Safe and reliable environmental perception is crucial for the highly automated or even autonomous operation of agriculture machines. However, developing such a system is challenging due to imperfect perception sensors. This article proposes a fault management system (FMS) for detecting, diagnosing, and mitigating risks that compromise the safety and reliability of perception systems. This article aims to develop an improved image quality safety model (IQSM) for the FMS to detect and diagnose the causes of performance insufficiencies in object detection. The IQSM exhibits remarkable performance, achieving an accuracy of about 98%, demonstrating its ability to effectively identify performance insufficiencies under pre-defined hazardous scenarios.