Search Results (39)

The widespread use of domestic LED lamps raises concerns about harmonic current aggregation when multiple units operate in parallel. This study presents a regression-based method for predicting aggregate current waveforms of identical LED lamps. Measurements conducted in accordance with IEC 61000-4-30:2015 involved 1–24 parallel-connected units of a 12 W lamp under controlled conditions. Individual harmonics through the 40th order were assessed against IEC 61000-3-2 product limits, while components up to the 50th order were retained for PCC-oriented characterization of large-scale aggregation, consistent with IEEE 519-2022. Although the product limits were satisfied, measured THD_I remained at 88.6–92%, dominated by the 3rd, 5th, and 7th harmonics. Within the measured range, per-harmonic regressions were evaluated using R² and RMSE, while reconstructed time-domain waveforms produced NRMSE values of 5–10% relative to measured RMS current. Consistent phase angles indicated predominantly constructive aggregation. The model was then applied to an illustrative scenario of up to 100 identical lamps. Under unchanged lamp and supply conditions, the projection indicated a near-linear increase in RMS current, persistent THD_I of approximately 90%, and continued dominance of low-order odd harmonics. Results beyond 24 lamps represent model-based extrapolation rather than experimental validation. The framework provides a baseline for harmonic current assessment in homogeneous LED installations. Full article

This paper presents a power-matched third-harmonic current analysis for a detuned series–series (S–S) compensated wireless power transfer (WPT) system operating across continuous conduction mode (CCM) and discontinuous conduction mode (DCM). In practical S–S WPT systems, the transmitter-side resonant frequency is often intentionally detuned from the switching frequency to satisfy the desired switching condition, which leaves a residual transmitter reactance and changes the harmonic current behavior. In addition, the rectifier conduction mode affects the receiver-side voltage waveform and its harmonic components. To analyze this behavior, the fundamental power-transfer path is modeled using the equivalent rectifier input resistance, whereas the harmonic path is formulated using the inverter and rectifier harmonic voltage sources coupled through the transmitter and receiver resonant tanks. Although the formulation is applicable to arbitrary odd harmonics, the third-harmonic current is selected as the main EMI-oriented comparison quantity because it is the dominant low-order harmonic in the considered operating range. Simulation and experimental results show that output power alone is not sufficient to determine the harmonic current level. When power-matched operating points exist across the CCM/DCM boundary, the CCM-side load point is generally more favorable, especially from the receiver-side third-harmonic viewpoint. When both power-matched points are in DCM, the load point closer to the CCM/DCM boundary is generally more favorable than the deeper DCM point. Full article

The increasing penetration of power electronic devices and distributed generation is significantly altering power quality conditions in low-voltage systems. While power quality assessment is commonly based on RMS currents, voltage quality indicators, and overall distortion metrics, these parameters may not fully reveal phase-selective harmonic behaviour in modern converter-dominated installations. This paper presents a measurement-based power quality assessment of a secondary school building equipped with a grid-connected photovoltaic (PV) system. A one-week monitoring campaign was conducted at the point of common coupling (PCC), capturing voltage, current, harmonic distortion, and power flow characteristics under real operating conditions. The results reveal pronounced phase-selective current harmonic distortion, with substantially elevated total harmonic distortion (THD_I) and total demand distortion (TDD) in one phase despite relatively balanced RMS current levels and acceptable voltage quality. The harmonic spectrum is dominated by low-order odd harmonics, whereas voltage distortion remains comparatively low and well balanced across phases. The study demonstrates that significant harmonic asymmetry may remain hidden in apparently balanced three-phase systems when assessment relies primarily on conventional RMS-based indicators. The findings highlight the importance of detailed current harmonic analysis and show that acceptable voltage quality does not necessarily imply acceptable current quality. The presented results provide measurement-based evidence of hidden harmonic asymmetry in modern low-voltage buildings and contribute to a better understanding of power quality challenges associated with nonlinear loads and distributed energy resources. Full article

