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Pumped-storage unit abnormality identification and fault alarming model based on Chebyshev inequation

机译:基于切比雪夫不等式的抽水蓄能机组异常识别与故障预警模型

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摘要

In order to solve problem on setting alarming values in pumped-storage unit status monitoring, working load point distributions of 14 power stations have been analysed. The statistics indicate that all the units run in constant power mode under most conditions, and the peak-to-peak values of run-outs and vibrations comply with normal distributions after the hypothesis test. Meanwhile the distribution of data has weak relation with water head. Based on the results obtained, parameter-adjustable abnormality identification model has been established by Chebyshev inequation, and pumped-storage unit status monitoring and alarming strategy for different working point has been fulfilled.
机译:为了解决抽水蓄能机组状态监测中设置报警值的问题,分析了14座电站的工作负荷点分布。统计数据表明,所有单元在大多数情况下均以恒定功率模式运行,并且在假设检验后,跳动和振动的峰峰值符合​​正态分布。同时,数据的分布与水头关系较弱。根据得到的结果,通过切比雪夫不等式建立了参数可调的异常识别模型,并实现了对不同工作点的抽水蓄能机组状态监测和报警策略。

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