Article(id=1228805181677175754, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228805175335383281, articleNumber=null, orderNo=null, doi=10.16385/j.cnki.issn.1004-4523.2025.04.022, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1686758400000, receivedDateStr=2023-06-15, revisedDate=1697472000000, revisedDateStr=2023-10-17, acceptedDate=null, acceptedDateStr=null, onlineDate=1770899585408, onlineDateStr=2026-02-12, pubDate=1744214400000, pubDateStr=2025-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1770899585408, onlineIssueDateStr=2026-02-12, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1770899585408, creator=13701087609, updateTime=1770899585408, updator=13701087609, issue=Issue{id=1228805175335383281, tenantId=1146029695717560320, journalId=1225147924628267009, year='2025', volume='38', issue='4', pageStart='663', pageEnd='888', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1770899583895, creator=13701087609, updateTime=1770901458539, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1228813038325789525, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228805175335383281, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1228813038329983830, tenantId=1146029695717560320, journalId=1225147924628267009, issueId=1228805175335383281, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=869, endPage=876, ext={EN=ArticleExt(id=1228805181966582742, articleId=1228805181677175754, tenantId=1146029695717560320, journalId=1225147924628267009, language=EN, title=Localized fault detection of gear with servo motor built-in encoder, columnId=null, journalTitle=Journal of Vibration Engineering, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Currently,gear fault detection based on vibration,acoustic emission,and other signals requires the installation of additional sensors. This approach faces limitations in terms of sensor placement,high sensor cost,and difficulties in analyzing signals due to modulation effects in gear systems with variable transmission paths,such as planetary gearboxes. A method for diagnosing local gear faults using the built-in encoder of the servo motor is proposed in this paper. Using the output signal of the built-in encoder to extract the feature related to local gear faults. The encoder signal acquisition wiring is drawn from the built-in encoder of the servo motor,and a high-speed counter is used to record the time interval between the rising edges of the angular position pulses of the rotary encoder. The instantaneous angular speed(IAS)signal is calculated,and the IAS signal is analyzed and feature extracted in the angular and order domains to achieve local gear fault detection. Taking the planetary gearbox gear localized fault detection as an example,the proposed method is validated through experiments. Results show that using the built-in encoder of the servo motor can effectively achieve the detection of gear partial faults under low and variable speed conditions. This provides a new approach to fault detection of transmission units such as gearboxes in applications driven by servo motors.

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提出一种使用伺服电机自带的编码器进行齿轮局部故障检测的方法,无需安装外置传感器,直接对自带编码器的信号进行数据处理实现齿轮局部故障的特征提取。从伺服电机自带编码器中引出信号采集接线,使用高速计数器记录旋转编码器角度位置脉冲上升沿之间的时间间隔;通过编码器信号计算瞬时角速度(instantaneous angular speed,IAS)信号,并在角域和阶次域对IAS信号进行分析和特征提取,实现齿轮局部故障的检测。以行星齿轮箱齿轮局部故障检测为例,通过试验对所提方法进行验证,结果表明,使用伺服电机自带编码器可有效实现低转速、变转速工况下的齿轮局部故障检测。

, correspAuthors=null, authorNote=null, correspAuthorsNote=
郭瑜(1971—),男,博士,教授。E-mail:
, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=IxrZGw95HkAKlygjRfWX0w==, magXml=UpcWe7EMZxaqQIKki/z1Eg==, pdfUrl=null, pdf=E8vZUThgB6UogZK59aZkGQ==, pdfFileSize=9507428, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=GlhNh0DMR7ZuKMwu+/c3oA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=U/FfguJZLLk+I+k6S9XRPQ==, mapNumber=null, authorCompany=null, fund=null, authors=

樊家伟(1994—),男,博士研究生。E-mail:

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樊家伟(1994—),男,博士研究生。E-mail:

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樊家伟(1994—),男,博士研究生。E-mail:

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Planetary gearbox parameters

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齿轮齿数
太阳轮Ns=21
行星轮Np=31
齿圈Nr=84
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行星齿轮箱参数

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齿轮齿数
太阳轮Ns=21
行星轮Np=31
齿圈Nr=84
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Characteristic orders of planetary gearbox

