## 4 Advanced Machinery Performance Monitoring
It was also noted that flood water can penetrate through non-watertight structures. They investigated a total of 2392 cases, and the results strongly indicate that the inverse method is applicable in determining a breach if the sensor arrangement is dense enough. The method could determine the floodwater origin accurately in 71.1% of the cases. The success rate of calculating the correct breach is presented in Figure 14. As seen, the average success rate of finding the primarily flooded room was 98.6%. Other research has focused on advanced ship systems and ship sensors' data collection for condition monitoring. Such research was conducted by [PERSON] et al. [89] and [PERSON] et al. [90]. [PERSON] et al. [89] investigated the Inspection Capabilities for Enhanced Ship Safety (INCASS) framework to bring an innovative solution for inspection and maintenance of ship structures and machinery. The INCASS framework consists of advanced structural risk assessment (SRA) and machinery risk assessment (MRA) tools. The results show that the INCASS framework has a reliable performance according to ship owners and operators. Furthermore, a follow-up study was presented by [PERSON] et al. [90] in the same year of 2016, where they reported that monitoring additional systems under actual operational situations would ensure safer operation and increased operational efficiency, including improved fuel efficiency and reduced emotions. Based on the implementation, sensors installed on a specific system allow for improving measurements and data collection and can be used further in analysis and assessment to enhance ship safety, maintenance, and performance and efficiency. Furthermore, research on robotic cleaning has also been increasingly discussed in maritime industries. [PERSON] [91] introduced the Fleet Cleaner robot, developed and deployed in the Netherlands. This remotely controlled robot is used for cleaning in ships, especially hull cleaning. The landmark research on the monitoring of advanced machinery performance is summarized in Table 4.  
Figure 14: The success rate of calculating the correct breach. (**a**) All doors closed and (**b**) fireproof doors open (redrawn based on data in [PERSON] and [PERSON] [88]). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Milestone** & **Author(s)** & **Observational Subject** & **Tools/Instrument** & **Important Remarks** \\ \hline
2007 & [PERSON] et al. [86] & Communication based & Wireless sensor network (WSN) & The wireless sensor  
In recent years, research focused on sensors for monitoring advanced machinery performance has been conducted by [PERSON] et al. (2020) and [PERSON] et al. (2020). [PERSON] et al. (2020) investigated the diagnosis of the coking of a marine diesel engine injector nozzle by performing a spectral analysis of the crankshaft's torsional vibrations. Laser heads clocked at 16 MHz were used for the measurements. The result showed that the data recorded from the 16-megahertz laser heads were satisfactory to determine the diesel-electric unit's shaft vibrations. It was also noted that it is possible to diagnose coking of a ship's diesel engine injection nozzle using spectral analysis of the shaft's torsional vibrations, as measured by optical sensors. The location of the ETNP-10 laser heads on both ends of the shaft can be seen in Figure 15. Recent ships are regularly provided with converters that utilize semiconductor power electronics devices such as thyristors or power transistors. Semiconductor power electronics attracted research such as that of [PERSON] et al. (2020), which aimed to detect early-stage damage. These semiconductor power electronics devices are mainly used in auxiliary padded drives and thrusters. [PERSON] et al. proposed a method for detecting early-stage damage of a gate turn-off thyristor using an acoustic emission sensor. The acoustic emission sensor and the thyristor packages are presented in Figure 16. The study showed that the acoustic emission sensor can detect waves from inside the semiconductor structure.