pendulum showed the time-frequency characteristics due to the nonlinear factors,which were validated by the experimental data.The analytical signal was formed by Hilbert transform of the angular displacement signal of the test object.The moment of inertia can be computed by the instantaneous undamped natural frequency with Hilbert transform.Prior to the implementation of Hilbert transform,the empirical mode decomposition was used to filter the experimental signal.The moment of inertia of the test object was measured by the torsion pendulum system.The experimental results show that the relative measurement error of the moment of inertia was within 0.7%,which indicated the validity of the measurement method.

ITERATIVE ALGORITHM FOR HILBERT TRANSFORM WITH LESS LEAKAGE

An iterative algorithm is developed for the Hilbert transform based on FFT using the phase in-formation of modulated signal.The feature of this iterative algorithm is frequency shifting on apart of non-integral frequency in a modulated signal,and the final result of the orthogonal signalwith less pollution caused by the leakage phenomenon is obtained.The algorithm has been appliedto estimate envelope,center frequency and initial phase,including simulation and engineering ex-amples.

An Application of Sinc Sum Function in Hilbert Transformer

An application of the sinc sum function in Hilbert transformer (HT) is studied. The expression of the frequency re- sponse of HT is expressed with sinc sum functions. Some properties of sub-amplitude response of HT are proved by using the properties of the sinc sum function. A general HT formula is obtained theoretically and it contains a general window function. As an example three new window functions are obtained. Different from the existing window func- tions obtained from lowpass filters, these window functions are obtained directly from HT. Comparisons show that new windows are better than the Hanning, Hamming, Blackman and Kaiser windows in terms of HT performances.

Complex Hilbert Transform Filter

Hilbert transform is a basic tool in constructing analytical signals for a various applications such as amplitude modulation, envelope and instantaneous frequency analysis, quadrature decoding, shift-invariant multi-rate signal processing and Hilbert-Huang decomposition. This work introduces a complex Hilbert transform (CHT) filter, where the real and imaginary parts are a Hilbert transform pair. The CHT filtered signal is analytic, i.e. its Fourier transform is zero in negative frequency range. The CHT filter is constructed by half-sample delay operators based on the B-spline transform interpolation and decimation procedure. The CHT filter has an ideal phase response and the magnitude response is maximally flat in the frequency range 0 ≤ ω ≤ π. The CHT filter has integer coefficients and the implementation in VLSI requires only summations and register shifts. We demonstrate the feasibility of the CHT filter in reconstruction of the sign modulated CMOS logic pulses in a fibre optic link.

Computation of Hilbert Transform via Discrete Cosine Transform

Hilbert transform (HT) is an important tool in constructing analytic signals for various purposes, such as envelope and instantaneous frequency analysis, amplitude modulation, shift invariant wavelet analysis and Hilbert-Huang decomposition. In this work we introduce a method for computation of HT based on the discrete cosine transform (DCT). We show that the Hilbert transformed signal can be obtained by replacing the cosine kernel in inverse DCT by the sine kernel. We describe a FFT-based method for the computation of HT and the analytic signal. We show the usefulness of the proposed method in mechanical vibration and ultrasonic echo and transmission measurements.

Determination of Instantaneous Frequencies of Low Plasma Waves in the Magnetosheath Using Empirical Mode Decomposition (EMD) and Hilbert Transform (HT)

The observations of in-situ spacecraft mission in the magnetosheath and a region of thermalized subsonic plasma behind the bow shock reveal a non-linear behaviour of plasma waves. The study of waves and optics in Physics has given the understanding of the effect of many waves coming together to form a wave field or wave packet. The common aspect of such study shows that two or more waves can superimpose constructively or destructively. The sudden high magnetic field data in the magnetosheath displays such possibility of superposition of waves. In this paper, we use the empirical mode decomposition (EMD) and Hilbert transform (HT) techniques to determine the instantaneous frequencies of low frequency plasma waves in the magnetosheath. Our analysis has shown that the turbulent behavior of magnetic field in the magnetosheath within the selected period is due to superposition of waves.

