# A Method for Broken Rotor Bars Diagnosis Based on Sum-Of-Squares of Current Signals
## 4 Experimental Validation and Discussion
### Results and Discussion
#### 4.2.3 The Effectiveness of the SS Method  
First, the experimental data of different health conditions, collected under the full load level, are analyzed by the SS method. The SS signals are calculated and are shown in Figure 4. There is no significant difference between the healthy motor and the faulty motor in the SS time-domain signals. The FFT is used to analyze SS signals, and the spectra of SS signals are also shown in Figure 4. By comparing the spectra of the SS signals of the healthy motor and faulty motor, it can be seen that the signature frequency components are conspicuous in the spectrum of the faulty motor. This proves that the SS method and the signal model proposed in this paper are effective for BRB detection.  
Then, the SS method is used to analyze the experimental data of the IMs under different load conditions. The results are shown in Figures 4-6. It can be seen that there is a huge difference in the spectra of the SS signals of a healthy motor and a faulty motor. The signature frequency components of the BRBs are obvious in the spectra of the SS signals of faulty motors. On the contrary, in the spectra of the SS signals of healthy motor current signals, the amplitude of signature frequency components is very small. The results demonstrate that the SS method proposed in this paper can effectively excavate the signature frequency components contained in the three-phase current signals under different load conditions.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Load Levels and Health Conditions** & **s** & \(\mathbf{f_{\text{brb}}}\) **(Hz)** \\ \hline
100\% load level faulty motor & 0.039189 & 3.532190 \\
100\% load level healthy motor & 0.035266 & 3.183333 \\
60\% load level faulty motor & 0.036284 & 3.294545 \\
60\% load level healthy motor & 0.031990 & 2.883333 \\
20\% load level faulty motor & 0.033149 & 2.996645 \\
20\% load level healthy motor & 0.030243 & 2.725926 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The result of slip and signature frequency.  
Figure 3: The three-phase current signals and their spectra of the healthy motor and faulty motor: (**a**) is the time-domain diagram of the three-phase current signals of the healthy motor, (**b**) is the spectrum of phase A of the healthy motor, (**c**) is the time-domain diagram of the three-phase current signals of the faulty motor, (**d**) is the spectrum of phase A of a faulty motor.  
Figure 4: The SS signal and its spectrum of healthy motor and faulty motor at 100% load.  
Figure 5: The SS signal and its spectrum of healthy motor and faulty motor at 60% load.  
Finally, the SS method is used to analyze the experimental data of the IMs under different motor rotation speeds. The experimental data are obtained when the motor supply frequency is 30.5 Hz, 40 Hz, and 48.5 Hz and the load level is 100%. The result of the SS method is shown in Figure 7. It can be seen that the slip of the motor gradually decreases as the rotation speed increases, and the signature frequency components are always obvious. This demonstrates that the SS method is also effective under different rotation speeds.  
The effectiveness of the SS method is verified through two experiments in this subsection. The results, shown in Figures 4-7, demonstrate that the SS method is effective at different load levels and different motor rotation speeds.  
Figure 6: The SS signal and its spectrum of healthy motor and faulty motor at 20% load.  
Figure 7: The SS signals and their spectra of the faulty motor under different rotation speeds.