Load Identification of Offshore Platform for Fatigue Life Estimation

The lifetime of an offshore platform is typically governed by accumulated fatigue damage. Thus, the load time history is an essential parameter for prediction of the lifetime of the structure and its components. Consequently, monitoring of structural loads is of special importance in relation to re-assessment of offshore platforms. Structural monitoring systems (SMS’s) on offshore structures typically consist of a set of sensors such as strain gauges, accelerometers, wave radars and GPS’s, however direct measuring of the actual loading is usually not feasible. One approach is to measure the loads indirectly by monitoring of the available dynamic responses of the structure. This work investigates the possibility for using an economically beneficial, model-based load estimation algorithm for indirect measuring of the loading forces acting on the offshore structure. The algorithm is based on the reduced order model of the structure and the discrete Kalman filter which recursively estimates unknown states of the system in real time. As a test-case, the algorithm is designed to estimate the equivalent total loading forces of the structure. The loads are estimated from noised displacement measurements of a single location on the topside of the offshore structure. The method is validated using simulated data for two wave loading cases: regular and irregular wave loadings.

[1]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[2]  Y. Chan,et al.  A Kalman Filter Based Tracking Scheme with Input Estimation , 1979, IEEE Transactions on Aerospace and Electronic Systems.

[3]  J. A. Fabunmi,et al.  Effects of structural modes on vibratory force determination by the pseudoinverse technique , 1986 .

[4]  G. M. L. Gladwell,et al.  Inverse Problems in Vibration , 1986 .

[5]  P. Bogler.  Tracking a Maneuvering Target Using Input Estimation , 1987, IEEE Transactions on Aerospace and Electronic Systems.

[6]  M. Hou,et al.  Comments on "Tracking a maneuvering target using input estimation , 1989 .

[7]  Lewis Zion,et al.  Predicting Fatigue Loads Using Regression Diagnostics , 1994 .

[8]  Li-Wei Fong,et al.  AN INPUT ESTIMATION APPROACH TO ON-LINE TWO-DIMENSIONAL INVERSE HEAT CONDUCTION PROBLEMS , 1996 .

[9]  Pär Johannesson,et al.  Rainflow Analysis of Switching Markov Loads , 1999 .

[10]  Daniel C. Kammer,et al.  Input force estimation using an inverse structural filter , 1999 .

[11]  E. Parloo,et al.  Force identification by means of in-operation modal models , 2002 .

[12]  Lars J.L. Nordström,et al.  A CRITICAL COMPARISON OF TIME DOMAIN LOAD IDENTIFICATION METHODS , 2002 .

[13]  T. Uhl,et al.  Intelligent Transducers of In-Operational Loads in Construction Fatigue Monitoring , 2002 .

[14]  Tadeusz Uhl,et al.  Identification of operational loading forces for mechanical structures , 2003 .

[15]  L. Nordström,et al.  A dynamic programming algorithm for input estimation on linear time-variant systems , 2005 .

[16]  E. Parloo,et al.  On-line identification of operational loads using exogenous inputs , 2005 .

[17]  D. Simon.  Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches , 2006 .

[18]  Dan Simon,et al.  Optimal State Estimation: Kalman, H∞, and Nonlinear Approaches , 2006 .

[19]  Claus-Peter Fritzen,et al.  An Updated Comparison of the Force Reconstruction Methods , 2007 .

[20]  Tadeusz Uhl,et al.  The inverse identification problem and its technical application , 2007 .

[21]  Ahsan Kareem,et al.  Estimation of modal loads using structural response , 2009 .

[22]  Geert Lombaert,et al.  An augmented Kalman filter for force identification in structural dynamics , 2012 .

[23]  Poul Henning Kirkegaard,et al.  Gearbox Fatigue Load Estimation for Condition Monitoring of Wind Turbines , 2012 .

[24]  Poul Henning Kirkegaard,et al.  Low-Cost Tower Root Fatigue Load Estimation for Structural Health Monitoring of Grouted Connections in Offshore Wind Turbines , 2013 .

[25]  Nevena Perisic.  System Identification of Wind Turbines for Structural Health Monitoring , 2014 .