Phase-unwrapping algorithm combined with wavelet transform and Hilbert transform in self-mixing interference for individual microscale particle detection

The self-mixing interferometry(SMI)technique is an emerging sensing technology in microscale particle classification.However,due to the nature of the SMI effect raised by a microscattering particle,the signal analysis suffers from many problems compared with a macro target,such as lower signal-to-noise ratio(SNR),short transit time,and time-varying modulation strength.Therefore,the particle sizing measurement resolution is much lower than the one in typical displacement measurements.To solve these problems,in this paper,first,a theoretical model of the phase variation of a singleparticle SMI signal burst is demonstrated in detail.The relationship between the phase variation and the particle size is investigated,which predicts that phase observation could be another alternative for particle detection.Second,combined with continuous wavelet transform and Hilbert transform,a novel phase-unwrapping algorithm is proposed.This algorithm can implement not only efficient individual burst extraction from the noisy raw signal,but also precise phase calculation for particle sizing.The measurement shows good accuracy over a range from 100 nm to 6μm with our algorithm,proving that our algorithm enables a simple and reliable quantitative particle characteristics retrieval and analysis methodology for microscale particle detection in biomedical or laser manufacturing fields.

基于声信号递归Hilbert变换的轴承故障诊断研究

轴承缺陷检测与损伤程度检测一直是旋转机械领域内非常重视的问题,虽然目前针对振动信号的研究已经取得相当好的结果,但是对于难以安装振动传感器的情况,诊断效果仍需改进。针对强背景噪声下故障轴承产生的声音,提出一种基于递归Hilbert变换和一维卷积神经网络的诊断方法来提取抽象特征并进行模式识别。卷积神经网络结构中引入了全局平均池化层来加速网络的运行。最后,通过数据集验证了所提方法的有效性,与其他常用分类方法进行对比,验证了该方法的优越性。结果表明:所提算法不仅能够准确识别轴承的损伤部位,而且能够准确区分部件的损伤程度。

基于改进Hilbert-Huang变换的管路环向裂纹故障诊断研究

在制造、加工、装配以及服役过程中,航空液压管路可能存在平面型缺陷。在适航载荷作用下,这些缺陷会萌生裂纹并发生扩展,最终导致管路破裂和油液泄漏。为了在管路产生微裂纹时对其进行故障诊断,采用了自行搭建的航空液压管路模态试验平台和测控系统,对存在环向裂纹航空液压管路的振动信号进行了采集和预处理。而在对管路振动信号进行分解时,由于经验模态分解(Empirical Mode Decomposition,EMD)算法存在模态混叠问题难以获得准确的本征模态函数(Intrinsic Mode Functions,IMF)。为提高信号处理精度,提出一种基于自适应噪声完备经验模态分解(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise,CEEMDAN)和Hilbert变换理论相结合的改进Hilbert-Huang变换方法对航空液压管路环向裂纹进行故障诊断。研究结果表明,该方法能够更准确地诊断航空液压管路的环向裂纹故障。

基于Hilbert变换的条纹-灰度线性投影三维测量

针对传统的条纹投影测量中绝对相位求解方法存在投影图像数量较多以及算法复杂程度高的问题,提出了一种基于Hilbert变换的条纹-灰度线性投影策略及相位求解方法,该方法仅使用3幅投影图像——1幅高频条纹图和2幅灰度线性变化图,通过Hilbert变换求得包裹相位,采用灰度线性变化图像得到基础相位,联立包裹相位和基础相位可得到条纹级数,进而得到绝对相位。通过构建的主动双目系统得到的三维重构结果发现,该方法可以有效恢复被测物体的三维形状,测量精度可达0.1 mm。

基于CEEMDAN-Hilbert变换的水下爆炸信号时频分析方法研究

研究水下爆炸冲击波信号的时频特性,对于舰艇利用弹药水下爆炸信号对抗自导鱼雷具有重要的实际意义。本文针对EMD-Hilbert方法中经验模态分解(EMD)存在模态混叠的问题,提出CEEMDAN-Hilbert方法实现水下爆炸冲击波信号精确的时频分析。在水深100 m处单发炸药爆炸,产生爆炸信号的频率主要分布在56.5 kHz以下的低频段,特别是0~28.3 kHz以下的能量最大,高于56.5 kHz的能量较少。通过与EMD-Hilbert方法相比,CEEMDAN-Hilbert方法在28.3~56.5 kHz频段的能量分布会更加明显,具有一定的优越性。