Harmonic Detection Research Articles

A Review of Harmonic Detection, Suppression, Aggregation, and Estimation Techniques

The rapid growth of power electronics-based devices, such as electric vehicles and renewable energy systems, has introduced nonlinear components into power systems, generating high-frequency harmonics that distort current and voltage waveforms. These distortions pose significant risks to the stability of power grids, potentially leading to equipment malfunctions, reduced efficiency, and even system failures. To address these challenges, advanced harmonic detection, suppression, and estimation techniques are required to ensure the reliable operation of modern power systems. This paper comprehensively reviews the most widely used methods for managing harmonic distortions, focusing on recent harmonic detection, suppression, and estimation advancements. Key techniques, such as Fourier analysis and wavelet transforms, are compared alongside emerging machine learning-based approaches and adaptive filtering methods, which offer enhanced accuracy in real-time and dynamic environments. Additionally, advancements in harmonic suppression technologies, including passive, active, and hybrid filtering, are discussed for their effectiveness in mitigating harmonic impacts. Furthermore, the paper explores harmonic aggregation techniques that assess the cumulative impact of multiple harmonic sources and innovative estimation models that improve harmonic quantification under complex grid conditions. With the growing integration of renewable energy and electric vehicles, this review highlights the importance of advanced harmonic management strategies to ensure the safety, efficiency, and long-term stability of power systems.

A Modified Control Strategy for Three-Phase Four-Switch Active Power Filters Based on Fundamental Positive Sequence Extraction

Three-phase four-switch active power filters (APFs) have attracted attention due to their low amount of semiconductors and low cost. The traditional control strategy of three-phase four-switch APFs usually includes phase-locked loops (PLLs) and rotating coordinate transformation for harmonic detection, resulting in complicated calculations and increased computation. In this paper, a modified control strategy for three-phase four-switch APFs based on fundamental positive sequence extraction is proposed, eliminating PLLs and rotating coordinate transformation with trigonometric calculations. Harmonic extraction is based on the fundamental positive sequence extraction method, while non-locked phase loop coordinate transformation is proposed to eliminate trigonometric calculations. Quasi-PR control is adopted for current tracking, and DC voltage control is designed to suppress voltage imbalance between the two split capacitors on the DC side. The space vector pulse width modulation (SVPWM) method is modified for a reduced-switch APF topology. The proposed control strategy guarantees excellent harmonic compensation: harmonic currents are significantly suppressed when the APFs are working, the THD of the source current decreases to 3.86%, the bus voltage fluctuation on the DC side is small, the voltage remains stable, and the computational complexity is reduced. Finally, a simulation and an experimental hardware platform are established to validate the feasibility and performance of the proposed control strategy. The experimental results show that it has good performance in suppressing harmonics and improving power quality.

Empirical Modal Decomposition Combined with Deep Learning for Photoacoustic Spectroscopy Detection of Mixture Gas Concentrations.

In photoacoustic spectroscopy based multicomponent gas analysis, the overlap of the absorption spectra among different gases can affect the measurement accuracy of gas concentrations. We report a multicomponent gas analysis method based on empirical modal decomposition (EMD), convolutional neural networks (CNN), and long short-term memory (LSTM) networks that can extract the exact concentrations of mixed gases from the overlapping wavelength-modulated spectroscopy with second harmonic (WMS-2f) detection. The WMS-2f signals of 25 different concentration combinations of acetylene-ammonia mixtures are detected using a single distributed feedback laser (DFB) at 1531.5 nm. The acetylene concentrations range from 2.5 to 7.5 ppm and the ammonia concentrations from 12.5 to 37.5 ppm. The data set is enhanced by cyclic shifting and adding Gaussian noise. The classification accuracy of the test set reaches 99.89% after tuning. The mean absolute errors of the five additional sets of data measured under different conditions are 0.092 ppm for acetylene and 1.902 ppm for ammonia, within the above concentration ranges.

