Material mark discrimination method and device

Abstract

The invention discloses a material mark discrimination method comprising the steps that spark acquisition is performed on a test sample according to acquisition parameters in a spark database so that first spark images are obtained, and the spark database includes second projection coefficients of multiple second spark images and characteristic space; the first spark images are vectorized and saved in a first matrix; the first matrix is projected to the characteristic space of the spark database, and the first projection coefficients of the first spark images are calculated; distance between the first projection coefficients and the second projection coefficients is calculated, and the second spark image corresponding to the minimum distance acts as a matching image of the test sample; and a material mark corresponding to the matching image is outputted. The invention also discloses a material mark discrimination device comprising an acquisition unit, a vectorization unit, a projection unit, a matching unit and an output unit. With application of the method and device, material marks and components can be rapidly identified by comparison of the spark images so that the method and the device are suitable for identification of any material marks capable of generating sparks.

Description

technical field [0001] The invention relates to the technical field of material analysis, in particular to a material brand identification method and device. Background technique [0002] In practical applications, the metal materials in the warehouse are prone to mixing during the handling and loading and unloading process. After the mixing, workers cannot distinguish the steel materials with the naked eye, which may easily lead to the selection of wrong types of steel for processing, and the processed parts It can only be verified in later tests, which not only delays the construction progress, but also wastes materials and increases production costs. [0003] Metallographic method, component analysis method and spark identification method are mainly used in the prior art. Metallographic method is to observe the internal structure of the metal through a microscope to reflect the specific shape of the metallographic phase of the metal, and cannot test the specific metal mod...

AI Technical Summary

Problems solved by technology

[0002] In practical applications, the metal materials in the warehouse are prone to mixing during the handling and loading and unloading process. After the mixing, workers cannot distinguish the steel materials with the naked eye, which may easily lead to the selection of wrong types of steel for processing, and the processed parts It can only be verified in the later stage of the test, which not only delays the construction progress, but also wastes materials and increases production costs

[0003] Metallographic method, component analysis method and spark identification method are mainly used in the prior art. Metallographic method is to observe the internal structure of the metal through a microscope and reflect the specific shape of the metallographic phase of the metal. It cannot test the specific metal model and specific composition

The component analysis method can determine the specific composition and type of the material, but the component analysis method has relatively high requirements for equipment, which cannot be equipped by general production units. If it is sent to a professional monitoring agency, the procedure is complicated, and the cost is high and the cycle is long, which will affect the production progress.

The spark identification method mainly refers to the identification of technicians with rich operating experience by visually observing the sparks emitted by steel friction. It can only roughly judge the grade and composition of the material, and it is prone to identification errors; moreover, it has high requirements for technicians and has great limitations

When the quantity of mixed materials is relatively large, relying entirely on the identification of technicians, the identification efficiency is low, it is easy to delay the construction period, affect the production schedule, and increase the production cost

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