基于数学形态学的电梯限速器飞重张角检测

The Flare Angle Detection of Elevator Governor Flyweight Based on Mathematical Morphology

提出一种基于运动物体图像识别的限速器飞重张角检测技术.设计了用于识别的可视标识符,完成图像拍摄和限速器线速度间的同步,采用数学形态学对图像进行预处理,并利用形状参数提取与过滤技术对标识符进行了实时识别,计算出飞重张角,利用最小二乘法进行张角与限速器线速度的二次拟合.试验结果表明,该方法正确率稳定在97%以上.

A new technique for flare angle detection based on moving image identification is proposed. It contains several technical measures as follows. The visual sign was designed for recognition and the synchronization between image acquisition and the speed of elevator governor was realized. The mathematical morphology was used for image pre-processing and the visual sign was recognized by using filtering and shape parameter extraction technology. Then, the flare angle of flyweight was calculated and the method of least square was used for quadratic curve fitting between flare angle and speed. The testing results indicate that the correct rate of detection can be stabilized at 97% or more.