Research on optimizing the fault diagnosis strategy of complex electronic equipment
Author(s) -
Hongxia Wang,
Xiaohui Ye,
Liang Wang
Publication year - 2010
Publication title -
computer science and information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.244
H-Index - 24
eISSN - 2406-1018
pISSN - 1820-0214
DOI - 10.2298/csis1001223w
Subject(s) - computer science , computation , fault (geology) , medical diagnosis , mathematical optimization , entropy (arrow of time) , selection (genetic algorithm) , fault detection and isolation , reliability (semiconductor) , sequence (biology) , artificial intelligence , algorithm , mathematics , medicine , power (physics) , physics , pathology , quantum mechanics , seismology , actuator , geology , biology , genetics
Diagnosis strategy is a testing sequence of the fault detection and isolation. For the distribution of the electronic equipment, a feasible engineering maintenance method is put forward based on the questions of test point selection and diagnosis strategy. The concepts of local diagnosis strategy and global diagnosis strategy are introduced. From which the local optimal diagnosis strategy is determined when the local optimal test points have been introduced by using the test information entropy, furthermore, the global optimal diagnosis strategy is determined by coalescing the local optimal diagnosis strategies. At last, the validity of the method is illustrated by an example from which the conclusion can be drawn that it is an optimal diagnosis strategy and the complexity of computation can be reduced.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom