ALTERABLE INTERVAL OPTICALELECTRONIC AUTOCOLLIMATION METHOD FOR STRAIGHTNESS MEASUREMENT OF PRECISION GUIDE

Optical-electronic autocollimation method is commonly used to measure straightness of precision guides in engineering application. However, the traditional fixed interval optical-electronic autocollimation method is not suitable for measuring straightness of an air-bearing guide with a long air-bearing bush or a precision straight guide with a long slide-carriage, because the air-bearing bush and the slidecarriage are actually taken as a big bridgeboard bigger than the length of the bridgeboard with the reflector, which is about 1/4-1/2 of total length of the measured guide. If straightness is measured according to the traditional method, only a few points are sampled so that the guide straightness can not be evaluated fully or accurately. In order to solve the problem, an alterable measuring interval method is proposed for straightness measurement based on analyzing the mutual relations and effects among the tilting angle of the reflector, the length of the bridgeboard, the measuring interval and the straightness of the guide. A straightness calculation model is also developed using the method, and the errors stemming from the method proposed are introduced in brief. A precision air-bearing guide with a long air-bearing bush is measured and evaluated using the method proposed, and the actual measurement and evaluation results prove that the method is correct in theory and practical in operation. The method proposed gives an effective and flexible solution to the straightness measurement of the precision guide with long slide-carriage or air-bearing bush in application. It is an extension of the traditional optical-electronic autocollimation method for straightness measurement.

Effective implementation and improvement of fast labeled multi-Bernoulli filter

Effective implementation of the fast labeled multi-Bernoulli(FLMB)filter is addressed for target tracking with interval measurements.Firstly,a sequential Monte Carlo(SMC)implementation of the FLMB filter,SMC-FLMB filter,is derived based on generalized likelihood function weighting.Then,a box particle(BP)implementation of the FLMB filter,BP-FLMB filter,is developed,with a computational complexity reduction of the SMC-FLMB filter.Finally,an improved version of the BP-FLMB filter,improved BP-FLMB(IBP-FLMB)filter,is proposed,improving its estimation accuracy and real-time performance under the conditions of low detection probability and high clutter.Simulation results show that the BP-FLMB filter has a great improvement of the real-time performance than the SMC-FLMB filter,with similar tracking performance.Compared with the BP-FLMB filter,the IBP-FLMB filter has better estimation performance and real-time performance under the conditions of low detection probability and high clutter.

A new method and instrument for accurately measuring interval between ultrashort pulses

Using second-order autocorrelation conception, a novel method and instrument for accurately measuring interval between two linearly polarized ultrashort pulses with real time were presented. The experiment demonstrated that the measuring method and instrument were simple and accurate (the measurement error < 5 fs). During measuring, there was no moving element resulting in dynamic measurement error.

Multi-criteria decision making method based on improved cosine similarity measure with interval neutrosophic sets

Purpose–The fuzziness and complexity of evaluation information are common phenomenon in practical decision-making problem,interval neutrosophic sets(INSs)is a power tool to deal with ambiguous information.Similarity measure plays an important role in judging the degree between ideal and each alternative in decision-making process,the purpose of this paper is to establish a multi-criteria decision-making method based on similarity measure under INSs.Design/methodology/approach–Based on an extension of existing cosine similarity,this paper first introduces an improved cosine similarity measure between interval neutosophic numbers,which considers the degrees of the truth membership,the indeterminacy membership and the falsity membership of the evaluation values.And then a multi-criteria decision-making method is established based on the improved cosine similarity measure,in which the ordered weighted averaging(OWA)is adopted to aggregate the neutrosophic information related to each alternative.Finally,an example on supplier selection is given to illustrate the feasibility and practicality of the presented decision-making method.Findings–In the whole process of research and practice,it was realized that the application field of the proposed similarity measure theory still should be expanded,and the development of interval number theory is one of further research direction.Originality/value–The main contributions of this paper are as follows:this study presents an improved cosine similarity measure under INSs,in which the weights of the three independent components of an interval number are taken into account;OWA are adopted to aggregate the neutrosophic information related to each alternative;and a multi-criteria decision-making method using the proposed similarity is developed under INSs.