Transient Current Signals Research Articles

Time-frequency analysis of Fourier transform mass spectrometry data by the hilbert transform-based time-domain method

Rich information possesses within the transient image current signal collected from a Fourier transform (FT) mass spectrometer. The central frequency corresponds to the mass to charge ratio of an ion, the amplitude decay profile corresponds to its collision cross sections (CCS). Conventionally, fast Fourier transform (FFT) was applied to transfer the time-domain transient data to frequency-domain. There are demanding needs to develop efficient data processing methods to improve the mass accuracy and resolution of the constructed mass spectrum, while shortening the length of the transient data for high-throughput analysis. In this work, a Hilbert transform based time domain method was developed, so that time-frequency analysis of ion transient data could be performed. This method could accurately extract the instantaneous ion motional frequency and amplitude, which could potentially improve the mass accuracy and mass resolution of a FT-based mass spectrometer. Furthermore, ion CCSs could also be acquired from the ion motion decay profiles.

Charge carrier trapping by dislocations in single crystal diamond

Charge carrier trapping in diamond crystals containing well-defined concentrations of dislocations was investigated by several complementary techniques. Samples with dislocation densities ndis between <1 × 107 and ≈1 × 109 cm−2 were grown heteroepitaxially on Ir/YSZ/Si(001). In optical pump–probe experiments, ambipolar diffusion coefficients were determined from the decay of light-induced transient free carrier gratings. Modeling their variation with excitation density yielded trapping cross sections σ of 29 and 10 nm for the dislocations and a stress-field-induced reduction in exciton binding energies from 80 to 73 and 60 meV at ndis = 1 × 108 and 1 × 109 cm−2, respectively. The lifetime measured by induced absorption scaled proportional to 1/ndis with absolute values ranging from 0.1 to 10 ns. In the electrical measurements on two sets of detector slices, electron–hole pairs were excited by α-particles and transport was measured separately for electrons and holes. Both types of carriers showed fast transient current signals. The time constant of the additional slow component exclusively seen for holes was in agreement with the activation energy of boron acceptors. Their concentration of ≈0.5 ppb yielded σ = 1.77 × 10−13 cm2 for charged point traps. Schubweg and carrier lifetime due to deep trapping roughly reproduced the 1/ndis trend. For electrons at 3 V/μm, a value σ = 40 nm was deduced. Cross sections for holes were significantly smaller. Differences in hole trapping between the samples are attributed to charging of dislocations controlled by chemical impurities. Increase in lifetime at high voltages is explained by reduced capture cross sections for hot carriers.

Transient Inrush and Fault Current Signal Extraction Using Discrete Wavelet Transform for Detection and Classification in Shunt Capacitor Banks

An unbalanced current protection relay (60C, 51NC) cannot operate fast enough to avoid catastrophic failure against high system fault currents within capacitor units because a traditional unbalanced current protection relay is not capable of classifying the transient fault current and switching inrush current. This article proposes a new algorithm for the detection and classification of these transient current signals. Simulations are performed using PSCAD/EMTDC programs. The outputs of the current signals are used as inputs for the discrete wavelet transform (DWT) process. The wavelet-based fault and inrush current detection and classification unit receive the captured transient current signals and use DWT to detect and analyze these signals. Actual inrush current signals from an experimental setup and shunt capacitor banks of 115 kV, 22 kV, and 6.6 kV are used to verify the proposed algorithm. The results show that the proposed algorithm provides good performance and accuracy in identifying faults and inrush currents.

Motor Bearing Fault Diagnosis Based on Frequency Conversion Estimation and Order Analysis

Order analysis (OA) has been proven to be an effective tool for motor bearing fault diagnosis under variable-speed conditions, but it is a challenge to perform OA when a tachometer is unavailable to obtain the rotating speed. In this study, a new angular resampling method based on instantaneous frequency estimation of the transient current signal is proposed for bearing fault diagnosis with speed fluctuation. First, the fundamental rotating frequency curve is extracted from the acquired phase current signal of a brushless direct current motor (BLDCM). The mechanical rotating angle curve is then calculated by integrating the fundamental frequency curve. The synchronous sampled vibration signal of the fault bearing is resampled in the angular domain according to the obtained rotating phase information. The effectiveness and efficiency of the proposed method are verified through a BLDCM experimental setup.

