基于不确定度理论的稳态检测方法及其应用

A steady state detection method based on uncertainty theory and its application

本文基于不确定度理论提出了一种多变量稳态检测方法,该方法通过将各主要运行参数对汽轮机性能指标随机不确定的影响控制在规定的范围内来提取稳态信息,并能自适应地确定稳态区间长度。采用该方法对某超超临界1 000 MW火电机组运行数据进行稳态检测。结果表明:电功率和给水流量是系统稳态评价的关键指标;利用检测出的稳态工况计算得到的性能指标准确度高、一致性好,可用于汽轮机组的性能监测与诊断。将稳态检测结果与滑动窗口法对比,发现该稳态检测方法具有更高的检测灵敏度和准确度。因此,本文提出的稳态检测方法为利用历史运行数据进行火电机组性能监测与评价、故障检测与诊断奠定了基础,具有一定的工程应用价值。

On the basis of the uncertainty theory, a multi-variable steady-state detection method is proposed. This method extracts steady state information by controlling the influence of each main operating parameter on random uncertainty of the performance index within a specified limits, which can adaptively determine the steady-state interval length. Moreover, this method is applied to carry out steady-state detection for operating data of an ultra-supercritical 1 000 MW thermal power unit. The results show that, the power and feed water flow are key indicators for the system’s steady state evaluation, the performance index calculated by the detected steady state condition has high accuracy and good consistency, which can be applied for performance monitoring and diagnosis of steam turbines. By comparing the steady-state detection results with the sliding window method, it finds that this method has higher detection sensitivity and accuracy. Therefore, the steady state detection method proposed in this paper lays a foundation for thermal power units’ performance monitoring and evaluation, fault detection and diagnosis by using historical operational data, which alleviates many problems faced by current steam turbines’ thermal performance tests and has certain engineering application values.