External diagnosis of Gas Circuit Breaker contact wearing
The internal inspection for a GCB (gas circuit breaker) is regularly performed to check and change contact parts in the case that the number of times of fault current breaking reaches a specified number, because TBM (time based maintenance) criteria is generally applied. Our new system, however, can change maintenance criteria to CBM (condition based maintenance). Current interval for internal inspection may be, however, redundant compared with the actual amount of contact wearing, because it is difficult to estimate the actual amount of contact wearing correctly from the outside. Then, in order to evaluate the precise amount of contact wearing from the outside, we developed a sophisticated system which can presume the accurate amount of contact wearing by using real breaking current and arcing time. Furthermore, this new system can evaluate the precise amount of contact wearing even if CT (current transformer) is saturated by DC in fault current and regardless of the current phase at the breaking. Therefore, the internal inspection period to replace contact materials can be extended up to nearly three-fold length compared with the traditional way.
The K value determination research of advanced breaking current weighted cumulative method for VCB electrical endurance detection
The integral action coefficient value K about the advanced breaking current weighted cumulative method (BCWC) used for the VCBs' contact system electrical endurance monitoring is studied. At first, the general selecting method of integral current coefficient K value is discussed, and the existent problem in the K value selecting, calculating process and potential improving room are analyzed. Considering the distribution, characteristics and factors which impact K value, and according to the analysis results the LM-BP neural network algorithm is adopted to research how dynamically select the K value based on the engineering application. The construct process, establishing skill, selecting method and determination criteria of the hidden layer node of researched K LM-BP neural network are significantly emphasized. In order to verify the feasibility and accuracy of the proposed LM-BP neural network the K value predict process was carried out by the researched neural network and the result indicate that the net has a good network optimization ability and forecast precision. Thus the feasibility of provided method can be achieved of this work The LM-BP neural network algorithm introduced can promise the K value selected more approximate to practical engineering, which can ensure and effectively improve the predicting accuracy.
Participation Improves Collective Decisions (When It Involves Deliberation): Experimental Evidence From Kenya
Abstract Citizen participation in decision making has been widely lauded as a method for improving societal outcomes. Deliberative discussion, in particular, is believed to be more transformative than a mere aggregation of individual preferences, leading to more socially optimal decision making and behavior. I report the results from a laboratory experiment with 570 subjects in Nairobi, directly testing the effect of participation in deliberative group decision making on collective outcomes. Participants engage in a group task to earn compensation toward a shared group fund. Randomly assigned treatments vary according to whether decision making over the task to be completed involves: (1) external assignment; (2) non-deliberative majority voting; or (3) consensus through deliberative discussion. I find that deliberation improves collective decision making. Deliberation is also associated with changes in preferences, greater agreement with decision outcomes, and greater perceived fairness. Evidence for behavior change is weaker, but there is some support for further research into the relationship between preference change and behavior change.