基于信号傅里叶变换的排水管道漏点自动化定位方法研究

传统排水管道漏点自动化定位方法是直接对排水管道泄漏判断阈值进行设定,未对泄漏信号进行滤波降噪,造成定位结果精准度较低。鉴于此,提出基于信号傅里叶变换的排水管道漏点自动化定位方法,对管道泄漏信号进行滤波降噪处理,并对降噪后的信号进行傅里叶变换,以便分析其频率成分和特征,从而对排水管道泄漏判断阈值进行设定,通过计算得到压力曲线,实现漏点自动化定位。实验结果表明,该研究方法得到的定位结果精准度较高,更具实用性。

Fractional S transform-Part 1:Theory

The S transform, which is a time-frequency representation known for its local spectral phase properties in signal processing, uniquely combines elements of wavelet transforms and the short-time Fourier transform （STFT）. The fractional Fourier transform is a tool for non-stationary signal analysis. In this paper, we define the concept of the fractional S transform （FRST） of a signal, based on the idea of the fractional Fourier transform （FRFT） and S transform （ST）, extend the S transform to the time-fractional frequency domain from the time- frequency domain to obtain the inverse transform, and study the FRST mathematical properties. The FRST, which has the advantages of FRFT and ST, can enhance the ST flexibility to process signals. Compared to the S transform, the FRST can effectively improve the signal time- frequency resolution capacity. Simulation results show that the proposed method is effective.

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.

MP-WFRFT and Constellation Scrambling Based Physical Layer Security System

In this paper, a multiple parameters weighted fractional Fourier transform(MPWFRFT) and constellation scrambling(CS) method based physical layer(PHY) security system is proposed. The proposed scheme is executed by two steps. In the first step, MPWFRFT, implemented as the constellation beguiling(CB) method, is applied to change the signal's identity. In the second step the additional pseudo random phase information, regarded as the encryption key, is attached to the original signal to enhance the security. Typically, the pseudo random phase information can be removed effectively by the legitimate receiver. In contrast to the cryptography based encryption algorithms and the conventional PHY secrecy techniques, the main contribution of the proposed scheme is concentrated on the variation in signal's characteristics. Simulation results show that the proposed scheme can prevent the exchanging signal from eavesdroppers' classifi cation or inception. Moreover, the proposed scheme can guarantee the BER performance at a tolerate increasing in computational complexity for the legitimate receivers.

Direction of Arrivals Estimation for Correlated Broadband Radio Signals by MVDR Algorithm Using Wavelet

A theoretical relationship between the wavelet transform and the fast fourier transformation(FFT) methods in broadband wireless signal is proposed for solving the direction of arrivals(DOAs) estimation problem. This leads naturally to the derivation of minimum variance distortionless response(MVDR) algorithm, which combines the benefits of subspace methods with those of wavelet, and spatially smoothed versions are utilized which exhibits good performance against correlated signals. We test the method's performance by simulating and comparing the performance of proposed algorithm, FFT MVDR and MVDR with correlated signals, and an improved performance is obtained.

Characteristics and interpretation of the seismic signal of a field-scale landslide dam failure experiment

Outburst floods caused by breaches of landslide dams may cause serious damages and loss of lives in downstream areas; for this reason the study of the dynamic of the process is of particular interest for hazard and risk assessment. In this paper we report a field-scale landslide dam failure experiment conducted in Nantou County, in the central of Taiwan.The seismic signal generated during the dam failure was monitored using a broadband seismometer and the signal was used to study the dam failure process.We used the short-time Fourier transform(STFT) to obtain the time–frequency characteristics of the signal and analyzed the correlation between the power spectrum density(PSD) of the signal and the water level. The results indicate that the seismic signal generated during the process consisted of three components: a low-frequency band(0–1.5 Hz), an intermediate-frequency band(1.5–10 Hz) and a highfrequency band(10–45 Hz). We obtained the characteristics of each frequency band and the variations of the signal in various stages of the landslide dam failure process. We determined the cause for the signal changes in each frequency band and its relationship with the dam failure process. The PSD sediment flux estimation model was used to interpret the causes of variations in the signal energy before the dam failure and the clockwise hysteresis during the failure. Our results show that the seismic signal reflects the physical characteristics of the landslide dam failure process. The method and equipment used in this study may be used to monitor landslide dams and providing early warnings for dam failures.

