Abstract
This paper provides an analytical proof and the theoretical development of the idea of using the torsional vibration measurements for a system-level condition monitoring of the drivetrain system. The method relies on modal parameter estimation of the drivetrain system by using the torsional measurements and subsequent monitoring of the variations in the system eigenfrequencies and normal modes. Angular velocity error function extracted from encoder outputs at both input and output of drivetrain is used to estimate modal parameters including natural frequencies and damping coefficients. In the proposed condition monitoring approach, it is shown that any abnormal deviation from the reference values of the drivetrain system dynamic properties can be translated into the progression of a specific fault in the system. In order to extract the condition monitoring features, local sensitivity analysis is engaged to establish a relationship between different categories of drivetrain faults with the system dynamic properties and the amplitude of torsional response, which helps with both to identify the state of the progressive faults and to localize them. Local sensitive analysis shows that abnormal deviations in stiffness and moment of inertia due to the presence of faults result in considerable changes in natural frequencies and modal responses which can be measured and used as fault detecting features by using the proposed analytical approach. Sensitivity analysis is also employed along with the estimated modal frequency for estimation of modal damping from the amplitude of response at the natural frequencies and their subsequent use for estimation of undamped natural frequencies which are later used in the proposed condition monitoring approach. The proposed approach is computationally inexpensive and can be implemented without additional instrumentation. Two test cases, using 10 MW simulated and 1.75 MW operational drivetrains have been demonstrated.
Highlights
Both predictive and condition-based maintenances are proposed in the literature as potential game changers and measures which could be taken to flatten the gap between OPEX in offshore and land-based wind turbines aimed at realizingF.K
Estimation of mechanical systems dynamical characteristics is mainly based on operational modal analysis (OMA) which is challenging for drivetrain as a complex dynamical system
If we apply the results of analytical sensitivity analysis of drivetrain dynamic properties as the function of equivalent model parameters, which are based on 10 MW drivetrain model, to 1.75 MW model, the 3% reduction of first natural frequency in general could happen due to either 6% reduction in the main shaft stiffness or 6% increase in the gearbox inertia
Summary
The EU 2050 plan by reduction of downtime and subsequently levelized cost of energy (LCOE) of offshore wind [1]. As the second step of this research, the analytical relationship between the 3-DOF equivalent model parameters and drivetrain dynamic properties is established, which helps to identify the drivetrain system condition/state-of-operation by monitoring the variations in the drivetrain dynamic properties (undamped natural frequencies and normal modes) which can be estimated from the operational measurements by using the proposed modal estimation approach or the other approaches proposed by the literature. By the increase of the order of equivalent model, more dynamic properties (higher natural frequencies which are not seen by 3-DOF model) can be employed, which can support a more detailed fault detection in the drivetrain It is a little challenging for currently available modal estimation approaches to observe higher modes which appear with a low amplitude in the frequency-domain response.
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