System functional structure based TFM three-dimensional information flow modeling method

Abstract

The invention discloses a system functional structure based TFM three-dimensional information flow modeling method. The TFM three-dimensional information flow modeling method has the following concrete steps: a step (1) of FFA analysis, a step (2) of TFM framework modeling, a step (3) of multiple signal flow graph based test-fault information association, and a step (4) of Bayes network based fault-maintenance information mapping. The method applies an information integration technology to a process of graphical modeling, adds relevant information assisting diagnosis into nodes of a model, andcombines a graph theory method with information inference to diagnose unknown new faults. An integrated process of fault diagnosis and maintenance troubleshooting work can be realized by the integrated modeling of three-dimensional information of test-fault-maintenance, which is more in line with the needs of engineering practice and improves the efficiency of the maintenance troubleshooting.

Description

technical field [0001] The invention relates to a TFM three-dimensional information flow modeling method based on a system function structure, and belongs to the technical field of modeling. Background technique [0002] As an important means to ensure the safety of equipment during operation, maintenance and troubleshooting technology has always been a research hotspot in various research fields. A complex system is generally a huge system consisting of multiple subsystems with different structures and characteristics. Each subsystem may fail, resulting in a variety of failures. Taking civil aircraft as an example, in July 2016, the Civil Aviation Administration of China (CAAC) collected a total of 446 aircraft service difficulty reports (SDR) reported by various airlines, and analyzed and processed them. The results are as follows: a total of 303 mechanical SDR reports, the top three are power plant, landing gear system and flight control system, of which there are 63 pow...

AI Technical Summary

Problems solved by technology

With the continuous improvement of the complexity of the system, the diagnostic accuracy requirements are getting higher and higher. The existing diagnostic methods based on graph theory models have the defects of poor model versatility and low diagnostic accuracy. The information in the system that is helpful for diagnostic reasoning It cannot be fully utilized in the graph theory model, and fault diagnosis based on the graph theory model alone cannot meet the requirements of fault diagnosis for complex large-scale systems.

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