## 6 Conclusions  
This paper presents an analogical experimental study to assess the feasibility of using FRA technology to detect internal faults within rotating machines. The paper is also aimed at providing a better understanding of the effect of faults within IMs on the FRA signature as compared to the effect of faults within power transformers. Similar to its application in power transformers, results show the ability of FRA to detect SC and OC faults within the stator winding of the IM. However, the measured FRA reveal dissimilar patterns in the two studied cases. In general, the IM results show that there is a minor variation between the faulty and normal FRA signatures at the MF and HF regions due to turn-to-turn, turn-to-ground, and coil-to-ground faults. It also shows average deviations due to coil-to-coil SC fault at the MF and HF regions. A significant variation within the entire frequency range can be noticed in the case of phase-to-phase SC and OC faults for the star-connected IM. Unlike the star stator winding, delta winding shows an average variation at the MF and HF regions due to phase-to-phase SC fault. To avoid misinterpretation of the FAR results, this paper recommends the adoption of several statistical indicators such as CC, SD, ASLE, MSE, RMSE, DABS, Covariance and MM to quantify the variation between the measured FRA signatures. From the results, a boundary between normal and faulty cases is provided or limits were proposed for each fault. Further research is essential to extend the application of FRA to detect other types of faults within different ratings of IMs to set more accurate threshold limits for the impact of each fault type on various statistical indicators. Also, the application of FRA to other assets such as power cables can be elaborated upon.  
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Condition/Threshold** & **CC** & **ASLE** & **SD** & **MSE** & **DABS** & **RMSE** & **COVAR** & **MM** \\ \hline Normal transformer & **Above 94** & \textless{}1.54 & \textless{}1.65 & \textless{}2.74 & \textless{}1.48 & \textless{}1.65 & \textless{}0.53 & \textless{}1.12 \\ Normal IM & **Above 0.98** & \textless{}1.0 & \textless{}1.2 & \textless{}1.0 & \textless{}1.0 & \textless{}1.2 & \textless{}0.2 & \textless{}1.01 \\ \hline \hline \end{tabular}
\end{table}
Table 11: The proposed limits to determine the good condition of transformer and induction motors using FRA and statistical indicators.  
**Author Contributions:** Conceptualization, S.M.A.-A., M.F.M.Y. and A.A.-S.; methodology, S.M.A.-A., M.F.M.Y., Z.A.N. and A.A.A.; software, S.M.A.-A. and A.A.S.; validation, S.M.A.-A. and M.F.M.Y.; investigation, S.M.A.-A., M.F.M.Y. and Z.A.-M.; resources, S.M.A.-A. and M.F.M.Y.; writing--original draft preparation, S.M.A.-A. and M.F.M.Y.; writing review and editing, M.F.M.Y., Z.A.N., A.A.S., A.A.-S., M.I.M.; A.A.A. and Z.A.-M.; Project administration: M.F.M.Y., Z.A.N. and M.I.M. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the Ministry of Higher Education Malaysia under the Fundamental Research Grant Scheme Vot No (06E12, 4B482, 05G88, and 05G89). and The Islamic University, Najaf, Iraq.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement**: Informed consent was obtained from all subjects involved in the study.  
**Data Availability Statement:** The data presented in this study are available in this article.  
**Acknowledgments:** The authors gratefully acknowledge the Malaysia Ministry of Education and Universiti Teknologi Malaysia for funding this research with grant no 06E12, 4B482, 05G88, and 05G89. The authors would like to thank [PERSON] in TNBR Malaysia for his assistance during the experiment. We would also like to thank all the subjects who volunteered to participate in this study.  
**Conflicts of Interest**: The authors declare no conflict of interest.