A pipeline vibration perception algorithm based on computer vision is proposed to solve pipeline damage or working fluid leakage at connecting flanges and valves due to a failure of timely warning induced by abnormal pipeline vibration in the production area of power plants. First, a convolutional neural network is used to estimate the optical flow information of the pipeline to be measured. Then, the information is analyzed to detect whether the pipeline vibrates or not. Finally, a vibration measurement module is employed to measure the vibration frequency and amplitude of the vibrating pipeline target in the monitor display for the perception of pipeline vibration. The experiments on the vibrating pipeline data taken by the original camera of a power plant show that the speed of the proposed method is about 4 f/s, and the measurement error of vibration frequency is less than 0.08. This method provides new ideas for computer vision technology to accomplish real-time pipeline vibration detection and measurement tasks without changing the original hardware devices of the power plants.