Conventional Current Sensors Research Articles

Single PCB sensor-based output current reproduction for three-phase inverter systems

This study proposes a practical output current measurement system in a three-phase inverter with a single printed circuit board (PCB) Rogowski coil sensor inserted in the bus between the DC-link capacitor and the power semiconductor module. This system demonstrates its advantage over conventional output current sensors, such as the Hall effect current sensors, in terms of the size, weight, operation temperature and cost. The system can be applied to 6-in-1 power modules as it does not require sensors in the inverter phase legs.In our previous works, we have developed a method called “envelope tracking”, which is used in this system as well. This method traces the switching current instead of the output current to reproduce the output current signal in real-time. Envelope tracking successfully reproduced the output current waveform for single phase inverters under certain conditions. However, a large error is observed in the three-phase inverter demonstration under a high switching frequency (narrow pulse) or when the switching of different phases overlap each other. These errors must be completely suppressed to implement the system for feedback control in three-phase inverters.In this study, a new analog basis output current waveform reproduction system is introduced to suppress the above mentioned errors. This system is implemented in a three-phase insulated-gate bipolar transistor (IGBT) inverter and successfully reproduces the output current with a single PCB sensor inserted between a 6-in-1 IGBT power module and DC-link capacitor, operating under a switching frequency of 3.5–7.0 kHz and output current of 6 A with DC-link voltage of 150 V.

Spindle Condition Monitoring With a Smart Vibration Sensor and an Optimized Deep Neural Network

Abstract This article presents a spindle condition monitoring methodology using a low-power smart vibration sensor and a near real-time deep neural network (DNN) classifier. The most frequent spindle failures, such as imbalance, ingression, and evidence of a crash with the workpiece, are analyzed in this study. Experiments were designed to induce various failure events to monitor the spindle behavior using conventional vibration, current and temperature sensors, and an intelligent vibration sensor. The smart sensor is a device with internal signal processing identifying eight dominant frequencies and the amplitude/power distributions. It requires low power and generates narrow bandwidth messages that can be communicated wirelessly. A Fog device and a test plan are designed to monitor and store a dataset needed to train a DNN classifier. The Fog device generates temperature, current, and vibration signals from sensors connected to the spindle and sends them to data storage in the cloud. The signals were analyzed using both conventional vibration analysis and Artificial Intelligence-based classifiers. Metrics such as crest factor, skewness, kurtosis, and overall enveloping were used to assess their ability to identify the failure condition. The data from the smart sensor are used to train an optimized DNN, and the spindle defect classification performance is measured. With 960 data points per failure mode and training data taken over 960 min of operation, the optimized DNNs can classify the spindle states with an accuracy of 98%. The study shows real-time spindle condition classification feasibility over long periods using inexpensive and low-power smart vibration sensors.

Current Sensor FTC Method for MPTC of Three-Phase Induction Motor Drives Without Speed Measurement

In encoderless Model Predictive Torque Control (MPTC) of three-phase Induction Motor (IM) drives, current sensors can face different electrical or mechanical faults in harsh industrial environments. In this research, single-phase current sensor Fault-Tolerant Control (FTC) method for MPTC of three-phase IM drives without speed measurement using a flux linkage observer and Model Reference Adaptive System (MRAS) algorithm is proposed. In the presented FTC method, Third-Difference operators, logic circuit module, flux linkage observer, and MRAS algorithm are utilized for fault detection, fault isolation, estimation of stator currents and fluxes, and speed estimation, respectively. In comparison with the conventional current sensor FTC methods, the proposed method can be utilized for encoderless three-phase IM drives. In order to confirm the usefulness and possibility of the proposed encoderless FTC method, experimental studies are performed for a 0.75 kW three-phase IM drive system in different situations. The achieved results demonstrate good performances of the proposed technique during both normal and faulty situations.

Improved detection of surface defects at sample edges using high-frequency eddy current amplitude and phase measurements

ABSTRACT The detection of surface cracks at or close to sample edges is a challenging problem because the interaction of the eddy current with the sample edge can make it difficult to distinguish changes in the eddy current signal due to a defect. Samples with poor electrical conductivity such as titanium alloys used extensively in aerospace applications can be more difficult to inspect due to the low amplitude eddy currents induced in them and increased electromagnetic skin depths due to lower electrical conductivity. As fatigue surface cracks or manufacturing surface defects can often occur close to edges, the challenges of detecting small defects close to sample edges is an important research area to address. High-frequency eddy currents of over 10 MHz are used in a transmit-receive configuration using two solenoid type coils adjacent to each other. While conventional eddy current sensors are commonly designed for operating at frequencies into the low MHz region, the supporting electronics here will be positioned immediately behind the coils to improve electrical stability and reduce induced noise. The magnitude and phase of the voltage on transmit and receiver coils are measured, and finite element modelling is used to validate the experimental measurements and gain insight into the system behaviour. Small defects of down to 1 mm are easily detected, on the edge and at the corner of a titanium alloy sample with excellent signal-to-noise.

