Dynamic Evaluation Methods for Equipment Technical Condition Based on Multi-dimensional Characteristic Parameters.

According to the fact that current condition evaluation models lay more emphasis on the static observations of characteristic parameters and less on trend information inherent in sequential observations, a new condition evaluation model with static and dynamic evaluations is proposed. For the weighting of multi-dimensional characteristic parameters, a mutative scale chaos algorithm is applied to achieve optimal objective weighting, and a static condition evaluation model is established. Based on static evaluation, a "distance" which measures real-time deteriorating speed and standard deteriorating speed is opted to modify the static evaluation result. NSD-WKFCM (neighbor sample density weighted kernel fuzzy C-means) clustering algorithm is used to solve standard vector of deteriorating speed. A dynamic adjusting function based on "distance" combined with its parameter optimization algorithm is proposed, and the complete dynamic condition evaluation model is established. A case study is performed to verify the effectiveness of the model. [ABSTRACT FROM AUTHOR]