Empirical Likelihood (EL) method introduced by Owen (1988) is a widely used non-parametric tool for constructing confidence regions due to its appealing asymptotic distribution of the likelihood-ratio-type statistic which is same as the one under the parametric settings. However, the EL method was introduced to be used with independent data, hence it becomes difficult to apply it to dependent data such as time series models. An EL-based detecting procedure for structural changes intime series data is developed. The asymptotic results such as the asymptotic null distribution of the test statistic, the consistency of the estimator of the change location and the test are established. Further, simulations are conducted to investigate the performance of the proposed test under various scenarios. Additionally, real data is used to illustrate the detection procedure.