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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Model-Based Water Wall Fault Detection and Diagnosis of FBC Boiler Using Strong Tracking Filter
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Model-Based Water Wall Fault Detection and Diagnosis of FBC Boiler Using Strong Tracking Filter

机译:强跟踪滤波器的基于模型的FBC锅炉水冷壁故障检测与诊断

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Fluidized bed combustion (FBC) boilers have received increasing attention in recent decades. The erosion issue on the water wall is one of the most common and serious faults for FBC boilers. Unlike direct measurement of tube thickness used by ultrasonic methods, the wastage of water wall is reconsidered equally as the variation of the overall heat transfer coefficient in the furnace. In this paper, a model-based approach is presented to estimate internal states and heat transfer coefficient dually from the noisy measurable outputs. The estimated parameter is compared with the normal value. Then the modified Bayesian algorithm is adopted for fault detection and diagnosis (FDD). The simulation results demonstrate that the approach is feasible and effective.
机译:近几十年来,流化床燃烧(FBC)锅炉受到越来越多的关注。水冷壁的腐蚀问题是FBC锅炉最常见,最严重的故障之一。与通过超声波方法直接测量管壁厚度不同,水壁的浪费被等同地视为炉中总传热系数的变化。在本文中,提出了一种基于模型的方法来从可测量的嘈杂输出中双重估算内部状态和传热系数。将估计的参数与正常值进行比较。然后采用改进的贝叶斯算法进行故障检测与诊断。仿真结果证明了该方法的可行性和有效性。

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