Simultaneous measurement of carbon monoxide and carbon dioxide for combustion diagnosis using 2 μm laser absorption spectroscopy

AbstractCarbon monoxide (CO) and carbon dioxide (CO2) are products of incomplete combustion and complete combustion, respectively. Time‐resolved knowledge of CO and CO2 exhaust concentrations will aid in improving combustion strategies, control, and efficiency. To achieve online high‐precision simultaneous measurement of CO and CO2, a tunable diode laser absorption spectroscopy‐based sensor is designed and constructed. Two diode lasers with central wavelengths of 2.3 and 2.0 μm are multiplexed in time‐division to cover the absorption spectral lines of CO at 4285.00 cm−1 and CO2 at 4989.96 cm−1, respectively. Wavelength modulation spectroscopy with second harmonic detection normalized by the first harmonic (WMS‐2f/1f) is employed. A software lock‐in amplifier and inversion algorithm are implemented for data processing and concentration acquisition. The entire measurement system is based on the idea of a virtual instrument and is carried out using a high‐speed data acquisition card and a computer. Experimental verification demonstrates that the measurement accuracies of CO and CO2 were 2.47% and 2.56%, respectively, with a time resolution of 20 ms. Dynamic measurement experiments with an alcohol blast burner validate the feasibility of measuring CO and CO2 in actual combustion environments. The developed sensor demonstrates the potential for real‐time and in situ carbon emission measurement for combustion diagnosis.

Research on Spatial Localization Method of Magnetic Nanoparticle Samples Based on Second Harmonic Waves

Existing magnetic tracer detection systems primarily rely on fundamental wave signal acquisition using non-differential sensor configurations. These sensors are highly susceptible to external interference and lack tomographic localization capabilities, hindering their clinical application. To address these limitations, this paper presents a novel method for achieving the deep spatial localization of tracers. The method exploits second harmonic signal detection at non-zero field points. By considering the combined nonlinear characteristics of the coil’s axial spatial magnetic field distribution and the Langevin function, a correlation model linking the signal peak and bias field is established. This model enables the determination of the tracer’s precise spatial location. Building on this framework, a handheld device for localizing magnetic nanoparticle tracers was developed. The device harnesses the second harmonic response generated by coupling an AC excitation field with a DC bias field. Our findings demonstrate that under conditions of reduced coil turns and weak excitation fields, the DC bias field exhibits exclusive dependence on the axial distance of the detection point, independent of particle concentration. This implies that the saturated DC bias field corresponding to the second harmonic signal can be used to determine the magnetic nanoparticle sample detection depth. The experimental results validated the method’s high accuracy, with axial detection distance and concentration reduction errors of only 4.8% and 4.1%, respectively. This research paves the way for handheld probes capable of tomographic tracer detection, offering a novel approach for advancing magnetically sensitive biomedical detection technologies.

Weak signal detection in chaotic noise background - based on VMD-EEMD and self-attention mechanisms

Abstract In this paper, a method for detection and estimation of weak harmonic signals in chaotic noise background is proposed. Firstly, the observed signal is smoothed by local weighted regression model to reduce the influence of noise. Then, the smoothed signals are decomposed into the intrinsic mode functions by Variational Mode Decomposition and Ensemble Empirical Mode Decomposition (VMD-EEMD). The components are reconstructed in the phase space, and the one-step prediction is carried out by adding a layer of the self-attention mechanism in the Long Short-Term Memory (LSTM). The one-step prediction error is obtained by summing up the prediction results of the components and the weak harmonic signals will be detected from the one-step prediction error. Finally, the periodogram method is used to detect whether the observed signals contain harmonic signals or not. If the observed signals contain harmonic signals, the amplitude and phase are estimated by the least squares method. Simulation experiments show that the method proposed in this paper has good performance. In detection of single harmonic signal, the Mean Absolute Error (MAE) and Mean Square Error (MSE) of the one-step prediction are 0.0212 and 0.00068 respectively; MAE and MSE of the signal estimation are 0.001977 and 0.0007 respectively. In detection of multiple harmonic signals, MAE and MSE of the one-step prediction are 0. 0248 and 0. 0006 respectively; MAE and MSE of the signal estimation are 0. 0035 and 1.681×10−5 respectively. The method proposed in this paper is able to efficiently detect weak harmonic signals from chaotic noise backgrounds and estimate the harmonic signals.

