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基于熱成像的機房熱點(diǎn)成因自動(dòng)診斷方法
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大連理工大學(xué) 電子信息與電氣工程學(xué)部

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TP29

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國家自然科學(xué)基金(64102074);


Automatic Diagnosis of Hot Spots in Computer Rooms Based on Thermal Imaging
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    摘要:

    服務(wù)器設備的異常高溫在機房?jì)炔繒?huì )形成熱點(diǎn),不僅會(huì )影響服務(wù)器的穩定和壽命,還會(huì )導致機房制冷效率的降低,從而增加機房的制冷能耗,增加運營(yíng)費用。導致產(chǎn)生熱點(diǎn)的原因有很多,例如空氣流通不暢、風(fēng)扇失靈、長(cháng)時(shí)間滿(mǎn)負荷運行等等。通過(guò)自動(dòng)診斷熱點(diǎn)的成因,可以有針對性的消除熱點(diǎn),為機房環(huán)境控制提供數據支持,有助于降低機房制冷能耗。根據熱像儀拍攝的服務(wù)器出風(fēng)口一側的紅外圖像,利用人工智能技術(shù),提出了自動(dòng)診斷熱點(diǎn)成因的方法。針對實(shí)際工程應用中熱點(diǎn)樣本數量不足的問(wèn)題,提出了基于深度卷積對抗生成網(wǎng)絡(luò )(DCGAN)合成熱點(diǎn)樣本的解決方案。通過(guò)多組實(shí)驗驗證了方法的有效性,熱點(diǎn)成因的診斷準確率約為95%。

    Abstract:

    The abnormal high temperature of server equipment will form hot spots in the computer room, which will not only affect the stability and life of the server, but also lead to the reduction of the cooling efficiency of the room, thus increasing the cooling energy consumption and operating costs of the room. There are many reasons for hot spots, such as poor air circulation, fan failure, long-term full-load operation and so on. Through automatic diagnosis of the cause of hot spots, the hot spots can be targeted to eliminate, provide data support for the environment control of the computer room, and help to reduce the cooling energy consumption. According to the infrared image taken by the thermal camera on the side of the outlet of the server, a method of automatically diagnosing the cause of hot spots is proposed by using artificial intelligence technology. Aiming at the problem of insufficient hot spot images in practical engineering application, a solution based on Deep Convolution Generative Adversarial Networks (DCGAN) composite hot spot images is proposed. The validity of the method was verified by multiple experiments, and the diagnostic accuracy was about 95%.

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劉航,鮑晨晨,謝婷,高山.基于熱成像的機房熱點(diǎn)成因自動(dòng)診斷方法計算機測量與控制[J].,2020,28(4):66-70.

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歷史
  • 收稿日期:2019-09-23
  • 最后修改日期:2019-09-23
  • 錄用日期:2019-10-15
  • 在線(xiàn)發(fā)布日期: 2020-04-15
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