Analyzing various metallic structures using a metallographic microscope
For many years, metallographic researchers have been qualitatively describing the microstructural characteristics of metal materials through microscope observation on the polished surface of metallographic samples, or evaluating the microstructure, grain size, and non-metallic properties by comparing with various standard pictures. Mixtures and phase particles, etc. This method is not highly accurate and has great subjectivity in the evaluation. The reproducibility of the results is also unsatisfactory, and it is all done after the metallographic sample is polished. When measured on a two-dimensional plane on the surface, there is a certain gap between the measurement results and the description of the real structure in three-dimensional space. The emergence of modern stereology provides people with a science that extrapolates from two-dimensional images to three-dimensional space, that is, the data measured on the two-dimensional plane are combined with the theoretical microstructure shape, size, quantity and shape of the three-dimensional space of the metal material. A science that connects distribution, and can establish an intrinsic relationship between the three-dimensional spatial organization shape, size, quantity and distribution of materials and their mechanical properties, providing reliable analytical data for scientific evaluation of materials.
Since the microstructure and non-metallic admixtures in metal materials are not evenly distributed, the measurement of any parameter cannot be determined by measuring one or several fields of view under a microscope. Calculation methods must be used to determine sufficient Only by carrying out many calculation tasks in multiple fields of view can the reliability of the measurement results be guaranteed. If only human eyes are used for visual assessment under a microscope, the accuracy, consistency, and reproducibility are very poor, and the measurement speed is very slow, and some even cannot be performed due to excessive workload. The image analyzer replaces human eye observation and calculation with advanced electronic optics and computer technology. It can perform calculation-significant measurement and data processing flexibly and accurately. It also has high precision, good reproducibility and avoids treatment. It has characteristics such as the influence of factors on metallographic evaluation results, and is easy to operate and can directly print measurement reports. It has become an indispensable method in quantitative metallographic analysis at that time.
The Olympus microscope image analyzer is a powerful instrument for quantitative metallographic research on materials. It is also a good assistant for daily metallographic inspections. It can avoid subjective errors caused by manual evaluation, and thus avoid the phenomenon of wrangling. Although it is impossible and unnecessary to use an image analyzer every time in daily metallographic inspection, when the product quality is abnormal or the metallographic structure level is between qualified and unqualified and cannot be judged, you can use the image analyzer to analyze It performs quantitative analysis to produce accurate results and ensure product quality. The application of image analyzers in metallographic analysis has expanded the testing items of metallographic inspection, promoted the improvement of testing levels, and is also very beneficial to improving the quality of testing personnel.
Introduction to the Principle and Function of Olympus Microscope Image Analyzer
The image analyzer system is an optical imaging system composed of a metallographic microscope and a microscopic camera stage. Its purpose is to form an image of a metallographic sample or photo. The metallographic microscope can directly perform quantitative metallographic analysis on metallographic samples; the microscopic camera stage is suitable for analyzing metallographic photos, negatives and other objects.
In order to use a computer to store, process and analyze images, the images must first be digitized. A frame of image is composed of a distribution that does not match the gray scale. The mathematical symbol is used to reveal j = j (x, y). Therefore, a frame of image can be displayed using an m×n moment leakage display. Each element in the moment corresponds to a pixel in the image. The value of aij is the grayscale of the pixel belonging to the i-th row and j-th column in the leakage display image. value. A CCD camera (Charge Coupled Device Camera) is an image digitization device. The microscopic features on the metallographic sample are imaged on the CCD through the optical system, and the CCD completes photoelectric conversion and scanning. Then it is taken out as an image flag, expanded by an expander, and quantified into grayscale for later storage. , and then obtain the digital image. The computer sets the gray value threshold T according to the gray value range of the feature to be measured in the digital image. Regarding any pixel in the digital image, if its grayscale is greater than or equal to T, its original grayscale will be replaced with white (grayscale value 255); if it is less than T, its original grayscale will be replaced with black (grayscale value 0). The grayscale can convert the grayscale image into a binary image with only two grayscales: black and white, and then perform the required processing on the image, so that the computing function can easily perform particle counting, area, and perimeter on the binary image. Measurement and other image analysis obligations. If pseudo-color processing is used, 256 gray levels can be converted into corresponding colors, so that details with very close gray levels and their surrounding conditions or other details can be easily identified, thereby improving the image and making it easier for computers to process multi-feature images. .
