Influence of laser intensity in second-harmonic detection with tunable diode laser multi-pass absorption spectroscopy

Tunable diode laser absorption spectroscopy （TDLAS） has been widely employed in atmospheric trace gases detection. The ratio of the second-harmonic signal to the intensity of laser beam incident to the multi-pass cell is proved to be proportional to the product of the path length and the gas concentration under any condition. A new calibration method based on this relation in TDLAS system for the measurement of trace gas concentration is proposed for the first time. The detection limit and the sensitivity of the system are below 110 and 31ppbv （parts-per-billion in volume）, respectively.

FAST IMPLEMENTATION OF ORTHOGONAL EMPIRICAL MODE DECOMPOSITION AND ITS APPLIGA-TION INTO HARMONIC DETECTION

Since the empirical mode decomposition （EMD） lacks strict orthogonality, the method of orthogonal empirical mode decomposition （OEMD） is innovationally proposed. The primary thought of this method is to obtain the intrinsic mode function （IMF） and the residual function by auto-adaptive band-pass filtering. OEMD is proved to preserve strict orthogonality and completeness theoretically, and the orthogonal basis function of OEMD is generated, then an algorithm to implement OEMD fast, IMF binary searching algorithm is built based on the point that the analytical band-pass filtering preserves perfect band-pass feature in the frequency domain. The application into harmonic detection shows that OEMD successfully conquers mode aliasing, avoids the occurrence of false mode, and is featured by fast computing speed. Furthermore, it can achieve harmonic detection accurately combined with the least square method.

An Intelligent Intrusion Detection System in Smart Grid Using PRNN Classifier

Typically,smart grid systems enhance the ability of conventional power system networks as it is vulnerable to several kinds of attacks.These vulnerabil-ities might cause the attackers or intruders to collapse the entire network system thus breaching the confidentiality and integrity of smart grid systems.Thus,for this purpose,Intrusion detection system(IDS)plays a pivotal part in offering a reliable and secured range of services in the smart grid framework.Several exist-ing approaches are there to detect the intrusions in smart grid framework,however they are utilizing an old dataset to detect anomaly thus resulting in reduced rate of detection accuracy in real-time and huge data sources.So as to overcome these limitations,the proposed technique is presented which employs both real-time raw data from the smart grid network and KDD99 dataset thus detecting anoma-lies in the smart grid network.In the grid side data acquisition,the power trans-mitted to the grid is checked and enhanced in terms of power quality by eradicating distortion in transmission lines.In this approach,power quality in the smart grid network is enhanced by rectifying the fault using a FACT device termed UPQC(Unified Power Quality Controller)and thereby storing the data in cloud storage.The data from smart grid cloud storage and KDD99 are pre-pro-cessed and are optimized using Improved Aquila Swarm Optimization(IASO)to extract optimal features.The probabilistic Recurrent Neural Network(PRNN)classifier is then employed for the prediction and classification of intrusions.At last,the performance is estimated and the outcomes are projected in terms of grid voltage,grid current,Total Harmonic Distortion(THD),voltage sag/swell,accu-racy,precision,recall,F-score,false acceptance rate(FAR),and detection rate of the classifier.The analysis is compared with existing techniques to validate the proposed model efficiency.

Power System Harmonic Detection Using Frequency-Domain Interpolation Wavelet Transform

Aiming at harmonic detection, fast Fourier transform can only detect integer harmonics precisely, short time Fourier transform can detect non-integer harmonics with low resolution, and some former wavelet based methods have no aliasing-reduction scheme which result in low measurement precision and poor robustness. A frequency-domain interpolation algorithm to detect harmonics is proposed by choosing Shannon wavelet. Shannon wavelet is an orthogonal wavelet possessing best ideal frequency domain localization ability, it can restrict wavelet abasing but bring about Gibbs oscillation phenomenon simultaneously. An interpolation algorithm is developed to overcome this problem. Simulation reveals that the proposed method can effectively cancel aliasing, spectral leakage and Gibbs phenomenon, so it provides an effective means for power system harmonic analysis.

