The safety computer in the train control system is designed to be the double two-vote-two\narchitecture. If safety-critical multi-input data are inconsistent, this may cause non-strict multi-sensor\ndata problems in the output. These kinds of problems may directly affect the decision making\nof the safety computer and even pose a serious threat to the safe operation of the train. In this\npaper, non-strict multi-sensor data problems that exist in traditional safety computers are analyzed.\nThe input data are classified based on data features and safety computer features. Then, the input\ndata that cause non-strict multi-sensor data problems are modeled. Fuzzy theory is used in the safety\ncomputer to process multi-sensor data and to avoid the non-strict multi-sensor problems. The fuzzy\nprocessing model is added into the onboard double two-vote-two architecture safety computer\nplatform. The fuzzy processing model can be divided into two parts: improved fuzzy decision tree\nand improved fuzzy weighted fusion. Finally, the model is verified based on two kinds of data.\nVerification results indicate that the fuzzy processing model can effectively reduce the non-strict\nidentical problems and improve the system efficiency on the premise of ensuring the data reliability.
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