Detection of oscillation is a necessary step for determining valve stiction, which is a common problem in process industries. More specifically, many stiction detection methods assume persistency of the oscillation pattern in the control loop signals, which is a necessary condition to achieve reliable detection results. However, the existing oscillation detection methods do not study the persistency of the oscillation patterns directly. Instead, these methods try to discover the presence of specific periodic characteristics in the signals, their autocorrelation, or power-spectrum. This paper aims to propose an oscillation detection method that directly evaluates the similarity of the shapes of subsequent oscillation periods by means of correlation coefficient. The proposed oscillation detection method is compared against five other methods reported in the literature. Furthermore, the stiction detection methods assuming oscillation in control loops have different robustness to the disturbances corrupting the analyzed signals. In order to prepare a basis for selecting the right stiction detection methods for the available data automatically, the paper introduces two indexes quantifying mean-nonstationarity and presence of noise in oscillating signals.