Supply Current Signal Research Articles

Application of the Time-Domain Signal Analysis for Electrical Appliances Identification in the Non-Intrusive Load Monitoring

The paper presents a novel method for non-intrusive appliances identification. It can be used for energy load disaggregation in a smart grid. The approach identifies changes in the state of the particular appliance by measuring and processing the common supply current signal. Analysis of the instantaneous changes in the aggregated current on the output of the analyzed circuit in the power network is exploited here. The signal is processed using the time alignment of the current and voltage signals samples represented in the array form. The scheme includes filtering, event detection and identification, which is performed by comparing parameters of the detected event against previously determined signatures of monitored appliances. The analysis is performed in the time domain; therefore (unlike other existing methods), the information contained in the original signal is not lost. The approach was tested in the laboratory designed specifically for this purpose. All tests have been conducted with up to 12 appliances operating at the same time in the single power supply circuit. The measurement setup was developed and used to record appliances’ switching on/off events. During tests, 2300 events for devices were recorded. Collected data were processed to identify particular devices with the accuracy of 98.8% and macro-averaged F-score measure of 0.9874. High identification accuracy was achieved despite the high number of devices operating in the background.

Experimental detection of defects in variable speed fan bearing using stator current monitoring

This article presents an experimental contribution to detect and diagnose mechanical faults, including bearing faults, which are the cause of most faults in single or variable speed fan motor systems. For this, we proceed to the extraction of the characteristics appearing in the supply current signal of the diagnostic system, by the application of three complementary approaches. During our experimental study, we found that one of the best methods for diagnosing single or multiple mechanical faults in induction motor systems is MCSA (Motors Current Signature Analysis), to which we applied the FFT (Fast Fourier transform) spectral analysis completed by the park vector approach orbital (OPVA) applied to the components of the current stator vector. In order to confirm the reliability of our diagnosis, these two approaches have been supplemented by the Gabor spectrogram (STFT). The practical validation of this plural methodology, in the case of a bearing degradation, was carried out on a variable speed fan motor of 0.25 HP. The results obtained by this fault detection technique are satisfactory and interesting because they make it possible to anticipate breakdowns and, therefore, to program and control the maintenance costs of industrial systems without affecting production.

Adaptive filter based current controller for Shunt Active filter

This paper deals with the harmonic mitigation and reactive power compensation using Shunt Active filter. The performance of the Shunt active filter depends on the design and current control technique for generating a reference current. The design of the filter involves the iterative procedure for choosing the filter components so that it compensates the harmonics and reactive power for maximum load condition. The current controller method adopted for indirect current control technique where the reference signal is similar to the supply current signal. The Adaptive filter used in current controller mitigates harmonics and reactive power and voltage control loop of SAF balancing the active power between the load and supply unit. The learning rate is fixed by repeated simulation. The SAF active filter is tested in four load condition ie., nonlinear load(37% Total Harmonic Distortion(THD)),highly nonlinear load(>100% THD), linear load(<8% THD, power factor(pf) <0.5) and both nonlinear and linear load(37% THD and 0.7 pf). The study is carried out in MATLAB Simulink and the results are presented.

Inclusion of Power Consumption Information in High-Level Modeling of Linear Analog Blocks

SystemC-AMS allows the modeling of complex heterogeneous systems at different levels of abstraction using different modeling styles, called Models of Computation (MoC). This work presents an approach for including energy consumption information in high-level modeling of linear electrical circuits described using the SystemC-AMS Linear Signal Flow (LSF) MoC. The method introduced here proposes to start from a description of the system at a low level of abstraction, which is a description using the SystemC-AMS Electrical Linear Network (ELN) MoC or a SPICE netlist. The following steps of the proposed approach automatically extract the state space model corresponding to the analyzed circuit. During the state equation extraction, the supply current signal is regarded as an output of the state space model. This output allows an instantaneous monitoring of the power consumption of the system at the LSF description level. The case study that we present as a proof of the proposed approach is a passive fourth-order low pass filter. Then, we present a possible application: a power consumption comparison between two circuits having the same transfer function.

FREQUENCY SPECTRA FROM CURRENT VS. MAGNETIC FLUX DENSITY MEASUREMENTS FOR MOBILE PHONES AND OTHER ELECTRICAL APPLIANCES

The frequency spectra of electromagnetic fields have to be determined to evaluate human exposure in accordance to ICNIRP guidelines. In the literature, comparisons with magnetic field guidelines have been performed by using the frequency distribution of the current drawn from the battery. In the present study we compared the frequency spectrum in the range 217 Hz to 2.4 kHz of the magnetic flux density measured near the surface of a mobile phone with the frequency spectrum of the supply current. By using the multiple frequency rule, recommended in the ICNIRP guidelines, we estimated the magnetic field exposure in the two cases. Similar measurements and estimations were done for an electric drill, a hair dryer, and a fluorescent desk lamp. All the devices have a basic frequency of 50 Hz, and the frequency spectra were evaluated up to 550 Hz. We also mapped the magnetic field in 3D around three mobile phones. The frequency distributions obtained from the two measurement methods are not equal. The frequency content of the current leads to an overestimation of the magnetic field exposure by a factor up to 2.2 for the mobile phone. For the drill, the hair dryer, and the fluorescent lamp, the supply current signal underestimated the exposure by a factor up to 2.3. In conclusion, an accurate exposure evaluation requires the magnetic flux density spectrum of the device to be measured directly. There was no indication that the devices studied would exceed the reference levels at the working distances normally used.