We constructed an acoustic emission (AE) localization system for aluminum alloy plate using fiber Bragg grating (FBG) sensor network and edge filtering, then used the wavelet transforms and support vector classifiers algorithm to identify acoustic emission localization. We explored the relationship between the AE region and signal characteristic according to the acoustic emission test on the divided area. On the basis of signal wavelet decomposition, we proposed the AE region identification method, which is based on the vibration energy calculated by a reconstructed signal using approximation coefficients and detail coefficients. Then, we built a multi-classification support vector machine whose input was vibration energy of the reconstructed signal and output was the AE region. The experimental results showed that for a 180 AE area identification test on a 400 mm×400mm×2mm aluminum alloy plate, a 176 AE region identification test was entirely accurate, which indicated accuracy at 97.78% and on a 30mm×30mm regional location.