Intelligent detection method for singular point characteristics of fluid conveying pipeline

The invention discloses an intelligent detection method for singular point features of a flow conveying pipeline, and the method comprises the following steps: firstly, forming a background parameter set; secondly, installing a vibration wave parameter test micro-nano device to each node position of the to-be-tested fluid conveying pipeline, and collecting pipeline global information transmitted between any two nodes on the to-be-tested fluid conveying pipeline through the vibration wave parameter test micro-nano device; and setting a pipeline singular point fracture threshold value. According to the method, the physical characteristic that water hammer vibration waves are transmitted along a pipeline line at the moment in the running process of a fluid conveying pipeline is utilized, vibration wave transmission parameters are tested at adjacent detection nodes, and on-chip integration is achieved through a vibration wave sensor and machine learning algorithm firmware; the flow conveying pipeline material change singular point, the pipe circumference contact boundary change and the like are obtained from the vibration wave transmission parameter set based on the modes of deep learning, data fusion and the like, and pre-judgment and fixed-point maintenance are actively achieved before the flow conveying pipeline singular point fracture threshold value is achieved. And constructing a novel intelligent detection method of the fluid conveying pipeline and optimizing fluid loss control.