Electrical current visualization sensor based on magneto-electrochromic effect

Electrical safety is a major threat to public safety worldwide, with fires and explosions causing damage to property and loss of life. Detection and monitoring of the occurrence of destructive current spikes can provide valuable insights into system health and inform preventative maintenance. Current sensors based on the Magnetoelectric (ME) effect have been regarded as optimal solutions because of the low power consumption and high sensitivity of ME devices compared to conventional current sensors (current transformers, Hall-effect current sensors, etc.). However, none of the conventional sensing techniques can provide ex-situ recording or a means for a human-readable signal output. Development of a current sensor that can sense, visualize, and record a current level remains a challenge. Here, we report an electric current visualization sensor that uses a coupled magnetoelectric/electrochromic effect to transform environmental current energy into electrical signals, and subsequently to a color change readily interpreted by a human observer. The current visualization sensor uses a PZT piezoelectric microfiber composite (MFC) / FeSiB alloy (Metglas) laminate combined with a Prussian blue-based electrochromic device (ECD). Such a current sensor demonstrates high efficiency self-powered current sensing and non-volatile signal recording.

Improved Three-Phase Current Reconstruction Technique for PMSM Drive With Current Prediction

In this article, we present an improved current reconstruction technique with current prediction for a permanent magnet synchronous motor drive system. In some conventional single current sensor techniques, current fluctuations occur at the sector-switching period (SSP) due to current holding between two adjacent sampling intervals, which can cause current distortion and introduce many current harmonics, especially when the motor speed is very high. Focusing on that, a current prediction method is proposed in this article to prevent the current fluctuation happening at SSP. The SSP is divided into two independent parts for the accurate calculation of the output voltage vector and the actual three-phase currents at SSP are determined on account of both the predicted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis currents and the measurable ones. As a result, compared with the previous current-holding strategy, the current fluctuations can be fundamentally eliminated under the proposed method with less current harmonics introduced, further improving the control performance of the whole system. The accuracy and practicability of the proposed method are verified by the experimental results.

Time-Multiplexed Self-Powered Wireless Current Sensor for Power Transmission Lines

Current measurement is a key part of the monitoring system for power transmission lines. Compared with the conventional current sensor, the distributed, self-powered and contactless current sensor has great advantages of safety and reliability. By integrating the current sensing function and the energy harvesting function of current transformer (CT), a time-multiplexed self-powered wireless sensor that can measure the power transmission line current is presented in this paper. Two operating modes of CT, including current sensing mode and energy harvesting mode, are analyzed in detail. Through the design of mode-switching circuit, harvesting circuit and measurement circuit are isolated using only one CT secondary coil, which eliminates the interference between energy harvesting and current measurement. Thus, the accurate measurement in the current sensing mode and the maximum energy collection in the energy harvesting mode are both realized, all of which simplify the online power transmission line monitoring. The designed time-multiplexed working mode allows the sensor to work at a lower transmission line current, at the expense of a lower working frequency. Finally, the proposed sensor is verified by experiments.

Study on High Lift-Off of Eddy Current Type Rail Displacement Sensor by High Quality Factor

As the conventional eddy current type rail displacement sensor has a small distance (liftoff) from the railhead top surface to a sensor, there is the possibility that a sensor wakes up trouble and malfunction for a collision with the snow and the gravel. As the conventional triangle coil has low Q level, a change of the impedance to depend on rail displacement for when I raise a liftoff is not provided enough. Therefore, the problem that the detection precision of the rail displacement falls to occurs. In this article, I improved a Q level by becoming examination, the high frequency of the drive circuit of the coil structure and enabled measuring it at 50mm that was conventional double size by a liftoff.

