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Optimum synthesis of linkages with autocorrelation concept (modified least squares technique)
Author(s) -
Lapalikar S. R.,
Rao A. C.
Publication year - 1983
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.1620191011
Subject(s) - autocorrelation , four bar linkage , mathematics , function (biology) , similarity (geometry) , least squares function approximation , linkage (software) , crank , correlation function (quantum field theory) , correlation , bar (unit) , measure (data warehouse) , product (mathematics) , algorithm , statistics , motion (physics) , computer science , geometry , spectral density , physics , data mining , biochemistry , chemistry , artificial intelligence , evolutionary biology , estimator , cylinder , meteorology , gene , image (mathematics) , biology
Correlation is a measure of similarity between two functions. When two functions are exactly similar and equal, the correlation between them is maximum. The correlation concept can be used for system design, e.g. the four‐bar mechanism, the slider crank mechanism, etc. The motion generated by four‐bar linkage can be expressed as a function of link dimensions, input and output angles. The product of generated function and desired function gives correlation. The best possible design would be when the deviation of actual correlation from its maximum value (i.e. 100 per cent correlation) is least. This concept, in fact, leads to a modified least squares approach and based on this an objective function is formulated and minimized to give link dimensions. The results obtained are better than the least squares technique, and this is illustrated through different numerical examples.