本研究論文主要是依照SHM(Structural Health Monitoring)結構健康監測應用特性,來監測以及分析感測器所擷取的數據,目的在於有效的監控數據異常的偏差值,並且訂定五個管制象限來做為後續異常處理事件的依據,達到有效數據的資訊傳遞,更進一步的分析精準的事件,並以智慧型居家系統架構為主要分析以及應用。 而在分析動作中,可分為 SPC(statistical process control) 以及 EPL(Effective Privilege Level) 兩大區塊處理方式,來過濾以及分析感測器原有龐大的數據資訊,並且利用SHM架構中的CM (cluster members)以及群組主要核心 CH(cluster heads)作為感測器處理及上送系統階層的依據,進而達到精準的判定。
The main thesis of this study is in accordance with SHM (Structural Health Monitoring) feature structural health monitoring applications, sensors to monitor and analyze the captured data, aimed at effective monitoring data anomalies offset value, and set five quadrant control as the basis for subsequent exception handling events, achieve effective information delivery of data, further analysis of the precise events, and smart home system architecture and application as the main analysis. In the analysis operation can be divided into two blocks SPC(statistical process control) and EPL(Effective Privilege Level) approach, to filter and analyze large data sensor original information, and the use of SHM architecture CM (cluster members) as well as the main core group CH ( cluster heads) as the sensor on the processing and delivery system according to class, thus achieving accurate determination.