| In recent years,with the application of a series of advanced technologies such as artificial intelligence,internet of things,big data,cloud computing and Beidou satellite in the rail,the high-speed rail has developed rapidly in the direction of intelligence and modernization.The Chinese Train Control System(CTCS)Level 3 and Automatic Train Operation(ATO)equipped with intelligent high-speed railways are the "central nervous system" to ensure the safe and reliable operation of trains.The requirements for safety are extremely strict,and it is of great practical significance to test CTCS.Combinatorial testing is an important test method to test system safety.If it is applied to the test of CTCS,the response behavior of core equipment to "fail-safe" principle is analyzed by fault injection method,which can improve the test efficiency.Intelligent high-speed rail system is complex,the constraints between the devices in systems of CTCS-3 and ATO will cause the system to produce invalid test cases,which makes it difficult to verify its function and safety.Taking CTCS-3 and ATO of intelligent high-speed rail equipment as research objects,a method of test case generation and fault localization under temporary speed restriction scenario was proposed by this dissertation.To begin with,the order of temporary speed restriction commands and the information transmission process were analyzed,and the equipment fault characteristics involved in the execution of temporary speed restriction were extracted as the input parameters of the combinatorial testing.According to the interaction and constraint relationship between input parameters,a test element table was established to meet the test requirements.Then,according to the constraint relationship between input parameters,a constraint satisfaction model is established,and the improved tabu search algorithm is used to generate test cases that meet the test requirements.The initial solution generation method and neighborhood search procedure of the algorithm are modified to optimize the test case generation process and reduce the test case.Furthermore,a test process test case generation and fault localization are proposed.Test cases are injected into CTCS in order to obtain test results.Additional test cases are generated according to failed test cases.Finally,to solve the problem that the generation of invalid additional test cases may reduce the efficiency of fault localization or make the localization enter a dead cycle,the Delta-Debugging algorithm is adopted to generate the concern pattern through the difference between failed test cases and additional test cases.The corresponding constraint processing strategy is used in the generation phase of additional test cases and concern patterns to avoid constraints until the minimal failure schema is located,that is,the combination of parameters that causes the system to fail.Based on the simulation platform of CTCS for Beijing-Zhangjiakou High-speed Rail,combined with real line data and equipment information on site,in the dissertation,the test efficiency is improved by the proposed method,and the minimal failure schema is effectively located Experimental results show that when solving test problems with many parameters,large coverage and complex fault modes,the proposed algorithm reduces the number of test cases by 5.04% on average in the test case generation stage compared with before adding constraint conditions,and can effectively locate the minimal failure schema in the fault localization stage.The number of additional test cases generated in 2-way and 3-way cover arrays decreased by 25% and 27%,respectively.Compared with traditional combinatorial test,the proposed method has higher fault detection capability and fault detection rate,and is more suitable for CTCS test.Moreover,the test results can provide references for the security verification and function optimization of CTCS. |
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