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Online wear particle image data processing method

A processing method and technology of image data, applied in image data processing, image enhancement, image analysis and other directions, can solve the problem of unsatisfactory denoising effect of abrasive grain images, and achieve the effect of protecting edge detail information and accurate characterization

Active Publication Date: 2020-07-24
XIAN TECHNOLOGICAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The technical problem to be solved in this application is to provide an online wear grain image data processing method to solve the problem of unsatisfactory denoising effect on wear grain image in the prior art

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  • Online wear particle image data processing method
  • Online wear particle image data processing method

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Embodiment Construction

[0023] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying embodiments. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0024] The present invention will be described in further detail below in conjunction with specific examples, but the embodiments of the present invention include but are not limited to the scope indicated in the following examples.

[0025] The image processing steps that the present invention proposes are as follows:

[0026] Step 1: For the wear particle image collected by online wear particle monitoring, because of the influence of th...

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Abstract

The invention relates to an online wear particle image data processing method. The method comprises the steps of S1, performing graying processing on a wear particle image; S2, adding random noise tothe grayed wear particle image, then denoising the wear particle image through a 3M-WVNID denoising algorithm, and integrating wavelet analysis denoising, two-dimensional variational mode decomposition and non-local mean filtering fusion by the 3M-WVNID denoising algorithm; S3, performing binarization image segmentation on the denoised wear particle image by adopting an Otsu algorithm; S4, carrying out boundary feature detection by adopting a canny operator and carrying out wear particle image segmentation by adopting a watershed algorithm; and S5, extracting characteristic parameters from thewear particle image after image processing. The extracted wear particle image characteristic parameters can more accurately represent the health state monitored by the equipment through the online wear particle monitoring method in time and accurately.

Description

technical field [0001] The invention belongs to the technical field of oil health state monitoring, and relates to an online wear particle image data processing method. Background technique [0002] In the field of health status monitoring, oil analysis has been widely used as a popular health status monitoring method in the 21st century. Oil monitoring is mainly divided into two methods: on-line wear monitoring and off-line wear monitoring. Online wear particle monitoring is popular mainly because it can monitor the health status of equipment without stopping the machine. The intelligent analysis method of wear particle images can directly digitize wear particle images, so that it is easier to obtain equipment health status. However, in the process of intelligent analysis of wear particle images, the wear particle images are often affected by noise, which leads to great deviations in the analysis results, and the current image denoising methods tend to have fewer wear par...

Claims

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Application Information

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IPC IPC(8): G06T7/12G06T5/00G06T7/136G06T5/50
CPCG06T7/12G06T7/136G06T5/50G06T5/70Y02P90/30
Inventor 曹蔚张晗王栋闫建颍韩昭陈子琦王海文
Owner XIAN TECHNOLOGICAL UNIV
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