# A Review on Vibration-Based Condition Monitoring of Rotating Machinery
## 2 Research Method
### Taxonomy
#### 2.2.1 Prospective Review  
For the prospective review, the papers are classified according to a double taxonomy:  
* The **phases** of the condition monitoring process mainly involved by the paper topic;
* The **components** of the machinery, mainly interested in the depicted monitoring techniques. In the classification by phases, five categories were identified:  
1. Signal type, sensors, pre-processing. This category collects methods and procedures that involve the early stages of the monitoring process, such as the definition of the most proper experimental setup, or  
Figure 1: Distribution of the identified products by type of document. The category “Other” combines four results for “Errata”, three for “Books”, and one product for “Editorial”, “Note”, and “Retracted”, respectively. Figure 2: Distribution of the identified products by publication year. For the two subsets “Conference Papers and Book Chapters” and “Articles and Reviews”; results are presented in stacked form. The black line depicts the cumulative number of published documents each year. the signal processing techniques required to read the raw data and prepare them for the application of feature extraction procedures. This class includes the choice or the development of sensors, their positioning strategies on the machine, and pre-filtering techniques on the acquired signals. * Features, signal processing. This category includes the methods for feature identification, extraction, and selection that are used in the second step of the monitoring process. Besides the most proper feature-related techniques, signal-processing methods can fall within this class, depending on the purpose of the user. For instance, statistical and frequency analysis techniques are classified in this category when used as a mean to highlight signal characteristics or compute quantities necessary for the following analysis steps. * Diagnostics. This category gathers algorithms and techniques used to actually discriminate whether or not the investigated system presents a healthy state. This class includes optimization strategies, techniques typical of the artificial intelligence field, as well as genetic algorithms-based solvers. * Modeling. This category collects the models developed or applied to study the investigated system from a methodological perspective. Those models could describe the physics of the overall system, for instance, presenting the equations that describe its dynamics, or focus on more detailed aspects of the process, such as models based on the finite element method (FEM) used to simulate vibration responses. The modeling category can therefore be considered associated to a preliminary phase of the pure condition monitoring process, since it provides the framework for the analysis, and the rationale for the interpretation of data and results. * Overview. This category includes comprehensive procedures that embrace more steps of the condition monitoring process, which compare more techniques and operative strategies, or that, in general, allow outlining an overview of the process or some phases. Therefore, unlike the previous classes, the overview category does not match a priori a single specific phase of the condition monitoring process. Condition monitoring techniques and methodologies are chosen and developed, depending on the characteristics and on the functioning of a specific component, more than on the final application field. According to this consideration, this review does not primarily focus on application fields, but the analysis grounds instead on the different machine components to which the condition monitoring is addressed, which are transversely widespread in different application fields. Eight categories were identified in the classification by components, representative of the intervention level, which is focused on the presented methods:  
* Bearings, also presenting the two subclasses:  
c6.a Blade; c6.b Drivertain; c6.c Generator. (c7) General/rotating machineries, indicating the application to the machine in general, as a whole.