TECHNIQUE USED INDETECTING EXTRANEOUS HARMONICS FOR VARIABLE SPEED CONSTANT FREQUENCY（VSCF）POWER SUPPLY

An extraneous harmonics detection scheme is introduced, based on the frequency shift technique. The main principle is described; practical operation scheme is il-lustrated; both related microcomputer system circuit and its software designs are alsobriefly described. Finally, the scheme is validated by the experiment results.

Harmonic detection an AC excited generation system based on in-phase correlation filtering

The paper reports results of investigation on the harmonic detection technique of a complicated power supply system such as an AC excited generation system, which has a variable fundamental frequency and low order harmonics with rich sub-harmonics whose frequencies are lower than the fundamental one. The in-phase correlation filtering technique, based on the frequency shifting principle, is proposed in this paper.Theoretical analysis and experimental results validate the effectiveness of this technique for the harmonic detections of AC excited generation systems.

In-Situ Domestic Load Harmonic Detection and Reduction Based on GLRM Algorithm for Optimum Filter Excerpt

Power Quality measures the reliable operation between the system and to the connected loads of same system. A poor power quality causes physical damage to the equipment and also results in lower productivity with increase in energy costs. Power disturbances range from micro seconds to hours and the prolonged disturbances in hours would damage the equipments. The power quality decreases due to growth of nonlinear loads in domestic appliances, such as home Uninterrupted Power Supplies (UPS), Induction stove, Television etc. Nowadays Domestic loads are controlled or powered with power electronic devices. The power electronic devices with Direct Current (DC) components generate high frequency signal for DC-Alternating Current (AC) conversion. The conversion introduces multiple frequencies in the AC power supply. The multiple frequencies in AC power supply are called as harmonics. The harmonics in AC supply affects the lifetime of home appliances, consumes more electric current, affects the power factor, transformer efficiency, and other electricity supply systems. Till now, to avoid harmonics, the filters are erected only in industrial loads or in the substations. In this paper a novel method to detect and control harmonics in domestic appliances is proposed. Harmonic control with various filters in the filter bank, based on detection of harmonic voltage let out from the domestic appliances for power saving. To select the appropriate filter to improve power quality, we apply a novel Genetic Algorithm based Linear Regression Method (GLRM) algorithm for optimum Filter Selection. From the results we were able to reduce the total harmonic distortion level to 3.68%.The current consumption of each household appliance is reduced considerably and finally the electricity bill is reduced to 15% and overall system efficiency improves to 85%.

Hydrogen sulphide detection using near-infrared diode laser and compact dense-pattern multipass cell

Sub-ppmv level detection of hydrogen sulphide(H2 S) using a 1.578-μm distributed feedback tunable diode laser combining with wavelength modulation spectroscopy and second harmonic detection scheme is reported. A home-developed novel compact dense-pattern multipass gas cell with an effective optical path length of 29.37 m is used to improve sensitivity and reduce sample volume. Detection parameters are optimized, including modulation frequency and amplitude. The analysis of Allan variance shows that a minimum detectable concentration 60 ppbv is obtained with a lock-in time constant of 10 ms, and a detection limit of 13 ppbv can be achieved by average in 300 s. The demonstrated H2 S sensor has a strong penitential application in natural gas process for regulating and controlling H2 S concentration.

Real-Time Method for Detecting Harmonic and Reactive Currents of Single-Phase Circuits

According to the characteristics of single-phase circuits and demand of using active filter for real-time detecting harmonic and reactive currents, a detecting method based on Fryze＇s power definition is proposed. The results of theoretical analysis and simula- tion show that the proposed method is effective in realtime detecting of instantaneous harmonic and reactive currents in single-phase circuits. When only detecting the total reactive currents, this method does not need a phase-locked loop circuit, and it also can be used in some special applications to provide different compensations on the ground of different requirements of electric network. Compared with the other methods based on the theory of instantaneous reactive power, this method is simple and easy to realize.

