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Research on Fault Prediction for Marine Diesel Engines

机译:海洋柴油发动机故障预测研究

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Condition-based maintenance based on fault prediction has been widely concerned by the industry. Most of the contributions on fault prediction are based on various sensor data and mathematical models of the equipment. The complexity of the model and data signal is the key factor affecting the practicability of the model. In addition, even for the same type and batch of equipment, the manufacturing process, operation environment and other factors also affect the model parameters. In this paper, a series event model is conducted to predict the fault of marine diesel engines. Numerical example illustrates that the proposed event model is feasible.
机译:基于故障预测的条件维护已被行业广泛关注。大多数对故障预测的贡献都基于各种传感器数据和设备的数学模型。模型和数据信号的复杂性是影响模型实用性的关键因素。此外,即使对于相同类型和批次的设备,制造过程,操作环境和其他因素也会影响模型参数。本文进行了一系列事件模型,以预测海洋柴油发动机的故障。数值示例说明所提出的事件模型是可行的。

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