The “four pipelines” of thermal power plant have been operating under high temperature and high pressure for a long time. During the perennial operation of the unit, due to the existence of peak shaving and other power tasks, the pipelines of the “four pipelines” will creep and produce displacement. Hence, the monitor of pipelines is needed to ensure the safe operation of the unit. A non-contact online measurement system is advanced in this paper to improve the measurement accuracy and reduce the measurement time, so as to achieve the purpose of high-precision three-dimensional pipeline displacement real-time monitoring. The system used two cameras to capture the chessboard grid target fixed on the four pipelines, and the captured image is processed by deep learning neural network, so that the system could be used in the measurement of actual environment without the process of distortion and binocular correcting of cameras after calibration in the laboratory. While realizing the high-precision monitoring of the three-dimensional displacement of the four pipelines, the measurement operation was more concise and the degree of system intelligence is further improved. The experimental results showed that the standard deviation of the system is less than 0.24 mm, the displacement measurement error is less than 0.3%, and the single point measurement time is less than 0.1 s. It was a set of measurement system suitable for high-precision three-dimensional displacement real-time monitoring of four pipelines.