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.

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.

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.

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%.

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.

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.

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.

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.

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.

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.

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.

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.

基于ARM嵌入式技术的单相电力谐波检测方法

为保证设备和系统的安全稳定运行,提高电能质量,提出一种基于ARM嵌入式技术的单相电力谐波检测方法。首先,以ARM处理器为核心设计单相电力数据采集模块,采集多通道数据。然后,设计信号调理电路和频率跟踪电路,用于处理单相电力数据,确保采样的同步性。最后,在通信模块和液晶显示屏的支持下,实现多端通信数据传输,对数据进行快速处理,展示在显示屏上,完成单相电力谐波检测工作。实验结果表明:该方法的测量误差在4%以下;曲线斜率最高,最接近1,说明该方法的检测精度高,能够适应复杂的工作环境,具有较强的检测稳定性。

基于TDLAS的电池干燥过程水汽浓度检测

采用基于可调谐半导体激光吸收光谱(TDLAS)的方法研究了在电芯干燥过程中由于压强变化产生的痕量水的测量误差问题,实现了对水汽含量无接触、高精度、实时的检测。首先,根据Lambert-Beer定律发现,水汽吸收谱线、光程及压强的变化会影响测量精度,通过HITRAN仿真的方法分别研究了105℃下水汽吸收谱线和测量有效光程,研究结果显示激光器工作在7181.17 cm^(-1)波段时水分子吸收测量结果最佳且没有背景气体干扰,光程在12 m时可以达到10^(-3)数量级的精度。压强的变化会导致二次谐波峰值改变进而影响水汽测量。研究不同压强下水汽的吸收情况,发现压强与吸收呈现正相关的规律,利用这一规律提出了使用归一化方法解决压强变化引起的测量误差。实验测试发现,经过压强补偿的二次谐波峰值波动从350 mV降为6.2 mV,5组实验结果表明水含量与二次谐波的峰值电压比值为0.24,标定后的测量误差小于1.2%。这些结果为提高电池干燥过程中水汽含量的检测精度具有重要的指导意义。

基于Matlab的p-q法与ip-iq法仿真分析

针对p-q法和ip-iq法的谐波电流检测效果的比较,由于两种检测方法都是首先检测出原电流基波分量,再与原电流做差得到原电流谐波分量,因此可以通过计算检测出的基波电流中的谐波含量或畸变率来比较两种方法的检测性能。在接有非线性负载的系统中,通过控制电压源的电压波形,在(0.8-0.9)s时间段内产生标准正弦电压,在(0.9-1.0)s时间段内产生的畸变电压,利用p-q法和ip-iq法分别对同一检测点进行谐波电流检测。通过Matlab软件仿真试验,在(0.8-0.9)s时间段内利用p-q法和ip-iq法测得的基波电流的畸变率分别为1.72%和2.04%,在(0.9-1.0)s时间段内利用p-q法和ip-iq法测得的基波电流的畸变率分别为32.73%和4.39%。从而得出结论:在检测点处电压无畸变时,两种方法的检测性能都比较好,基波电流畸变率低,误差小;当电压发生畸变时,p-q法检测性能变差,基波电流畸变率变高,而ip-iq法检测性能无明显变化,适用范围更广。

基于ip-iq法的并联有源滤波器在微网中的应用

首先分析了基于三相瞬时无功理论的ip-iq谐波电流检测法的基本原理,将基于ip-iq法的并联有源滤波器应用于微网系统,分析有源滤波器的控制方式,并在SIMULINK中建立接有非线性负载的微电网模型,对其基波电流、谐波电流、电网电流和负载电流进行检测分析,计算电流畸变率,以证明基于ip-iq谐波电流检测法的并联有源滤波器在微网中应用的可行性。

基于谐波检测的调相机失磁保护研究

首先对现有的调相机失磁保护进行分析,结果表明在系统低电压工况下调相机发生部分失磁故障,现有的失磁保护不能可靠动作,保护存在死区。通过研究调相机失磁后的励磁电流变化规律,得出调相机发生失磁故障后气隙合成磁势中含有高次谐波分量,将在定子绕组中产生对应的谐波电流。在此基础上,提出了一种基于谐波检测的调相机失磁保护方法。利用定子绕组中偶次谐波电流含量构建新的失磁保护策略,解决了系统低电压工况下失磁保护不能识别部分失磁故障的问题。最后,通过PSCAD/EMTDC建立了带有调相机的扎鲁特-青州±800 kV特高压直流输电模型,仿真结果验证了该方案的可行性。

电网阻抗自适应的混合式孤岛检测方法

针对并网逆变器存在的孤岛效应,提出一种电网阻抗自适应的混合式孤岛检测方法。首先,采用被动法与主动法结合的混合式孤岛检测方法,基于分布式发电系统进行分析。其中被动法采用电压不平衡法,主动法采用零序电压正反馈法,主动法仅在被动法怀疑发生孤岛时启动,以避免因主动法导致的电能质量下降。其次,采用电压不平衡法,通过理论推导获得被动法设定阈值与电网阻抗的关联式,通过谐波注入法检测电网阻抗,从而有效解决被动法阈值设定困难的问题。最后通过实验验证所提方法的有效性和抗干扰性。实验结果表明,该方法对于不同电网情况以及不同本地负载均能有效检测,对于电网电压波动的情况也具有较强的抗干扰能力。

基于云计算的分布式光伏并网谐波检测系统的设计

针对传统集中式光伏并网谐波检测方法实时性差、效率低的问题,提出了一种基于云计算的分布式光伏并网谐波检测系统。该系统采用OpenStack云平台和Kafka分布式消息队列,实现了谐波数据的实时采集、动态调度和并行处理。同时,系统采用小波变换算法对谐波进行精确提取,并通过Web可视化技术实现了谐波数据的交互式分析。实验结果表明,该系统在谐波检测实时性、精度和资源利用率方面均优于传统方法,可有效支撑大规模光伏电站的谐波治理。