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基于圖像噪點(diǎn)去除的微波設備火情預警系統
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上海工程技術(shù)大學(xué) 機械工程學(xué)院,上海工程技術(shù)大學(xué) 機械工程學(xué)院,上海工程技術(shù)大學(xué) 機械工程學(xué)院,上海工程技術(shù)大學(xué) 機械工程學(xué)院,

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上海市教委產(chǎn)學(xué)研專(zhuān)項基金(12ZT14)印刷電路板鉆銑技術(shù)


Fire Alarm System of Microwave Equipment Based on Image Noise Removal
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    摘要:

    物料在微波干燥過(guò)程中,由于物質(zhì)處于運動(dòng)狀態(tài),起火時(shí),色彩、顆粒大小、反光程度都有其特殊性,容易造成火苗或閃光的光源變得模糊,特征難以提取,令傳輸的圖像出現噪點(diǎn),導致感溫探測器和紅外探測器誤報率高,有時(shí)甚至出現設備停機的情況。針對微波設備火情的這種特殊性和復雜性,提出了采用基于圖像處理技術(shù)搭建微波設備的火情預警模型,通過(guò)采用帶防護裝置的 CCD 攝像頭對火情的圖像進(jìn)行采集,以解決復雜工作環(huán)境下傳統探測儀器有時(shí)停機的問(wèn)題。該圖像處理中采用火焰圖像色彩識別與灰度圖亮度識別方法相互結合,以防止傳感器誤報,針對性解決圖像噪點(diǎn)去除問(wèn)題,補充采用條件語(yǔ)句循環(huán)結構算法和嵌入閾值過(guò)濾程序。數據線(xiàn)上的USB接口連接到NI myRIO的硬件接口,借助內嵌于硬件系統的LabVIEW軟件編程,對接收的圖像進(jìn)行處理。實(shí)驗數據的分析和測試顯示:該系統能有效的克服感溫、感煙、感光,氣體,復合型傳感器所帶來(lái)的誤報問(wèn)題。

    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.

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楊坤,朱建柳,黃立新,金曉怡,馬盼.基于圖像噪點(diǎn)去除的微波設備火情預警系統計算機測量與控制[J].,2018,26(7):178-181.

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  • 收稿日期:2017-10-27
  • 最后修改日期:2017-11-27
  • 錄用日期:2017-11-27
  • 在線(xiàn)發(fā)布日期: 2018-07-26
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