A Modal Approach for Holistic Hull Structure Monitoring from Strain Gauges Measurements and Structural Analysis

Abstract

In this paper, a general method is presented which combines strain gauges’ data with 3D Finite Elements analysis of a hull structure, allowing the complete reconstruction of the structural response everywhere in the structure, based on the measurements from only a few sensors. By using sensors, one is getting rid of all the usual assumptions on wave loads and structural response which are made in standard desktop analyses. Usually, the main drawback of using sensors is that only a limited number of them can be used so in most current implementations, the structural response is only monitored in a few selected areas. The new method developed here allows to rebuild the response everywhere from just a few sensors measurements. The method is based on earlier works using a conversion matrix approach and a linear decomposition of the structural response on a base of a few modes. The measured time series at the strain gauges are then used to reconstruct the linear combination of modal responses which gives at those locations the same values on the 3D FE model as measured. The modes are defined as the response of the structure on selected load cases and a specific methodology is developed for the selection of those modes since their selection is fully dependent on the number and location of the strain gauges in the hull. The method is also used to automatically derive an optimized strain gauges’ setup by looking at correlations between strain gauges’ measurements in numerical simulations. The method is validated numerically by simulating measurements in an analysis and using them to reconstruct the complete response. Then actual strain gauges’ measurements on a hull are used to validate the method on a real case. Both fatigue damages and extreme stress values are compared, and it is found that on a real case, the fatigue damage and extreme stresses can be predicted with good accuracy in most of the hull structure based on less than 8 strain gauges’ measurements. From that new insight, an optimized inspection and maintenance plan can be developed and updated throughout the life of the structure, leading to safer and more cost-effective operations. Another key benefit to operators is the possibility to keep track of the remaining life of the structure and being able to demonstrate it, which is crucial when it comes to selling or redeploying an asset. The method has been used by DNV on commercial projects for various offshore structures including flare towers, MOPU platforms and sloating structures.

A Framework for Optimal Sensor Placement to Support Structural Health Monitoring

“…This inverse prediction capability is also pertinent in the development of digital-twin-based monitoring. As demonstrated by [24], digital-twin-based monitoring can be implemented with the aid of a selection of structural response measurements and an inverse problem solver so that holistic structural monitoring can be achieved. In either case, the accuracy of the inverse prediction is dependent on the number of sensors [25].…”