Fault diagnosis of gear box bolt pull-off

杳铪 螺栓 高 高 高 高 高 高 高 高 高 高 高 高 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要 摘要It is effective to analyze the prevention of similar things and to determine the fault location afterwards!

The key components of the high-speed rolling mill wheel box are often damaged due to the poor condition of the 1st, because the gearbox structure is more complicated. There are many sources of excitation. The measured vibration signal component is also more complicated. The signal has the impact signal of the rolled steel when it is bad. There are various random signals, which are typical unstable time-varying characteristics. There is no effective fault feature extraction method. According to the usual self-mountain trigger to collect vibration signals and perform spectrum analysis, it is not obvious that the fault is not obvious, and it is difficult to accurately diagnose the Fu 7. Leaf transform analysis method requires that the signal is time-domain stable, non-time-varying, and exists in the project. Many non-stationary signals, such as mechanical components, are not well-known. Wavelet transform or wavelet analysis is a new field of rapid development of applied mathematics before 3, which can solve many difficult problems that can not be solved by the Fourier transform. It is a good localization property in both the time domain and the frequency domain. It can focus on any detail of the signal, has a strong recognition ability for the abrupt signal, and provides a new method for gearbox fault diagnosis. The discrete wavelet transform formula Like the partial and detail parts, the multiples are decomposed by 0 through the scale 2, and finally decomposed into 4, 4 which respectively contain the different frequencies of the factory signal from frequency to low frequency. , so it is called multi-resolution slaughter. Simultaneously. Each of them contains the original application example 1. The monitoring equipment and the fault condition monitoring equipment are the fourth vertical bearing of the automatic rolling mill of the Handan Iron and Steel Co., Ltd., and the universal shaft is connected to the vertical roller. January 26, 2, 2, 4:00 pm. It was found that the rolling rakes went off when passing through the 4 rolling mills.

Inspection, the result is that the connection between the roller sleeve and the connecting shaft is made. 7. Feeling the ground, the stomach stomach Qingzhi Zhiqing, oh!

At 1514:06, the 3 rough portions of the wavelet transform are 613 and 54. The 3 rough portions of the wavelet transform have all been broken.

And the fault time domain signal waveform at 15, 14:06, 3 is the normal signal waveform when the gearbox is running before the bolt is pulled off, such as 13:54.

Wavelet transform is performed on the above groups of signals (1). After the wavelet layer is decomposed, the faults after wavelet transform can be seen. The domain signals 4 and 5 have obvious mutation characteristics, that is, in the position of 4 = 0.28 and 5! The position around =0.58 is obvious but there is no obvious signal fluctuation. The shaft frequency of the universal joint shaft of the gearbox output shaft is 0.371 and the gear meshing frequency of the two output shafts is 25.39.

Before the bolts are completely broken, at the low frequency of the two spectrums of 7 and 8, the current resonance peak group has a center frequency of 25.39 out of 9. The resonance peak group may be due to the impact force when biting the steel, the key suddenly turns off or the bolt suddenly breaks. The gearbox output shaft universal joint shaft parts are caused by severe vibration, and the gear meshing condition is extremely bad. The first low-frequency resonance peak is suspected to be the first key flipped off, the first low-frequency resonance peak is suspected that the first key is turned up and down; ç½”10 is the spectrum of the normal operation signal of the gearbox at 27, 13:54 before the bolt is broken. There is a resonance peak group at the low frequency.

In addition, it is a good method to combine wavelet analysis and Victoria Falls analysis methods for diagnosis. In the diagnosis, first use the Victoria Falls to browse a large amount of data, it is easier to find the difference between the normal data group and the fault data group, and then perform deep analysis on the difference part, and the leaf finds the fault feature faster.

1 Mei Cui Jintai. Cheng Xing translation. Introduction to Wavelet Analysis Xi'an Jiaotong University Press.

4 Yang Fusheng. Ding of wavelet transform. The scores should be folded. Science Press. 1999 5, Zheng Xing. Wavelet analysis algorithm 4 application. An Jiaotong University Press. 8 6 Hu Changhua, Zhang Junbo. System Analysis and Design Wavelet Analysis Based on 1 Hole and 6 8 Liang An Electronic Science and Technology University Press, 2, W02.16 2虞和济. Equipment failure, broken Ding. Metallurgical Industry Press, 2001 Peng Huabo and the application of the application of the Department of Science and Technology Publishing Du Shen author Tonglian Beijing Gongye University 10002 edited trillion equipment transformation, improve the precision of the machine tool spindle, the effective way of life and dynamic pressure bearing integrated static pressure bearing and dynamic pressure All the advantages of the bearing, eliminating the lack of its development, the world's advanced level of wear-free sliding bearings.

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