A data-driven ground fault detection and isolation method for main circuit in railway electrical traction system. (April 2019)
- Record Type:
- Journal Article
- Title:
- A data-driven ground fault detection and isolation method for main circuit in railway electrical traction system. (April 2019)
- Main Title:
- A data-driven ground fault detection and isolation method for main circuit in railway electrical traction system
- Authors:
- Chen, Zhiwen
Li, Xueming
Yang, Chao
Peng, Tao
Yang, Chunhua
Karimi, H.R.
Gui, Weihua - Abstract:
- Abstract: Due to the complex and harsh operation conditions, like corrosion, aging cable and static electricity, of electrical traction drive system, ground fault will generate large short circuit current to harm the key components. Effective fault diagnosis is important, but also challenging. The conventional method used for ground fault detection only takes advantage of voltage measurements of DC-link. Other measurements onboard are also available, which are correlated with the voltage measurements. Taking the correlation into account will improve the detection performance. To this end, this paper presents a data-driven solution, which makes full use of the correlation between the voltage measurements with other measurements onboard. The proposed method consists of two components: (1) a canonical correlation analysis-based fault detection method, which takes into account the correlation within measurements; (2) a fault isolation method by means of the fault direction, which can be obtained with the available faulty data stored in the long-term operation. The developed method is applied to a traction drive system. It is shown that the proposed approach is able to improve the fault detection and isolation performance significantly with respect to three performance indicators, namely fault detection rate, detection delay and correct isolation rate, in comparison with the conventional method, which only uses the voltage measurements of DC-link. Highlights: IntroduceAbstract: Due to the complex and harsh operation conditions, like corrosion, aging cable and static electricity, of electrical traction drive system, ground fault will generate large short circuit current to harm the key components. Effective fault diagnosis is important, but also challenging. The conventional method used for ground fault detection only takes advantage of voltage measurements of DC-link. Other measurements onboard are also available, which are correlated with the voltage measurements. Taking the correlation into account will improve the detection performance. To this end, this paper presents a data-driven solution, which makes full use of the correlation between the voltage measurements with other measurements onboard. The proposed method consists of two components: (1) a canonical correlation analysis-based fault detection method, which takes into account the correlation within measurements; (2) a fault isolation method by means of the fault direction, which can be obtained with the available faulty data stored in the long-term operation. The developed method is applied to a traction drive system. It is shown that the proposed approach is able to improve the fault detection and isolation performance significantly with respect to three performance indicators, namely fault detection rate, detection delay and correct isolation rate, in comparison with the conventional method, which only uses the voltage measurements of DC-link. Highlights: Introduce characteristics of typical ground faults in the electrical traction system. An CCA solution is proposed using the correlation between the measurements onboard. A fault isolation method is proposed using the residual and fault direction info. … (more)
- Is Part Of:
- ISA transactions. Volume 87(2019)
- Journal:
- ISA transactions
- Issue:
- Volume 87(2019)
- Issue Display:
- Volume 87, Issue 2019 (2019)
- Year:
- 2019
- Volume:
- 87
- Issue:
- 2019
- Issue Sort Value:
- 2019-0087-2019-0000
- Page Start:
- 264
- Page End:
- 271
- Publication Date:
- 2019-04
- Subjects:
- Data-driven -- Ground fault diagnosis -- Canonical correlation analysis -- Electrical traction drive monitoring
Engineering instruments -- Periodicals
Engineering instruments
Periodicals
Electronic journals
629.805 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00190578 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.isatra.2018.11.031 ↗
- Languages:
- English
- ISSNs:
- 0019-0578
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4582.700000
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