The gearbox option is a critical issue that needs to be addressed for the choice of the drivetrain configuration due to its longest downtime per failure among all drivetrain components of TCECs. Evidence of these potentially high failure rates highlights the need for adopting the most resilient drivetrain options with a high degree of maintainability. While many drivetrain designs and configurations of TCECs inherit from those of wind turbines, different operational constraints, e.g., high-torque and low-speed conditions, make TCECs potentially suffer from high failure rates in harsh deep-sea environments. Currently, the development of commercial projects using TCECs is still in the demonstration phase. This paper presents a review-based comparative study of state-of-the-art technologies, technical challenges and research barriers, and development trends of gearboxes used in tidal current energy converters (TCECs). Experimental results show that the proposed system can reliably detect tool conditions in drilling operations in real time and is viable for industrial applications. The monitoring system can detect tool breakage and tool wear conditions using very simple current sensors. Finally, the two methods above are integrated to establish an intelligent tool condition monitoring system for drilling operations. Subsequently, fuzzy classification methods are used to detect tool wear states based on the above models. Next, the models of the relationships between the current signals and the cutting parameters are established under different tool wear states. First, continuous and discrete wavelet transforms are used to decompose the spindle and feed ac servo motor current signals to extract signal features so as to detect the breakage of drills successfully. Wavelet transforms and fuzzy techniques are used to monitor tool breakage and wear conditions in real time according to the measured spindle and feed motor currents, respectively.
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