Electrical　capacitance　tomography　is　a　non-invasive　imaging　technique　that　uses　measured　capacitances　to　recover　the　unknown　permittivity　distribution　in　the　medium.　A　new　method　using　fuzzy　theory　and　quantifiers　in　enhancing　the　ECT　sensor　system　design　and　the　associated　data　fusion　is　presented.　Unlike　the　traditional　methods　that　set　a　single　indicator　as　the　optimization　objective,　the　method　presented　in　the　paper　provides　a　way　to　integrate　multiple　evaluation　criteria　(some　may　conflict　with　others)　of　ECT　sensors　into　a　single　comparable　index.　The　uniformity　index,　the　correlation　coefficient　and　combinatorial　fuzzy　index　of　ECTs　are　set　as　the　optimization　objectives　respectively　at　the　experimental　stage　to　evaluate　the　validity　of　the　method.　The　experiments　are　set　up　based　on　multi-index　orthogonal　design　and　the　experimental　results　indicate　that　the　fuzzy　optimization　method　can　derive　an　optimized　sensor　structure　with　an　evenly　distributed　sensitivity　field　and　a　better　imaging　reconstruction　result　at　the　same　time.　It　proves　the　method　is　intuitive,　reliable,　and　practical.