High dimensional feature space of the kernel principle component was divided into principle component subspace and residual space in this paper.A residual space based fault isolation algorithm was proposed

which reduced the subitem reflecting the principle component subspace

made the computational complexity dramatically decreased.Fault isolation algorithm applying residual space of kernel principle component analysis has such advantages as restriction of residual contamination and easy to be realized

so it can be used for sensor fault diagnosis.Taking the regenerative system of a 600 MW unit as an example

analysis on the measured data shows that

this method can timely diagnose the sensor fault of different types

even when multiple sensors' failures occur simultaneously

it can accurately diagnose the fault and isolate the fault sensor in time.