Fault Detection in DC Microgrids Using Short-Time Fourier Transform

Grcić, Ivan; Pandžić, Hrvoje; Novosel, Damir

doi:10.3390/en14020277

Cited by 27 publications

(11 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Safety and reliability issues include switches and protection schemes, which are not as developed as their AC counterparts. Means to anticipate and overcome possible faults (fault detection and avoidance techniques) in the DC MG need to be thoroughly investigated before the large-scale deployment of such architectures [115][116][117].…”

Section: Future Trends and Challengesmentioning

confidence: 99%

State of the Art of Low and Medium Voltage Direct Current (DC) Microgrids

et al. 2021

View full text Add to dashboard Cite

Direct current (DC) microgrids (MG) constitute a research field that has gained great attention over the past few years, challenging the well-established dominance of their alternating current (AC) counterparts in Low Voltage (LV) (up to 1.5 kV) as well as Medium Voltage (MV) applications (up to 50 kV). The main reasons behind this change are: (i) the ascending amalgamation of Renewable Energy Sources (RES) and Battery Energy Storage Systems (BESS), which predominantly supply DC power to the energy mix that meets electrical power demand and (ii) the ascending use of electronic loads and other DC-powered devices by the end-users. In this sense, DC distribution provides a more efficient interface between the majority of Distributed Energy Resources (DER) and part of the total load of a MG. The early adopters of DC MGs include mostly buildings with high RES production, ships, data centers, electric vehicle (EV) charging stations and traction systems. However, the lack of expertise and the insufficient standards’ framework inhibit their wider spread. This review paper presents the state of the art of LV and MV DC MGs in terms of advantages/disadvantages over their AC counterparts, their interface with the AC main grid, topologies, control, applications, ancillary services and standardization issues. Overall, the aim of this review is to highlight the possibilities provided by DC MG architectures as well as the necessity for a solid/inclusive regulatory framework, which is their main weakness.

show abstract

Section: Future Trends and Challengesmentioning

confidence: 99%

State of the Art of Low and Medium Voltage Direct Current (DC) Microgrids

et al. 2021

View full text Add to dashboard Cite

show abstract

“…The frequency analysis of the drill string vibration signal mainly uses two methods, fast Fourier transform (FFT) and short-time Fourier transform (STFT) [36,37]. Fast Fourier transform can analyze each frequency component in drill string vibration, and short-time Fourier transform can clarify the change law of each frequency with time.…”

Section: Frequency Analysis Of Vibration Signalmentioning

confidence: 99%

Measurement and Analysis of Downhole Drill String Vibration Signal

Wang

Shan

et al. 2021

Applied Sciences

View full text Add to dashboard Cite

Downhole drill string vibration data can provide an effective reference for research drill string vibration during drilling. In this paper, the research group used a storage-type downhole vibration measurement equipment equipped with an orthogonal, three-axis accelerometer to measure and collect drill string vibration signals during drilling in an oil well. Based on the installation characteristics of the sensor, the relationship between the acceleration measurement value of the sensor and the center acceleration value of the drill string is obtained. Then the time-domain signals representative of the vibration in igneous rock drilling is analyzed. It can be found that the occurrence of stick-slip vibration can be judged by the regular wave packets in the time-domain signal, while the time-domain signal of whirl is disorderly. The main frequency of stick-slip vibration in the low-frequency band is 0.1221 Hz and the period of stick-slip vibration is very close to 10 s through Fast Fourier (FFT) and Short-time Fourier transform (DTFT) methods. In the process of whirling, two frequencies, respectively, 0.05341 Hz and 155.5 Hz, play a major role. The frequency 0.05341 Hz is very close to the reciprocal of the period of 20 s when the peak energy spectrum density appears, indicating that the occurrence of whirl is very likely to be related to the natural frequency of the drilling tool. Through further time-frequency analysis, it also can be found that the occurrence of whirl and stick-slip is greatly related to the use of torsional impactors and jars.

show abstract

“…On the other hand, the application of signal processing-based algorithms for fault detection and isolation is discussed in refs. [ 17 , 18 , 19 ]. Furthermore, to design bearing fault diagnosis techniques, various approaches have been carried out that can be used in three main domains: the time domain, the frequency domain, and the time–frequency domain.…”

Section: Introductionmentioning

confidence: 99%

Bearing Fault Diagnosis Using a Hybrid Fuzzy V-Structure Fault Estimator Scheme

Piltan

Kim

2023

Sensors

View full text Add to dashboard Cite

Bearings are critical components of motors. However, they can cause several issues. Proper and timely detection of faults in the bearings can play a decisive role in reducing damage to the entire system, thereby reducing economic losses. In this study, a hybrid fuzzy V-structure fuzzy fault estimator was used for fault diagnosis and crack size identification in the bearing using vibration signals. The estimator was designed based on the combination of a fuzzy algorithm and a V-structure approach to reduce the oscillation and improve the unknown condition’s estimation and prediction in using the V-structure method. The V-structure surface is developed by the proposed fuzzy algorithm, which reduces the vibrations and improves the stability. In addition, the parallel fuzzy method is used to improve the robustness and stability of the V-structure algorithm. For data modeling, the proposed combination of an external autoregression error, a Laguerre filter, and a support vector regression algorithm was employed. Finally, the support vector machine algorithm was used for data classification and crack size detection. The effectiveness of the proposed approach was evaluated by leveraging the vibration signals provided in the Case Western Reserve University bearing dataset. The dataset consists of four conditions: normal, ball failure, inner fault, and outer fault. The results showed that the average accuracy of fault classification and crack size identification using the hybrid fuzzy V-structure fuzzy fault estimation algorithm was 98.75% and 98%, respectively.

show abstract

Fault Detection in DC Microgrids Using Short-Time Fourier Transform

Cited by 27 publications

References 37 publications

State of the Art of Low and Medium Voltage Direct Current (DC) Microgrids

State of the Art of Low and Medium Voltage Direct Current (DC) Microgrids

Measurement and Analysis of Downhole Drill String Vibration Signal

Bearing Fault Diagnosis Using a Hybrid Fuzzy V-Structure Fault Estimator Scheme

Contact Info

Product

Resources

About