| 摘要 |
A method for the condition monitoring of a fleet of machines, plants, or processes includes the generation of a single generic network for the fleet using historic data from the members of the fleet and using novelty detection tools for analyzing and reducing the data. Scaling factors relevant to each individual fleet member are stored in a scaling file. The fleet members are monitored during operation by comparing test data to the network and calculating quantization errors. Signals on the condition of the fleet members are given based on the quantization errors. The network is adapted by adding new data representing changes in a plant such as due to degradations of components. The method is performed with significantly increased time and engineering efficiency compared to methods of the state of the art, both for the generation and maintenance of the network as well as in the analysis of the data for model generation, maintenance, and monitoring. Due to the individual scaling of data from the different fleet members, the method achieves a sensitivity of monitoring that is comparable to that of methods of the state of the art.
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