A method for probabilistic fatigue life assessment of steel bridges by using long-term
monitoring data is proposed and applied for fatigue reliability analysis of the suspension Tsing Ma
Bridge. In this method, the daily number of cycles for each stress range is obtained from the measured
stress history and its probability distribution is estimated based on statistical analysis of long-term
measurement data. The statistics obtained for all concerned stress ranges is combined with the S−N
relationships stipulated in specifications to conduct a probabilistic assessment of fatigue life with the
use of the Palmgren-Miner rule, from which the mean value and standard deviation of the fatigue life
as well as the failure probability and reliability index versus fatigue life are obtained. The proposed
method is illustrated by using 80-day strain measurement data from the suspension Tsing Ma Bridge
which is instrumented with a long-term structural health monitoring system.