The increasing penetration of inverter-based distributed energy resources (DERs) within distribution networks has resulted in harmonic distortion risks that can affect transformer thermal loading, service life, and network hosting capacity. This study assesses harmonic behaviour under increasing DER penetration using a detailed MATLAB 2025b/Simulink model of the CIGRÉ low-voltage benchmark feeder, adapted to reflect representative network parameters and run at a 400 V point of common coupling (PCC). DER penetration is incrementally increased from 0% to 195% of feeder load, and for each penetration level the PCC currents and voltages are examined using FFT-based spectrum extraction. The short-circuit strength is first calculated (I_SC/I_L = 14.1), and harmonic current and voltage distortion thresholds are benchmarked against IEEE 519:2022 and NRS 048-2:2025 respectively. Results show that while DER inverters introduce increasing odd-order harmonics, mainly the 3rd, 5th, 7th and 11th, the feeder’s moderate short-circuit capacity suppresses PCC voltage distortion, keeping voltage THD below 3% across all scenarios. As the inverter-based DER penetration increases, so does the harmonic current distortion. At 180%, Total Demand Distortion (TDD) nears the IEEE limit of 5%. Full article

Background: Fine particulate matter (PM_2.5) is an established systemic toxicant, yet its association with clinical skin aging remains incompletely characterized. Although pigmentary changes and wrinkles are commonly attributed to ultraviolet exposure, experimental and epidemiologic evidence suggests that long-term PM_2.5 exposure may contribute to extrinsic skin aging through oxidative, inflammatory, and aryl hydrocarbon receptor-mediated pathways. However, human studies specifically quantifying PM_2.5 exposure in relation to validated skin aging outcomes are sparse, and no prior meta-analysis has systematically synthesized this evidence. Objective: To conduct a systematic review and meta-analysis of epidemiologic studies reporting measured or modeled long-term PM_2.5 exposure and extractable quantitative associations with clinical skin aging outcomes. Methods: We performed a comprehensive PRISMA 2020-guided search of PubMed, Embase, Web of Science, and Scopus (inception to 18 November 2025). Eligible studies included human participants, quantified long-term PM_2.5 exposure, validated clinical or imaging-based skin aging outcomes, and extractable effect estimates. Ratio-type effect measures (arithmetic mean ratios, geometric mean ratios, and odds ratios) were transformed to the natural-log scale, standardized to a common exposure contrast of per 10 µg/m³ PM_2.5, and synthesized as generic relative association metrics. Random-effects models with DerSimonian–Laird estimation and Hartung–Knapp adjustment were applied for pigmentary outcomes. VISIA imaging β-coefficients were synthesized narratively. Results: Four epidemiologic cohorts met predefined eligibility criteria. From these, we extracted seven PM_2.5-specific pigmentary effect estimates, one clinically assessed wrinkle estimate, and two VISIA imaging outcomes. The pooled relative association for pigmentary aging corresponded to a ratio of 1.11 per 10 µg/m³ PM_2.5 (95% CI, 0.82–1.50), indicating a directionally positive but statistically imprecise association compatible with both increased and unchanged pigmentary aging. All individual pigmentary estimates were directionally positive. A single cohort reported a 3.2% increase in wrinkle severity per 10 µg/m³ PM_2.5 (ratio 1.032). VISIA imaging showed significant worsening of brown spot severity (+9.5 percentile per 10 µg/m³), while wrinkle percentiles showed a non-significant change. Conclusions: Based on a comprehensive PRISMA-guided search, the available epidemiologic evidence suggests a consistent directionally positive association between long-term PM_2.5 exposure and pigmentary skin aging outcomes, with limited and uncertain evidence for wrinkle-related phenotypes. The current evidence base remains small, heterogeneous, and of low certainty. Accordingly, these findings should be interpreted as hypothesis-generating and underscore the need for larger, longitudinal, and methodologically harmonized studies. (Registration: PROSPERO CRD420251231462) Full article