A comparison of tonal-broadband decomposition algorithms for propeller noise

The usage of propellers is increasing as an alternative to traditional aircraft and has become the primary option for new urban mobility vehicles. However, noise emissions from rotating blades can be a challenge for the certification of these new vehicles. The acoustic sources from a propeller can be decomposed into deterministic and random components. Therefore, academic research has focused on developing methods to separate these components. This study compares the performance of several methods available in the literature to decompose propeller noise signals into tonal and broadband components. Initially, the methods were applied to synthetic data that represents the main characteristics of rotating blade noise. Later, the methods were tested on realistic acoustic data collected from an isolated propeller test rig. The results showed that methods based on phase-averaging recorded signals satisfactorily detected harmonic components. The method based on cross-correlation between data blocks effectively extracted the broadband spectra, but it performed poorly on harmonic detection. Additionally, the wavelet transform and Proper Orthogonal Decomposition methods were capable of reconstructing time series related to both deterministic and random parts. However, further investigation is required regarding the separation of POD modes, as unexpected trends were observed with the wavelet-based method.

A multifunctional inverter power quality coordinated optimization strategy based on comprehensive evaluation

The large-scale integration of renewable energy sources and power electronic devices has led to increasingly dispersed and networked characteristics of power quality disturbances in distribution systems. Traditional control devices, limited by their fixed-point control, no longer meet the development needs of modern distribution systems. Considering the distribution and structural characteristics of the current new-type sources and loads, a multifunctional inverter power quality coordinated control strategy based on comprehensive evaluation is proposed. This strategy aims to achieve power quality coordinated control by utilizing optimal compensation capacity while the grid-connected inverter provides active power output. Firstly, the traditional ipiq power quality detection method is analyzed and improved to enable detection of harmonics, reactive power, and three-phase imbalance currents in single-phase systems or three-phase four-wire systems. Secondly, in the power quality assessment, a balanced algorithm is employed to obtain the comprehensive evaluation index of power quality, thereby improving the deficiencies of single-weight evaluation. Next, to ensure the grid-connected inverter achieves optimal power quality coordinated control with minimal compensation capacity, an optimization compensation function is established between compensation capacity and comprehensive power quality index. This function is optimized using non-dominated sorting genetic algorithm to enhance equipment utilization and system economy. Finally, the feasibility and effectiveness of the proposed method are validated through simulations, demonstrating the achievement of optimal capacity configuration for power quality coordinated control while ensuring active power output by the grid-connected inverter.

Multiwavelength lateral-shearing spherical interferometry for a large-aperture dichroic mirror

Large-aperture dichroic mirrors play an important role in various high-power laser systems and have been proposed for multiwavelength wavefront measurements. In this study, we first developed the theory of multiwavelength lateral-shearing spherical interferometry to achieve signal separation under coaxial conditions. Subsequently, an experiment on wavefront sensing from one interferogram was successfully performed on a dichroic mirror with a diameter of 350 mm. The results are consistent with those of the Zygo interferometer, indicating the proposed method’s potential applications in high-order harmonic detection, multiwavelength interferometric imaging, and laser plasma diagnosis.

