基于数据预测的静电除尘器闪络故障恢复策略

Recovery Strategy for Flashover Fault of Electrostatic Precipitators Using Data Prediction

静电除尘器除尘效率极大地取决于电场电压输出,其控制关键在于电场发生闪络故障后的电压恢复策略。经典闪络故障恢复方法,如三线法、二线法,大多通过设定较长的低电压运行区间或设定输出电压上限实现电压输出控制,前者平均电压输出过低,而后者对电场特性的变换适应能力不足。为克服上述方法的不足,本文提出一种基于支持向量回归数据预测的方法,通过对临近故障电压的分析,推测出当前电场可能的闪络故障电压,并以此为基础,对二线法进行改进。4组不同工况的对比实验结果证明,本文方法不仅保留了三线法的环境自动适应能力,而且提高了系统的平均电压输出,其优越性得到验证。

The dust removing efficiency of electrostatic precipitators（ESPs）greatly depends on the voltage output of power supplies,and the fault recovery strategy when flashover fault happens plays an important role to ensure the efficiency.In classical recovery methods,such as three-line method and the two-line method,the output voltage of ESP power supplies has to operate in low value areas for a long time or to be given a limited up bond.Thus,the average output voltage is low.Moreover,for approach such as the two-line method,the adaptive capacity to environment is also poor when the electric field changes.For overcoming above deficiencies,this paper presents a new fault recovery strategy based on support vector regression（SVR）.The strategy firstly predicts the voltage at which the soon-coming spark is likely to occur by analyzing near fault voltages.And then on this basis,it optimizes the process and parameters of two-line method to strengthen its adaptive capacity to environmental change and increase the average output voltage.Four groups of comparative experiments are made in the paper.Among all the experiments,the proposed strategy not only has the adaptability of the three-line method to the environmental change,but also yields a higher average output voltage than the traditional methods.Thus,the superiority of the proposed method is validated.