Wavelet Analysis Of Full Information And Equipment Diagnosis Project Applied Research

The vibration information of rotor is picked up from two channels, but the traditional information processing is mostly based on the signal coming from single channel. The vibration information picked up from different channels may be completely different, thus the traditional analysis method cannot integrally embody the characters of this section. Two channels information of one rotor's section are fused by full information technology, which can integrally describe the vibration characters of this section. Vector spectrum, one of full information technology, can fully confirm the spectrum structure and vibration intension, and can receive information of precession direction and phase characters. Wavelet analysis has the character of time-frequency location, and can make signal separate at different frequency and at different time. Based on this, the merits of vector spectrum and wavelet analysis are united and Full Information Wavelet Analysis (FIWA) is proposed. The main content in this article is as follows:1. The vector spectrum is combined with wavelet analysis thus the new theories of FIWA is proposed in this article. According to the fault character, proper wavelet basis and decomposed level is selected, and dual signals are respectively decomposed, and domains that contain character frequency are reconstructed, the corresponding reconstructed signals of two channels are fused by vector spectrum technology. Loose coupling fault signal is employed to experiment, results indicate: FIWA can not only separate different character frequency but also fuse two channels' information and acquire the united vibration characters.2. Though wavelet analysis has property of time-frequency location and can decompose signal effectively, but the frequency resolution is poor at high frequencies and the time resolutions is poor at low frequencies. Wavelet packet analysis offer a more complex and flexible analysis, the details as well as the approximations are split. Thus wavelet packet analysis can improve the poor frequency resolution at high frequencies. So based on FIWA, Full Information Wavelet Packet Analysis (FIWPA) is also proposed. Oil whirl fault signal is applied to study, weak vibration signals are extracted successfully, and two channels information are fused. Study results show FIWPA is effective and usable.3. Whether wavelet analysis or wavelet packet analysis has a problem: The constructing of wavelet is irrelevant to the analyzed signal and can not effectively...