Automobile hub identifying and matching method

A matching method and the technology of automobile hubs, which are applied in special data processing applications, measuring devices, instruments, etc., can solve the problems of high false recognition rate and long recognition time, achieve strong environmental adaptability, improve matching efficiency, and meet flexible detection required effect

Active Publication Date: 2018-06-15
EUCLID LABS NANJING CORP LTD
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AI Technical Summary

Problems solved by technology

Manual observation and classification rely on the experience of workers, supplemented by manual measurement to identify the wheel hub model on the assembly line, and manually input the identification results into the equipment. This method not only needs to suspend the production line, but also takes a long time to identify and has a high misidentification rate.

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  • Automobile hub identifying and matching method
  • Automobile hub identifying and matching method

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Embodiment Construction

[0029] The method of the present invention will be described in further detail below in conjunction with specific examples.

[0030] In this embodiment, the hubs involved are specifically: the No. 1 hub, the No. 2 hub, and the No. 3 hub, and the hub to be matched is the No. 3 hub. The line laser sensor MoonFlowerLine900 produced by Nanjing Ecred Vision Technology Co., Ltd. is used for the wheel hub classification test. Combined with the flow chart, the specific working process is as follows:

[0031] 1. Create a database, use the line laser sensor to obtain the contour pixel point array projected by the single-line laser on the contour of all the wheels to be classified, and input them into the database, which is recorded as contoursSet[m][n](m=1, 2, 3..., m are hub indexes, n=1, 2, 3..., n are indices of contour points corresponding to the hub).

[0032] Specifically, the No. 1 hub m=1, the No. 2 hub m=2, and the No. 3 hub m=3 (3 types of hubs in total). In each hub pixel ...

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Abstract

The invention discloses an automobile hub identifying and matching method comprising the following steps: creating a contour pixel data database; calculating the average height M0 of the contour pixeldata in the database; calculating the square root mean square error MSE of the arithmetic mean sum of the difference squares of the Y coordinates of the pixels of the contour and the average height M0; and obtaining contour data of a specific position of a to-be-classified hub on an assembly line, matching the contour data with the contour data of hubs in the contour pixel data database one by one, and outputting the hub model with the minimum matching error as a final result. The automobile hub identifying and matching method is a non-contact real-time online measuring method based on a linear laser sensor. A contour is pre-matched according to the statistical features of the contour, and a hub is finally matched in a pre-matched contour set. There is no need to match all contours. The matching efficiency is improved. The method can replace manual measurement, and can be used to quickly and accurately identify different hub models.

Description

technical field [0001] The invention relates to a method for identifying and matching automobile hubs, in particular to a method for using a line laser sensor to acquire a hub profile and performing real-time online matching with a hub profile database, belonging to the field of machine vision. Background technique [0002] The wheel hub, that is, the wheel of the car, is an important bearing part of the vehicle form in the car, and one of the most important parts that affect the performance of the vehicle. In the continuous development and promotion of intelligent manufacturing technology, auto parts processing plants and integrated manufacturers are faced with complicated model classification problems. Only by quickly and accurately obtaining the wheel hub model category can the complete manufacturing process be obtained and the continuous operation of the automated production line be maintained. Therefore, accurate online detection and matching classification are extremel...

Claims

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Application Information

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IPC IPC(8): G01B11/24G06F17/30
CPCG01B11/24G06F16/903
Inventor 刘尧严律王明松敬淑义王杰高
Owner EUCLID LABS NANJING CORP LTD
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