Zhang Zhijing

High frequency group pulse electrochemical machining

In the process of machining ultrathin metal structure parts, the signal composition of high frequency group pulse, the influence of frequency to reverse current, and the design of the cathode in high frequency group pulse electrochemical machining (HGPECM) are discussed. The experiments on process were carried out. Results indicate that HGPECM can greatly improve the characteristics of the inter-electrode gap flow field, reduce electrode passivation, and obtain high machining quality. The machining quality is obviously improved by increasing the main pulse frequency. The dimensional accuracy reaches 30–40 μm and the roughness attained is at 0.30–0.35 μm. High frequency group pulse electrochemical machining can be successfully used in machining micro-parts.

Directional Sub-pixel Edge Detection Based on Limited Window Local Entropy

To realize precise micro-vision positioning based on edge detection of micro-structure parts, a pixel-level edge points detection method based on limit local entropy was proposed. 2-3 pixel were extended in the gradient direction to both sides from the edge points to construct the 3 cubic spline interpolation function of edge transition zone. Using function derivation to obtain the floating value of sub-pixel coordinates, then, sub-pixel coordinate was located according to the positioning principle of directional sub-pixel coordinates. Finally, the fine grinding standard gauge block and LIGA micro-spring were taken as example, using traditional gradient edge detection and the method proposed in this paper to realize image edge detection, and achieve the width measurement. The results show that the edge positioning accuracy of the method proposed in this paper is higher than the traditional gradient edge detection method. And whether the pixel level edge positioning accuracy or sub-pixel edge positioning accuracy are much higher than the positioning accuracy required of micro-assembly systems (5µm).

Evaluation Method for the Psychological Ecology of Enterprise Organization System

As an important indicator measuring enterprise management level, psychological ecology level of enterprise organization is an important basis for behavior prediction and management decision. Enterprise organization is made up of individual. The combination of individual psychological state decides the psychological ecology of enterprise organization. The work experience of individuals is mainly exhibited by job satisfaction. To carry out evaluation on the psychological ecology of organization, this paper constructs the dimensional system of job satisfaction degree. On the basis of this, a corresponding questionnaire and testing methods of reliability and validity of the questionnaire are designed. The dimensional objective empowerment methods and entropy evaluation methods of evaluating organization psychological ecology level are presented. Finally, the author developed investigation and evaluation system based on internet environment and a case study about an enterprise is implemented. The results show that this measurement method can exhibit the status of dimensions of organization psychological ecology according to the importance of dimensions, to provide the necessary decision-making basis for managers.