In this paper a basic idea of a fault-tolerant monitoring and decision support system will be explained. Fault detection is an important part of the fault-tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault detection will be presented for a containership with a real decision support system onboard. All possible faults can be simulated and detected using residuals and the generalized likelihood ratio (GLR) algorithm. INTRODUCTIONThe SeaSense system (Nielsen et al., 2006) has been installed on several containerships and navy vessels. The system provides an estimation of the actual sea state, information about the longitudinal hull-girder loading, seakeeping performance of the ship, and decision support on how to operate the ship within acceptable limits. It is able to identify critical forthcoming events and to give advice regarding speed and course changes to decrease the wave-induced loads. The system, sketched in Figure 1, includes a number of sensors all of which are used to estimate hull girder responses and predict wave loads, with the purpose of avoiding critical levels of hull stresses and ship motion(s). In this paper, it is suggested to improve the system by converting the system into a faulttolerant monitoring and decision support system. All the changes are on the software side, but the hardware remains the same. The wave elevation could be obtained using SeaSense system by combining the relative wave height and the vertical acceleration. The wave elevation has been -artificiallyincluded in the sensor fault detection procedure as a virtual (non-existent) sensor. The sensor fault detection is performed using several measurements: vertical acceleration, heave, pitch,

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Abstract. Fault detection and isolation are very important elements in the design of faulttolerant decision support systems for ship operator guidance. This study outlines remedies that can be applied for fault diagnosis, when the ship responses are assumed to be linear in the wave excitation. A novel numerical procedure is described for the calculation of residuals using the ship's transfer functions which correlate the wave excitation and the ship responses. As tests, multiplicative faults have artificially been imposed to full-scale motion measurements and it is shown that the developed model is able to detect and isolate all faults.

In this paper a new approach for increasing the overall reliability of a monitoring and decision support system will be explained. The focus is on systems used for ship operator guidance with respect to, say, speed and heading. The basic idea is to convert the given system into a fault tolerant system and to improve multi-sensor data fusion for the particular system. Fault isolation is an important part of the fault tolerant design for in-service monitoring and decision support systems for ships. In the paper, a virtual example of fault isolation will be presented. Several possible faults will be simulated and isolated using residuals and the generalized likelihood ratio (GLR) algorithm. It will be demonstrated that the approach can be used to increase accuracy of sea state estimations employing sensor fusion quality test.

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