A Fast Vacuum Arc Detection Method Based on the Neural Network Data Fusion Algorithm for the High-Voltage DC Power Supply of Vacuum Tubes

Vacuum arc is one of the most important failure factors of the vacuum tubes. The amount of delivered energy from the high-voltage dc power supply to the vacuum tube is an important issue during the vacuum arc in the tube. Vacuum arc acts as a short-circuit fault (SCF) at the power supply output. The majority of converters use a single current sensor to measure only the converter output current for detecting the SCF. However, the sensor may provide unreliable data because of the noise effect. Application of a low-pass filter reduces the noise effect. Regarding the delay of the low-pass filter, the interval of arc detection increases and more energy is delivered to the tube. In this article, a fast vacuum arc diagnosis system is proposed based on the neural network data fusion algorithm. The proposed scheme consists of two sensors: the conventional current sensor and the existing voltage sensor used for controlling and monitoring. The data of these two sensors are combined by neural networks to diagnose the vacuum arc and to reject false alarms in noisy environments. The proposed method has a fast response time to the real SCFs while it remains inactive against the false data which are generated by noise. Simulations and experimental tests are carried out to evaluate the proposed scheme.

Analysis of Various Pickup Coil Designs in Nonmodule-Type GaN Power Semiconductors.

Gallium nitride (GaN) devices are advantageous over conventional Silicon (Si) devices in terms of their small size, low on-resistance, and high dv/dt characteristics; these ensure a high integrated density circuit configuration, high efficiency, and fast switching speed. Therefore, in the diagnosis and protection of a system containing a GaN power semiconductor, the transient state for accurate switch current measurement must be analyzed. The pick-up coil, as a current sensor for switch current measurement in a system comprising a surface-mount-device-type nonmodular GaN power semiconductor, has the advantages of a higher degree-of-freedom configuration for its printed circuit board, a relatively small size, and lower cost than other current sensors. However, owing to the fast switching characteristics of the GaN device, a bandwidth of hundreds MHz must be secured along with a coil configuration that must overcome the limitations of relatively low sensitivity of the conventional current sensor. This paper analyzes the pick-up coil sensor models that can achieve optimal bandwidth and sensitivity for switch current measurement in GaN based device. So four configurable pick-up coil models are considered and compared according to coil-parameter using mathematical methods, magnetic, and frequency-response analysis. Finally, an optimal coil model is proposed and validated using a double-pulse test.

Design of enhanced energy meter using GSM prepaid system and protective relays

Nowadays, technology has developed to an advanced level so customer demand for systems with automation and high security. The prepaid meter is important in making the consumer having sense about his or her energy consumption as well as in resolving the issues facing by the utility labor in getting the reading of conventional meter and eliminating the error incurred in bills issuing. This research aims to enhance an existing conventional energy meter integrate with prepaid system and protection system. The designed prepaid meter consists of an Arduino, conventional energy meter, GSM (Global System for Mobile Communications) module, current sensor and relay. The proposed prototype comprises into two parts: GSM technology and overcurrent protection, whereas GSM technology is used for communication and reloads purpose; overcurrent protection is done with a current sensor and relay working together.

Self-Calibration of Phase Current Sensors With Sampling Errors by Multipoint Sampling of Current Values in a Single PWM Cycle

The accuracy of current sensors is most crucial for the performance of an interior permanent magnet synchronous motor (IPMSM) drive. However, it may have sampling errors that are unavoidable for an actual drive. Therefore, to cope with this problem, in this article, a self-calibration strategy for phase-current sensors is proposed by utilizing the proposed topology and the correlation among the multiple current values obtained by current sampling values during one single pulsewidth modulation cycle, making minor changes for the cablings of the conventional current sensors in the premise of not affecting the normal operation of the drive, and abandoning complex observers or filters for easing the computational burden. Besides, its effectiveness was verified by the experimental results on a 5-kW IPMSM motor prototype, which showed that such sampling errors could be well estimated and eliminated.

Improved Current Sensor for Water Diffusion Testing of Composite Insulators.

An improved current sensor aimed at measuring currents of different parts in composite insulator samples was proposed. Conventional current sensors used in water diffusion tests aim to examine the performance of composite insulators, however, it is difficult for the conventional current sensors to locate the defects. Thus, we designed a new electrode structure to measure the currents of different components in short samples of composite insulators. Based on a finite analysis method, the influence of relative permittivity and conductivity on the current was analyzed. New samples with different interfaces and samples after operation were tested using the new and conventional current sensors. The performance of a certain part in short samples can be diagnosed by analyzing the current and phase information extracted from the test results. By comparing the test results of new and traditional current sensors, it was proved that the new electrode structure is more effective in locating the defects of insulators.

