  The Search for Extraterrestrial Intelligence (SETI) attempts to address the
possibility of the presence of technological civilizations beyond the Earth.
Benefiting from high sensitivity, large sky coverage, an innovative feed cabin
for China's Five-hundred-meter Aperture Spherical radio Telescope (FAST), we
performed the SETI first observations with FAST's newly commisioned 19-beam
receiver; we report preliminary results in this paper. Using the data stream
produced by the SERENDIP VI realtime multibeam SETI spectrometer installed at
FAST, as well as its off-line data processing pipelines, we identify and remove
four kinds of radio frequency interference(RFI): zone, broadband, multi-beam,
and drifting, utilizing the Nebula SETI software pipeline combined with machine
learning algorithms. After RFI mitigation, the Nebula pipeline identifies and
ranks interesting narrow band candidate ET signals, scoring candidates by the
number of times candidate signals have been seen at roughly the same sky
position and same frequency, signal strength, proximity to a nearby star or
object of interest, along with several other scoring criteria. We show four
example candidates groups that demonstrate these RFI mitigation and candidate
selection. This preliminary testing on FAST data helps to validate our SETI
instrumentation techniques as well as our data processing pipeline.
