Vortex shedding is historically a concern among tall tubular pole structures, whose geometric characteristics present an ideal scenario for the phenomenon to occur. Vortex shedding leads to amplified vibration responses that may lead to structural fatigue damage under constant cyclic loading for the duration of a wind event. This potentially long and frequent duration of cyclic loading can ultimately cause catastrophic failure of the structure well before it reaches the end of its design life. Various mitigation techniques can be used to prevent such failures, so detection of this behavior would be advantageous in preserving the health of the structure. Detection of vortex shedding is defined by two components: wind direction and the primary direction of motion of a structure at a particular modal frequency. Vortex shedding is present if the amplified vibration response can be characterized and is determined to be perpendicular to the wind direction. This chapter presents a study that explored the development and application of an algorithm to efficiently characterize the independent directions of the amplified vibration responses of a pole structure and compares these to the wind direction for a particular time period of interest. The motion of the structure can vary significantly over a period of time, even when wind speed and direction are constant. The algorithm considers this and produces a quantitative confidence value providing insight on the presence of vortex shedding. Further data analysis can utilize this value and correlate it with wind speed data to ultimately predict if vortex shedding is likely to occur in a future wind event. An existing tubular pole structure was equipped with a structural health monitoring system capable of measuring accelerations and lateral displacements at the top of the pole for this study. This pole structure historically had visible amplified vibrations under wind loads which made the dataset promising for the development of the vortex shedding detection algorithm. The pole was not equipped with an anemometer; therefore, data from a nearby weather station was collected to provide the required wind parameters needed for the analysis. This chapter describes the structural health monitoring system, the data collection and analysis, and the development and implementation of the vortex shedding algorithm. The implemented algorithm was able to automatically detect vortex shedding activity with good confidence.