In order to improve the gas turbine engine health monitoring capability, using multiple detector fusion method in the monitoring system of gas turbine data monitor. Multi detector frame fusion includes point bias anomaly detector, contextual bias anomaly detector and collective bias anomaly detector, common to analyze the new arrival data, and the possible abnormal state to vote and weighted statistics as a result output. The experimental results show the method can effectively detect the mutation phenomenon, relatively slow changes and abnormal behavior discordant to the conditions. The framework applied to the gas turbine engine can effectively enhance the health diagnosis ability, will be highly applied for real industry. Multi-detector frame fusion includes point bias anomaly detector, contextual bias anomaly detector and collective bias anomaly detector, common to analyze the new arrival data, and the possible abnormal state to vote and weighted statistics as a result output. The framework results to the gas turbine engine can effectively enhance the health diagnosis ability, will be highly applied for real industry.