In-time motion adjustment in laser cladding manufacturing process for improving dimensional accuracy and surface finish of the formed part

This paper presents in-time motion adjustment in laser cladding manufacturing process as a means to improve dimensional accuracy and surface finish of the built part. Defects occurring during laser cladding degrade the part quality such as dimensional accuracy and surface finish. In this paper, in-time motion adjustment strategy was presented to remedy and eliminate defects occurring during laser cladding to improve the dimensional accuracy and surface finish. Based on the relationship between the motion of laser head relative to the growing part and other parameters in effects on clad profile, the laser traverse speed, stand-off distance and laser approach orientation to the existing clad layer were adjusted by instructions from a close-loop control system in real time to remedy and eliminate defects. The results of the experiments verified the effects of in-time motion adjustment on dimensional accuracy and surface finish.     

Investigations of He implantation and subsequent annealing effects in InP

The influence of 70 keV He⁺ ion implantation and subsequent annealing of Cz-indium phosphide (InP) samples has been investigated using a slow positron beam-based Doppler broadening spectrometer. Three samples with ion fluences of 1 × 10¹⁶, 5 × 10¹⁶ and 1 × 10¹⁷ cm⁻² were studied in the as-implanted condition as well as after annealing at 640 °C for times between 5 and 40 min. It was found that the line-shape parameter of the positron-electron annihilation peak in the implanted layer increases after 5 min annealing, then after longer annealing times it starts to decline gradually until it reaches a value close to the value of the as-grown sample. This implies that vacancy-like defects can be created in InP by He implantation followed by short-thermal annealing at T > 600 °C. Comparison of the results with a study where cavities were observed in He-implanted InP has been carried out.     

Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems

An approach to dealing with missing data, both during the design and normal operation of a neuro-fuzzy classifier is presented in this paper. Missing values are processed within a general fuzzy min–max neural network architecture utilising hyperbox fuzzy sets as input data cluster prototypes. An emphasis is put on ways of quantifying the uncertainty which missing data might have caused. This takes a form of classification procedure whose primary objective is the reduction of a number of viable alternatives rather than attempting to produce one winning class without supporting evidence. If required, the ways of selecting the most probable class among the viable alternatives found during the primary classification step, which are based on utilising the data frequency information, are also proposed. The reliability of the classification and the completeness of information is communicated by producing upper and lower classification membership values similar in essence to plausibility and belief measures to be found in the theory of evidence or possibility and necessity values to be found in the fuzzy sets theory. Similarities and differences between the proposed method and various fuzzy, neuro-fuzzy and probabilistic algorithms are also discussed. A number of simulation results for well-known data sets are provided in order to illustrate the properties and performance of the proposed approach.     

Structural manipulation of pyrochlores: Thermal evolution of metastable Gd2(Ti1−yZry)2O7 powders prepared by mechanical milling

The structural and microstructural characteristics of metastable Gd₂(Ti_1−yZr_y)₂O₇ powders prepared by mechanical milling have been studied by a combination of XRD and Raman spectroscopy. Irrespective of their Zr content, as-prepared powder phases present an anion-deficient fluorite-type of structure as opposed to the pyrochlore equilibrium configuration obtained for the same solid solution by other synthetic routes. These fluorites are stable versus thermal activation, at least up to temperatures of 800 °C. For the Ti-rich compositions, thermal treatments at higher temperatures facilitate the rearrangement of the cation and anion substructures and the relaxation of mechanochemically induced defects whereas for compositions with high Zr content, the fluorite crystal structure is retained even at temperatures as high as 1200 °C. Interestingly enough, transient pyrochlores showing a very unusual cation distribution were observed during the thermally induced defect-recovery process.     

