Abrasive particle chain self-adaptive segmentation method orienting online ferrographic image automatic identification

An automatic identification and abrasive chain technology, applied in image analysis, image enhancement, image data processing, etc., to achieve the effect of realizing intelligence and automation, improving accuracy, and giving full play to resources and advantages

Active Publication Date: 2014-06-25
XI AN JIAOTONG UNIV +1
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Problems solved by technology

[0013] Aiming at the defects of the prior art, the present invention provides an adaptive segmentation method of wear particle chains oriented to automatic recognition of online ferrographic images, and a method for image segmentation of wear particle chains combined with grayscale and morphological information, which realizes the wear resistance in online ferrogra

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  • Abrasive particle chain self-adaptive segmentation method orienting online ferrographic image automatic identification
  • Abrasive particle chain self-adaptive segmentation method orienting online ferrographic image automatic identification
  • Abrasive particle chain self-adaptive segmentation method orienting online ferrographic image automatic identification

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[0043] best practice

[0044] The content of the present invention will be further described below in conjunction with the accompanying drawings.

[0045] The algorithms in this implementation are all realized by commercial software Matlab.

[0046] Adaptive segmentation method of wear particle chains for automatic recognition of online ferrographic images, with figure 1 The picture shown is the material, refer to figure 2 ,Proceed as follows:

[0047] Step 1. Separate the transmitted light images provided by the ferrographic sensor (see figure 1 -c) and reflected light images (see figure 1 -a) After preprocessing, they are converted into binarized images and grayscale images respectively.

[0048] (1) Grayscale the reflected light image to obtain a grayscale image, see figure 1 -b shown.

[0049] The RGB value of each pixel point (x, y) in the image is calculated according to the formula (1) to obtain the gray value of the point, and the final processing result is a g...

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Abstract

Provided is an abrasive particle chain self-adaptive segmentation method orienting online ferrographic image automatic identification. Step one, a transmitted light image and a reflected light image respectively provided by a ferrographic sensor are respectively preprocessed and converted into a binary image and a graying image; step two, the reflected light image Imgf is adopted to perform coarse segmentation on the basis of gray scale morphology; step three, fine-multi-scale binary morphological segmentation is performed on the binary image after coarse segmentation; a variable scale corrosion-expansion algorithm is adopted on each abrasive particle chain to realize segmentation of large and small abrasive particles so that a binary segmentation line is acquired; and step four, the binary segmentation line is superposed on the original transmitted light image and the reflected light image so that an abrasive particle image after segmentation can be acquired. An online abrasive particle chain image segmentation problem can be solved, and the method can also be applied to abrasive particle chain automatic segmentation in a conventional offline ferrographic image so that the method is significant for realizing intellectualization and automation of a ferrographic image analysis technology.

Description

technical field [0001] The invention relates to the technical field of state monitoring of mechanical systems, to an automatic analysis technology of ferrographic images, and in particular to an adaptive segmentation method for wear particle chains oriented to automatic identification of online ferrographic images. Background technique [0002] Wear particle analysis is a key technology to obtain the wear state information of the machine by analyzing the lubricating medium and the wear particles carried by the tested machine, which plays a vital role in the diagnosis, prediction and maintenance decision-making of wear faults. [0003] As an important wear particle analysis method, traditional off-line ferrography image analysis has been successfully applied to the wear state monitoring of industrial equipment, forming a standardized wear state evaluation system. However, this technique has obvious defects: 1) The sampling and analysis cycle is long and the efficiency is low;...

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Application Information

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IPC IPC(8): G06T7/00G06T5/00
Inventor 武通海吴虹堃彭业萍
Owner XI AN JIAOTONG UNIV
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