Though　voting-based　consensus　algorithms　in　blockchain　outperform　proof-based　ones　in　energy-and　transaction-efficiency,　they　are　prone　to　incur　wrong　elections　and　bribery　elections.　The　former　originates　from　the　uncertainties　of　candidates＇　capability　and　availability,　and　the　latter　comes　from　the　egoism　of　voters　and　candidates.　Hence,　in　this　paper,　we　propose　an　uncertainty-and　collusion-proof　voting　consensus　mechanism,　including　the　selection　pressure-based　voting　algorithm　and　the　trustworthiness　evaluation　algorithm.　The　first　algorithm　can　decrease　the　side　effects　of　candidates＇　uncertainties,　lowering　wrong　elections　while　trading　off　the　balance　between　efficiency　and　fairness　in　voting　miners.　The　second　algorithm　adopts　an　incentive-compatible　scoring　rule　to　evaluate　the　trustworthiness　of　voting,　motivating　voters　to　report　true　beliefs　on　candidates　by　making　egoism　consistent　with　altruism　so　as　to　avoid　bribery　elections.　A　salient　feature　of　our　work　is　theoretically　analyzing　the　proposed　voting　consensus　mechanism　by　the　large　deviation　theory.　Our　analysis　provides　not　only　the　voting　failure　rate　of　a　candidate　but　also　its　decay　speed.　The　voting　failure　rate　measures　the　incompetence　of　any　candidate　from　a　personal　perspective　by　voting,　based　on　which　the　concepts　of　the　effective　selection　valve　and　the　effective　expectation　of　merit　are　introduced　to　help　the　system　designer　determine　the　optimal　voting　standard　and　guide　a　candidate　to　behave　in　an　optimal　way　for　lowering　the　voting　failure　rate.