Radiation-Induced Transient Currents in Films of Poly(arylene ether ketone) Including Phthalide Moiety.

The electrical properties of thin films of poly(arylene ether ketone) copolymers (co-PAEKs) with a fraction of phthalide-containing units of 3, 5, and 50 mol% in the main chain were investigated by using radiation-induced conductivity (RIC) measurements. Transient current signals and current-voltage (I-V) characteristics were obtained by exposing 20 ÷ 25 μm thick films of the co-PAEKs to monoenergetic electron pulses with energy ranging from 3 to 50 keV in an electric field ranging from 5 to 40 V/μm. The Rose-Fowler-Vaisberg semi-empirical model based on a multiple trapping formalism was used for an analysis of the RIC data, and the parameters of the highly dispersive charge carrier transport were evaluated. The analysis revealed that charge carriers moved in isolation from each other, and the applied electric fields were below the threshold field triggering the switching effect (a reversible high-to-low resistivity transition) in the co-PAEK films. It was also found that the co-PAEK films, due to the super-linear I-V characteristics, are highly resistant to electrostatic discharges arising from the effects of ionizing radiation. This property is important for the development of protective coatings for electronic devices.

Design of integrated test system for current/frequency conversion circuit

In order to quickly and accurately measure the performance parameters of the current/frequency conversion circuit (I/F conversion circuit) of inertial navigation system, an I/F conversion circuit test system is designed. Constant current signal, sinusoidal current signal and transient step current signal are provided to the measured system by a program-controlled constant current source. Through the designed frequency measurement circuit, the output frequency signal is measured accurately, the static, dynamic and transient responses of three kinds of I/F converter circuits are analyzed.

Transmission Line Fault Detection, Classification and Location using Wavelet Transform

This paper present a new algorithm for fault detection, classification and location of overhead transmission line using Wavelet Transform (WT) based Discrete Wavelet Transform (DWT) is proposed. The different system faults such as LG, LLG and LLLG in transmission line should be detect, classify and locate rapidly. The proposed method is based on the voltage and current signal information from the power model in MATLAB to generate the transient voltage and current signal in both time and frequency domain. DWT using “db6” as a mother wavelet is used to capture transient current signals and extract the high frequency detail coefficient for detecting and classifying the fault disturbance. The classification process is based on ground threshold value. The location of faults is carried out by obtaining the fault information from source terminal end to remote terminal end along with the total transmission line length. The proposed method is tested on the MATLAB/SIMULINK environment with the Simulink model. In simulation process the proposed algorithm achieved the fault detection, classification and locate all eleven types of possible fault in transmission line and the result are compared with the AR and MED method.

Design Principles for Sensing Particle Number Concentration and Mean Particle Size With Unipolar Diffusion Charging

Diffusion charging followed by particle capture and measurement is a promising method for determining particle number concentration of automotive exhaust. In addition, the method allows for the determination of a mean particle size, which is of high relevance with respect to health impacts. We investigate three different measurement configurations based on unipolar diffusion charging and electrostatic particle capture, using an analytical non-dimensional model, as well as a transient, multi-physical 3D model. The comprehensive modeling techniques enable prediction of the transient electrical current signals induced by the motion of charged aerosols. Comparison of the multi-physical modeling approach to analytical calculations and experimental data demonstrate model validation. The understanding gained from the modeling techniques enables a study of sensor design and calibration. Particle number concentration sensing is demonstrated for both a modulated precipitation configuration and a two-stage measurement configuration. With the latter, additional information on the mean particle size is extracted.

High voltage transmission line protection principle using transient signals

Based on the concept of multi-resolution morphological gradient (MMG) in mathematical morphology, a new scheme of single-ended transient protection is proposed. On the basis of MMG, the window function energy spectrum of the transient current signal generated by the fault is extracted to realize the identification of faults in the area and outside. A typical 500 kV EHV transmission line is selected and simulated by PSCAD/EMTDC. The results show that the scheme is not affected by fault type, fault location, transition resistance and initial phase angle. At the same time, the calculation amount of the algorithm is smaller than that of the multi-scale wavelet transform, which is beneficial to engineering implementation.

