The Effect of Normal Load and Sliding Frequency on the Reciprocating Friction Behavior of Nanocrystalline CuO-Based Alumina Ceramics

A novel approach toward microstructure evaluation of sintered ceramic materials through image processing techniques

“…The physical properties like the degree of densification, hardness, and fracture toughness of sintered alumina are shown in Table 1. 8,9 The noises present in these microstructures are removed using nonuniform low pass Gaussian filter. Noise-free filtered image of respective microstructures are shown in Figure 3B,D.…”

“…The refinement of microstructure with varying grain size was controlled by doping of 1-weight percent nanoadditives separately in alumina matrix. 8,9 The scanning electron micrograph (SEM) of the polished surface of sintered alumina ceramics with varying magnification was selected as an input image of this investigation. The used SEM image is in 8-bit gray scale.…”

“…The conventional ceramic fabrication technique was used to prepare TiO 2 ‐ and CuO‐doped sintered alumina ceramics at 1600°C. The refinement of microstructure with varying grain size was controlled by doping of 1‐weight percent nanoadditives separately in alumina matrix 8,9 . The scanning electron micrograph (SEM) of the polished surface of sintered alumina ceramics with varying magnification was selected as an input image of this investigation.…”

“…The microstructures are also controlled by different process parameters like sintering temperature, soaking time, the effect of foreign inclusion, nature and concentration of doping, etc. 8,9 In this context the microstructure related studies based on different computing techniques such as fuzzy logic, neural network, and statistical image analysis should be highlighted. Dutta et al 10 have studied tensile fractography of AISI 304LN austenitic stainless steel to detect and characterize The proposed algorithm is compared with linear intercept method and the grain sizes obtained are very close to each other.…”

“…The properties of engineering materials are related to the variation in grain size, size distribution, and pores present in the microstructure. The microstructures are also controlled by different process parameters like sintering temperature, soaking time, the effect of foreign inclusion, nature and concentration of doping, etc 8,9 . In this context the microstructure related studies based on different computing techniques such as fuzzy logic, neural network, and statistical image analysis should be highlighted.…”