Grey correlation analysis based health grading evaluation method adopting all observation indexes
A technology of gray relational analysis and index scheme, which is applied in the field of gray relational analysis and health grade evaluation, can solve the problems such as the limitations of calculating gray relational degree, and achieve accurate health grade evaluation results, objective and comprehensive determination of weights, and reasonable and accurate calculations Effect
Inactive Publication Date: 2016-09-21
BEIHANG UNIV
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[0012] The purpose of the present invention is to solve the problem of the limitations of the existing gray relational degree calculation, to determine the health state of the system more accurately, and to provide a gray relational analysis health grading evaluation method using the full observation index scheme
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[0035] The present invention will be further described in detail with reference to the accompanying drawings and embodiments.
[0036] The present invention utilizes the non-health state-test correlation model (NH-T correlation model) to provide the weight improvement method based on full test points, according to the percentage weight ω of all n observed indicators obtained k(k=1,2,…,n) and the obtained gray correlation coefficient, using the formula The gray correlation degree can be calculated γ 0i . Find the behavior sequence X of all m system factors 1 ,X 2 ,…X m with system characteristic behavior sequence X 0 The gray relational degree constitutes the gray relational sequence. In the gray correlation sequence, the factor behavior sequence with the largest correlation degree is the optimal factor, that is, the factor in the current mode of the system to be investigated, so that the health status of the current system can be judged, and the health grade evaluation ...
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The invention provides a grey correlation analysis based health grading evaluation method adopting all observation indexes, and belongs to the technical field of fault diagnosis. According to the invention, an all test point based weight improvement method is provided by using a non-healthy state-test correlation model, the grey correlation degrees are calculated according to an acquired percentage weight omega<k> of all observation indexes and a calculated grey correlation coefficient, the grey correlation degrees are sorted so as to form a grey correlation sequence, a factor behavior sequence with the maximum correlation degree in the grey correlation sequence is the optimal factor, and a mode to be inspected at present of the system is located in the factor, so that the health state of the current system can be judged, health grading evaluation is provided, and finally parameter measurement evaluation is provided for the health grading evaluation. The weight set in the invention more conforms to system characteristics, calculation of the grey correlation degree is more reasonable and more accurate, and a result of health grading evaluation is more accurate, so that the system state and system factors resulting in sub-health can be predicted more accurately.
Description
technical field [0001] The invention belongs to the technical field of fault diagnosis, and is specifically aimed at a gray relational analysis health grading evaluation method involving the use of a full-observation index scheme. Background technique [0002] Various existing systems or products in different fields are increasingly highly integrated and modularized, with more and more functions, and more and more complex structures and levels. Many of these factors are not fatal to the normal operation of the system. Once these factors If an exception or failure occurs, the system will enter a "sub-healthy" state. In this state, if the system is stopped, it may cause huge economic losses and lead to task failure; but if the system is allowed to continue to work without taking corrective measures, it may cause failure due to this "sub-health" state. Anticipated severe loss and damage. In view of this situation, it is of great practical value to conduct health grading evalu...
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Login to View More IPC IPC(8): G06Q50/22
CPCG06Q50/22
Inventor 石君友何庆杰杨忆凡刘衎
Owner BEIHANG UNIV