This paper is concerned with the problem of power harmonic detection subject to communication resource constraints and measurement outliers. A dynamic tracking model is established to capture the dynamics of harmonic signals considering that the underlying system is subject to multiplicative noises, additive noises and outliers. Furthermore, an outlier-resistant event-triggered mechanism is designed to prevent the transmission of unnecessary measurements and outliers. In order to guarantee the satisfactory filtering performance, this paper aims to design a recursive strong tracking filtering algorithm under the event-triggered mechanism, where an upper bound on the filtering error covariance matrix is obtained by solving a set of Riccati difference equations, and minimized to recursively compute the filter gain matrix. Finally, the effectiveness of the proposed algorithm is verified through carrying out two sets of simulations.