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Part assembly quality digital detection system and method based on machine learning

A part assembly and machine learning technology, applied in the field of inspection, can solve the problems of low inspection efficiency and large errors, and achieve the effect of improving reasoning ability, reducing error rate, and modular automatic inspection.

Pending Publication Date: 2021-10-08
NORTHEASTERN UNIV
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Problems solved by technology

[0003] In view of the above problems, the present invention proposes a machine learning-based digital detection system and method for parts assembly quality. By collecting image data of parts and analyzing the image data, the quality feature elements corresponding to parts are obtained. The model detects the quality characteristic elements, obtains the quality inspection results of the parts, realizes the automatic inspection of the hole making and riveting quality of the parts, solves the problems of low detection efficiency and large errors in the aircraft assembly process, saves manpower and time costs, and completes the manufacturing process. Process and modularization of hole and riveting quality inspection

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[0049] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application. It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0050]It should be noted that the terms "first" and "second" in the description and claims of the present application and the above drawings are used to distinguish similar objects, but not...

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Abstract

The invention provides a part assembly quality digital detection system and method based on machine learning. The system comprises an image collection module which is used for obtaining the image data of at least one part, an image analysis module which is used for performing image information analysis on the image data to obtain a plurality of quality feature elements corresponding to the image data, and a quality detection module which is used for constructing a target quality detection model based on particle swarm parameter optimization, and performing drilling and / or riveting quality detection on the part by using the target quality detection model according to quality characteristic elements to obtain a quality detection result of the part. According to the part assembly quality digital detection system and method based on the machine learning of the invention, the quality detection of hole making and riveting in the part assembling process is realized in a process-oriented, modularized, automatic and efficient manner, the accuracy of a quality detection result is improved, and the manpower and time cost is greatly saved.

Description

technical field [0001] The invention relates to the technical field of detection, in particular to a machine learning-based digital detection system and method for parts assembly quality. Background technique [0002] At present, most of the inspection methods for hole making and riveting quality in the aircraft assembly process are traditional manual inspection. The manual inspection method refers to the manual inspection of quality after hole making or riveting. Blocks, etc., have repeatedly measured the quality characteristics of hole making and riveting during the assembly process of aircraft parts to determine whether the quality of hole making or riveting is qualified. However, manual inspection often leads to low detection efficiency and difficult to trace quality information. Contents of the invention [0003] In view of the above problems, the present invention proposes a machine learning-based digital detection system and method for parts assembly quality. By co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/62G06N3/00
CPCG06T7/0004G06N3/006G06T2207/10004G06F18/214G06F18/241
Inventor 郝博王鹏王明阳徐东平董明强张力
Owner NORTHEASTERN UNIV
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