Multiscale characterizations of painted surface appearance by continuous wavelet transform

The appearance of paint is an important factor in the overall product quality of engineered surfaces, especially in the automotive industry. This paper introduces a multiscale characterization technique of surface topography from roughness to waviness. It uses continuous wavelet transform to correlate the characteristic scale of the surface texture to the paint's appearance. The results show good correlation between the multiscale roughness spectrum and standard distinctness of image (DOI) measurement. After an extensive review of the mathematical and numerical implementations, the multiscale attenuation function of the painting process (MAF) is defined to study the effect of the successive layers of paint coat and the painting orientation modes (horizontal, oblique and vertical).     

Sensitivity and power modeling of CMOS mems single axis convective accelerometers

In this paper, we present 3D finite element modeling and simulation of a CMOS MEMS single axis convective accelerometer. We describe the sensor architecture and present a sensor geometry model to be used in 3D FEM simulations. Differences between 3D and previously published 2D simulations are discussed. This work investigates 3D effects which give the opportunity to better predict not only sensor sensitivity but also power dissipation. Experimental sensitivity values and 3D FEM ones are compared for two different sensor geometries and two different heater temperatures. For a prototype having a heater-cavity border distance of 340 µm and a heater length of 230 µm, maximum sensitivity point is obtained for detectors localized at a distance of 125 µm from heater center. This distance should be moved to 90 µm if a 50 µm heater length is used. So, detectors should be placed closer to the heater than the usually used mid distance. Moreover, optimal detectors location shifts closer to the heater as heater length shrinks. We also show that if heater length is reduced by 80% (from 230 to 50 µm), then both electrical power and sensitivity decrease by 63% and 55%, respectively. So, best efficiency is obtained for shorter heaters. In addition, detector's length decrease is found to have a significant effect on sensitivity, with an increase of 58% and 87% using heater lengths of 230 µm and 50 µm, respectively. Here, detector's length decreased from the total side bridge length to a fraction of this length equals to 2.5%. Optimal length is obtained when detectors are implemented on the same side bridge fraction as that used to implement the heater on the central bridge.     

Automatic classification of asymptomatic and osteoarthritis knee gait patterns using kinematic data features and the nearest neighbor classifier

The aim of this work is to develop an automatic computer method to distinguish between asymptomatic (AS) and osteoarthritis (OA) knee gait patterns using 3-D ground reaction force (GRF) measurements. GRF features are first extracted from the force vector variations as a function of time and then classified by the nearest neighbor rule. We investigated two different features: the coefficients of a polynomial expansion and the coefficients of a wavelet decomposition. We also analyzed the impact of each GRF component (vertical, anteroposterior, and medial lateral) on classification. The best discrimination rate (91%) was achieved with the wavelet decomposition using the anteroposterior and the medial lateral components. These results demonstrate the validity of the representation and the classifier for automatic classification of AS and OA knee gait patterns. They also highlight the relevance of the anteroposterior and medial lateral force components in gait pattern classification.     

A new representation of shape and its use for high performance in online Arabic character recognition by an associative memory

The purpose of this study is to investigate a new representation of shape and its use in handwritten online character recognition by a Kohonen associative memory. This representation is based on the empirical distribution of features such as tangents and tangent differences at regularly spaced points along the character signal. Recognition is carried out by a Kohonen neural network trained using the representation. In addition to the Euclidean distance traditionally used in the Kohonen training algorithm to measure the similarities among feature vectors, we also investigate the Kullback–Leibler divergence and the Hellinger distance, functions that measure distance between distributions. Furthermore, we perform operations (pruning and filtering) on the trained memory to improve its classification potency. We report on extensive experiments using a database of online Arabic characters produced without constraints by a large number of writers. Comparative results show the pertinence of the representation and the superior performance of the scheme.     

Enhanced 3-axis sensitivity of a CMOS MEMS convective accelerometer using a new power efficient heater structure

Microsystem Technologies - In this paper, a new 3-axis micromachined convective accelerometer is designed using restrictions of both 0.35 µm CMOS technology and front-side bulk...     

Effect of phenol functionalized carbon nanotube on mechanical,dynamic mechanical,and thermal properties of isotactic polypropylene nanocomposites

In this work, multiwall carbon nanotubes (MWCNT) were functionalized with phenol and characterized by using Fourier transform infrared spectroscopy (FTIR). Isotactic polypropylene (iPP)/MWCNT composites of both the unfunctionalized and functionalized MWCNT were prepared by melt blending in a miniextruder at different loadings of nanotubes (i.e., 0.1, 0.25, 1.0, and 5.0 wt%). The tensile properties of the composites were found to increase with increase in nanotube loading with a maximum in Young's modulus being achieved at 1.0 wt% loading of phenol functionalized MWCNT. The differential scanning calorimetry (DSC) studies reveal the nucleating effect of MWCNT on the crystallization of iPP. Percentage crystallinity was found to increase on phenol functionalization of MWCNT. Results of X‐ray diffraction studies of the composites are in conformity with that of DSC studies. Dynamic mechanical studies reveal that the functionalized MWCNT causes many fold increase in the storage modulus, and the effect is pronounced in the case of functionalized MWCNT. POLYM. ENG. SCI. 2012. © 2011 Society of Plastics Engineers     

Effect of roughness scale on contact stiffness between solids

In this work we have used the Hölder exponent to characterise the scale of roughness and to study the scale effect of high spatial frequencies on elastic contact between solids. The mathematical approach shows that the Hölder exponent of roughness is a sophisticated tool for modelling realistic surface roughness at different scales of observation. The incidence of Hölder exponent on the prediction of pressure, bearing area and stiffness is studied in elastic contact between a smooth plane and rough surface.     

Characterisation of the 3D waviness and roughness motifs

The surface summits and their waviness envelope constitute the boundary surface of contact area during the tribological life of solids. The form, scale and orientation of the three-dimensional motifs play an important role on flatness behaviour of engineered surfaces, contact mechanics, adherence, friction, lubrication and leakage problems. The basic idea of this work considers that the three-dimensional motifs of the surface are a key elements of surface topography in regard to different field of tribology. The 2D motif is defined as the part of profile which associates tow peaks separated a deep valley (pit). The extension of the 2D motif definition to the 3D morphology needs the simultaneous assessment of waviness and roughness. The approach developed in this work is based on a geomorphologic definition of 3D motif. The approach is improved by a new algorithm of waviness envelope construction and a morphologic filter using the waviness envelope as a low-frequency surface of filtering.     

A resonant microstructure tunability analysis for an out-of-plane capacitive detection MEMS magnetometer

In this paper, the method of tuning the resonant frequency of a micro-resonant clamped–clamped beam has been successfully applied to a MEMS capacitive magnetometer. The resonant structure frequency, which presents the vital component of the sensor, was tuned by applying a bias voltage between the interdigitated capacitive comb-fingers in order to control its spring constant. It has been proved that an applied DC voltage increases the structure stiffness and as a result the resonance frequency to higher values, especially for low motion magnitude. The shifting causes were described through an accurate analytic analysis using the generated electrostatic force between movable and fixed combs, and thereafter have been proved by characterization. The measured resonance frequency of the clamped–clamped beam structure was changed by up to 38 % from the original value (around 18.2 kHz) when a bias voltage of 52 V was applied. Tuning the resonant frequency of the resonating structure has many advantages for the magnetometer since it can serve as a feedback mechanism for error compensation.