This article is Part I of our series of full papers on a gauge-invariant “linear” perturbation theory on the Schwarzschild background spacetime which was briefly reported in our short papers by the present author in 2021. We first review our general framework of the gauge-invariant perturbation theory, which can be easily extended to the “higher-order” perturbation theory. When we apply this general framework to perturbations on the Schwarzschild background spacetime, gauge-invariant treatments of $l=0,1$ mode perturbations are required. On the other hand, in the current consensus on the perturbations of the Schwarzschild spacetime, gauge-invariant treatments for $l=0,1$ modes are difficult if we keep the reconstruction of the original metric perturbations in our mind. Due to this situation, we propose a strategy of a gauge-invariant treatment of $l=0,1$ mode perturbations through the decomposition of the metric perturbations by singular harmonic functions at once and the regularization of these singularities through the imposition of the boundary conditions to the Einstein equations. Following this proposal, we derive the linearized Einstein equations for any modes of $l\ge 0$ in a gauge-invariant manner. We discuss the solutions to the odd-mode perturbation equations in the linearized Einstein equations and show that these perturbations include the Kerr parameter perturbation in these odd-mode perturbations, which is physically reasonable. In the Part II and Part III papers of this series of papers, we will show that the even-mode solutions to the linearized Einstein equations obtained through our proposal are also physically reasonable. Then, we conclude that our proposal of a gauge-invariant treatment for $l=0,1$-mode perturbations is also physically reasonable. Full article

Driven by frequency conversion, the windings of a three-phase permanent magnet synchronous motor (PMSM) contain both odd and even harmonic currents. Due to the motor’s pole–slot conductance modulation, the interaction between the magnetic fields generated by these harmonic currents and the permanent magnet field results in harmonic radial vibrations of the motor. This paper analyzes the three-phase currents of the prototype and derives the radial magnetomotive force (MMF) spatiotemporal models for symmetric harmonic currents. By integrating Maxwell’s magnetic force formula and vibration response formula, the radial vibration models for symmetric harmonic currents are developed. The characteristics of vibrations caused by odd and even harmonic currents, as well as positive sequence and negative sequence harmonic currents, are analyzed separately. A cyclic sequence, low-frequency vibration suppression control method incorporating multiple harmonic current injections was designed. Experimental results of this method are compared with those obtained using an ideal sinusoidal current. Except for the second harmonic vibration, all other vibrations are significantly suppressed, with a maximum suppression rate of 92.28%. The total vibration level is reduced by 12.7619 dB, and the average torque is reduced by 0.67% with the total harmonic distortion of the current at 2.89%. The experimental results show that the vibration method in this paper has little influence on the average torque of the motor, the current distortion rate is small, and the vibration suppression effect is good. Full article

In the speed-sensorless vector control of induction motors (IMs), the speed estimation accuracy suffers from the deteriorated current measurement caused by the current sensor faults, such as open circuit in one phase, DC bias, and odd harmonics. In this paper, a novel speed estimation strategy based on the current sensor fault-tolerant control is proposed to improve the speed estimation accuracy under the current sensor faults. First, to detect the current sensor faults in real time, the sequential probability ratio test is introduced to the system by using the innovations of the extended Kalman filter (EKF). Second, to ensure speed estimation accuracy, a double-cascading second-order generalized integrator (DSOGI) is employed to reconstruct the faulty current information when a fault is identified. Finally, the reconstructed current information is fed back to the sequential probability extended Kalman filter (SPEKF), which estimates the rotor speed of the IM, and high-accuracy speed estimation under the condition of current sensor faults is achieved. The effectiveness of the proposed strategy is validated by a series of experiments, which were conducted on a 3 kW induction motor drive platform. Full article

This brief presents a comprehensive analysis of the output-dependent modulation (ODM) in a current-steering digital-to-analog converter (CS-DAC) based on the differential-quad switching (DQS) structure. A mathematical model is proposed to accurately describe ODM, which is categorized into two types: output transition errors and boundary effect errors. A novel approach of adding isolation devices is introduced and reinterpreted to mitigate the effect of ODM. The simulation results indicate that the inclusion of isolation devices efficiently suppresses the odd harmonics at mid-to-high frequency by a value that is 13 dB lower than before. Experimental validation is conducted on a 16-bit 250 MS/s CS-DAC fabricated in a 180 nm process. Full article

