A Fault Tree Optimization Retrieval Method Based on Experience Vectors and Eigenvectors

Abstract

The invention discloses a fault tree optimization retrieval method based on an experience vector and a feature vector. The method includes the following steps of 1, attaching the experience vector and the feature vector for both an intermediate event and a bottom event in a fault tree; 2, firstly, planning the traversal sequence of current interlayer events according to the experience vector, conducting traversal according to the traversal sequence, when traversing the intermediate event or the bottom event, determining whether or not a current event occurs according to the feature vector, and then, determining whether or not traversal is conducted downward along the current event according to a determined result; 3, finally, based on the traversal sequence and the determined result, determining the bottom event of a primary cause which leads to a fault. The method innovatively uses a technological means of adding the experience vector and the feature vector for the intermediate event and the bottom event in the fault tree, achieves the optimal retrieval mechanism of the same-layer events and the automatic retrieval mechanism of the current events, and therefore effectively improves the retrieval efficiency of the fault tree of a complex system.

Description

technical field [0001] The present invention relates to the field of fault tree technology, more specifically, the present invention is a fault tree optimization retrieval method based on experience vectors and feature vectors. Background technique [0002] The fault tree analysis method is currently the most widely used and recognized as the most effective fault analysis technology for complex systems. It can quickly troubleshoot and locate the cause of the target fault. Specifically, the fault tree organizes fault phenomena, fault causes, and logical relationships in the form of a tree, and the logical relationships include logical relationships between fault phenomena and fault causes, and logical relationships between fault causes. The main elements of the fault tree include top event, intermediate event, bottom event and logical objects, among which, the top event represents the fault phenomenon, the intermediate event represents the intermediate fault cause, the bottom...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problem of low retrieval efficiency and difficulty in fast retrieval of complex fault trees in conventional fault tree retrieval methods, the present invention innovatively proposes a fault tree optimization retrieval method based on experience vectors and feature vectors, based on adding hierarchical auxiliary information to fault trees and other technical means to realize the retrieval efficiency of the fault tree at a relatively small cost, and the present invention effectively ensures the scalability of the fault tree structure

Images