Tool condition monitoring is gaining a parallel development with the advancement of automatic manufacturing processes in the last thirty years due to the increasing need for improvement of product quality. The advances of digital image processing techniques used in tool condition monitoring are an important research interest due to the improvement of machine vision system, computing hardware and non-tactile application. In this paper, a review of development of digital image processing techniques in tool condition monitoring is discussed and finally a conclusion is drawn about required systematic research in this field.

Application of digital image processing in tool condition monitoring: A review

Machine vision based condition monitoring and fault diagnosis of machine tools using information from machined surface texture: A review

This paper presents a theoretical and experimental investigation into the effect of the workpiece material on surface roughness in the ultra-precision milling process. The influences of material swelling and tool-tip vibration on surface generation in ultra-precision raster milling are studied. A new method is proposed to characterize material-induced surface roughness on the raster-milled surface. A new parameter is defined to characterize the extent of surface roughness profile distortion induced by the materials being cut. An experiment is conducted to compare the proposed method with surface roughness parameters and power spectrum density analysis method by machining three different workpiece materials. The results show that the presence of elastic recovery improves the surface finish in ultra-precision raster milling and that, among the three materials being cut in the experiment, aluminum bronze has the greatest influence on surface finish due to its highest elastic recovery rate and hardness. The results also show that, in the case of faster feed rates, the proposed method more efficiently characterizes material-induced surface roughness.

An investigation into material-induced surface roughness in ultra-precision milling

The study of gecko adhesion is necessarily interdisciplinary due to the hierarchical nature of the adhesive system and the complexity of interactions between the animals and their habitats. In nature, geckos move on a wide range of surfaces including soft sand dunes, trees, and rocks, but much of the research over the past two decades has focused on their adhesive performance on artificial surfaces. Exploring the complex interactions between geckos and their natural habitats will reveal aspects of the adhesive system that can be applied to biomimetic research, such as the factors that facilitate movement on dirty and rough surfaces with varying microtopography. Additionally, contrasting suites of constraints and topographies are found on rocks and plants, likely driving differences in locomotion and morphology. Our overarching goals are to bring to light several aspects of ecology that are important for gecko-habitat interactions, and to propose a framework for how they can inspire material scientists and functional ecologists. We also present new data on surface roughness and topography of a variety of surfaces, and adhesive performance of Phelsuma geckos on surfaces of varying roughness. We address the following key questions: (1) why and how should ecology be incorporated into the study of gecko adhesion? (2) What topographical features of rocks and plants likely drive adhesive performance? (3) How can ecological studies inform material science research? Recent advances in surface replication techniques that eliminate confounding factors among surface types facilitate the ability to address some of these questions. We pinpoint gaps in our understanding and identify key initiatives that should be adopted as we move forward. Most importantly, fine details of locomotor microhabitat use of both diurnal and nocturnal geckos are needed.

The Ecomechanics of Gecko Adhesion: Natural Surface Topography, Evolution, and Biomimetics.

With the development and application of optoelectric technology, laser technology and computer technology in mind, we have developed a method to evaluate three-dimensional surface roughness using surface profile information. This article proposes a three-dimensional measuring technique, which is used to survey components surface roughness, based on the digital image processing technology, and establishes athree-dimensional surface roughness evaluation system consisting of both hardware and software architecture. The hardware used in the present experiment is listed as follows: a stereomicroscope, a digital camera with special interface, a parallel light (by halogen lamp), an X, Y bidirectional laboratory bench and a computer. A computer-aided system (CAS), developed with Visual C++ , is used in the image pretreatment and data processing analysis. In the experiment, image information gathered from the digital camera is pre-processed by median filtering, grayscale equalization and histogram conversion amplification. Then the data are analyzed by normalized cross-correlation and surface fitting techniques. Lastly, the correlation between m, σ,
Sq, S

 ku
 and Ra is discussed for different surface roughness specimens.

Ma Xuehong

Papers

Evaluation of three-dimensional surface roughness parameters based on digital image processing.