Advanced Materials Research Vol. 411

Abstract: The modified analytical embedded atom method is applied to calculate the phonon dispersion of body-centered cubic 3d transition metals Cr and Fe along five symmetry directions [q 0 0], [1 q q], [q q q], [q q 0] and [1/2 1/2 q]. Our results of phonon dispersion curves are in good agreement with the available experimental data. For the two transition metals Cr and Fe, along the same direction, a similar phonon dispersion curve is obtained in spite of the phonon frequency decreases for Cr and Fe due to the atom mass increases. There are no experimental results for comparison along the directions [1 q q] and [1/2 1/2 q], further experimental measurement are needed.

Abstract: This paper describes the structure and performances of Diamond-Like Carbon (DLC) films and introduces the film damage testing principle and methods. It also compares the different deposition techniques of DLC film laser induced damage threshold (LIDT), highlighting the influence of external electric field on the DLC film's LIDT. The photoelectron produced by the excitation of laser and the free electron in DLC film will perform a speedy movement, it indirectly decreases some part of the laser-irradiated area energy density, slows down the DLC film's graphitizing process and consequently improves its anti-laser damage ability.

Abstract: This paper compared wearability of the non-smoothed unit body of the samples treated in water medium with in air, by studying on cast iron intimating the body surface organism at the same laser processing parameters. The research indicated that the size and microhardness of non-smoothed unit body determined the wearability of the samples, and the wearability of the samples treated in water medium was relatively better than in the air.

Abstract: Polylactide (PLA)-based wood plastic composites (WPCs) were manufactured by extrusion blending followed by injection molding. The fracture surfaces created from the impact test were recorded with SEM. Fractal analysis has been used to calculate the fractal dimension of the fracture surfaces with four different fractal analysis techniques. Then, the correlation between the fractal dimension of the fracture surfaces and its impact strength of the PLA-based WPCs was investigated by the linear regression. The results showed that there is a positive correlation between the impact strength and the fractal dimension.

Abstract: The effect of coal based polyaniline compounds (CPANI) added into epoxy coating on the corrosion of mild steel in solutions of 5% sodium chloride (NaCl) has been investigated in relation to the proportion of the CPANI from 0% to 40% by various monitoring corrosion techniques. Interface morphology was studied by SEM. Results obtained revealed that the CPANI compound has good inhibitive corrosion for mild steel.

Abstract: The traditional Behavior Selection Mechanism (BSM) has two problems: it can’t be achieved autonomously under uncertainty conditions; its selection is absence of diversity under the same conditions. Being inspirited by the research achievements in emotion mechanism application to affective calculation and reinforcement learning, emotion is applied to BSM research to settle its problems. An emotion-affected mechanism is suggested. It is design-based totally; there are not the corresponding academic supports on it. Therefore, there exist three problems: the necessary elements, which it should have had, have not involved in; its architectures and emotion models are different; in addition, systematic analysis and comparisons have not been conducted among them. The suggestions are offered that the emotion-affected behavior selection mechanism should start off with mining the internal consistency among relevant research results of emotion in microeconomics, psychology, ethology, etc. Meanwhile, comparative research method will be meaningful.

Abstract: BP neural network based data-driven method is proposed to predict reliability in this paper. The BP neural network prediction using Gradient Descent Method (GDM), Additional Momentum Gradient Descent Method (AMGDM) and Levenberg-Marquardt Method(L-M) based on numerical optimization theory of training algorithm are compared with different neuron number. The proposed approach is validated via age data collected from computer numerical control (CNC) machine tool in the field. The results from the proposed method show that perfect predicting performance is achieved under considering selecting suitable number of the hidden neurons and training algorithm. Remarks are outlined regarding the fact that BP neural network based on data-driven method is feasible, effective and adequate predicting accuracy can be obtained.

Abstract: For the purpose of addressing non-stationary, poor repeatability, abundant information in the speed-up and speed-down process of a rotor-bearing system, combining with volterra series (VS) and neighborhood rough sets (NRS), a new hybrid intelligent diagnosis method is proposed. The VS is a type of nonparametric model of a nonlinear system, it can model a wide range of nonlinear systems, and can get the volterra kernel that includes the related characteristics of the system through identification. The NRS extracts useful information based only on the data itself, and is used for redundant attributes reduction to make the selected features more objective. In this paper, speed signal and vibration peak-peak value were selected as input and output signals, identified volterra kernels were applied as fault features first, then the NRS was applied for feature selection, and finally support vector machine(SVM) was used as a classifier to recognize faults of the speed-up and speed-down process. The experiment results demonstrate the proposed model not only identifies the fault type, but also identifies the fault severity.

Abstract: Aim at the problem that there is an irregular data distribution when using multi-sensor to monitor machine conditions, a genetic clustering algorithm using geodesic distance metric (GCGD) is adopted to perform machine fault detection. In GCGD, a geodesic distance based proximity measure is employed replacing Euclidean distance that cannot correctly describe the relationship between data lying in a manifold, and GCGD determines partitioning of the feature vectors from a combinatorial optimization viewpoint. Fault detection experiments of inlet valve leakage in a two-stage reciprocating compressor reveal that GCGD achieves a better performance of fault detection than the K-means algorithm and a genetic algorithm based clustering technique.

Abstract: In this paper, an on-line ferrograph sensor was used to monitor the wear condition of a gearbox in mechanical equipment. A Grey-Markov model was studied to predict its wear trend, and simulation results proved the effectiveness of the model. It provides a reliable method for wear condition monitoring and remaining life prediction of mechanical transmission systems.