基于神经网络的状态预测技术及其在给水泵中的应用
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摘要
发电设备状态预测作为运行维修工作站(O&M)的重要组成部分,接受来自各种监测与诊断系统或现场运行人员的状态报告,预测设备未来的发展趋势,并根据预测结果评价设备状态、合理安排维修时间与维修项目,这对于发电设备的运行与维修决策具有重大的意义。近年来,基于神经网络预测在许多领域中的成功应用,为发电设备的状态预测技术的发展开拓了新的途径。
    本论文在分析神经网络算法的基础上,进一步阐述了基于神经网络的状态预测模型、设备发展规律及状态预测相关技术,结合发电设备运行特征提出一种组合式预测模型,并开发了一套的发电设备状态预测软件。
    给水泵是电站单元机组的重要设备之一,它的失效将带来巨大的经济损失。开展给水泵状态预测的研究,提高给水泵运行的安全性、可靠性及状态维修,都具有重要的现实意义。因此,本论文将基于神经网络状态预测技术的理论成果应用于主给水泵及液力耦合器状态预测,为其它发电设备开展状态预测提供了一种的思路与方法。
As the important integrant of the Operating and Maintenance Workstation, the condition forecasting of power generating equipment accepts condition report coming from various monitoring and diagnosing system or personnel on the site, forecasts the developing trend of equipment, evaluates the condition of equipment and arranges the schedule and items of maintenance rationally according to the results of forecasting, which has great signification to maintenance decision-making of power generating equipment. In recent yeas, the successful using of neural network based forecasting in many fields has exploited new way for the development of condition forecasting technology of power generating equipment.
    This paper analyzed the basic problems of neural network based condition forecasting of power generating equipment, the developing rule of equipment and concrete realization method of condition forecasting on the basis of analyzing the neural network algorithms, put forward combination forecasting model according to operating characteristic of power generating equipment and developed a set of condition forecasting software of power generating equipment.
    The feed water pump of boiler is one of important equipment of boiler unit. The invalidation of it will bring large economic loss. It has important real signification to study the condition forecasting of feed water pump, advance the safety and reliability of operation of feed water pump and to develop condition maintenance to feed water pump. Therefore, this paper applied the study fruit of neural network based condition forecasting technology to the condition forecasting of master feed water pump and hydraulic coupling. This provides new idea or method for condition forecasting of other power generating equipment.
引文
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