Harmonic phase-sensitive detection for quartz-enhanced photoacoustic-thermoelastic spectroscopy

Quartz tuning fork (QTF)-based techniques of photoacoustic spectroscopy and thermoelastic spectroscopy play a significant role in trace gas sensing due to unique high sensitivity and compactness. However, the stability of both techniques remains plagued by the inevitable and unpredictable laser power variation and demodulation phase variation. Herein, we investigate the phase change of a QTF when integrating both techniques for enhanced gas sensing. By demonstrating harmonic phase-sensitive methane detection as an example, we achieve stable gas measurement at varying laser power (2.4–9.4 mW) and varying demodulation phase (−90–90°). Besides, this method shows more tolerance to resonant frequency drift, contributing to a small signal fluctuation of ≤ 6.4 % over a wide modulation range (>10 times of the QTF bandwidth). The realization of harmonic-phase detection allows strengthening the stability of QTF-based sensors in a simple manner, especially when stable parameters, such as laser power, demodulation phase, even resonant frequency, cannot always be maintained.

Generation and registration of high harmonics at surface plasma in coherent wake emission and relativistic oscillating mirror modes by high-power laser pulses

A universal technique is developed for the detection of high harmonics generated by relativistic and subrelativistic laser pulses irradiating a solid target. The characteristic features typical of two different generation methods are analyzed: parametric generation in the mid-IR range and amplification of chirped pulses in the near-IR range. Experimental spectra of harmonics in the range up to 35 nm were recorded. They can be used as a source of coherent radiation in the extreme UV region.

Supraharmonics Reconstruction Method Based on Blackman Window and Compressed Sensing

This paper proposes a method that combines window functions with compressed sensing for the detection of ultra-high harmonics in the frequency range of 2–150 kHz. By analyzing the sparsity of the signal, the Bruckmann window function, which is most suitable for the compressed sensing reconstruction process and the characteristics of ultra-high harmonics, is selected. Simulations indicate that, compared to existing methods, the proposed algorithm based on the fusion of the Bruckmann window and compressed sensing achieves a sparser post-observation signal with reduced fluctuations. The robustness and anti-interference capabilities are enhanced, while the harmonic detection accuracy and signal reconstruction performance are significantly improved. The reconstruction error reaches 4.15 × 10−6, the mean squared error percentage (MSE) reaches 4.13 × 10−6, and the signal-to-noise ratio (SNR) is as high as 97.69 dB, marking an increase of 54.11%. This study provides a new theoretical and methodological approach for the analysis and processing of ultra-high harmonics caused by a high proportion of power electronic devices.

Design and research of grounding current monitoring device for converter transformer core and clamp

The effective monitoring of the grounding current of the core and clamp of the converter transformer can prevent partial overheating, gassing of oil, and other abnormal conditions caused by the grounding fault of the core and clamp, ensuring the safety and stability of the power system. At present, the main detection and diagnosis method is to use the clamp current meter to detect the effective value of the grounding current. However, due to the larger capacity, higher voltage level, more complex structure and electromagnetic field distribution of the converter transformer, there is no clear standard and detection diagnosis method. Firstly, this paper analyzes the causes of grounding current and related calculations. And the design of the monitoring system for the grounding current of the converter transformer core and clamp design of the hardware system for the grounding current of the converter transformer is studied and the design process of the main circuit is given. Secondly, aiming at the problem of amplitude measurement deviation and non-integer frequency of harmonic generated by the grounding current of the core and clamp, a harmonic current detection and analysis scheme based on four Blackman-harris algorithms and the specific design process are proposed. Third, a diagnostic method based on probabilistic neural network is proposed, and a software platform is built to display and diagnose the grounding current state according to it. Finally, a prototype was manufactured and experimental study was carried out to verify the correctness of the proposed scheme.

Harmonic Detection Methods and Optimization Strategies for Charger in Power Grid

The charger’s operation in the power grid will cause harmonic pollution, affecting the service life of the equipment and the quality of the power grid. The harmonic characteristics and detection during the charging process are studied. The simulation model of charger is established first using MATLAB, the results of the experiment show that odd harmonics are mainly generated during charging, and the distortion rate of the current harmonics remains between 0.231 and 0.443 during the charging process. A new wavelet neural network is proposed to detect the harmonic method. Experimental results indicate that, compared with previous detection methods, this network has better detection efficiency and accuracy for harmonics. But detection result of this network is unstable and does not even converge. A new adaptive bat algorithm with improved focusing distance is presented here to optimize the wavelet neural network, which effectively solves the defect of being sensitive to the node number of hidden layer, resulting in higher detection accuracy, faster detection speed, and stable convergence. The detection error range is reduced from −0.03 to 0.02, and the number of iterations is reduced to around 1000.

