The active guided wave structural health monitoring enables real-time online monitoring of structural condition. However, the time-varying influence can make crack evaluation more difficult and reduce the accuracy. The time-varying factors make the guided-wave monitoring signal characteristics show obvious heteroscedasticity. The variance of the distribution of the characteristics changes with time. To address this issue, this article proposes a quantile regression-assisted online crack evaluation method, which uses quantile regression to estimate the variance of the guided wave monitoring signal characteristics with service time under the time-varying influence, and realizes the treatment of the heteroscedasticity uncertainty in the monitoring data. The proposed method is evaluated by using experimental data of the notched beam structure. The maximum absolute error of the evaluation is 1. 1 mm, and the root mean square error is 0. 4 mm. The proposed method can effectively deal with the effect of time-varying heteroscedasticity, quantify its uncertainty and provide a reference value for the evaluation results.