For over a century, induction furnaces have been used in the core of foundries for metal melting and heating. They provide high melting/heating rates with optimal efficiency. The occurrence of faults not only imposes safety risks but also reduces productivity due to unscheduled shutdowns. The problem of diagnosing faults in induction furnaces has not yet been studied, and this work is the first to propose a data-driven framework for diagnosing faults in this application. This paper presents a deep neural network framework for diagnosing electrical faults by measuring real-time electrical parameters at the supply side. Experimental and sensory measurements are collected from multiple energy analyzer devices installed in the foundry. Next, a semi-supervised learning approach, known as the local outlier factor, has been used to discriminate normal and faulty samples from each other and label the data samples. Then, a deep neural network is trained with the collected labeled samples. The performance of the developed model is compared with several state-of-the-art techniques in terms of various performance metrics. The results demonstrate the superior performance of the selected deep neural network model over other classifiers, with an average F-measure of 0.9187. Due to the black box nature of the constructed neural network, the model predictions are interpreted by Shapley additive explanations and local interpretable model-agnostic explanations. The interpretability analysis reveals that classified faults are closely linked to variations in odd voltage/current harmonics of order 3, 11, 13, and 17, highlighting the critical impact of these parameters on the model’s prediction. Full article

This paper proposes a new and simplified Nearest Vector Control (NVC) modulation technique for a grid-connected photovoltaic (PV) system using a Modular Multilevel Converter (MMC). Compared to the Nearest Level Control (NLC) technique, which defines three independent states for the three phases of medium to large four-wire multilevel converters, NVC offers a more coordinated behavior for three-wire converters. The proposed scheme is easy to implement, and it simplifies the understanding of using vectors when detecting the vector of the converter nearest to a given reference. Because it uses natural coordinates, namely, ab, bc and ca, the proposed method is easier to understand and more useful for further developments. Compared with earlier NVC methods, this approach offers full independence of the number of levels at the converter and it can readily accommodate changes in the number of levels, with no need for lookup tables or artificial coordinate transformations. The proposed NVC method was implemented on a 16-cell MMC used for PV generation and then it was compared to NLC, leading to a smaller and more consistent low-order harmonic distortion, requiring about the same complexity of implementation. Furthermore, in comparison to NLC, when applying the proposed NVC modulation, a behavior more insensitive to changes in the grid voltage was found, the most hazardous odd harmonics from the 5th to the 19th were reduced, and a consistent reduction of about 25 dB was achieved on the 5th and 7th harmonics. The newly proposed method is supported by simulations and experimental results with constant and sharply changing solar irradiance, leaving or removing the 100 Hz component of the MMC circulating currents. Full article

Two-dimensional (2D) piezoelectric semiconductor materials are garnering significant attention in applications such as intelligent sensing and energy harvesting due to their exceptional physical and chemical properties. Among these, molybdenum disulfide (MoS₂), a 2D wide-bandgap semiconductor, exhibits piezoelectricity in odd-layered structures due to the absence of an inversion symmetry center. In this study, we present a straightforward chemical vapor deposition (CVD) technique to synthesize monolayer MoS₂ on a Si/SiO₂ substrate, achieving a lateral size of approximately 50 µm. Second-harmonic generation (SHG) characterization confirms the non-centrosymmetric crystal structure of the wide-bandgap MoS₂, indicative of its piezoelectric properties. We successfully transferred the triangular MoS₂ to a polyethylene terephthalate (PET) flexible substrate using a wet-transfer method and developed a wide-bandgap MoS₂-based micro-displacement sensor employing maskless lithography and hot evaporation techniques. Our testing revealed a piezoelectric response current of 5.12 nA in the sensor under a strain of 0.003% along the armchair direction of the monolayer MoS₂. Furthermore, the sensor exhibited a near-linear relationship between the piezoelectric response current and the strain within a displacement range of 40–100 µm, with a calculated response sensitivity of 1.154 µA/%. This research introduces a novel micro-displacement sensor, offering potential for advanced surface texture sensing in various applications. Full article