Transient Current Similarity-Based Protection for Interconnecting Transformers in Wind Farms

Large-scale wind farms are usually integrated into transmission systems through interconnecting transformers. Applying traditional, steady-state, fundamental frequency-based differential protection (DP) strategies in these interconnecting transformers creates challenges. First, the fault current of wind farms might be dominated by non-fundamental frequency components caused by the activation of their own protection systems during low-voltage ride-through (LVRT). Second, the fault current contains low-order components that may affect the second-harmonic restraint algorithm of the transformer DP, thereby blocking the differential relay for a long time. Therefore, a novel transient current similarity-based protection scheme is proposed to deal with these issues. The current protection scheme uses the fundamental frequency and non-fundamental frequency characteristics and can, therefore, reduce the influence of LVRT to a minimum. The proposed method uses transient current (within 15 ms after fault inception) and ignores the features of steady-state fault current. In the proposed method, an improved Hausdorff distance algorithm is used to calculate the similarity of transient current signals at both ends of the interconnecting transformer. The simulation results demonstrate that using a common sampling frequency, the proposed protection scheme reveals current information, correctly identifies magnetizing currents and internal transformer faults in a short period, and achieves superior performance in cases of abnormal data, missing data and noise.

“Kink” in AlGaN/GaN-HEMTs: Floating Buffer Model

We report on a floating buffer model to explain “kink,” a hysteresis in the output characteristics of Fe-doped AlGaN/GaN HEMTs observed at low drain bias. Unintentionally doped background carbon can make the GaN buffer p-type allowing it to electrically float. We further note that reverse bias trap-assisted leakage across the junction between the 2DEG and the p-type buffer can provide a mechanism for hole injection and buffer discharging at just a few volts above the knee, explaining the “kink” bias dependence and hysteresis. We show that HEMTs with a different background carbon have dramatically different kink behaviors consistent with the model. Positive and negative magnitude drain current transient signals with 0.9-eV activation energy are seen, corresponding to changes in the occupation of carbon acceptors located in different regions of the GaN buffer. The observation of such signals from a single trap calls into question conventional interpretations of these transients based on the bulk 1-D deep-level transient spectroscopy (DLTS) models for GaN devices with floating regions.

Transient current similarity based protection for wind farm transmission lines

Large-scale wind farms are usually integrated into the transmission system. Applying traditional steady-state power-frequency based protection strategies in these transmission lines creates challenges such as: (1) the fault current of the wind farm might be dominated by non-power-frequency components caused by the activation of their own protection systems during fault ride through (FRT). The frequency of the dominant component is determined by the rotor speed at the fault inception and might vary from 0.7 to 1.3 times the power frequency. This will create errors in phasors calculated at the power-frequency. (2) The steady-state fault current angles of wind farms are fully controlled by their power converters. The variety of control actions of the different converters during FRT makes these phase angles greatly deviate from those of the synchronous generators. Protection systems that use double-ended phasors such as current differential schemes will suffer from low sensitivity or even malfunction when large-scale wind farms are integrated. Therefore, a novel full-time transient current waveform similarity based protection scheme is proposed to deal with these issues. The full-time current protection scheme uses both the power-frequency and non-power-frequency characteristics and can therefore reduce the influence of power-frequency phasor calculation errors to a minimum. The proposed method uses the transient current (within 10 ms after the fault inception) and is ignores the features of the steady-state fault current. In other words, the proposed protection is suitable for wind farms with a variety of controls. In the proposed method, the correlation coefficient index is used to calculate the similarity of the transient current signals at both ends of the line. Both experimental and field testing results show that using a common sampling frequency, the proposed protection scheme only uses current information and can correctly identify all types of external and internal line faults in a short period of time and can offer better performance for high fault resistance and noise, both for different types of wind farms. All these features and contributions make the new protection feasible for industry application.

