Research On Test Optimization Method Based On Multi-Signal Model

With the continuous development of science and technology,especially the widespread application of computer technology,while improving and perfecting the performance of systems and weaponry,it has also greatly increased the complexity of the system.Problems such as long testing time,high cost,and difficulty in locating the source of the fault have attracted the attention of researchers.In order to improve the combat effectiveness of weapons and ensure their reliable operation and good combat status,they must be tested and diagnosed efficiently and quickly.The optimal configuration of test resources is an important part of system testability design.It can detect and isolate faults in a timely and efficient manner,improve the reliability and safety of the system,shorten the time for fault detection and isolation,and thus reduce the corresponding maintenance time and improve the system.Availability,reduce system maintenance costs.First,the correlation matrix generation method based on the multi-signal flow graph model is studied.By reading the model information file and analyzing the model connection relationship,the adjacency matrix of the model is obtained.Then the accessibility matrix is further generated based on the adjacency matrix;due to the equivalence of the test point and the test,on the basis of the accessibility matrix,the test point is expanded into a test,and the fault module is deleted to obtain the complete fault matrix;through the complete fault matrix,Determine whether the signal of the faulty module and the test signal have an intersection to obtain a functional fault matrix;finally read the fault weights set in the model file,and merge the complete fault matrix and the functional fault matrix to obtain the correlation matrix.Second,the testability analysis based on the correlation matrix is studied.It is divided into static testability analysis and dynamic testability analysis,of which static testability analysis is divided into single failure analysis and multiple failure analysis.Mainly obtained parameters such as fuzzy group,redundant test,hidden fault and cover fault,isolation rate and detection rate.In the dynamic testability analysis,the failure probability,test cost,and test cost are considered,and the parameters such as the weighted fault detection rate and the weighted fault isolation rate are obtained.At the same time,the genetic algorithm is used to complete the optimization of the test set,and the fault detection rate and fault isolation rate of the system are achieved with the least test cost.Third,the test optimization method in the loop is studied.There are three main steps: loop search,loop interruption,and testing.Due to the existence of the loop,the isolation accuracy of the fault is not enough,so it is necessary to interrupt the loop and increase testing at the interruption.By designing a heuristic test evaluation function,interrupt the loop with the lowest test cost,and select the appropriate test to isolate the fault.Finally,the design and implementation ideas of the test resource configuration software are introduced,the overall design requirements and design principles of the software,the software’s graphical interface and functions are introduced,and the parameters in the report generated by the testability analysis are explained.