Abstract
A new fusion sensing (FS) method was proposed by using the improved fractal box dimension (IFBD) and a developed maximum wavelet coefficient (DMWC) for fault sensing of an online power cable. There are four strategies that were used. Firstly, the traditional fractal box dimension was improved to enlarge the feature distances between the different fault classes. Secondly, the IFBD recognition algorithm was proposed by using the improved fractal dimension feature extracted from the three-phase currents for the first stage of fault recognition. Thirdly, the DMWC recognition algorithm was developed based on the K-transform and wavelet analysis to establish the relationship between the maximum wavelet coefficient and the fault class. Fourthly, the FS method was formed by combining the IFBD algorithm and the DMWC algorithm in order to recognize the 10 types of short circuit faults of online power. The designed test system proved that the FS method increased the fault recognition accuracy obviously. In addition, the parameters of the initial angle, transient resistance, and fault distance had no influence on the FS method.
Highlights
It is important for power systems to run without faults
In neutral grounded power systems, single-phase ground faults account for 70%–80%, two-phase faults and two-phase ground faults account for 10%, and three-phase faults account for 5% of all faults that occur
The LabVIEW software was used for the interface platform
Summary
It is important for power systems to run without faults. different types of faults often occur [1,2]. It can highlight mutative components of the processed processed signals by flexibly changing the window of the time-frequency domain, and can extract the power cable fault information effectively. Another study proposed a fault location method based on the genetic algorithm using the transient components of three-phase currents [24]. These methods have made[23]. A new fusion sensing methodwas was proposed by using The organization of this this paper isis as follows: follows: Short-circuit fault components in online online power. The organization of paper as components in power using the improved fractal dimension and a developed maximum wavelet modulus for short-circuit fault recognition of online power cables in this paper. The analysis ofthe the experiment and the results are reported cables are described in.Section
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