Evaluating ultrasound signals of carbon steel fatigue testing using signal analysis approaches

The application of ultrasound techniques to monitor the condition of structures is becoming more prominent because these techniques can detect the early symptoms of defects such as cracks and other defects.The early detection of defects is of vital importance to avoid major failures with catastrophic consequences.An assessment of an ultrasound technique was used to investigate fatigue damage behaviour.Fatigue tests were performed according to the ASTM E466-96 standard with the attachment of an ultrasound sensor to the test specimen.AISI 1045 carbon steel was used due to its wide application in the automotive industry.A fatigue test was performed under constant loading stress at a sampling frequency of 8 Hz.Two sets of data acquisition systems were used to collect the fatigue strain signals and ultrasound signals.All of the signals were edited and analysed using a signal processing approach.Two methods were used to evaluate the signals,the integrated Kurtosis-based algorithm for z-filter technique(I-kaz) and the short-time Fourier transform(STFT).The fatigue damage behaviour was observed from the initial stage until the last stage of the fatigue test.The results of the I-kaz coefficient and the STFT spectrum were used to explain and describe the behaviour of the fatigue damage.I-kaz coefficients were ranged from 60 to 61 for strain signals and ranged from 5 to 76 for ultrasound signals.I-kaz values tend to be high at failure point due to high amplitude of respective signals.STFT spectrogram displays the colour intensity which represents the damage severity of the strain signals.I-kaz technique is found very useful and capable in assessing both stationary and non-stationary signals while STFT technique is suitable only for non-stationary signals by displaying its spectrogram.

A FREQUENCY OFFSET ESTIMATION ALGORITHM FOR OFDM SYSTEMS

A new fine carrier frequency offset estimation algorithm in Orthogonal Frequency Division Multiplexing (OFDM) system is proposed. The correlation item is the training sequence instead of the received signal in the new algorithm. Simulation results show that the performance of the new algo- rithm is 4dB-9dB better than that of Schmidl's algorithm. Coarse frequency offset estimation is also discussed in this paper, which is the improvement of Zhang's method. The estimation range using the improvement method is twice as that using the Zhang's method. Based on the hardware of the receiver and the improved algorithm, a method using Fast Fourier Transform (FFT) is proposed to implement the coarse frequency estimation. The chip area of OFDM system can be reduced by using the proposed method.

New Levels of the Pr Atom with Almost Similar Energies

A Fourier transform （FT） spectrum of praseodymium （Pr） extending from UV to IR was investigated. Hyperfine （hf） structures of unclassified lines with sufficiently high signal to noise ratio （SNR） were analyzed and some new levels were found. We present these new levels in this work. Some of the new levels have energies almost equal to the energies of already known or other new levels, distinguished either by different values of angular momentum J or by their parity.

A Parametric Autoregressive Model for the Extraction of Electric Network Frequency Fluctuations in Audio Forensic Authentication

This paper proposes a new method for extracting ENF （electric network frequency） fluctuations from digital audio recordings for the purpose of forensic authentication. It is shown that the extraction of ENF components from audio recordings is realizable by applying a parametric approach based on an AR （autoregressive） model. The proposed method is compared to the existing STFT （short-time Fourier transform） based ENF extraction method. Experimental results from recorded electrical grid signals and recorded audio signals show that the proposed approach can improve the time resolution in the extracted ENF fluctuations and improve the detection of tampering with short alterations in longer audio recordings.

A dynamic phasor estimation algorithm based on angle-shifted energy operator

Under dynamic conditions, the signals of power system have time-varying magnitude and frequency, which might lead to considerable errors for synchrophasor measurement. The traditional discrete Fourier transform (DFT) based algorithms used in Phasor Measurement Unit (PMU) are hard to meet the requirements of measurement accuracy because of the existence of spectral leakage. A dynamic phasor measurement algorithm is proposed in this paper in which the input sampled data are considered as non-stationary signals with amplitude modulation-frequency modulation (AM-FM) form, and the measurement is achieved by AM-FM demodulation. An angle-shifted energy operator (ASEO) is used to extract the instantaneous amplitude and low pass differential filter is introduced for frequency estimation. Simulation results indicate that the proposed algorithm can effectively improve the phasor measurement accuracy and has very short response time for PMU under dynamic conditions.