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参考方式啮合阶次行星架旋转阶次太阳轮旋转阶次太阳轮故障阶次
以太阳轮为参考16.80.21.02.4
以行星架为参考841512
), ArticleFig(id=1229121422946259650, tenantId=1146029695717560320, journalId=1225147924628267009, articleId=1228805181677175754, language=CN, label=表2, caption=

行星齿轮箱特征阶次

, figureFileSmall=null, figureFileBig=null, tableContent=
参考方式啮合阶次行星架旋转阶次太阳轮旋转阶次太阳轮故障阶次
以太阳轮为参考16.80.21.02.4
以行星架为参考841512
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利用伺服电机自带编码器的齿轮局部故障检测
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樊家伟 , 郭瑜 , 尹兴超 , 邹翔 , 王红伟
振动工程学报 | 2025,38(4): 869-876
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振动工程学报 | 2025, 38(4): 869-876
利用伺服电机自带编码器的齿轮局部故障检测
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樊家伟 , 郭瑜 , 尹兴超, 邹翔, 王红伟
作者信息
  • 昆明理工大学机电工程学院,云南 昆明 650550
  • 樊家伟(1994—),男,博士研究生。E-mail:

通讯作者:

郭瑜(1971—),男,博士,教授。E-mail:
Localized fault detection of gear with servo motor built-in encoder
Jiawei FAN , Yu GUO , Xingchao YIN, Xiang ZOU, Hongwei WANG
Affiliations
  • Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650550,China
出版时间: 2025-04-10 doi: 10.16385/j.cnki.issn.1004-4523.2025.04.022
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提出一种使用伺服电机自带的编码器进行齿轮局部故障检测的方法,无需安装外置传感器,直接对自带编码器的信号进行数据处理实现齿轮局部故障的特征提取。从伺服电机自带编码器中引出信号采集接线,使用高速计数器记录旋转编码器角度位置脉冲上升沿之间的时间间隔;通过编码器信号计算瞬时角速度(instantaneous angular speed,IAS)信号,并在角域和阶次域对IAS信号进行分析和特征提取,实现齿轮局部故障的检测。以行星齿轮箱齿轮局部故障检测为例,通过试验对所提方法进行验证,结果表明,使用伺服电机自带编码器可有效实现低转速、变转速工况下的齿轮局部故障检测。

故障检测  /  齿轮  /  伺服电机自带编码器  /  变转速工况  /  瞬时角速度信号

Currently,gear fault detection based on vibration,acoustic emission,and other signals requires the installation of additional sensors. This approach faces limitations in terms of sensor placement,high sensor cost,and difficulties in analyzing signals due to modulation effects in gear systems with variable transmission paths,such as planetary gearboxes. A method for diagnosing local gear faults using the built-in encoder of the servo motor is proposed in this paper. Using the output signal of the built-in encoder to extract the feature related to local gear faults. The encoder signal acquisition wiring is drawn from the built-in encoder of the servo motor,and a high-speed counter is used to record the time interval between the rising edges of the angular position pulses of the rotary encoder. The instantaneous angular speed(IAS)signal is calculated,and the IAS signal is analyzed and feature extracted in the angular and order domains to achieve local gear fault detection. Taking the planetary gearbox gear localized fault detection as an example,the proposed method is validated through experiments. Results show that using the built-in encoder of the servo motor can effectively achieve the detection of gear partial faults under low and variable speed conditions. This provides a new approach to fault detection of transmission units such as gearboxes in applications driven by servo motors.

