Research On Brinell Hardness Measure Based On Machine Vision

Hardness measure, which has the measuring characteristics of simple and fast and beingeasy to implement, is one of the main ways to get the mechanical properties of material. It isone of the key means to check product quality. The accurate hardness measure value is thebasis of determining the suitable production process. However, the hardness value of Brinellhardness measure is slightly influenced by test samples. Brinell hardness measure has highmeasure accuracy and its measure results have small disparity, meanwhile, it can objectivelyreflect material performance. Due to the above advantages, Brinell harness measure hasbecome one of the most widely-used measure ways of hardness.The measure based on machine vision has advantages of non-contact, fast measuring,high accuracy and good flexibility. The current measure method of Brinell hardness, whichmostly aims at the once measurement with relative ideal condition, has low adaptability.However, in the case of second measurement with more scratches, rust and other strongdisturbance, the current measure method can not satisfy measure requirements. Based onimage processing algorithm, this paper introduced a measure method from pixel calibrationto hardness calculation. This method is not only suitable to the once measure, but also issuitable to the second measure with strong disturbance.This paper includes the followings:(1) The research status and research significance of Brinell hardness measure wasanalyzed. Based on the research status and its disadvantages, the research goal of this paperwas proposed.(2) The basic principle of Brinell hardness measure was introduced. And the nationalbasic requirements on hardness measure device and measure technique were also introduces.Based on error analysis theory, the research emphasis was focused on how to improve theprecision of calibration and indentation. The research thinking was that firstly to implementpixel calibration with high precision measure tool, then to extract the pixel width ofindentation diameter, and finally to calculate the hardness.(3) In pixel calibration, based on the features of images of glass graduated scale, andcombining the Hough transformation principal, the effective lines extraction method andlines clustering method were proposed, which guarantees the calibration accuracy.(4) In indentation extraction, in view of both real-time and high accuracy, the two stepsindentation method with rough searching and refined fitting was proposed. The measureresults show that this method has high accuracy and strong adaptability. (5) Combining the above method and by virtue of VC development environment, thehardness measure software was designed. In view of practical measure requirements, thesoftware was designed with friendly operator interface, affluent information and fullfunction.