## 3 Results
### System-Level vs. Component-Level Focus  
Component-level faults typically affect a single physical asset, such as bearing wear in a turbine or overheating in a PV module. In contrast, system-level faults involve interactions across multiple subsystems--for example, a sensor failure in a steam pressure unit leading to erroneous boiler control, which cascades into a turbine shutdown. These distinctions are essential when designing FDD systems with varying scopes and levels of abstraction.  
A large portion of articles focused on individual components (turbines, boilers, PV modules, etc.). Only 17.3% analyzed full-system faults.  
The scope of diagnostic analysis in the reviewed literature varies considerably in terms of the physical scale and subsystem targeted. This review categorized articles based on whether they addressed component-level issues--focusing on specific units such as turbines, boilers, or pumps--or system-level faults, which require a more holistic approach spanning multiple subsystems within the power plant.  
Out of the 185 articles analyzed, only 32 articles (17.3%) were classified as addressing full-system-level faults, while the remaining 82.7% focused on specific components or localized equipment. This distribution suggests that much of the research in this field is still constrained to modular or isolated diagnostics, likely due to the complexity and data requirements associated with full-plant modeling and simulation.  
The most frequently analyzed components included the following:* Steam turbines and drum-type boilers, often associated with temperature or pressure instability;
* Electrical converters and control units, where cyber-physical vulnerabilities and signal interference were focal points;
* Service water pumps and hydraulic subsystems, especially in safety-critical environments such as nuclear power stations;
* PV modules and heat exchangers, particularly in renewable or hybrid energy systems.  
While these component-level studies have yielded valuable insights and significant advancements in fault classification, their limited operational context often restricts the applicability of results to broader plant-level decision-making. Moreover, component-level approaches rarely consider fault propagation across interconnected systems, nor do they offer guidance on plant-wide optimization strategies.  
In contrast, system-level studies typically rely on integrated monitoring architectures, simulation-based validation (e.g., digital twins or multi-domain modeling), and require significantly more computational and infrastructural resources. These studies are more likely to propose hybrid diagnostic frameworks that combine model-based reasoning with real-time data streams, although such approaches remain the exception rather than the rule.  
As modern power plants adopt increasingly interconnected and dynamic configurations, the ability to perform cross-component diagnostics and fault propagation analysis will be essential. There is, thus, a pressing need for methodologies that scale beyond isolated components and enable comprehensive, plant-wide fault detection, localization, and intervention.  
Further comparison between representative studies, highlighting differences in pipeline completeness, validation, and algorithmic scope, is provided in Section 3.14.