Slow positron beam study of corrosion-related defects in pure iron

Corrosion-related defects of pure iron were investigated by measuring Doppler broadening energy spectra (DBES) of positron annihilation and positron annihilation lifetime (PAL). Defect profiles of the S-parameter from DBES as a function of positron incident energy up to 30 keV (i.e. ∼1 μm depth) were analyzed. The DBES data show that S-parameter increases as a function of positron incident energy (mean depth) after corrosion, and the increase in the S-parameter is larger near the surface than in the bulk due to corrosion. Furthermore, information on defect size from PAL data as a function of positron incident energy up to 10 keV (i.e. ∼0.2 μm depth) was analyzed. In the two-state trapping model, the lifetime τ₂ = 500 ps is ascribed to annihilation of positrons in voids with a size of the order of nanometer. τ₁, which decreases with depth from the surface to the bulk, is ascribed to the annihilation of positrons in dislocations and three-dimensional vacancy clusters. The corroded samples show a significant increase in τ₁ and the intensity I₂, and near the surface the corroded iron introduces both voids and large-size three-dimensional vacancy clusters. The size of vacancy clusters decreases with depth.     

Identity of defect causing nonideality in nearly ideal Au/n-Si Schottky barriers

We have proposed a mechanism of nonideality, i.e., the temperature dependence of the ideality factor, in nearly ideal Au/n-Si Schottky barriers. Because of the nature of metal-induced gap states, positively ionized defects close to the interface are considered to cause local lowering of the Schottky barrier height (SBH) due to downward bending of the energy band. These positively charged defects become neutralized in equilibrium with the Fermi level due to the band bending, when they are very close to the interface. However, because the SBH lowering disappears by the neutralization of donor, the energy level of donor with a usual energy level scheme rises above the Fermi level after the neutralization. This contradiction to the equilibrium neutralization is resolved by Si self-interstitial with a large negative-U property, which is generated by the fabrication process. The energy level of the donor estimated from the SBH lowering is in good agreement with that of theoretical calculation of Si self-interstitial. Thus, the defect is concluded to be the Si self-interstitial, which is distributed to more than 10 Å depth from the interface.     

运用反例基于识别的手写数字串分割

采用基于识别的分割方法进行手写数字串分割.在识别的过程中,运用反例样本估计分类器参数,实验数据表明,这种运用反例样本训练的分类器与没有经过反例样本训练的分类器相比,将提高拒识率到19%左右,从而保证了较高的识别率,验证了只有经过反例训练的分类器的输出结果才是可信赖的.     

The Method of Virtual Experts in Mathematical Diagnostics

Mathematical Diagnostics (MD) deals with identification problems arising in different practical areas. Some of these problems can be described by mathematical models where it is required to identify points belonging to two or more sets of points. Most of the existing tools provide some identification rule (a classifier) by means of which a given point is assigned (attributed) to one of the given sets. Each classifier can be viewed as a virtual expert. If there exist several classifiers (experts), the problem of evaluation of experts’ conclusions arises. In the paper for the case of supervised classification the method of virtual experts (the VE-method) is described. Based on this method, a generalized VE method is proposed where each of the classifiers can be chosen from a given family of classifiers. As a result, a new optimization problem with a discontinuous functional is stated. Examples illustrating the proposed approach are provided. The work of the second author was supported by the Russian Foundation for Fundamental Studies (RFFI) under Grant No 03-01-00668.     

The Effects of M2O3 on Stabilizing Monocopper over the Surface of Cu-ZnO-M2O3 Catalysts for Mathanol Synthesis

The effects of M₃O₃ (M = Al, Sc etc.) in Cu-ZnO-M₂O₃ catalysts on methanol synthesis at low pressure were studied with ESR, XPS and TPR spectroscopy. The results of ESR showed that the generation of monovalent cationic defects was because the valence state and electronic charge on the ZnO lattice lost their balance as M³⁺ doped into ZnO. The induced effect by Sc³⁺ is stronger than that by Al³⁺. The results of XPS and TPR indicated that the amount and stabilization of Cu⁺ on the surface of reduced copper-based catalyst and its catalytic activity were affected by the monovalent cationic defects on the surface of ZnO.