Research On Rolling Element Bearing Diagnosis Method Using EMD

Rolling bearing is a key component of the machinery device. It is also the most potential component to fail. It has an important impact to the whole unit whether its working condition is normal, so it is very central to research on bearing condition monitoring and fault diagnosis techniques, in this paper, rolling bearing is the research object. Starting with the failure mechanism and signal characteristics, two new signal processing methods for bearing condition monitoring is studied, and applying signal processing techniques, a series of studies on the fault diagnosis of rolling bearing are carried out. The main works of this dissertation are as follows:1. Rolling bearing basic theory is studied. Based on the analysis of structure, failure mechanism and vibration mechanism of bearing, the function of characteristic and natural frequency of fault bearing is introduced, The common fault diagnosis methods are also studied, and the laboratory acquired signal is used to testify the effectiveness of the common method.2. A denoise method based on EMD-Sample entropy is proposed. The signal to noise ratio is very low in the incipient process because of interfering by normal features and some other noise, and this makes it difficult to actual diagnosis, so how to detect rolling bearing fault in the early stage is very urgent. In the view of the difficulty to solve the problem, EMD denoising based on filter-based processing is used in fault diagnosis, a criterion based on sample entropy is proposed according to the characteristic of faulty signal. Combining spectral kurtosis and EMD denoising theory, it is easy and accurate to detect the fault, Simulated and practical signal are used to verify the effectiveness.3. A bearing fault diagnosis method based on EMD (empirical mode decomposition) and ICA is proposed In the field of applying the ICA to diagnose rolling bearing fault, the single-channel signal is always the big problem, above this, a method of SDICA based on EMD is put forward, the IMFs and original signal are taken as the input of ICA, fault diagnosis is realized accurately by ICA analysis. Simulated and practical signal are used to verify the effectiveness.4.Using LabVIEW and MATLAB hybrid programming, the system of rolling bearing fault diagnosis system is developed, the system development environment and overall structure design are introduced. Then the implement method and function of each module are discussed. Through the analysis and diagnosis of practical vibration signal, the subsystem is verified to be reliable and effective.