Harmonic Detection Method Based on Parameter Optimization VMD-IWT Combined Noise Reduction

Aiming at the problem that the existing harmonic detection methods are susceptible to noise interference in the actual working environment, which leads to the reduction of detection accuracy, this paper introduces a novel harmonic detection technique utilizing a RIME optimization algorithm (RIME) to enhance variational mode decomposition (VMD) combined with an improved wavelet threshold (IWT) approach. Initially, RIME optimization refines VMD for the decomposition of harmonic current signals, yielding several modal components. Subsequently, a correlation coefficient method distinguishes between effective and ineffective modal components, discarding the latter. The effective components undergo noise reduction through an enhanced wavelet thresholding technique, and these denoised components are then reconstructed to produce the final noise-reduced signal. Finally, the Hilbert transform is applied to the denoised signal to extract harmonic parameters. Verification through both simulated and actual signal measurements demonstrates that the proposed method not only surpasses other noise reduction algorithms in signal-to-noise ratio and root-mean-square error, but also shows superior accuracy and robustness compared to alternative detection techniques. This method effectively filters out signal noise under noise interference, minimizes detection errors, and achieves precise harmonic signal detection with improved accuracy.

Temperature-Switch-Controlled Second Harmonic Mode Sensor for Brain-Tissue Detection.

Identifying brain-tissue types holds significant research value in the biomedical field of non-contact brain-tissue measurement applications. In this paper, a layered metastructure is proposed, and the second harmonic generation (SHG) in a multilayer metastructure is derived using the transfer matrix method. With the SHG conversion efficiency (CE) as the measurement signal, the refractive index ranges that can be distinguished are 1.23~1.31 refractive index unit (RIU) and 1.38~1.44 RIU, with sensitivities of 0.8597 RIU-1 and 1.2967 RIU-1, respectively. It can distinguish various brain tissues, including gray matter, white matter, and low-grade glioma, achieving the function of a second harmonic mode sensor (SHMS). Furthermore, temperature has a significant impact on the SHG CE, which can be used to define the switch signal indicating whether the SHMS is functioning properly. When the temperature range is 291.4~307.9 Kelvin (K), the temperature switch is in the "open" state, and the optimal SHG CE is higher than 0.298%, indicating that the SHMS is in the working state. For other temperature ranges, the SHG CE will decrease significantly, indicating that the temperature switch is in the "off" state, and the SHMS is not working. By stimulating temperature and using the response of SHG CE, the temperature-switch function is achieved, providing a new approach for temperature-controlled second harmonic detection.

Harmonic FMCW Radar System: Passive Tag Detection and Precise Ranging Estimation.

This paper details the design and implementation of a harmonic frequency-modulated continuous-wave (FMCW) radar system, specialized in detecting harmonic tags and achieving precise range estimation. Operating within the 2.4-2.5 GHz frequency range for the forward channel and 4.8-5.0 GHz for the backward channel, this study delves into the various challenges faced during the system's realization. These challenges include selecting appropriate components, calibrating the system, processing signals, and integrating the system components. In addition, we introduce a single-layer passive harmonic tag, developed specifically for assessing the system, and provide an in-depth theoretical analysis and simulation results. Notably, the system is characterized by its low power consumption, making it particularly suitable for short-range applications. The system's efficacy is further validated through experimental evaluations in a real-world indoor environment across multiple tag positions. Our measurements underscore the system's robust ranging accuracy and its ability to mitigate self-interference, showcasing its significant potential for applications in harmonic tag detection and ranging.

