Abstract
Gear break and pitting are two common faults in transmission system, when these two faults coexist and form a compound fault, the damage speed and frequency of gear transmission system will be greatly increased. Taking the gear fault-pitting compound fault as the object, the dynamic model of gear single fault and compound fault is established, and the vibration characteristics of gear single fault, pitting single fault and broken tooth-pitting compound fault signal are analyzed. The characteristic manifolds of the intrinsic dimension space in the case of gear single failure and compound fault are extracted by using the Laplacian Eigenmaps algorithm, the evolution trend of single fault and compound fault in the overlapping region of the feature space, the degree of correlation and the curvature of the fault circle core are analyzed and obtained. The study found that with the deepening of the fault severity, the overlapping area of fault circle between compound fault and single fault become smaller gradually, that is, the degree of correlation become weakened, tooth broken single fault and compound fault can be identified in mid-late stage of fault, while the pitting single fault and compound fault are in the late stage. The experimental results of gearbox compound fault correlation show that the conclusion of the simulation analysis is correct and effective, which provides a new idea for the diagnosis of mechanical complex faults.
Highlights
Gearbox, as one of the core parts of mechanical transmission system, is extremely prone to various faults due to the long run under harsh working environment
Gear teeth broken-pitting compound fault dynamics model and single failure dynamic model was established by ADAMS in the paper, and simulation data was obtained, combination of manifold learning method (LE) and correlation analysis for fault diagnosis
At the simulation speed of 10 Hz, 20 Hz, 30 Hz, according to the above steps to deal with broken teeth-pitting compound fault and broken single fault simulation data, the results shown below, in which the center of each figure 1, 2, 3, 4 correspond to the four severities of the fault
Summary
As one of the core parts of mechanical transmission system, is extremely prone to various faults due to the long run under harsh working environment. An integer wavelet transform is proposed by Lizhi Xiong, it shows that this scheme outperforms all of other existing RDH schemes in encrypted domain in terms of higher PSNR at the same amount of payload [5]. It is effective in diagnosing and classifying different states of gearbox in short time. THE CORRELATION ANALYSIS OF GEAR TOOTH BROKEN-PITTING COMPOUND FAULT AND SINGLE FAULT BASED ON LAPLACIAN EIGENMAPS. Gear teeth broken-pitting compound fault dynamics model and single failure dynamic model was established by ADAMS in the paper, and simulation data was obtained, combination of manifold learning method (LE) and correlation analysis for fault diagnosis. Extracting features manifolds of faults based on Laplacian eigenmaps algorithm
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