## 1 Introduction  
Wind energy in recent years has gained popularity because of low life cycle emissions and efforts to reduce costs. From a business perspective, the cumulative installed wind energy capacity globally is anticipated to reach 817 GW in 2021, where Asia will be leading with an installed capacity of 153.5 GW in the years 2017 to 2021, as reported by the Global Wind Energy Council (GWEC) [1]. Due to technology maturity, an exponential increase in wind turbine (WT) installation has been recorded. Due to the significant rise in turbine installation, condition monitoring activities have become more challenging, which causes a substantial increase in operation and maintenance (O&M) costs. Therefore, many research activities are focusing on using advanced technologies to improve turbines' expensive components' life expectancy as well as minimising O&M costs. In addition to this, offshore wind farms (WFs) are generally situated in distant areas subject to harsh operating environmental conditions, which make offshore accessibility challenging and costly due to logistic and transport issues unlike onshore. A recent study [2] found that their O&M costs were estimated to account for 25-30% of the life cycle costs of an offshore WF. O&M visits make use of specialised vessels or helicopters for planned and unplanned repair activities. The O&M costs increase due to the higher incidence of failures that cause underperformance, high downtime and low availability. Furthermore, unscheduled maintenance occurs due to unexpected failures and affects the weather window; these need to be identified as quickly as possible to prevent critical damage and improve availability. All these factors together cause performance deterioration and significant loss in revenue that strongly affects the net economic value of the offshore WF [3]. Thus, WF developers and operators are continuously seeking cost-effective strategies to minimise O&M costs, improve performance, and maintain wind power availability while increasing at the same time, the return on their investment. According to recent statistics, it is estimated that the global business for WF O&M is expected to expand by up to $ 27,400 USD million by 2025 [4], supported by data-driven technologies. This, therefore, outlines the importance of the O&M sector concerning the technical and commercial aspects for offshore WFs. Condition monitoring (CM) is a process that has been widely used to monitor the operational status of machines in order to detect potential anomalies at an early stage to prevent catastrophic damage and to improve performance [5]. Three maintenance strategies are in use by the wind industry; these are reactive maintenance, corrective maintenance (run-to-failure) and preventive maintenance [5,6]. Preventive maintenance can be scheduled or condition-based, depending upon the problems. System physics-based techniques (e.g., oil debris analysis, vibration signal analysis) based on O&M activities consist of consolidation of run-to-failure and scheduled maintenance operations. Still, these techniques are costly as they cause significant downtime as well as a premature replacement of components. That is why O&M strategy is shifting from corrective and scheduled towards condition-based maintenance [6]. Predictive (condition-based) maintenance of the machine can be undertaken on a continuous basis without disrupting power generation, as well as being useful in determining the optimum point between corrective and scheduled maintenance. This improves maintenance activities and reduces unplanned downtime [7,8]. Within this framework, a condition-based maintenance approach is found to be cost-effective in improving reliability and reducing downtime [9,10], while minimising O&M costs [11,12]. As already stated, CM is an integral part of O&M that covers the essential activities associated with O&M at the different stages of WTs' operation.