Performance and harmonic detection algorithm of phase locked Loop for parallel APF

As the boost of power electronics technology, the harmonic problem in the power system is becoming increasingly prominent. Fourier decomposition is performed on the load current in the power system, and components with a frequency that is an integer multiple of the fundamental wave are referred to as harmonic components. Harmonic control is essential to establish a safe and reliable power grid environment and provide high-quality and clean electricity to power users. The study focused on parallel active power filters, proposed a specific harmonic detection method on the grounds of synchronous harmonic rotating coordinate system, and developed a phase-locked loop design on the grounds of order generalized integrator. Meanwhile, a compensation current control method on the grounds of space vector pulse width modulation was introduced. The results showed that in the full compensation simulation experiment, the compensated A-phase grid side current waveform was significantly improved and presented a sinusoidal shape. After 0.05 s, the actual output compensation current closely followed the command current. Meanwhile, after compensation, the total harmonic distortion rate decreased from 26.58 to 3.06%. In specific harmonic compensation simulation experiments, when the sum of 5th, 7th, and 11th harmonic components was used as the command current for compensation, the distortion of the current waveform was improved after the load undergoes a sudden change. After compensation, the 5th, 7th, and 11th harmonic content significantly decreased, and the total harmonic distortion rate decreased to 4.08%. This indicated that the proposed phase-locked loop design and harmonic detection method for active power filters had high stability and effectiveness. The study’s primary contribution is to enhance the utilization efficiency of DC voltage and improve the dynamic response ability of current. Additionally, it offers a new method for reducing the impact of harmonics on the power grid and improving power quality. It provided an effective method reference for technological progress in related fields such as power electronics and control engineering.

Bearing fault diagnosis under variable speed conditions on adaptive time frequency extraction mode decomposition

Improvements in measurement technology have made it possible to detect problems with rolling bearings more accurately, which is important to ensure that they work properly in mechanical systems under different variable speed conditions. Time–frequency distribution (TFD) methods are widely used in variable-speed rolling bearing fault diagnosis, we construct a new method: adaptive time frequency extraction mode decomposition (ATFEMD) by capturing the distinctive time–frequency information within the TFD through ridge extraction, subsequently, the reconstruction components are further refined into adaptive modes through the harmonic detection and noise testing process. This method is a time–frequency post-processing method that effectively solves the problems of time–frequency energy lack of concentration, poor robustness of instantaneous frequency extraction, and mode aliasing in signal decomposition. This article analyzes the simulated bearing vibration and test bench bearing vibration signals to demonstrate the performance of ATFEMD. Results indicated that the proposed method is characterized by strong robustness, and good feature extraction results compared to other methods.

A Sliding-Mode Current Decoupling Control Strategy for an Active Power Filter Based on an Internal Model

With the ongoing development of electronic power technologies, harmonic pollution in the power grid has become a topic of great concern. This study takes a substation as its background. The safe and steady operation of the station’s equipment was impacted by a 10 kV bus’s harmonic current, which was significantly higher than the required amount. We propose a sliding-mode current decoupling control strategy based on an internal model to address the problems of complex harmonic current detection and distortion in the power supply current when there are nonlinear load changes in hybrid active power filters. By establishing a mathematical model for a HAPF, our proposed strategy can be used for inner current loops with the goal of stability, decoupling control between the d- and q-axes, fast-tracking harmonic reference currents, and optimizing the controller by enhancing the system’s anti-jamming performance to ensure that the system operates stably when line parameter ingressions or step changes in the load demand occur. The outer voltage loop uses the fractional-order sliding-mode control method to keep the capacitor voltage smooth and to dynamically adjust when the load changes suddenly. Finally, this filter is compared with a filter controlled by a PI in MATLAB/Simulink, and the feasibility and effectiveness of the proposed control strategy are verified based on a diode-embedded three-level parallel-type HAPF platform. The simulation and experimental results show that our sliding-mode current decoupling control strategy based on the internal mode is characterized by simplicity, stability, and fast responses.