fault detection  /  gear  /  servo motor built-in encoder  /  variable speed condition  /  instantaneous angular speed
樊家伟, 郭瑜, 尹兴超, 邹翔, 王红伟. 利用伺服电机自带编码器的齿轮局部故障检测. 振动工程学报, 2025 , 38 (4) : 869 -876 . DOI: 10.16385/j.cnki.issn.1004-4523.2025.04.022
Jiawei FAN, Yu GUO, Xingchao YIN, Xiang ZOU, Hongwei WANG. Localized fault detection of gear with servo motor built-in encoder[J]. Journal of Vibration Engineering, 2025 , 38 (4) : 869 -876 . DOI: 10.16385/j.cnki.issn.1004-4523.2025.04.022
齿轮传动作为机械传动中最重要的传动形式之一,也是故障检测与诊断领域的重要研究对象[1-2]。目前针对齿轮的故障检测和诊断大都基于振动[3]或者声发射[4]等信号。然而使用此类信号进行故障检测时通常需安装外置传感器及信号采集设备,存在传感器安装位置受限、成本较高,以及在周转轮系中易受信号时变传递路径影响等问题,在低速、变转速工况下进行信号处理和分析也存在一定的局限[5-6]。因此,研究不受传感器安装位置影响、成本较低的故障检测途径对工程应用有重要价值。
近年来,基于旋转编码器信号的故障检测由于特有的优势引起了国内外学者的关注和研究。旋转编码器与轴系直接相连,由编码器获得的信号计算而来的瞬时角速度(instantaneous angular speed,IAS)信号中包含丰富的故障信息,可以作为故障诊断的有效数据,例如:BOURDON等[7]通过采集安装在输出轴上的编码器的数据,分析轴承IAS信号中的扭振信息,实现了轴承的故障诊断;ZHAO等[8]将编码器外置安装在行星齿轮箱的传动轴上并获取其信号,然后使用峭度引导的局部多项式微分器(KLPD)得到行星齿轮箱的IAS信号,实现了齿根故障的检测;欧曙东等[9]在行星齿轮箱的输入轴和输出轴上安装编码器,基于编码器信号使用快速主成分追踪(fast principal component pursuit,FPCP)算法实现低转速工况下行星齿轮箱的故障诊断;尹兴超等[10]结合编码器信号的优势,提出一种基于编码器信号窄带解调技术的太阳轮故障检测方法,在齿轮箱输出端安装外置编码器,实现低转速下行星齿轮箱的局部故障检测。编码器还具有以下优势:编码器与行星齿轮箱的输入轴同轴安装,可以避免基于振动信号的故障诊断方法中由于信号时变传递路径所导致的问题[11-12];编码器采集的是轴系的转速、转角信号,受外界噪声干扰较小;编码器在低转速工况下仍能采集到故障导致的转速波动信息,而振动传感器低频响应的截止频率受限、低转速下故障激起的振动能量较弱,难以采集到高信噪比的信号;编码器采集的信号与角度严格对应,无需进行阶次跟踪,即可直接用于变转速工况下的分析,因此由编码器信号获得的IAS信号更易分析处理。研究中注意到,伺服电机在工业机器人、数控机床等高端装备中大量使用[13-14],其自带用于精确控制角度、转速的旋转编码器,若能使用伺服电机自带的编码器获取信号进行机械系统的故障检测,则可以有效解决外置传感器安装受限和成本高等问题,但目前基于伺服电机自带编码器进行故障检测的相关研究尚未开展。
综上所述,本文提出一种基于伺服电机自带编码器信号的齿轮故障检测方法。首先从自带编码器中获得记录旋转编码器角度位置的脉冲信号,由此计算得到IAS信号,然后在角域和阶次域分别对IAS信号进行分析和故障特征提取,实现齿轮局部故障的检测。最后以行星齿轮箱齿轮局部故障为例,在试验台上对所提方法进行试验,验证了本文所提方法的有效性。
