  A time-domain test for the assumption of second order stationarity of a
functional time series is proposed. The test is based on combining individual
cumulative sum tests which are designed to be sensitive to changes in the mean,
variance and autocovariance operators, respectively. The combination of their
dependent $p$-values relies on a joint dependent block multiplier bootstrap of
the individual test statistics. Conditions under which the proposed combined
testing procedure is asymptotically valid under stationarity are provided. A
procedure is proposed to automatically choose the block length parameter needed
for the construction of the bootstrap. The finite-sample behavior of the
proposed test is investigated in Monte Carlo experiments and an illustration on
a real data set is provided.