SPEECH ENHANCEMENT USING HARMONICS REGENERATION BASED ON MULTIBAND EXCITATION

This paper proposes an algorithm that adopts the harmonic regeneration as post-processing to improve the performance of speech enhancement using traditional Short Time Spectral Amplitude(STSA).The proposed algorithm aims to alleviate the distortion of the high harmonics of enhanced speech via the traditional STSA,and consequently improves the speech quality.We first detect the pitch,or fundamental frequency,of the enhanced speech via the traditional STSA,and then,divide the whole spectrum into multiple sub-bands which center on each harmonic.After that,a series of specially designed windows centered on each harmonic are applied to all the sub-bands,in order to redistribute the energy in the sub-bands.The results of experiment demonstrate that the method has both theo-retical and practical basis.

Active Power Filter Based on Adaptive Detecting Approach of Harmonic Currents

The ip-iq detection method based on instantaneous inactive power theory has been applied widely in active power filter because of its good real-time. But it needs large computation, and three-phase currents are processed as integrity, thus calculation accuracy can't be ensured. Based on adaptive interference canceling theory, this paper presents a new ad- aptive detection method for harmonic current, it is a continuously regulated closed-loop system, and its operating characteristics are almost independent of the parameter variations of the elements, thus it performs better than that based on traditional theory. At last this paper provides the simulation of active power filter including the detecting cir-cuit which proved the design is feasible and correct.

A New Sensorless Technique for the Speed Detection of an Induction Motor

This paper presents a new sensorless method, the so-called harmonic impedance / admittance, for detecting speed of induction motors, which is based on the impedance measurement, harmonic analysis and digital signal processing. The method improves theperformance of conventional voltage-based and current-based techniques, because the impedance or admittance harmonics is independent of input or output of motor system due to the system-inherent nature of impedance. It has been used successfully in detecting the rotor speed of three-phase induction motors. A comparison between the proposed method and the conventionalcurrent-based method is also demonstrated.

Harmonicity Spectrum

Perceiving harmonic information (especially weak harmonic information) in time series has important scientific and engineering significance. Fourier spectrum and time-frequency spectrum are commonly used tools for perceiving harmonic information, but they are often ineffective in perceiving weak harmonic signals because they are based on energy or amplitude analysis. Based on the theory of Normal time-frequency transform (NTFT) and complex correlation coefficient, a new type of spectrum, the Harmonicity Spectrum (HS), is developed to perceive harmonic information in time series. HS is based on the degree of signal harmony rather than energy or amplitude analysis, and can therefore perceive very weak harmonic information in signals sensitively. Simulation examples show that HS can detect harmonic information that cannot be detected by Fourier spectrum or time-frequency spectrum. Acoustic data analysis shows that HS has better resolution than traditional LOFAR spectrum.

一种混合低谐无盲区的孤岛检测方法

主动式检测方法作为一种常用的孤岛检测方法,虽然可以通过增加扰动强度使孤岛检测盲区得以减小,但同时会增大对电网的谐波污染程度。针对此问题,提出了一种混合模糊低谐无盲区的孤岛检测方法,即首先对盲区进行判断,优先使用对电网无谐波污染的被动式孤岛检测方法,若此时处于被动式检测方法盲区之内,则使用一种具有模糊扰动控制的对输出电流第二、四个1/4周期进行扰动的模糊低谐孤岛检测方法。最后搭建相应的仿真模型对所提方法的有效性进行验证。

车用SLM成形DP780钢的疲劳损伤非线性电磁超声换能检测

为了提高对车用选区激光熔化(SLM)成形DP780钢的疲劳损伤检测精度,提出了一种基于非线性电磁超声换能的疲劳加载信号分析方法,通过高次谐波检测技术测定合金的损伤情况。研究结果表明:时域信号波形相对较为稳定,基波幅值在频率为5 MPa时出现,在5000次疲劳测试后,与初始试件相比,试样中产生信号的幅值更显著。非线性电磁超声换能检测很容易影响二次谐波的产生。二次谐波具有更高的幅值,大量疲劳裂纹存在于基体内部。本研究可满足精准检测疲劳损伤条件。在对疲劳损伤程度确定时,参考疲劳寿命和循环加载周次,超声非线性系数在周边测试点处增长幅度相对较小,中心测试点较大,主要原因是内部结构变形情况更明显。

