An Online Pipeline Structural Health Monitoring Method Based on the Spatial Deformation Fitting

Abstract

In pipeline maintenance, the advent of cloud computing and Internet of Things technologies enable effective pipeline management. Practically, it is impossible to provide fast-response, full-scale, multiterrain, and spatial-level monitoring of pipelines by sparse sensors. In this article, a fitting method for online pipeline structural health monitoring (SHM) is presented. The contribution includes three aspects. First, a new pipeline SHM method based on spatial deformation fitting is proposed, which is useful for three-dimensional full-scale assessment and multiterrain applications with the sparse sensor array. There are no strict restrictions on the number and arrangement of sensors, and no finite-element-model prior information is needed. The monitoring results can be delivered to multiterminals. Second, a rational cubic spline-based fitting algorithm mainly implemented by cloud computing is provided for rapid response. It features three-time interpolation fitting and one-time coordinate transformation. The value correspondence between the measured attitude angles and the fitted deformation is dexterously established. The fitted curve is locally adjustable. Third, the fitting error on deformation is analyzed, and the effectiveness of the method is tested and verified. Reasonable parameter values for the sensor quantity and the fitting spline are suggested.