Fatigue Estimation in Deepwater Risers Based on Wavelets and Second Order Blind Identification

Abstract

The safety of deepwater risers is essential for sustainable operation of offshore platforms. The structural health monitoring (SHM) system for deepwater risers is important to detect damage and perform repairs before failure occurs. Two main sources of damage are fatigue and corrosion. Failure of the riser would not only be an economical and environmental disaster, but also have far reaching consequences affecting communities. Combining global and local monitoring can greatly increase the accuracy of damage detection and fatigue estimation. Local inspection using robotic Magnetic Flux leakage (MFL) sensors is efficient and provides high resolution estimate of wall thickness changes due to corrosion or damage, while proposed vibration-based system identification can estimate global damage locations and fatigue life. A new SHM system for deepwater risers was recently developed to monitor damage to the risers with both global and local monitoring methods proposed in this paper. The global monitoring is achieved by wavelet transform (WT) and second order blind identification (SOBI) method, from which, the likely location of fatigue damage is estimated. Once the location of the damage is identified by the proposed Wavelets/SOBI global identification method, local monitoring is performed using a robotic crawler with MFL sensors to further estimate the extent of the damage. Local monitoring with MFL sensors is verified by experimental results. Wavelets/SOBI global identification method is verified using Gulfstream test data. Possible applications for the proposed SHM systems are for deepwater risers and deepwater platforms. A robotic MFL crawler can be used for in-line inspection for various pipelines. The proposed damage detection method and fatigue estimation can be adapted to other offshore structures, both fixed and floating. The proposed global method can also be used to analyze Tensioned Leg Platforms (TLP). To demonstrate the applicability of the proposed Wavelets/SOBI method to risers and floating platforms, verification using Gulfstream riser field data and TLP model data is presented in the paper.

Experimental study on bridge structural health monitoring using blind source separation method: arch bridge

“…The wavelet modified SOBI (Huang et al 2012) can be divided into four steps instead of three steps. Details are as follows (see Fig.…”

Seismic responses and vibration control of offshore wind turbines considering hydrodynamic effects based on underwater shaking table tests

“…Vibration control methods are divided into four types: passive, active, semi-active, and hybrid control. 30 Among the vibration control devices, 31 TMDs are widely used in civil engineering 32 and provide excellent wind-induced vibration control for high-rise buildings with great economy and efficiency. A variety of improved tuned devices have been developed: multiple tuned mass dampers (MTMD), tuned liquid dampers (TLD), pendulum tuned mass dampers (PTMD), and hybrid forms, etc.…”

“…Vibration control devices are required for OWTs with a high risk of seismic damage. Vibration control methods are divided into four types: passive, active, semi‐active, and hybrid control 30 . Among the vibration control devices, 31 TMDs are widely used in civil engineering 32 and provide excellent wind‐induced vibration control for high‐rise buildings with great economy and efficiency.…”

Output-Only Structural Health Monitoring for Deepwater Risers: Experimental Study of Wavelet Modified SOBI and Distributed Force Index Algorithm

“…The wavelet modified SOBI (WMSOBI) 16 can be divided into four steps instead of three steps. Details are as follows (see Figure 3):…”

“…In other words, curvature change based damage detection method cannot detect the damage location in this measurement setup. Further details on the curvature/DFC comparison can be found in Huang's thesis 16 . Similar results for single crack with damage level II and multiple cracks, as shown in Figure 8 and Figure 9, validate the effectiveness of the proposed DFC index methods.…”