基于Adaline算法的高速磁浮列车谐波检测及抑制方法

[目的]为了减小高速磁浮谐波对牵引网产生的影响,保障高速磁浮列车的正常运行,需研究高速磁浮牵引供电系统中的谐波特性及其相应的谐波抑制方法。[方法]分析了高速磁浮牵引供电系统的构成,并对双三相半控12脉冲多重整流电路及其谐波进行了理论分析和仿真。根据Adaline神经网络算法原理和高速磁浮谐波特性,构建基于Adaline的高速磁浮谐波检测模型。采用谐波补偿控制策略,产生与检测出的谐波方向相反、大小相等的电流作为补偿信号,对系统畸变电流进行谐波抑制。[结果及结论]仿真结果表明:采用基于Adaline算法的谐波检测及抑制方法前,谐波畸变率为11.16%,而采用该方法后,各次谐波含量明显降低,谐波畸变率下降为1.41%。研究结果表明:所提谐波检测及抑制方法可以有效减少谐波畸变,提高牵引供电系统的稳定性和工作效率。

基于一种新型正弦幅值积分器的谐波检测方法

针对基于瞬时无功理论的ip-iq谐波检测法结构复杂、响应速度慢等问题,提出了一种采用改进正弦幅值积分器结构的谐波电流检测方法。首先,利用二阶广义积分器的输出滤波特性及正弦幅值积分器的极性选择特性,使其相结合构造出了一种滤波性能更强,同时具有频率及极性选择作用的新型积分器。然后,利用该积分器快速准确地提取基波正序分量,并有效应用于谐波检测环节中。当电网电压存在直流偏置问题时,该积分器所构造的锁相环也能准确锁定电网频率及相位信息。最后,理论分析及仿真实验结果表明:该方法无需进行瞬时对称分量分离,就可提取出电网电压及负载电流基波的正负序分量,计算量小,谐波检测更精确。

基于分数阶小波变换的电力系统谐波检测方法

针对稳态和暂态谐波检测易受噪声干扰的问题,提出一种基于分数阶小波变换(fractional wavelet transform,FRWT)的电力系统谐波检测方法。首先,通过快速傅里叶变换(fast Fourier transform,FFT)检测出各频谱的频率,根据频率确定分解层数;其次,利用FRWT对信号进行分解和重构,实现基波与各次谐波分量的分离;最后,对各次谐波分量进行Hilbert变换(Hilbert transform,HT),获取各次谐波分量的频率和幅值检测结果以及暂态扰动的起止时刻。对多种谐波信号的仿真试验结果表明,FRWT方法可以有效实现对含噪信号中稳态和暂态谐波的检测,即使信噪比较低也能保证各项结果的检测精度,证明FRWT方法是检测谐波的一种有效新方法。

柔性直流输电系统的高频谐波保护方法与工程实践

柔性直流输电系统受电力电子设备本身特性以及控制系统影响,在多种运行工况下易出现不同频率的振荡问题。作为实现设备安全和电网稳定运行的决定因素,保护系统应实现对系统谐波的准确监测以及可靠动作。根据高频振荡时的电流能量累积作用,给出了基于反时限动作的电流类谐波保护算法。基于高频谐波电压特性,分别给出了过零点监测保护算法、谐波畸变率保护算法以及宽谐波保护算法,各保护算法相互配合,实现对不同电压振荡类型的全面保护。最后,给出了国内柔性直流工程实践中配置的高频谐波保护,结合保护原理对系统发生高频振荡后的动作特性进行分析,验证了高频谐波保护的有效性和准确性。

基于小波Adaline改进的充电桩谐波分析及扰动定位方法

针对Adaline网络在复杂信号谐波检测中基波频率难以获取的问题,提出一种小波重构与改进型Adaline网络结合的谐波分析方法,并将该方法应用于充电桩谐波分析中。首先,用Mallat算法对原信号分解,再将细节信号重构实现扰动定位,将近似信号重构得到去噪原信号与基波信号,通过基波获取频率。其次,对Adaline网络相位提取算法进行优化,使其兼容全部相位范围,将去噪原信号通过优化后的Adaline网络检测谐波幅值及其对应的相位,综合误差为0.766%,比传统的Adaline模型精度提升了28.642%;最后,将该方法应用于充电桩模型,实现谐波检测,并精准定位扰动发生时段,进一步论证了该方法的适用性。