The vibration signal of gear box shows the information of its running state. The thesis explains the basic model and its algorithm of blind source separation, simulates the common fault of gear box in the condition of laboratory, disposing the fault signals of gear box by blind source separation and intelligently identifying the faulty condition of gear box by the method of support vector machine (SVM) after extracting eigenvector, which achieves success.
A lumped mass model with six degrees of freedom for the vertical vibration of four roller hot strip rolling mill stand was proposed, while its natural frequencies were calculated by MATLAB software. The numerical calculation results were proved more accurate through field vibration test. This vertical vibration model can be applied for dynamic simulation and structural dynamic modification with important theoretical and practical significance in mastering the vibration characteristics of four-roll mill, avoiding vertical self-excited vibration and improving production efficiency.
This research has carried on the vibration test to the roller gap displacement sensor structure by the one-point excitation and multi-point acceleration response. Based on the experimentation modal analysis theory, the modal parameters of the sensor structure have been extracted by the least square complex exponent (LSCE) method.The analysis results take the vital significance in establishing simulation model of the rolling mill depress system as well as carrying on the structure dynamics modification.
Three-dimensional digital model of hot rolling-mill housing was built. The natural frequency and vibration mode shape of the first 10 order modes of hot rolling mill housing were calculated using ANSYS software. The vibration mode shape was studied in detail. The striking vibration signal and subsequently the natural frequencies were measured by placing two 3-Dimensional accelerators in the key points of the rolling mill horsing. Theoretical calculations and experimental results verified each other,high agreement was shown between the experimental results and the theoretical results. The first 10 mode frequency all appeared in the experiment signal with low error. The main mode frequency (117.3Hz) of the experimental signal has the lowest error down to 0.07%.
The wavelet and EMD method are taken in order to accurately extract the fault information from the audio signal with a lot of noise. The bearings were studied for the object. This paper proposed a method based on wavelet and EMD frequency characteristics of the acoustic signal information extraction, and the method used in bearing fault feature extraction. The experimental results show that: the method can effectively extract the fault characteristic frequency of bearing.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.