High Accuracy Open-Type Current Sensor with a Differential Planar Hall Resistive Sensor.

In this paper, we propose a high accuracy open-type current sensor with a differential Planar Hall Resistive (PHR) sensor. Conventional open-type current sensors with magnetic sensors are usually vulnerable to interference from an external magnetic field. To reduce the effect of an unintended magnetic field, the proposed design uses a differential structure with PHR. The differential structure provides robust performance to unwanted magnetic flux and increased magnetic sensitivity. In addition, instead of conventional Hall sensors with a magnetic concentrator, a newly developed PHR with high sensitivity is employed to sense horizontal magnetic fields. The PHR sensor and read-out integrated circuit (IC) are integrated through a post-Complementary metal-oxide-semiconductor (CMOS) process using multi-chip packaging. The current sensor is designed to measure a 1 A current level. The measured performance of the designed current sensor has a 16 kHz bandwidth and a current nonlinearity of under ±0.5%.

An optimal current observer for predictive current controlled buck DC-DC converters.

In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally.

The Modified Control Method for the Single-Stage Three-Phase GridConnected Photovoltaic System

Single-stage topology and the maximum power point tracking (MPPT) algorithm have advantages such as simple configuration and high efficiency in grid-connected photovoltaic (PV) systems. In conventional systems, current and voltage sensors of PV system are normally used for MPPT. This paper presents a modified control algorithm for the single-stage three-phase grid-connected PV system without PV current sensor with a variable step MPP-tracker. This algorithm is not derived from complex state equations and is not dependent on any circuit parameters. It simply calculates the output power of the inverter to replace the input power of the PV systems in the MPPT algorithm. The modified algorithm is simulated by using Matlab/Simulink software and implemented in the experimental prototype. With the single-stage configuration and PV current sensorless method, the prototype is suitable for lowcost high efficient implementation in the practice.

A new MagFET-based integrated current sensor highly immune to EMI

This paper deals with the susceptibility to radio frequency interference of the integrated circuits used to monitor the current of power devices. A circuit based on the mirroring principle of common use in commercial devices is first considered, then a new contact-less fully integrated current sensor based on the Hall effect is proposed. The design of this current sensor is shown in detail and its susceptibility to radio frequency interference is investigated through time-domain simulations. The results of these analyses are presented then compared with those obtained from similar analysis carried out on a conventional (wired) current sensor.

Spun Optical Microfiber

The first report of spun optical microfiber (OM) is presented, with details on its fabrication method and a demonstration of its important role in making practical Faraday-based microcoil current sensors. These sensors have shown potential for significantly higher bandwidth and compactness compared to conventional fiber-optic current sensors. We demonstrate that spun OM exhibits superior resistance to bend- and packaging-induced linear birefringence, which can improve the responsivity and reproducibility of the sensor head.

Diagnóstico de Fallas en Máquinas Eléctricas Rotatorias Utilizando la Técnica de Espectros de Frecuencia de Bandas Laterales

In this article a methodology to diagnose faults in rotating electrical machines is presented. The method uses spectral frequency analysis of the phase currents sidebands. Online systems to verify the magnitude of these frequencies, caused not only by mechanical faults but also electrical faults, are presented. The results of a faulty set formed by a direct current motor plus a synchronous generator of 5 kVA and two squirrel-cage induction motors of 5 HP, one with slacked bearings faults and other with broken rotor bars, are presented. Also, the results of the spectra using a conventional current sensor are compared with those of a Rogowski coil, showing that the results of both sensors are suitable to detect machine faults.

Fluxgate DC Earth Leakage Current Sensor

This paper describes results obtained from analysis and experiments done on a fluxgate dc earth leakage current sensor for electric vehicles and photovoltaic power generation systems. As fluxgate current sensors are extremely sensitive to room temperature, various applications need this characteristic. However, conventional fluxgate current sensors have a problem in that they can only measure a narrow range of currents. To address this issue, we propose that the turns of the excitation coil be optimized with a simulator. This new sensor consists of a coiled wire that is wound around a toroidal amorphous core and through a bus bar. The sensor detects variations in excitation current according to dc current. The sensor was analyzed with a simulator. The magnetic field simulator was used to calculate the excitation current, and the output voltage according to the excitation current was calculated with a circuit simulator. We found that the results from simulations almost corresponded to those from measurements, and were able to verify the validity of the basic analytical model. As a result of analysis with the simulator, 35 turns of the excitation coil were used to achieve a wide range of measurements of ±600 mA.