**5. Conclusion**

In this paper, a signal processing method for AE signal by envelope analysis with discrete wavelet transforms is proposed. For the detection of faults generated from a gear system

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using the suggested signal processing, a gearbox was installed in the test rig system. Misalignment was created by twisted case caused by arc-welding to fix the base and bearing inner race fault is generated by severe misalignment. To identify the sensing ability of the AE, vibration signal was acquired through accelerometer and compared to the AE signal. Also, to find the advantage of the proposed signal processing method, it was compared with traditional envelope analysis.

According to the experiment result, AE sensor can detect the fault earlier than an accelerometer because of high sensitivity and in the power spectrum, the harmonics of the rotating speed and the gear mesh frequency clearly occurred. Misalignment was observed and bearing faults were also detected in the early fault stage. The proposed envelope analysis is worked to evaluate the faults and indicated the faults frequencies, rotating speed, sideband of BPFI, gear mesh frequency and harmonics, explicitly.

For the detection of the crack growth on the shaft, a cracked shaft was installed on the test rig, and the crack was seeded by wire-cutting with 0.5 mm depth. The cracked shaft was lifted 6.5 mm by the lifting tool. The AE signals were transformed by FFT to create the power spectrums, and in the spectrums several peaks were occurred by the crack growth. Along the growth of the crack, the characteristic of the power spectrum was changed and displayed different frequencies.

In the power spectrum, it was shown that the harmonic components of the rotating speed and bearing cage frequency were excited by the crack growth as shown in the Fig. 6, especially on the 3X (28.6Hz) and 31Hz. And the AE signal caused by the crack growth is generated on the whole ultrasonic frequency range; the initial crack could be detected using the PAC-Energy on wavelet level 1 to 4, and after that, it could be presented on wavelet level 5 until the fracture of the shaft. Therefore, in this paper, it could be shown that the crack growth in rotating machinery is able to be considered and to be detected; in addition, PAE-Energy can be used to detect the early detection of the crack.

Therefore, the proposed signal processing method that is the envelope analysis intercalated DWT using Daubechies mother function between BPF and wave rectification can be shown to provide better result than traditional envelope analysis.
