This thesis project aims to increase the safety of multirotor Unmanned Aerial Vehicle (UAV) systems by researching Fault Detection and Diagnosis (FDD) modules to fit into an Active Fault-Tolerant Control (AFTC) system designed to recover a damaged multicopter, hence avoiding crashes. In order to meet the ever-increasing safety standards set by authorities for these vehicles, the research immerses itself in the analysis of various FDD methods implemented on multicopters, focusing on Loss of Effectiveness (LoE) estimation. The end-product of the research project is anticipated to be a fast and reliable FDD framework which ensures rapid response by the AFTC system saving the multirotor UAV from crashing after a fault is detected. The proposed framework is aimed to be flexible, meaning that its implementation on various multicopter platforms is straightforward and requires little effort, thus making it available for widespread use. Ensuring that multirotor UAVs are able to detect their faults and update their control system accordingly will propel the development of AFTC system for drones, leading to faster certification of such systems by authorities, enabling large scale and more flexible utilization of autonomous flying.