This study proposes an approach to determine the cyclic component of the time series of technical condition registration during the long-term operation of complex energy facilities and their bench tests by real-time means. The relevance of solving the specified scientific and applied problem is due to the need for current analysis of the technical condition of the specified facilities to establish the possibility of their operation according to the established resource, taking into account the cyclic (periodic, seasonal) component, the influence of which is an important factor in establishing the actual technical condition of the studied facilities. An analysis and comparison of methods for assessing the cyclic component of time series in terms of the possibility of their implementation by real-time means was performed using analytical justification and solving a test case, and analyzing real data during bench tests of a complex energy facility built based on a gas turbine engine. The hypothesis is proposed and confirmed that the dimension of the analysis window corresponds to the period of the specified component if the eigenvalues of the autocorrelation matrix of a time series are equal, which corresponds to the presence of a periodic component in its orthogonal distribution.The known method of estimating the cyclic component of measurement data, namely, the method of singular spectral analysis, provides the theoretically smallest mean square error of estimation, but has a significant computational complexity. We propose a method for estimating the cyclic component of real-time measurement data by non-recursive digital filtering based on a quadrature filter with weighted coefficients according to a certain dependence. A new modification of the method of singular spectral analysis of time series for estimating the cyclic component is proposed for the first time, allowing the development of high-precision real-time algorithms.