A new fusion sensing (FS) method was proposed by using the improved fractal box\ndimension (IFBD) and a developed maximum wavelet coefficient (DMWC) for fault sensing of\nan online power cable. There are four strategies that were used. Firstly, the traditional fractal box\ndimension was improved to enlarge the feature distances between the different fault classes. Secondly,\nthe IFBD recognition algorithm was proposed by using the improved fractal dimension feature\nextracted from the three-phase currents for the first stage of fault recognition. Thirdly, the DMWC\nrecognition algorithm was developed based on the K-transform and wavelet analysis to establish the\nrelationship between the maximum wavelet coefficient and the fault class. Fourthly, the FS method\nwas formed by combining the IFBD algorithm and the DMWC algorithm in order to recognize the\n10 types of short circuit faults of online power. The designed test system proved that the FS method\nincreased the fault recognition accuracy obviously. In addition, the parameters of the initial angle,\ntransient resistance, and fault distance had no influence on the FS method.
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