基于图像噪点去除的微波设备火情预警系统

Fire Alarm System of Microwave Equipment Based on Image Noise Removal

摘要:

物料在微波干燥过程中，由于物质处于运动状态，起火时，色彩、颗粒大小、反光程度都有其特殊性，容易造成火苗或闪光的光源变得模糊，特征难以提取，令传输的图像出现噪点，导致感温探测器和红外探测器误报率高，有时甚至出现设备停机的情况。针对微波设备火情的这种特殊性和复杂性，提出了采用基于图像处理技术搭建微波设备的火情预警模型，通过采用带防护装置的 CCD 摄像头对火情的图像进行采集，以解决复杂工作环境下传统探测仪器有时停机的问题。该图像处理中采用火焰图像色彩识别与灰度图亮度识别方法相互结合，以防止传感器误报，针对性解决图像噪点去除问题，补充采用条件语句循环结构算法和嵌入阈值过滤程序。数据线上的USB接口连接到NI myRIO的硬件接口，借助内嵌于硬件系统的LabVIEW软件编程，对接收的图像进行处理。实验数据的分析和测试显示：该系统能有效的克服感温、感烟、感光，气体，复合型传感器所带来的误报问题。

Abstract:

During the drying process by microwave, the image of illuminant of fire and flashlight will become blur due to the?motorial material and the differences of color, size and the degree of reflection when material gets fire, which make it difficult to extract features. This phenomenon makes the images of transmission have lots of noise which contributes to the high rate of wrong alert by temperature detector and infrared detector and even leads to the machines out of service. Aiming at the particularity and complexity of microwave equipment to detect fire, we build a fire warning model for microwave equipment based on the research that the image of fire is collected by CCD with protective device in order to solve the problem that traditional instruments sometimes are out of service in complex working environment. During the image processing, we combine the recognition of flame image color and the recognition of gray level brightness in case of wrong alert. We target to remove noise on images by adopting conditional statement cyclic structure algorithm and embedded threshold filter program as a complementary. The USB ports are connected to hardware interface of NI myRIO. With the help of LabVIEW software programming embedded in hardware system, we process the received image. The result of analyzing the datum shows that this system can overcome the problem of wrong alert by adopting temperature，smoke，?photon，gas，composite detectors.