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Abstract
During operations, vessels will experience rough weather conditions and therefore fatigue accumulation in the ship’s structure. To ensure the vessel’s reliability, calculations can be executed to determine actual loads on the hull, forecast maintenance needs and allow for rational decisions on lifetime extension when this becomes relevant.
This paper presents the setup of three types of monitoring schemes and shows the feasibility of a Virtual Hull Structure Monitoring (VHSM) system, which only considers publicly available data. In his paper, Stambaugh [1] emphasized differences in terms of cost and accuracy depending on the monitoring scheme used. The VHSM uses data from the Automatic Identification System (AIS) together with wave hindcasts to estimate the fatigue consumption. This system does not require any onboard sensors. However, AIS data has limited coverage, especially for military ships. Therefore, a minimal structural monitoring scheme has been defined as well. In this setup, a dedicated GPS system is used to monitor ship operations. A motion sensor is used to estimate wave characteristics from the ship motions. The results of these approaches are compared to data from a traditional Hull Structure Monitoring system. Data from strain gauges installed onboard a USCG cutter is used to quantify the fatigue accumulation at selected details on the ship.
Regarding the use of a true VHSM system, the lack of AIS data makes it hard to make a strong conclusion on the fatigue accumulation in the ship’s hull. However, this lack of data can be overcome through installation of a dedicated GPS unit. Fatigue assessments based on the combination of GPS measurements and hindcast data have shown good agreement with the fatigue accumulation obtained using the strain gauges. It has been observed that the hindcast models underestimates peak values of the significant wave height. Wave height estimates based on motion data outperform the hindcast models in such cases. A hybrid solution using hindcast data and motion measurements is therefore considered the best solution to obtain accurate wave data.
This paper shows the feasibility of structural monitoring of a ship using limited onboard instrumentation and indicates its accuracy. This allows operators to continuously assess seakeeping loads during operations for an entire class of vessels with limited instrumentation effort. The methodology can be further strengthened by including more extensive structural monitoring on a small number of vessels. This data can be used to estimate the effect of nonlinearities and other (unknown) features in the loads for the class of vessels.
This paper presents the setup of three types of monitoring schemes and shows the feasibility of a Virtual Hull Structure Monitoring (VHSM) system, which only considers publicly available data. In his paper, Stambaugh [1] emphasized differences in terms of cost and accuracy depending on the monitoring scheme used. The VHSM uses data from the Automatic Identification System (AIS) together with wave hindcasts to estimate the fatigue consumption. This system does not require any onboard sensors. However, AIS data has limited coverage, especially for military ships. Therefore, a minimal structural monitoring scheme has been defined as well. In this setup, a dedicated GPS system is used to monitor ship operations. A motion sensor is used to estimate wave characteristics from the ship motions. The results of these approaches are compared to data from a traditional Hull Structure Monitoring system. Data from strain gauges installed onboard a USCG cutter is used to quantify the fatigue accumulation at selected details on the ship.
Regarding the use of a true VHSM system, the lack of AIS data makes it hard to make a strong conclusion on the fatigue accumulation in the ship’s hull. However, this lack of data can be overcome through installation of a dedicated GPS unit. Fatigue assessments based on the combination of GPS measurements and hindcast data have shown good agreement with the fatigue accumulation obtained using the strain gauges. It has been observed that the hindcast models underestimates peak values of the significant wave height. Wave height estimates based on motion data outperform the hindcast models in such cases. A hybrid solution using hindcast data and motion measurements is therefore considered the best solution to obtain accurate wave data.
This paper shows the feasibility of structural monitoring of a ship using limited onboard instrumentation and indicates its accuracy. This allows operators to continuously assess seakeeping loads during operations for an entire class of vessels with limited instrumentation effort. The methodology can be further strengthened by including more extensive structural monitoring on a small number of vessels. This data can be used to estimate the effect of nonlinearities and other (unknown) features in the loads for the class of vessels.