基于数据驱动的WSN故障检测框架

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中图分类号：TP391 文献标志码：A 文章编号：1001-3695（2025）06-029-1815-07

doi：10.19734/j.issn.1001-3695.2024.10.0426

Data-driven WSN fault detection based framework

Xu Hana， Tong Yinghuaa，bt （a.DeptofComper，.TeStateKeybooofbenItellgentIfoaionPresing&AcoQingiNlUesit， Xining810008，China）

Abstract：Wirelessensor network nodes typicallydeployincomplex environments，where failuresare inevitable.Toaddress thischallenge，thispaperproposedadata-drivenframeworkforreal-timefaultdetectioninWSN.Thesystemfilteredandcollectedinitialoperationaldatafromwirelesssensornetworks，usingthisdatatoconstructdatasetsfortrainingfaultdetection models，withthegoalof enhancing modelaccuracy.Theapproach segmented thedata intotime windows，alowing the fault diagnosis model to identifyandcorectsensorfaults withinthemostrecent window.The modelthenreusedtherefined dataset toretrainitself，preparingforthedetectionoffaultsintheupcoming window.Throughcontinuouscyclesof raininganddetection，thesystemensuredthereal-timeupdateof thedetectionmodeltoimproveitsperformance.Experimentalresultsdemonstratethat，whencomparedtoclassicalandstate-of-the-artmachineleamingdetectionmodels，thisapproachachievesbetter precision，accuracy，and eficiencyacrossvarious typesoffaultdatasets.Consequently，theframework offerssuperiordetection capabilities and adapts more effectively to the dynamic nature of WSN environments.

Key words：wireless sensor network；fault tolerance；faultdetection；machinelearing；datadriven；data interpolation

0 引言

在无线传感器网络（wirelesssensornetwork，WSN）中，传感器故障会导致传感器读数不可靠和不准确[1]。（剩余15464字）