Hybrid spin‐CMOS stochastic spiking neuron for high‐speed emulation of In vivo neuron dynamics

The spintronic stochastic spiking neuron (S3N) developed herein realises biologically mimetic stochastic spiking characteristics observed within in vivo cortical neurons, while operating several orders of magnitude more rapidly and exhibiting a favourable energy profile. This work leverages a novel probabilistic spintronic switching element device that provides thermally-driven and current-controlled tunable stochasticity in a compact, low-energy, and high-speed package. In order to close the loop, the authors utilise a second-order complementary metal-oxide-semiconductor (CMOS) synapse with variable weight control that accumulates incoming spikes into second-order transient current signals, which resemble the excitatory post-synaptic potentials found in biological neurons, and can be used to drive post-synaptic S3Ns. Simulation program with integrated circuit emphasis (SPICE) simulation results indicate that the equivalent of 1 s of in vivo neuronal spiking characteristics can be generated on the order of nanoseconds, enabling the feasibility of extremely rapid emulation of in vivo neuronal behaviours for future statistical models of cortical information processing. Their results also indicate that the S3N can generate spikes on the order of ten picoseconds while dissipating only 0.6-9.6 μW, depending on the spiking rate. Additionally, they demonstrate that an S3N can implement perceptron functionality, such as AND-gate- and OR-gate-based logic processing, and provide future extensions of the work to more advanced stochastic neuromorphic architectures.

Deep-Learning-Based Earth Fault Detection Using Continuous Wavelet Transform and Convolutional Neural Network in Resonant Grounding Distribution Systems

Feature extraction for fault signals is critical and difficult in all kinds of fault detection schemes. A novel simple and effective method of faulty feeder detection in resonant grounding distribution systems based on the continuous wavelet transform (CWT) and convolutional neural network (CNN) is presented in this paper. The time-frequency gray scale images are acquired by applying the CWT to the collected transient zero-sequence current signals of the faulty feeder and sound feeders. The features of the gray scale image will be extracted adaptively by the CNN, which is trained by a large number of gray scale images under various kinds of fault conditions and factors. The features extraction and the faulty feeder detection can be implemented by the trained CNN simultaneously. As a comparison, two faulty feeder detection methods based on artificial feature extraction and traditional machine learning are introduced. A practical resonant grounding distribution system is simulated in power systems computer aided design/electromagnetic transients including DC, the effectiveness and performance of the proposed faulty feeder detection method is compared and verified under different fault circumstances.

Broken Rotor Bar Fault Detection of IM Based on the Counter-Current Braking Method

This paper presents an improved method for the broken rotor bar detection in a squirrel-cage induction motor (IM). The method is based on the spectral analysis of the transient stator current signal during the counter-current braking (CCB). Contrary to the classical CCB, the proposed method results in the low braking current, which is a small fraction of the rated value and serves as a broken bar detection test signal only. This kind of the broken rotor bar fault diagnosis is independent of loading conditions and can be carried out even for a free shaft motor. The existence of spectral components in the low CCB current signal indicating the faulty conditions is first proven with the generalized theory of symmetrical components. The method is then verified via simulations, using an IM model based on the finite-element analysis and the magnetically coupled multiple circuits approach. Afterward, the experiments are performed, showing a good agreement with both the theoretical prediction and the simulation results, confirming the presence of the fault-induced components in the stator current spectra.

Measurement of Charge Transfer to Aqueous Droplets in High Voltage Electric Fields.

The electric charge acquired by aqueous droplets when they contact an electrode is a crucial parameter in experimental and industrial applications where electric fields are used to manipulate droplet motion and coalescence. For unclear reasons, many investigators have found that aqueous droplets acquire significantly more positive than negative charge. Extant techniques for determining the droplet charge typically rely on a hydrodynamic force balance that depends on accurate characterization of the drag forces acting on the droplet. Here we present an alternative methodology for measuring the droplet charge via direct measurement of the electric current. As the droplet approaches the electrode the current is observed to gradually increase, followed by a large pulse when the droplet makes apparent contact. We interpret the transient current signals as the superposition of the natural response of an RLC circuit and an induced current described by the Shockley-Ramo theory. Nonlinear regression of the observed current to the theoretical model allows for the droplet charge to be extracted, independent of any assumptions about the force balance on the droplet. We demonstrate that regression of the current signal yields charge values that are on average within 4% of charges measured via a force balance. We use the chronocoulometric methodology to investigate how the charge varies with the applied potential, and we demonstrate that deionized water droplets contacting planar electrodes acquire on average 69% more positive charge than negative charge.

