Fault diagnosis of AMT gear shifting process based on semi-quantitative SDG model
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Graphical Abstract
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Abstract
In order to diagnose gear shifting process in automated manual transmission (AMT), a semi-quantitative signed directed graph (SDG) model is applied. Mathematical models are built by analysis of the power train dynamic and the gear shifting control process. The SDG model is built based on related priori knowledge. By calculating the fuzzy membership degree of each compatible passway and its possible fault source, we get the possibilities of failure for each possible fault source. We begin with the nodes with the maximum possibility of failure in order to find the failed part. The diagnosis example shows that it is feasible to use the semi-quantitative SDG model for fault diagnosis of the gear shifting process in AMT.
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