Non-intrusive load monitoring (NILM) technology, crucial for intelligent electricity management, has gained considerable attention in residential electricity usage studies. NILM enables monitoring of total electrical current and voltage in homes, offering insights vital for enhancing safety and preventing domestic electrical accidents. Despite its importance, accurately discerning the operational status of appliances using non-intrusive methods remains a challenging area within this field. This paper presents a novel methodology that integrates an advanced clustering algorithm with a Bayesian network for the identification of appliance operational states. The approach involves capturing the electrical current signals during appliance operation via NILM, followed by their decomposition into odd harmonics. An enhanced clustering algorithm is then employed to ascertain the central coordinates of the signal clusters. Building upon this, a three-layer Bayesian network inference model, incorporating leak nodes, is developed. Within this model, harmonic signals are used as conditions for node activation. The operational states of the appliances are subsequently determined through probabilistic reasoning. The proposed method’s effectiveness is validated through a series of simulation experiments conducted in a laboratory environment. The results of these experiments (low mode 89.1%, medium mode 94.4%, high mode 92.0%, and 98.4% for combination) provide strong evidence of the method’s accuracy in inferring the operational status of household electrical appliances based on NILM technology. Full article

In this study, a frequency doubler that consists of a tunnel field-effect transistor (TFET) with dual pocket doping is proposed, and its operation is verified using technology computer-aided design (TCAD) simulations. The frequency-doubling operation is important to having symmetrical current characteristics, which eliminate odd harmonics and the need for extra filter circuitry. The proposed TFET has intrinsically bidirectional and controllable currents that can be implemented by pocket doping, which is located at the junction between the source/drain (S/D) and the channel region, to modify tunneling probabilities. The source-to-channel (I_SC) and channel-to-drain currents (I_CD) can be independently changed by managing each pocket doping concentration on the source and drain sides (N_S,POC and N_D,POC). After that, the current matching process was investigated through N_S,POC and N_D,POC splits, respectively. However, it was found that the optimized doping condition achieved at the device level (namely, a transistor evaluation) is not suitable for a frequency doubler operation because the voltage drop generated by a load resistor in the frequency doubler circuit configuration causes the currents to be unbalanced between I_SC and I_CD. Therefore, after symmetrical current matching was performed by optimizing N_S,POC and N_D,POC at the circuit level, it was clearly seen that the output frequency was doubled in comparison to the input sinusoidal signal. In addition, the effects of the S/D and pocket doping variations that can occur during process integration were investigated to determine how much frequency multiplications are affected, and these variations have the immunity of S/D doping and pocket doping length changes. Furthermore, the impact of device scaling with gate length (L_G) variations was evaluated. Based on these findings, the proposed frequency doubler is anticipated to offer benefits for circuit design and low-power applications compared to the conventional one. Full article

For many machines with turning process systems, the application of economical indirect Tool Condition Monitoring (TCM) is enhanced by utilizing internal encoder spindle motor current signals. In this study, we proposed a novel approach to extract the total harmonic distortion (THD) feature associated with the metal cutting frequency of a specific working tool in the time domain. Our method entailed the application of filtered variational mode decomposition (VMD) combined with envelope analysis to demodulate the motor current signal and define TCM features based on the THD of odd harmonics, which are more related to the motor structure. These features serve as inputs for a hybrid prognostics technique, employing the Geometric Brownian Motion (GBM) to stochastically model the degradation process along with a deep learning transformer-based framework called the time series Transformer (TST) to improve the life prediction. Finally, to validate our approach, we conducted experiments based on 36 sets of tool run-to-wear data extracted from a CNC machine operating under turning process conditions using two different tools. Finally, we compared the degradation models based on the extracted odd-THD and even-THD features. Full article