ReviewA review of current issues of marine current turbine blade fault detection
Introduction
The oceans, which account for 70% of the Earth's surface, contain abundant energy (Cheng et al., 2018). With the depletion of oil resources, many countries worldwide have turned their attention to new sources for clean, pollution-free new energy. According to BP World Energy Outlook 2018, global energy demand growth will slow down in 2018–2040, and renewable energy should rapidly develop, increasing by about 33% by 2040 (Launch). Table 1 gives an estimate of the potential marine energy worldwide (Chen et al., 2018a).
As one of the new electrical energy power generation technologies, MCTs have attracted worldwide attention (Khalil et al., 2018; Lee, 2020). Different reviews that consider the design of MCT have been recently published (Chen and Lam, 2015; Rodrigo et al., 2018; Ke et al., 2020a). Specific reviews on fault detection, however, have not yet explicitly been published. Although the maritime domain contains endless renewable energy, wave, and turbulence conditions inevitably disturb turbine operations. Shear flow is one of the triggers for MCT hydro-dynamic asymmetry (Ke et al., 2020b). Meanwhile, the growth of marine organisms or marine pollutants may also cause mechanical faults in blades, and which consequently generate damages to other components of the MCT, such as generators (Whitby and Galde-Loo, 2014; Duhaney and Khoshgoftaar, 2010, 2012; Hu and Du, 2012; Mjit et al., 2011a), bearing (Waters et al., 2012, 2013), and winding's insulation systems (Wang et al., 2019; Liu et al., 2016). Blade faults have a crucial impact on the safety and reliability of MCT systems (Amir Hossein and Bibeau, 2016; Mohammad and Bibeau, 2020; Rosli, 2020; Zhang et al., 2014). Alternatively, blade fault detection approaches have been widely applied to gas turbines or wind turbines (WTs).
This paper aims to analyze the impact of blade faults and discuss open research issues related to MCT blade fault detection. Fault detection techniques are reviewed from sensor and signal-based perspectives. We survey fault detection methods based on used measurements and the different techniques used so far. The rest of the paper is organized as follows. Section 2 describes the root causes of blade fault and models resultant torque imbalance. In Section 3, the blade fault detection methods are reviewed based on whether they use specific sensors or embedded electrical measurements (i.e., phase currents or voltages). Section 4 concludes the paper and draws some perspectives for future works.
Section snippets
Effects of the environment on the blades
The MCT is installed undersea and therefore operates in harsh conditions (seawater corrosion, mud, plankton, biofouling, etc.) with variable environmental parameters such as sudden changes in instantaneous flow velocity (Chen et al., 2012). These harsh working conditions (Malki et al., 2013) favour the appearance of faults or failures.
Specific sensor-based fault detection methods
In the case of an MCT, one should implement appropriate sensors to monitor the blade condition: this includes pressure sensors (i.e., to evaluate vessel integrity and inspect the surface of the blade), tachometers (i.e., to measure the rotational velocity of the blades), temperature sensors (i.e., to evaluate if internal blades are overheating compared with other components), and strain gauges (i.e., to control if the blades are deformed, for example attached by plankton) (Edwards et al., 2011;
Perspectives
Table 7 provides a comprehensive comparison of MCT blade fault detection techniques. Their characteristics such as intrusive, complexity and maintenance are respectively addressed, and we suggest the following four directions for future research work:
- a)
A fault model of unstable conditions such as surge and turbulence should be established. As mentioned before, the frequent occurrence of waves and turbulence causes blade faults. This happens randomly and leads to non-linear behavior and
Conclusion
The objective of this paper was to give an overview of the existing methods and techniques used for MCT blade fault detection. The methods have been classified depending on whether the measures are collected using specific sensors (e.g., accelerometers, cameras, temperature) or the built-in generator phase currents sensors. It appears that specific sensor-based methods suitable for fault detection of WTs blades are not necessarily suitable for MCTs. Given similar MCT and WT, the Pros & Cons for
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
This research is supported by the National Natural Science Foundation of China (61673260).
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