Fault detection of broken rotor bar in LS-PMSM using random forests

This paper proposes a new approach to diagnose broken rotor bar failure in a line start-permanent magnet synchronous motor (LS-PMSM) using random forests. The transient current signal during the motor startup was acquired from a healthy motor and a faulty motor with a broken rotor bar fault. We extracted 13 statistical time domain features from the startup transient current signal, and used these features to train and test a random forest to determine whether the motor was operating under normal or faulty conditions. For feature selection, we used the feature importances from the random forest to reduce the number of features to two features. The results showed that the random forest classifies the motor condition as healthy or faulty with an accuracy of 98.8% using all features and with an accuracy of 98.4% by using only the mean-index and impulsion features. The performance of the random forest was compared with a decision tree, Naïve Bayes classifier, logistic regression, linear ridge, and a support vector machine, with the random forest consistently having a higher accuracy than the other algorithms. The proposed approach can be used in industry for online monitoring and fault diagnostic of LS-PMSM motors and the results can be helpful for the establishment of preventive maintenance plans in factories.

Fault Diagnosis of Smart Grid Distribution System by Using Smart Sensors and Symlet Wavelet Function

In today's era of smart grid system scenario, the fault diagnosis is of utmost important task. Present distribution networks change drastically due to expansion and inclusion of large number of distributed generation units into power system at distribution level. To face the challenges of modernized girds, conventional fault diagnosis methodologies require drastic change by making use of advanced infrastructure and technologies. This will be helpful to achieve automation in fault diagnosis tasks, improved power quality, reliability, resilience and self healing property of the power system. This paper proposes the use of smart sensors and advanced communication technology that will be available in future smart grids to carry out automated fault diagnosis tasks using signal processing techniques. Methods of using Standard deviation features of fault transient signal and a fault location factors are proposed. Performance of various scaling levels, features and components of fault transient current signals extracted using the latest non conventional Symlet mother wavelet function are evaluated and compared. The attempt is made to select optimal features and components of fault transient currents to improve the performance of present limited types of available fault locators. The tests are taken on standard model of smart grid distribution system but can be applied for fault diagnosis of any other power equipment. Results show adequate accuracy to extend the use of proposed method for real time applications.

Analysis of statistical features based on start-up current envelope for broken rotor bar fault detection in line start permanent magnet synchronous motor

Line start-permanent magnet synchronous motor (LS-PMSM) is one of the modern high efficiency motor introduced to the industry, recently. Like other types of electrical machines, various failures may happen in LS-PMSM during its life time. Among different failures which may occur in the motors with squirrel cage rotor, rotor fault (broken rotor bar) is the most significant one. This paper investigates defect diagnosis of LS-PMSM, based on statistical analysis of the signals acquired from motor in time domain to find the performance feature for rotor faults detection. To extract the features related to broken rotor bar, a time domain analysis was applied to the transient current signal envelope. In this regards, thirteen statistical parameters were calculated and their reliability were compared for broken rotor bar detection. ANOVA analysis was used to complete the information obtained from those parameters adjusted based on motor condition; starting load condition and their interaction. To perform a statistical comparison among the means for the selected features at different conditions, Tukey’s honest significant differences method was applied as post hoc testing procedure.

Direct Observation of the Collision of Single Pt Nanoparticles onto Single-Crystalline Gold Nanowire Electrodes.

We observed the collision of single Pt nanoparticles (NPs) onto an Au nanowire (NW) electrode by using electrocatalytic amplification. Previously, such observations had typically been performed by using a microscale disk-type ultramicroelectrode (UME). The use of a NW electrode decreased the background noise current and provided a shielding effect, owing to adsorption of the NPs onto the insulating sheath. Therefore, the transient current signal that was caused by the collision of single NPs could be more clearly distinguished from the background current by using a NW electrode instead of a UME. Furthermore, the use of a NW electrode increased the collisional frequency and the magnitude of the transient current signal. The experimental data were analyzed by using a theoretical model and a random walk simulation model.