  As the sensitivity and observing time of gravitational-wave detectors
increase, a more diverse range of signals is expected to be observed from a
variety of sources. Especially, long-lived gravitational-wave transients have
received interest in the last decade. Because most of long-duration signals are
poorly modeled, detection must rely on generic search algorithms, which make
few or no assumption on the nature of the signal. However, the computational
cost of those searches remains a limiting factor, which leads to sub-optimal
sensitivity. Several detection algorithms have been developed to cope with this
issue. In this paper, we present a new data analysis pipeline to search for
un-modeled long-lived transient gravitational-wave signals with duration
between 10 and 1000 s, based on an excess cross-power statistic in a network of
detectors. The pipeline implements several new features that are intended to
reduce computational cost and increase detection sensitivity for a wide range
of signal morphologies. The method is generalized to a network of an arbitrary
number of detectors and aims to provide a stable interface for further
improvements. Comparisons with a previous implementation of a similar method on
simulated and real gravitational-wave data show an overall increase in
detection efficiency depending on the signal morphology, and a computing time
reduced by at least a factor 10.

Instrumentation and Methods for Astrophysics;General Relativity and Quantum Cosmology