## 4 Experimental Verification  
To validate the proposed ITF diagnosis method, experiments were conducted using a 12 kW, four-pole, three-phase IM with both Y and \(\Delta\) winding configurations. Figure 7a shows the manufactured machine. The stator windings were separated to allow for fault injection in each phase as shown in Figure 7b, and the winding connections were configured via a terminal box as shown in Figure 7a. A TELEDYNE oscilloscope (Teledyne Technologies, Thousand Oaks, CA, USA) was used to capture the current waveforms, while a control desk was employed to manage the inverter and IM operation. The inverter utilized in the experiments was equipped with an SPS600 GB10S6 dual-pack MOSFET module from SEMI POWEREX (Seattle, WA, USA). A digital signal processor (DSP), specifically the TMS320F28069, was employed to compute the \(\alpha\)- and \(\beta\)-axis current based on the measured three-phase currents, as shown in Figure 8a. The three-phase currents were digitized using an analog-to-digital converter (ADC), and the resulting \(\alpha\beta\)-axis currents were obtained through coordinate transformation on the DSP. The \(\alpha\)- and \(\beta\)-axis currents were converted to analog signals through a digital-to-analog converter (DAC) and monitored using the oscilloscope. The manufactured IM was coupled with a dynamometer to conduct the fault experiment during motor operation, as shown in Figure 8b. ITFs were implemented at the terminal box by connecting a fault resistance (TGHGCR0050 FE from OHMITE, Warrenville, IL, USA) in parallel with the fault phase of the IM. Although the nominal value of the fault resistor is 0.5 m\(\Omega\), the total resistance increased to approximately 3.5 m\(\Omega\) due to additional lead wire resistance. To activate the fault during motor operation, an electrical relay was connected in series with the fault resistance and the faulted phase winding, as illustrated in Figure 8c. Figure 8d presents the measured current waveforms before and after the fault through the electrical relay. The experimental parameters, including operating speed,  
Figure 6: ITF diagnosis based on the current vector pattern. switching frequency, and motor specifications, are shown in Table 3. The experiments were conducted under low-speed conditions, approximately 200 rpm, to guarantee safety. For each fault phase, the stator currents were measured using the current sensor and observed from the oscilloscope. The current vector patterns during the steady-state operation are illustrated in Figures 9 and 10 for Y and \(\Delta\) connections, respectively. Under healthy conditions, the current vector formed a nearly circle pattern as shown in Figures 9a and 10a. Upon implementing the faulty condition, the current vector pattern distorted into an ellipse, consistent with the FEA and simulation results, as illustrated in Figures 9b-d and 10b-d. The main axis of the ellipse varied with the faulted phase, demonstrating the algorithm's capability to distinguish not only between healthy and faulty conditions, but also to accurately identify the specific faulted phase. These results validate that the current vector pattern-based fault diagnosis method is effective across different winding configurations. Figure 8: Experiment environment: (**a**) inverter, control desk, and oscilloscope; (**b**) IM, terminal box, and winding; (**c**) fault resistance and relay; (**d**) current waveform. Figure 7: Manufactured machine: (**a**) IM and terminal box; (**b**) winding configuration. Figure 10: Experiment results of IM with Y connection: (**a**) health condition; (**b**) Phase A fault condition; (**c**) Phase B fault condition; (**d**) Phase C fault condition. \begin{table}
\begin{tabular}{c c c} \hline
**Content** & **Value** & **Unit** \\ \hline Operating speed & 200 & rpm \\ Switching frequency & 500 & Hz \\ Phase resistance & 11.5 & m\(\Omega\) \\ Phase inductance & 0.6 & mH \\ Fault resistance wo/w lead wire & 0.5/3.5 & m\(\Omega\) \\ \hline \end{tabular}
\end{table} 
Table 3: Experimental parameters.