Detection method of mechanical failure

A detection method and technology for mechanical faults, which are applied in the field of weak detection of mechanical faults, obtain weak characteristic signals from mechanical fault signals, and can solve problems such as frequency aliasing

Inactive Publication Date: 2014-06-04
CHINA UNIV OF PETROLEUM (BEIJING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The traditional lifting transformation performs down-sampling operation, which is prone to frequency aliasing

Method used

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  • Detection method of mechanical failure
  • Detection method of mechanical failure
  • Detection method of mechanical failure

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Embodiment 1

[0146] Embodiment 1 (fault detection of reciprocating pump):

[0147] Taking the reciprocating water injection pump (model 5ZB-20 / 43) in Tarim Oilfield as an example, the method provided by the present invention will be described in detail below. The conveying medium of the reciprocating water injection pump is clean water and sewage. The motor drives the crankshaft to run through the pulley. The rated speed of the crankshaft is 300rpm (that is, the period per revolution is 60 / 300=0.2s) (Note: This data is used for final verification, see Figure 4A ). The data acquisition system consists of three parts, which is the self-developed EDCS-4 type. The acceleration vibration signal X(n) measured on the surface of the cylinder liner (substitute into formula (1)), the sampling length is n=8192 (substitute into formula (1)), and the sampling frequency is 16kHz (to be used in the calculation process, such as Figure 3A When drawing a time domain diagram, sampling length / sampling fre...

Embodiment 2

[0150] Embodiment 2: (fault detection of motor):

[0151] Taking the water injection centrifugal pump in Tarim Oilfield as an example, the method provided by the present invention will be described in detail below. The water injection centrifugal pump is driven by a three-phase asynchronous motor, the model is YKK630-2, the rated power is 1250kW, and the rated speed is 3000fmin. The bearings at both ends of the motor are sliding bearings, and the bearing model is DQ14-160B. The acceleration sensor is installed in the vertical direction of the bearing seat at the load end of the motor, the sampling frequency is 16kHz, and the sampling length is 2048 points. During a test, it was found that the vibration at the load end of the motor was too large, and the time domain and frequency domain of the original vibration were as follows: Figure 5A with Figure 5B shown. It can be seen that the main frequency component of the vibration is 50Hz, but it cannot be judged whether there ...

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Abstract

Provided in the invention is a detection method of a mechanical failure. The method comprises: continuation data at two terminals of an original signal are predicted according to a second-order Volterra series prediction model so as to obtain a non-boundary oscillation signal; redundant lifting wavelet packet decomposition is carried out on the non-boundary oscillation signal to eliminate frequency aliasing and generate a reconstruction signal; and singular value decomposition and noise reduction are carried out on the reconstruction signal and thus a fault feature signal is obtained, wherein the signal is used for mechanical failure detection.

Description

technical field [0001] The invention relates to the field of mechanical fault detection, in particular to a weak detection method for mechanical faults, and more specifically to a method for obtaining weak characteristic signals from mechanical fault signals. Background technique [0002] Since the failure of mechanical components can lead to fatal consequences and undesired loss of production, machinery condition monitoring and fault diagnosis have received high attention in recent decades. Mechanical faults, especially the friction between reciprocating mechanical pistons and cylinder liners, friction between rotating mechanical shafts and bearing bushes, and pitting corrosion, broken teeth and wear of gears will all produce periodic, non-stationary, and high-frequency shock vibration signals. If analyzed correctly, the signal measured by an accelerometer installed near a critical component can not only reflect a certain fault, but also point out its location. However, in...

Claims

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Application Information

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IPC IPC(8): G01M13/00G01M7/08
Inventor 张来斌段礼祥
Owner CHINA UNIV OF PETROLEUM (BEIJING)
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