# On the Fault Detection and Diagnosis of Railway Switch and Crossing Systems: An Overview
## 3 FDD of Railway S&C Systems
### Data-Driven FDD Methods for Railway S&C Systems
#### 3.2.3 FP Methods
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Approach** & **Application** & **Method(s) Used** & **Signals (Sensors)** & **Faults Type(s)** \\  & & & **Acquired** & **Considered** \\ \hline \multirow{8}{*}{FD methods [10; 74; 75; 76]} & & Voltage [74; 76]; force [74; 76]; current & Slide chair-related faults (i.e., dry, contaminated, excessive friction or resistance) [74; 75; 76]; faults (only \\  & & & **Vultage** [74; 76]; force [74; 76]; current [74; 76]; current [75]; speed [76]; linear position of the switch [76]. \\  & & & **Vultage** [74; 76]; force [74; 76]; current [  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Approach** & **Application** & **Method(s) Used** & \ \begin{tabular}{c} **Signals (Sensors)** \\ **Acquired** \\ \end{tabular}  & \begin{tabular}{c} **Faults Type(s)** \\ **Considered** \\ \end{tabular}  \\ \hline FD methods [86, 87, 88, 89, 88, 89, 88, 89, 88, 89, 88, 89, 88, 89, 89, 88, 89, 89, 89, 89, 89, 89, 89, 89, 89, 8  
More recently, other two PHM methods for railway S&C systems were proposed in [130; 131]. The proposed PHM method in [130] was focused only on predicting the RUL of the slide chair. Failure degradation of the sliding chair was simulated by accelerated aging of a real system, and field data were collected. The force sensor was considered (for resistive force measurements) and was installed on an electromechanical point machine. For the PHM algorithm, different health indicators (HIs) were extracted and selected first--for the selection procedure, two steps were considered: the first was intraclass analysis, in which all HIs with a higher monotonicity value were selected; the second was interclass analysis, where a similarity matrix was constructed from the HIs selected (in the first step) using the Euclidean distance--then a \(k\)-means clustering method was applied for FD. Finally, a degradation model for failure prognosis was built using a double exponential function. The proposed PHM method could predict the RUL with acceptable precision because \(k\)-means could only detect bigger changes in the slide chair health conditions and were less sensitive to smaller changes, which caused late RUL predictions. [PERSON] et al. [131] developed a FP technique that used the maximal overlap discrete wavelet packet transform (MODWPT) and Shannon entropy (SE) to extract the spectral features. Then, the Lasso (Least absolute shrinkage and selection operator) regularization was used for selection. The extracted and selected features were fused with some system time domain information to predict the lifetime of crossing, where the RUL was prognosed by a linear degradation stochastic model with recursive Bayesian update to optimize the scheduled inspections for the common crossings. The authors concluded that their method has shown good quality of prognosis results, but need a high number of measurements. A summary of all reviewed FDD methods for railway S&C systems and a list of all reviewed CM papers, with their application, method(s) used, signal(s) acquired, and fault type(s) considered, is presented in Table 2.  
From the summary of all reviewed papers in the field of FDD methods for railway S&C systems shown in Table 2, the shortage of research works applying model-based approaches compared to data-driven approaches for railway S&C system health conditions is clear. A quantitative summary of these reviewed articles in the field of FDD for railway S&C systems is shown in Figure 18. It shows an opportunity for researchers in this field to perform more research works in future that apply model-based techniques to deal with FD, FDD, and/or FP of the different possible fault modes in railway S&C systems. Figure 18: Quantitative summary of the approach used in the reviewed articles in the field of FDD for railway S&C systems: (**a**) model-based, (**b**) data-driven. Although several fault scenarios have been considered, almost all are related to wear-induced faults (i.e., slide chair-related faults and/or switch-related faults).