Model-Based Field Winding Interturn Fault Detection Method for Brushless Synchronous Machines
Abstract
:1. Introduction
2. Operational Principles of the Fault Detection Method
2.1. Theoretical Construction of the Healthy Model
2.1.1. First Stage: Main Machine Model
- On the one hand, voltage measurements (UA and/or and/or UB and/or UC) and/or current measurements (IA and/or IB and/or IC). Eventually, line voltages (UAB and/or UAC and/or UBC) could be also used instead of phase voltages;
- On the other hand, the active power measurement (P) and/or reactive power measurement (Q). Alternatively, the apparent power measurement (S) could be used as a replacement for either P or Q.
2.1.2. Intermediate Rectifier Relationship
2.1.3. Second Stage: Exciter Model
2.2. Fault Detection Method
- Main machine model
- 2.
- Intermediate rectifier relationship
- 3.
- Exciter model
3. Computer Simulations
3.1. Computer Simulation Model
3.2. Healthy Condition Simulations
3.3. Faulty Condition Simulations
4. Experimental Tests
4.1. Experimental Setup
- An ammeter at the excitation DC input of the exciter;
- An ammeter at the three-phase connection between the exciter and the rectifier;
- An ammeter at the DC connection between the rectifier and the main machine field winding;
- Three-phase voltage and current sensors and a wattmeter at the output of the main machine.
4.2. Healthy Condition Tests
4.3. Faulty Condition Tests
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Main Method Categories | Advantages | Disadvantages |
---|---|---|
Current or voltage signal analysis | Simplicity and accessibility Commonly used equipment (PT, CT) Non-invasiveness Reliability | Low accuracy Measurement errors Electrical noise Computational complexity and cost |
Air gap flux analysis | High accuracy Reliability Range of measurements | Invasiveness Installation constraints Machine design constraints Computational complexity and cost |
Stray flux analysis | Simplicity of installation Non-invasiveness Range of measurements | Low accuracy Computational complexity and cost |
Alternator Type | Synchronous 3-Phase | |
---|---|---|
Rated power | 5 | kVA |
Rated speed | 1500 | rpm |
Rated voltage | 400 | V |
Rated current | 7.2 | A |
Pole pairs | 2 | |
Rated frequency | 50 | Hz |
IP | 21 | |
Isolation class | F | |
Rated excitation voltage | 33 | V |
Rated excitation current | 4.10 | A |
Alternator Type | Synchronous 3-Phase | |
---|---|---|
Rated power | 277 | VA |
Rated speed | 1500 | rpm |
Rated voltage | 40 | V |
Rated current | 4 | A |
Pole pairs | 4 | |
Rated frequency | 100 | Hz |
IP | 21 | |
Isolation class | F | |
Rated excitation voltage | 33 | V |
Rated excitation current | 0.61 | A |
P [W], Q [var] | 0 | 250 | 500 | 750 | 1000 | 1250 | 1500 |
---|---|---|---|---|---|---|---|
−1000 | 0.85% | −0.77% | −1.83% | −1.03% | −4.25% | −4.88% | −3.51% |
−750 | −1.23% | −0.31% | −0.73% | −4.29% | −4.14% | −5.01% | −4.10% |
−500 | 0.36% | 0.87% | −0.60% | −5.96% | −2.39% | −5.84% | −2.20% |
−250 | 1.87% | −1.53% | −2.17% | −5.80% | −5.12% | −5.99% | −4.07% |
0 | −1.54% | −1.70% | −2.53% | −4.65% | −4.32% | −5.85% | −5.57% |
250 | −0.89% | −2.73% | −3.56% | −4.38% | −2.83% | −5.54% | −5.14% |
500 | 0.48% | −0.65% | −2.51% | −4.61% | −2.40% | −5.32% | −5.17% |
750 | 0.45% | −1.42% | −1.96% | −2.51% | −2.20% | −4.41% | −2.97% |
1000 | −0.41% | −1.63% | −1.23% | −1.62% | −2.19% | −3.81% | −2.34% |
1250 | −0.07% | −0.02% | −1.49% | −1.21% | −1.70% | −3.01% | −1.79% |
1500 | 0.17% | −0.01% | 0.04% | −0.49% | −0.94% | −2.10% | −3.46% |
1750 | 1.50% | 0.24% | −0.01% | −0.24% | −0.04% | −2.25% | −2.21% |
2000 | 2.80% | 0.56% | 0.07% | 1.09% | −0.97% | −1.11% | −2.16% |
2250 | 3.22% | 1.68% | 0.47% | 1.21% | −0.62% | 0.12% | −2.03% |
2500 | 3.88% | 3.21% | 2.49% | 5.75% | 0.95% | −0.19% | 0.01% |
Rn [Ω] | N/Ntotal [%] |
---|---|
1.8 | 15.91 |
3.9 | 11.17 |
7.5 | 7.40 |
14.9 | 4.36 |
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Mahtani, K.; Guerrero, J.M.; Beites, L.F.; Platero, C.A. Model-Based Field Winding Interturn Fault Detection Method for Brushless Synchronous Machines. Machines 2022, 10, 1227. https://doi.org/10.3390/machines10121227
Mahtani K, Guerrero JM, Beites LF, Platero CA. Model-Based Field Winding Interturn Fault Detection Method for Brushless Synchronous Machines. Machines. 2022; 10(12):1227. https://doi.org/10.3390/machines10121227
Chicago/Turabian StyleMahtani, Kumar, José M. Guerrero, Luis F. Beites, and Carlos A. Platero. 2022. "Model-Based Field Winding Interturn Fault Detection Method for Brushless Synchronous Machines" Machines 10, no. 12: 1227. https://doi.org/10.3390/machines10121227
APA StyleMahtani, K., Guerrero, J. M., Beites, L. F., & Platero, C. A. (2022). Model-Based Field Winding Interturn Fault Detection Method for Brushless Synchronous Machines. Machines, 10(12), 1227. https://doi.org/10.3390/machines10121227