# Improved Temporal Fuzzy Reasoning Spiking Neural P Systems for Power System Fault Diagnosis
## 2 ITFRSNP System
### Comparison Analysis with Other Methods
#### 4.3.2 Performance Comparison
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multirow{2}{*}{**Fault Diagnosis**} & \multirow{2}{*}{**Search Method for** **Suspected Faulty**} & \multirow{2}{*}{**Calculation Tasks**} & \multirow{2}{*}{**Calculation Methods and Calculation**} & \multirow{2}{*}{**Performance**} \\  & & & **Components** & & **Amounts** & \\ \hline \multirow{4}{*}{This study} & No need to build separate models & Search for suspected faulty components & Correlation reasoning between confidence degrees and temporal constraints & Matrix operation with a calculation amount of \(\mu\
u\) and the fault diagnosis model \\  & No need to adjust diagnosis models for topology changes & Search for suspected faulty components & Correlation reasoning between confidence degrees and temporal constraints & Multiple operation principles & Simple reasoning and calculation principles \\  & No need to adjust diagnosis models for topology changes & Search for suspected faulty components & Correlation reasoning between confidence degrees and temporal constraints & Multiple operation principles & Strong generality and adaptability of the fault diagnosis model \\  & Construction of the objective function & Search for suspected faulty components & Search for suspected faulty components & Multiple operation principles & Relatively slow convergence speed \\  & No need to adjust diagnosis models for suspected faulty suspected faulty components & Search the outage area to identify suspected faulty components & Search correlation, data operation with a calculation amount of \(2\mu\
u\) & High calculation complexity in the alarm message association and temporal matching process \\  & Individual construction of fault diagnosis models for suspected faulty components. & Search for the outage area to identify suspected faulty components & Search correlation, data transmission of alarm messages & Multiple operation principles & Multiple operation principles \\  & Need for reconstruction of models based on topology changes for fault diagnosis. & Search for suspected faulty components & Search correlation, data transmission of alarm messages & Multiple operation principles & Multiple operation principles \\  & & & & & \\ \hline \multirow{4}{*}{[21]} & \multirow{4}{*}{[22]} & \multirow{4}{*}{[22]} & \multirow{4}{*}{[23]} & \multirow{4}{*}{[24]} & \multirow{4}{*}{[24]} & \multirow{4}{*}{[24]} \\  & & & & & \\ \cline{1-1}  & & & & & \\ \cline{1-1}  & & & & & \\ \cline{1-1}  & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Performance comparison between the proposed method and existing methods. amount of computation and reduced fault efficiency. Moreover, when diagnosing multiple faults, only the outage area with complete boundary CB alarm messages can be correctly identified, and faulty components located in the unrecognized outage area are missed, thereby reducing the fault diagnosis accuracy. The proposed method suspected faulty components within the isolation range of tripped CBs based on the operation logic of the PRs and CBs. Compared with other methods, the search algorithm for suspected fault components in this study does not need to traverse the whole grid topology, thus enhancing search efficiency. Meanwhile, it can narrow down the diagnosis scope of a single fault without missing faulty components in multiple faults in the case of missing alarm messages of boundary CBs. In the case of rejections and missing/false alarm messages, this study combines confidence degrees and temporal constraints for fault diagnosis to reduce misdiagnoses and missed diagnoses. Owing to the different types and topologies of the components, it is necessary for [10; 20; 21; 22; 24] to build the corresponding fault diagnosis model for each component separately. The structure and parameters of the fault diagnosis model are reconstructed or adjusted according to topology changes.