In order to improve reliability of distributions, the neutrals are usually insulated or compensated with Peterson coil. Thus, the currents of single-phase to ground fault are weak, leading to difficulty in fault line selection problem. This paper investigates an evidence theory based integrated fault line selection method which employs multiple fault components to improve the performances of selection for neutral compensated distributions. Aim of this method is through the fusion strategy of the multi-fold unreliable fault components to arrive at more reliable solution. Three kinds of fault components including the transient, the abrupt changing, and the damped DC are developed. Fault measures are introduced for each line to quantitatively describe the likelihood of the line being the fault line. The fault components are extracted by dual-tree complex wavelet and atom decomposition. And the algorithms of calculating fault measures for the three components are developed according to the principle of the fault. The basic probability assignment (BPA) functions of evidence theory are established with the cloud model algorithm of data driven. Examples validate that through fusion algorithm of the multifold fault components, the line selection is more robust and reliable to varied circumstance than utilizing individual component.