Research Article
Empirical Mode Decomposition and Neural Networks on FPGA for Fault Diagnosis in Induction Motors
Table 5
Main characteristics of previous works and of the proposed work.
| Work |
Faults | Methodology based on | A priori design required | Signals | Hardware | Yes | No | S | T | PC | FPGA |
| [12–16] | Bearings | EMD | | X | X | X | X | |
| [17–22] | Broken bar | EMD | | X | X | X | X | |
| [22–25] | Rotor eccentricities | EMD | | X | X | X | X | |
| [26] | Broken bar Unbalance Misalignment | FFT | X | | | X | X | X |
| [27] | Broken bars Unbalance Looseness | FFT | X | | | X | X | X |
| This work | Broken bars Bearings Unbalance | EMD | | X | X | X | X | X |
|
|
S: stationary; T: transient.
|