Rotating speed tracking and sampling and spectrum number curing and analyzing method of variable speed mechanical fault diagnosis

A technology of mechanical failure and rotational speed signal, which is applied in the direction of speed/acceleration/shock measurement, linear/angular velocity measurement, measuring device, etc. It can solve the problems that the signal sample does not meet the periodicity, cannot diagnose the limitation of the fault, and determine the frequency spectrum. Achieve the effect of facilitating computer automatic diagnosis, improving time coverage and preventing blind spots

Active Publication Date: 2010-09-29
北京唐智科技发展有限公司
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Problems solved by technology

[0008] The purpose of the present invention: to solve the classic fault diagnosis in the prior art when using the astronomical clock to control the analog-to-digital conversion of the signal, the obtained signal samples cannot be determined by Fourier transform because they do not conform to the so-called periodicity, and thus the fault cannot be diagnosed limitations

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  • Rotating speed tracking and sampling and spectrum number curing and analyzing method of variable speed mechanical fault diagnosis
  • Rotating speed tracking and sampling and spectrum number curing and analyzing method of variable speed mechanical fault diagnosis
  • Rotating speed tracking and sampling and spectrum number curing and analyzing method of variable speed mechanical fault diagnosis

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Embodiment 1

[0053] Below in conjunction with embodiment do further explanation.

[0054] For example, assume that the rotational speed frequency of a certain axle is fn, the multiplication factor is X=200, the speed tracking sampling sample length is N=2048, and the transmission ratio η=76 / 17=4.4706 of the adjacent shaft pinion to the axle, according to Table 4 From Equation 8, the fault-curing characteristic clef of the pinion is:

[0055] PH8=ηN / X=76 / 17*2048 / 200=45.77

[0056] Figure 4 When the average speed of the axle is 242r / min (the average speed of the pinion is 1082r / min), the fault waveform of the speed tracking sampling, the FFT analysis spectrum and the "theoretical abstract spectrum" of the pinion bearing and pinion calculated according to Table 4. Among them, the actual clef of the pinion fault is 45.74, which is in line with the theoretical clef;

[0057] Figure 5 It is the fault waveform, FFT analysis spectrum and the "theoretical abstract spectrum" of the pinion bear...

Embodiment 2

[0061] Speed ​​tracking sampling for fault diagnosis of variable speed machinery and speed signal sharing technology for clef solidification analysis method.

[0062] In the field of rail transit, vehicles are organized into trains. But not only the diameters of the wheels of different vehicles are different, but also the diameters of the two wheels of one axle of the same vehicle are different from the two wheels of other axles. Only the diameters of the two wheels of the same axle are controlled to be negligible within the margin of error. Due to the limitation of the cost and the allowable installation position, it is almost impossible to install the rotational speed sensor 1 and the frequency multiplier 2 for each axle to obtain the Xfn signal of the axle. Therefore, it is expected to obtain Yfn from the rotational speed sensor 1 of one axle, and process it into an Xfn signal through the frequency multiplication circuit 2 for sharing by the whole vehicle.

[0063] To thi...

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Abstract

The invention relates to a rotating speed tracking and sampling spectrum number solidifying method of variable speed mechanical fault diagnosis, which is characterized by comprising the steps of: sampling mechanical related fault signals by replacing rotating speed pulse signals with frequency of Xfn in a moving machine with astronomical clock recurrent pulse signals; and then carrying out numerical analysis on the signals by applying an FFT (Fast Fourier Transform) technology, reconstructing a classical frequency coordinate system of FFT analysis output information into a spectrum number coordinate system of rotating speed tracking FFT analysis, and establishing a recognition function of spectrum numbers corresponding to information characteristics. The invention can change the classical rotating speed variable state which can not be monitored and diagnosed in a process of sampling a astronomical clock period into a state which can be monitored and diagnosed by rotating speed tracking and sampling, thereby greatly improving the time coverage rate of safety monitoring, preventing a dead zone of a classical technology, and being especially suitable for fault diagnosis in fields of city light rail traffic, subway, city buses, wind power generation and the like. The recognition of the classical technology to spectrogram and frequency spectrum is greatly simplified by applying a curing characteristic spectrum number formula, which is beneficial to manual spectrum recognition and more computer automatic diagnosis.

Description

technical field [0001] The invention relates to a rotational speed tracking sampling and clef solidification analysis method for fault diagnosis of variable speed machinery, which belongs to the technical category of reliability and safety of mechanical equipment. technical background [0002] In the 18th century, the famous mathematician Fourier proposed to analyze the Fourier series corresponding to the frequency spectrum X(f) contained in the periodic signal in the time-domain signal X(t), so that the frequency connotation in the complex time-domain signal can be expressed at a glance. It is called Fourier transform; since the 20th century, with the development of computer and computing technology, people have proposed a fast Fourier transform definition algorithm based on Fourier transform - FFT, which has opened up an epoch-making new field for the spectrum analysis of periodic signals. This technology is gradually introduced into the signal analysis of modern fault dia...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01P3/481
Inventor 唐德尧王定晓宋辛晖曾承志黄贵发
Owner 北京唐智科技发展有限公司
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