A State Evaluation Method of Equipment Based on Safe Operation State Space Extraction with Zero-failure Data

For high reliability equipment and newly designed products, it is difficult to accurately evaluate the equipment status because almost no failure data will be generated during testing or using period. At present, the analysis of zero fault data mainly focuses on reliability estimation and unsupervised fault detection, and there is little research on the safe operation state of equipment to evaluate whether the equipment is in normal state. In this paper, we propose an equipment state evaluation method based on safe operation state space extraction, and verify the feasibility of this method through real data experiments. This method uses algorithms such as LOF (local outlier factor) and k-means algorithm to extract the parameter range of normal operation of the equipment from the historical zero-failure operation data, so as to judge whether the equipment is in a safe operation state. Compared with other methods, this method is simple and easy to use, and has wider applicability and stronger interpretability.