Multi-signal Flow Graph Model Research Articles

Testability Modelling and Optimization Technology of Ship Electrical Equipment Based on Multi-Signal Flow Diagram

With the development of ship power systems, the degree of integration, complexity and automation of ship generators has increased significantly, which places higher requirements on its testability. The marine generator is a complex electromechanical system with multiple disciplines including electricity, magnetism, force, heat, and mechanics. Its main features include: various types of fault modes, a wide range of faults, and many types of fault features. Therefore, compared with electronic products, the testability modelling and optimization methods of marine generators are very different. First of all, this paper sorts out 11 typical failure modes of marine generators. Then, analyse the failure characteristics of each failure mode and set up 17 test points initially. Based on this, a multi-signal flow graph model is constructed, and the test point is optimized based on the correlation model. By comparing and analysing the test point optimization results, the feasibility and effectiveness of the proposed method are verified.

A Method Based on Multi-signal Flow Graph Model for Disassembly and Assembly Process Simulation

Maintenance procedure simulation of disassembly and assembly is an important way to record trouble shooting, applying it in the field of maintenance training will benefit the air crew to improve their skill any time they want. Because of the shortage of disassembly and assembly modeling about the whole process simulation, we build matrix relations of tool flow, parts relation flow and assembly and disassembly process flow, then build the whole process simulation model about troubleshooting. Applying the method in the operation of temperature fault of afterward cargo compartment, and proves the method reasonable and effective for disassembly and assembly simulation.

A Research on the Electrical Test Fault Diagnostic and Data Mining of a Manned Spacecraft

The paper introduces the modeling method and modeling tool for the fault diagnosis of manned spacecraft, the multi-signal flow graph model of a manned space equipment was established using this method; the framework of the fault detection and diagnosis system of manned spacecraft is proposed, the function of ground system and function of the spacecraft are clearly defined. The structure of the functional module is given separately; finally, the tool builds the fault detection and diagnosis system, the application of fault diagnosis method for manned spacecraft is used for reference.

Error-Rate Estimation Based on Multi-Signal Flow Graph Model and Accelerated Radiation Tests.

A method of evaluating the single-event effect soft-error vulnerability of space instruments before launched has been an active research topic in recent years. In this paper, a multi-signal flow graph model is introduced to analyze the fault diagnosis and meantime to failure (MTTF) for space instruments. A model for the system functional error rate (SFER) is proposed. In addition, an experimental method and accelerated radiation testing system for a signal processing platform based on the field programmable gate array (FPGA) is presented. Based on experimental results of different ions (O, Si, Cl, Ti) under the HI-13 Tandem Accelerator, the SFER of the signal processing platform is approximately 10−3(error/particle/cm2), while the MTTF is approximately 110.7 h.

Method of testability evaluation using hierarchical testability model

The layered and modularized design is always used in complex electronic equipment,where the maintenance level and test requirement are both characterized by hierarchy configuration. Therefore,a novel evaluation approach was presented based on hierarchical testability model. The multi-signal flow graph model has ability to present multi-fault factors,according to the hierarchical classification based on maintenance level and physical structure of equipment,the multi-signal flow graph model could be established for each level respectively. For any part which can't be tested or maintained,the multi-signal flow graph model would be established on lower level; thereby the hierarchical testability model was built up. The hierarchical dependence matrix was obtained based on above model,and then the testing level of equipment on each maintenance level was obtained by using the mathematical model of testability evaluation. The analysis results of example prove that this method could effectively evaluate the testability levels of equipments in different situations,at the same time this method could provide available guidance and assistance for the design of testability and maintenance.

Fault Diagnosis Method of Vehicle Power System Using Bayesian Network

The fault diagnosis of vehicle power system that the structure and characteristics of components are complex, each module and internal modules exist coupling, cross-linked mutual relations and the uncertainties, the system status and working conditions are difficult to describe by precisely mathematical model, and test cost expensive, less fault samples. Thus its fault diagnosis is the decision problem of uncertain information in a small sample. it is proposed that combining multi-signal flow graph model with Bayesian network fault diagnosis method. The fault diagnosis model of power system and the corresponding Bayesian network structure are built, which achieve the fault diagnosis of power system, Diagnosis example shows that the method of the vehicle power has a higher failure troubleshooting capabilities of the system single and multiple faults.

Diagnosis knowledge representation and interference - Understanding fundamental ideas behind graphical models

In this article, we presented three graphical modeling techniques for diagnostic knowledge representation and inference: behavioral Petri nets (BPNs), multisignal flow graphs, and Bayesian networks (BNs). By using the same example from (Portinale, 1997) we showed that both multisignal flow graph model and BN model yield the same diagnosis. In addition, we showed that the P-invariant concept in BPN is similar to the D-separation concept in BNs