应用数字图像边缘检测理论,提出了基于数学形态学的暂态电力扰动检测和时间定位方法.该方法根据正常情况下和扰动情况下电力信号变化的不同特点,采用图像边缘检测算子获取电力扰动发生时信号“阶梯变化”产生的奇异点,并采取形态滤波、优化采样频率和结构元素长度等措施抑制信号噪声和正常情况下信号“斜坡变化”对扰动检测的影响,提高检测灵敏度.算法实现简单,计算量小,定时精度高,实时性好,对硬件要求低.对多种常见暂态电力扰动的仿真检测,验证了所提方法的可行性和有效性.
By applying digital image edge detection theory, this paper presented a new method for transient power disturbance detection based on mathematical morphology. The different characteristics between normal power signals and the signals under disturbing conditions were compared, and the signal singular points, which are caused by the signal "step change" at the disturbing moment, were detected by image edge detecting opera- tor. In order to reduce the impact of noises and the signal "ramp change" under normal conditions, some useful means were employed, such as morphological filtering, optimal decision of sampling rate and structure element length. As a result, the detecting sensitivity is improved greatly. Detecting simulations of common transient power disturbance were performed, and the simulation results verify the outstanding features of the method: easy implementation, less computing complexity, high time resolution and low demand of hardware.