应用 Ω_t. -SNE流形学习方法的盾构刀盘磨损信号降维

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关键词：盾构刀盘；性能评估： ;t- 分布随机邻域嵌入；信号降维中图分类号：U455 文献标志码：A 文章编号：1671-5276（2025）03-0096-04

Dimension Reduction of Shield Cutterhead Wear Signal by t -SNE Manifold Learning Method

HUANG Yuhua1，LI Feng² （1.School of Architecture and Electrical Engineering，Hezhou University，Hezhou 532899，China; 2.School of Civil Engineering，Guangxi University of Science and Technology，Liuzhou 545oo6，China）

Abstract：Inordertoenhancetheabilityofmonitoringtherunningstabilityofshieldcuterhead，amethodfordimensionality reduction and performance evaluation of torque vibration signal of shield cutterhead based on t- SNE manifold learning was designed.Acording totheactual parametersof shieldequipment，theidentificationofcuterstateparameters wasrealizedby data driven.The results show that compared with ISOMap，LLE，KPCA，etc.，using t -SNEmanifold dimensionalityreduction can obtain a longer t -distribution，so that thelow-dimensional far end pointswillhave a larger low-dimensional interval，and canaccuratelyclasifynormalanddegeneratesamples，andaccuratelyidentifyhigh－dimensionaldatacontaining low一 dimensional manifold.Thevariationof normaloperatingconditionsandfaultmaintenancesampling interval in Markov spaceis small，andtheuseof time-dependent Markovdistance measure toevaluatetoolperformancecanobtain higherprecision， efctivelyeliminatethecorrelationbetween diferentdimensions，and havebeterperformancethanEuclideandistance.

Keywords：cutter head of shield tunneling；performance evaluation； t- distributed random neighborhood embedding；signal dimension reduction

0 引言

刀盘在盾构装备中是一个核心受力部件，能够实现掘进并维持开挖面稳定，直接影响掘进效率[1-2]。（剩余4443字）