Environmental-stress-screening using degradation measurements

ESS (environmental stress screening) has been extensively used to reduce infant mortality by precipitating defects. The existing ESS plans precipitate defects by stressing all products for specified durations. The plans usually require long screen durations to allow nearly all defective items to fail, and thus generate excessive aging effects on good items. For some products, failures are defined in terms of performance characteristics exceeding their critical values. This paper describes the principles of using degradation measurements of performance characteristics to screen the products. In an ESS, the performance characteristics of defective items degrade considerably faster than those of good ones, yielding a bimodal distribution of the characteristics. As screen duration increases, the 2 modes of the distribution shift apart. It is possible to find a tightened critical value to weed out the defective items before they fail. This paper, based on these principles, further designs the optimal 2-level screen plans which minimize a segment of life-cycle cost and which simultaneously meet the reliability requirement. The minimum cost is achieved by choosing optimal part-level and unit-level screen durations and tightened critical values of parts. A numerical example is followed by discussion. Because the ESS regime of this paper allows defective parts to be screened out before they fail, the developed optimal ESS plans can reduce life-cycle cost, shorten part-level screen duration, and alleviate aging effects on good products     

步进式加热炉钢坯跑偏测试

钢坯在炉内的横向跑偏和纵向跑偏位移量,是步进式加热炉设备的重要性能之一.重点介绍了鞍钢1780热连轧生产线步进式加热炉钢坯跑偏测试的应用技术.     

吐丝圈径对大规格高碳盘条组织性能的影响

计算与分析了斯太尔摩冷线上盘条的吐丝圈径、搭接密度及"佳灵"装置横向布风曲线之间的关系,研究了吐丝圈径的大小对大规格82B盘条组织和性能的影响,确定了大规格82B盘条最小吐丝圈径应为980mm.     

Adaptive cell division for ray tracing

In ray tracing the two most commonly used data structures are the octree and uniform cell division. The octree structure allows efficient adaptive subdivision of space, while taking care of the spatial coherence of the objects in it; however, the tree structure locating the next node in the path of a ray is complex and time consuming. The cell structure, on the other hand, can be stored in a three-dimensional array, and each cell can be efficiently accessed by specifying three indices. However, such a uniform cell division does not take care of object coherence. The proposed data structure combines the positive features of the above data structures while minimising their disadvantages. The entire object space is implicitly assumed to be a three-dimensional grid of cells. Initially, the entire object space is a single voxel which later undergoes “adaptive cell division.” But, unlike in the octree structure, where each voxel is divided exactly at the middle of each dimension, in adaptive cell division, each voxel is divided at the nearest cell boundary. The result is that each voxel contains an integral number of cells along each axis. Corresponding to the implicit cell division we maintain a three-dimensional array, with each array element containing the voxel number which is used to index into the voxel array. The voxel array is used to store information about the structure of each voxel, in particular, the objects in each voxel. While a ray moves from one voxel to another we always keep track of the cell through which the ray is currently passing. Since only arrays are involved in accessing the next voxel in the path of the ray, the operation is very efficient.     

Finite-element grid improvement by minimization of stiffness matrix trace

A new and simple method of finite-element grid improvement is presented. The objective is to improve the accuracy of the analysis. The procedure is based on a minimization of the trace of the stiffness matrix. For a broad class of problems this minimization is seen to be equivalent to minimizing the potential energy. The method is illustrated with the classical tapered bar problem examined earlier by Prager and Masur. Identical results are obtained.     

Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at