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Gabor conversion and extreme learning machine neural network-based seal performance detection method for aluminum foil seal

An extreme learning machine and sealing detection technology, which is applied in the direction of neural learning methods, biological neural network models, neural architectures, etc., can solve the problems of slow detection efficiency, low detection accuracy, and low degree of automation, and achieve fast response speed, The calculation process is simple and the effect of strong generalization

Inactive Publication Date: 2018-09-07
LIAONING UNIVERSITY OF PETROLEUM AND CHEMICAL TECHNOLOGY
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Problems solved by technology

[0003] In view of the above problems, the present invention provides a method for detecting the airtightness of aluminum foil seals based on Gabor transformation and extreme learning machine (ELM) neural network, which solves the problem of low automation and low detection accuracy in the airtightness detection process of aluminum foil seals. , slow detection efficiency and other issues

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  • Gabor conversion and extreme learning machine neural network-based seal performance detection method for aluminum foil seal
  • Gabor conversion and extreme learning machine neural network-based seal performance detection method for aluminum foil seal
  • Gabor conversion and extreme learning machine neural network-based seal performance detection method for aluminum foil seal

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Embodiment Construction

[0012] 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 specific embodiments and with reference to the accompanying drawings.

[0013] figure 1 The flow chart of the aluminum foil sealing airtightness detection method based on Gabor (Gabor) transform and extreme learning machine (ELM) neural network that the embodiment of the present invention provides, the method comprises:

[0014] The step of collecting the thermal image of the aluminum foil seal includes:

[0015] Image acquisition is performed for each target passing through the thermal imager, and different types of thermal images are collected as training samples and test samples for the neural network.

[0016] The steps of image preprocessing include:

[0017] Image enhancement is used as preprocessing, and the image enhancement adopts the processing method of pseudo-color image enhance...

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Abstract

The invention discloses a Gabor conversion and extreme learning machine neural network-based seal performance detection method for an aluminum foil seal. The method comprises the steps of firstly performing Gabor conversion on a thermogram set of different feature types of collected aluminum foil seals, and training an extreme learning machine (ELM) neural network by utilizing a conversion result;and secondly performing real-time image texture feature extraction, classification identification and seal performance judgment on thermograms by utilizing the trained neural network. Through comparative analysis with a back propagation (BP) neural network for extracting color features, it is discovered that the Gabor conversion and ELM-based detection method has the advantages of strong networkgeneralization, high response speed, relatively high algorithm precision and the like, and can meet precision requirements of seal performance detection.

Description

technical field [0001] The invention belongs to the field of airtightness detection, in particular to a method for detecting the airtightness of an aluminum foil seal based on a Gabor transformation and an extreme learning machine (ELM) neural network. Background technique [0002] With the advancement of science and technology, people's living standards are improving day by day, and the research on aluminum foil packaging in the packaging field has attracted more and more attention. Because of its convenient and quick use, it is enthusiastically sought after by consumers. In European and American countries, the total demand for aluminum foil for packaging has accounted for 70%. Although aluminum foil packaging is convenient to use, it also has its shortcomings. In the process of sealing the product with aluminum foil, it is inevitable that there will be pressure puncture or aluminum foil damage. These are easy to cause the phenomenon of poor sealing, which is an important...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/40G06T7/00G06N3/08G06N3/04
CPCG06N3/084G06T7/0002G06T7/40G06T2207/20056G06N3/048
Inventor 李维军周益邦
Owner LIAONING UNIVERSITY OF PETROLEUM AND CHEMICAL TECHNOLOGY
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