增量式光电编码器是伺服电机中最常用的编码器[15],其主要功能是检测电机运动的角度和速度,结构如图1所示,由光栅编码盘、光源及其对应的感光元器件组成。编码器中光栅盘的刻线间隔均等,每转过一个分辨率区间,编码器输出一个增量脉冲方波。
光源与感光元器件位于编码盘的两侧,光源A和光源B用于生成A、B相的正交编码信号。在编码盘的内圈零位处刻有一个光栅,用于产生零位信号,即Z相。当编码盘旋转,其光栅经过光源时感光元器件便会接收到透过光栅的光学信号并将其转化为电信号以高低电平的方式输出,两个上升沿之间的时间对应一个光栅转过的角度,光栅编码器A、B、Z三个相位的波形如图2所示,图中M表示编码器的分辨率(线数),即每转的脉冲数。A、B相的信号在制造时严格保证这两个信号的相位差为90°,根据A、B相信号的超前和滞后可以判断电机的旋转方向。
伺服电机自带的增量式光电编码器输出信号包括A、B、Z三相位置信号和U、V、W三相互差120°的霍尔信号。这些输出信号中,输出的A、B、Z相信号用于反映转子在运动中的位置变化和速度,U、V、W相信号按照一定的时间顺序输出脉冲构成一低压三相电源用于控制电机的旋转[16]。A、B和Z相信号包含转子旋转的角度位置和转速信息,可用作旋转机械故障检测的信号来源。
伺服电机驱动器以固定时间间隔通过计数器获取编码器信号,从而测得当前角度位置和旋转速度,实现对电机旋转速度和角度的反馈控制。然而电机驱动器访问计数器的时间间隔相对于故障检测所需的采样频率较低,不适合故障检测。研究中在编码器信号接入电机驱动器之前直接对A、B、Z三相信号进行采集,用于IAS信号的精确估计。将自带编码器的A、B、Z三相信号分别分为两路,其中一路输入伺服电机驱动器用来反馈编码器的旋转角度、调整电机旋转位置,另外一路连接一个高速计数器,该高速计数器用于记录旋转编码器角度位置脉冲之间的时间间隔。用于控制伺服电机运动和采集伺服电机自带编码器信号的编码器接线如图3所示,图中VCC和GND分别为电源和接地连线,用于为电路提供工作电压。
使用伺服电机自带编码器信号对齿轮进行故障检测,首先需要获取编码器信号并将编码器脉冲信号转换为IAS信号。研究中使用T法[17]对被采集伺服电机自带编码器的相邻编码脉冲上升沿之间的时间间隔∆ti进行记录。设高速计数器获取的第i个(i=1,2,3,…)编码器脉冲上升沿的角度为φi,编码器的线数为M,则两编码器脉冲信号之间的相邻光栅间隔角度Δφ=2π/M。通过向前差分法[18]将采集到的编码器信号转换为IAS信号,即
式中,vφi)为在编码器角度φi处的IAS信号。
基于自带编码器信号的齿轮局部故障检测方法的流程图如图4所示,具体步骤如下:
(1)从伺服电机自带编码器中引出A、B、Z三相角度位置信号接线,通过高速计数器使用T法采集脉冲信号,并记录角度位置脉冲信号中相邻脉冲上升沿之间的时间间隔∆ti
(2)使用向前差分算法将采集到的编码器脉冲信号转换为IAS信号。
(3)使用S-G(Savitzky-Golay)滤波器进行误差抑制,S-G滤波是基于局域多项式最小二乘法拟合的滤波方法,根据编码器的线数确定合适的滤波窗长和拟合阶次,对获得的IAS信号进行滤波可以降低信号中的随机误差及编码器刻线位置等误差的干扰[19]
(4)在角域和阶次域对IAS信号进行数据处理及故障特征提取,实现齿轮局部故障的检测和诊断。
在如图5所示的行星齿轮箱传动试验台上进行试验,该传动试验台由一个伺服电机、一个NGW型行星齿轮箱和一个磁粉制动器及电机驱动器组成,伺服电机自带编码器为2500线的增量式光电编码器,行星齿轮箱的输入轴为太阳轮,输出轴为行星架。为验证本文方法的有效性,从试验台中伺服电机自带编码器引出接线采集自带编码器信号,另外在行星齿轮箱输出轴安装一个用来对比的2500线的外置编码器。
