# Improved Temporal Fuzzy Reasoning Spiking Neural P Systems for Power System Fault Diagnosis
## 2 ITFRSNP System
### Fault Case Analysis
#### 4.1.4 More Cases  
More fault cases are presented to demonstrate the accuracy and fault tolerance of the proposed method, and the fault diagnosis results are presented in Table 2. Since the reasoning processes in these cases are consistent with the above cases, their specific reasoning processes are not provided. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
Cases 4 and 5 are based on Case 1, simulating the missing alarm message and rejection of CBs. Although the number of suspected faulty components and spike values of non-faulty components increased, the proposed method still accurately diagnoses the faulty bus. Cases 6 and 7 are bus faults with missing alarm messages and rejection of the bus PR. If the spike value is the diagnosis basis and its threshold is set to 0.6, B\({}_{03}\) will be diagnosed as a non-faulty component in Case 6, and the lines adjacent to B\({}_{03}\) will be misdiagnosed as fault components in Case 7. Because the bus PR is related to multiple CBs and remote backup PRs, the missing alarm message and maloperation of the bus PR significantly affect the diagnosis results of the faulty bus and adjacent non-faulty components. In this case, the proposed method can still diagnose a faulty bus without missed diagnosis and misdiagnosis. In Case 9, the CB refused to operate, the main PR alarm message was lost, and the spike values of L\({}_{1718}\) and B\({}_{18}\) are 0.5333 and 0.6, respectively, which are close to the threshold. Because the fault times of L\({}_{1718}\) and B\({}_{18}\) cannot be inferred, L\({}_{1718}\) and B\({}_{18}\) are independent of the operating PR and CB and are not faulty components. The main PR configuration of the transformer is similar to that of the bus, whereas that of the remote backup PR configuration is similar to that of the line. Therefore, when the CB alarm message is lost (Case 11), the diagnosis results of the suspected faulty components are similar to those in Case 4 (bus fault with a missing CB alarm message). When the CB refuses to operate, and the backup PR is initiated (Case 12), the diagnosis results of the suspected faulty components are similar to those in Case 12 (line fault with CB rejection). Cases 8-12 prove that the proposed method can accurately diagnose faulty lines and transformers in complex fault scenarios. Compared with the single faults in the above fault cases, the adjacent faulty components in the double faults (Cases 13-16) have a greater impact on the non-faulty components. For example, the confidence degrees of B\({}_{18}\) in Case 13, L\({}_{1718}\) in Case 14, and L\({}_{0318}\) and L\({}_{1718}\) in Case 16 are close to or even exceeded the threshold. In Case 16, because the main PR of the transformer is associated with multiple CBs, the loss of the main PR alarm message causes the spike value of the faulty transformer to be lower than 0.6. The diagnosis results of Cases 12-16 are still accurate because of the measured values as the diagnosis basis, which proves that the proposed method still has high accuracy and fault tolerance for double faults.