# Improved Temporal Fuzzy Reasoning Spiking Neural P Systems for Power System Fault Diagnosis
## 2 ITFRSNP System
### Fault Case Analysis
#### 4.1.4 More Cases
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**No.**} & \multirow{2}{*}{**Fault Descriptions**} & **Brief** & **Suspected** & **Sipke** & **Time-Point** & **Measured** & **Faulty** \\  & & **Descriptions** & **Computents** & **Values** & **Constraints** & **Values** & **Components** \\ \hline \multirow{6}{*}{14} & & L\({}_{1803}\)m(0), & L\({}_{0318}\) & 0.8562 & [\(-\)20, 10] & 0.8993 & \\  & & L\({}_{0318}\)m(2), & & & & & \\  & & CB\({}_{038}\)(30), & L\({}_{1718}\) & 0.5333 & \(\varnothing\) & 0.3733 & \multirow{2}{*}{\(\mathrm{L}_{0318}\)} \\  & & L\({}_{1718}\)(520), & & & & & \\  & & CB\({}_{1718}\) (541), & & & & & \\  & & CB\({}_{1727}\) (100), & & & & & \\  & & CB\({}_{1727}\) (135), & & & & & \\  & & CB\({}_{1716}\) (140), & & & & & \\ \hline \multirow{6}{*}{15} & & B\({}_{03}\)(0), & B\({}_{03}\) & 0.8549 & [\(-\)27, \(-\)10] & 0.8984 & \multirow{6}{*}{\(\mathrm{B}_{03}\)} \\  & & CB\({}_{0302}\)(29), & & & & & \\  & message of CB\({}_{0318}\) is missing. A & & CB\({}_{0304}\)(31), & & & & \\  & & fault occurs on B\({}_{03}\), but the & & & & & \\  & timestamp of CB\({}_{1445}\) is incorrect. & & CB\({}_{1440}\)(275), & & & & \\  & & CB\({}_{1415}\)(284), & & & & & \\  & & CB\({}_{1413}\)(385) & & & & & \\ \hline \multirow{6}{*}{16} & & A fault occurs on B\({}_{18}\), B\({}_{18}\) fails & L\({}_{0318}\)(50), & B\({}_{18}\) & 0.725 & [\(-\)534, \(-\)510] & 0.8075 & \multirow{6}{*}{\(\mathrm{B}_{18}\)} \\  & to operate, and remote backup & L\({}_{17178}\)(55), & L\({}_{0318}\) & 0.6583 & \(\varnothing\) & 0.4608 & \\ \cline{1-1}  & PRs operate. A fault occurs on & CB\({}_{0318}\)(32), & L\({}_{1718}\) & 0.5917 & [\(-\)20, 20] & 0.7142 & \multirow{2}{*}{\(\mathrm{T}_{1213}\)} \\ \cline{1-1}  & T\({}_{1213}\), and the alarm on B\({}_{11}\) is & CB\({}_{1718}\)(35) & & & & \\ \cline{1-1}  & missing; a fault occurs on L\({}_{0204}\). & & CB\({}_{1321}\)(50), & B\({}_{13}\) & 0.3306 & \(\varnothing\) & 0.2314 & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._It is found that the timestamp error of alarm messages (Cases 8 and 15) and adjacent component faults (Cases 13 and 14) affect temporal reasoning. The former is because the wrong time-point constraint cannot satisfy the time-distance constraint. The latter is because the CB time-point constraint cannot satisfy the time-distance constraints for all corresponding PRs. The proposed method can complete temporal reasoning by simultaneously performing reverse reasoning on the CBs and PRs. When the PR or CB in a subnet satisfies the temporal constraint, the temporal reasoning proceeds normally. Moreover, the merged reasoning between subnets can mutually verify whether the temporal reasoning results of the subnets are correct. Therefore, PR/CB maloperation/rejection, timestamp errors, and complex faults have little effect on the temporal reasoning of this method, and the accuracy and fault tolerance of the diagnosis results are not reduced. The fault diagnosis method based on the ITFRSNP system simultaneously accomplishes temporal and confidence reasoning. The results of temporal and confidence reasoning are quantized using the measurement function, and the results of confidence inference are corrected using temporal reasoning. The proposed method can diagnose faulty components and fault times with high accuracy and fault tolerance in complex fault scenarios, such as single faults, multiple faults, PR/CB rejection, missing alarm messages, and timestamp errors. The fault diagnosis model and reasoning method have good generality and can be applied to the fault diagnosis of buses, lines, and transformers.