研究中,为使伺服电机自带编码器同时用于反馈调整电机转速及角度位置和输出用于故障检测的信号,按照1.2节接线方式将自带编码器接线中A、B、Z三相信号分为两路,引出接线如图6所示。将伺服电机自带编码器及用于对比的外置编码器连接至由微处理器芯片、高速时钟芯片和数据传输接口组成的高速计数器。所用高速计数器的时钟频率为40 MHz,采集方式为等角度采样,即每个光栅通过感光元器件时,在TTL输出信号的上升沿触发采样。通过高速计数器记录编码脉冲上升沿的时间点,通过微处理器得到相邻编码脉冲上升沿之间的时间间隔,然后通过传输接口传输至PC保存。试验中同时采集自带编码器及外置编码器的信号。
试验台中所用的NGW行星齿轮箱相关参数如表1所示。为模拟太阳轮局部故障,在太阳轮的一个齿上采用电火花加工一个深度约为0.4 mm的齿面剥落故障,如图7所示。
根据行星齿轮箱传动理论[20]可知,行星齿轮箱的传动比n为:
啮合阶次Om计算公式如下式所示:
式中,Os为太阳轮旋转阶次;Op为行星轮旋转阶次;Oc为行星架旋转阶次。
则太阳轮相对于行星架的相对旋转阶次为:
太阳轮旋转一圈,故障轮齿与3个行星轮分别啮合一次,故太阳轮故障阶次为Ors=3(Os-Oc)。
根据研究中使用行星齿轮箱的齿数,分别计算得到以太阳轮旋转频率为参考和以行星架旋转频率为参考的特征阶次,如表2所示。
在恒定转速工况下采集伺服电机自带编码器和输出端外置编码器的信号,转换为IAS信号后在角域和阶次域进行分析,验证基于伺服电机自带编码器信号的故障检测方法。试验中,设置伺服电机的输入转速为200 r/min,磁粉制动器的电压设置为10 V,采样时长设为180 s。
首先在正常状态下,对行星齿轮箱传动试验台中两个编码器信号进行采集,计算得到自带编码器的IAS信号如图8(a)所示,外置编码器的IAS信号如图8(b)所示,可以观察到自带编码器采集到的转速为200 r/min,外置编码器采集到的转速为40 r/min,与研究所用行星齿轮箱的传动比n=5相对应。
之后对太阳轮故障状态下行星齿轮箱传动试验台的两个编码器信号进行采集,计算得到自带编码器的IAS信号如图9(a)所示,外置编码器的IAS信号如图9(b)所示,从图中可以观察到输入和输出的转速与正常状态大体一致。在角域中对正常状态和太阳轮局部故障状态下两编码器获得的IAS信号进行对比分析。正常与故障状态下自带编码器获得的IAS信号对比如图10(a)所示,正常与故障状态下外置编码器采集的转速信号对比如图10(b)所示。从图中可以看出,与正常状态相比,太阳轮故障状态下两编码器采集的转速信号中均出现了由故障引起的转速周期性波动。
在阶次域中对正常状态和太阳轮局部故障状态下自带编码器获得的IAS信号进行对比分析。对两组不同状态下的自带编码器IAS信号作傅里叶变换,分别得到正常状态下和太阳轮局部故障状态下自带编码器IAS信号的阶次谱,如图11(a)和(b)所示。可以看出,正常状态下自带编码器的IAS信号阶次谱中与故障阶次Ors相关的谱线及边带均不明显,太阳轮故障状态下自带编码器的IAS信号阶次谱中出现了较为明显的与故障阶次Ors相关的谱线及边带,啮合阶次的边带中出现与故障阶次相关的边带可以说明故障的存在[21],因此证明太阳轮存在局部故障。由于在电机运行过程中,电机轴转速信号中会出现与电机磁极对数相对应的频率分量[22],研究中使用的电机磁极对数为5,因此在正常和故障信号的阶次谱中均出现了与5阶及其倍数相关的阶次谱线。
对正常和太阳轮局部故障状态下的外置编码器IAS信号作傅里叶变换,得到阶次谱分别如图12(a)和(b)所示。可以看出,正常状态下的IAS信号阶次谱中与故障阶次Ors相关的谱线及边带均不明显,太阳轮故障状态下的IAS信号阶次谱中出现了较为明显的与故障阶次Ors相关的谱线及边带。这与文献[9-10]在行星齿轮箱输出轴安装编码器获得的结果一致。
与外置编码器获得的IAS信号相比,使用自带编码器获得的IAS信号同样可以提取到行星齿轮箱的故障特征,并且无需外置设备,验证了使用自带编码器信号进行故障检测的优势。在研究所使用的试验台中,自带编码器与行星齿轮箱轴系刚性连接,而外置编码器与行星齿轮箱轴系通过联轴器连接且外接负载,因此外置编码器获得的IAS信号受到的干扰更为严重,在自带编码器IAS信号的阶次谱中故障谱线更加清晰。
为证明低转速工况下采用伺服电机自带编码器信号进行故障特征提取的可行性,分别以自带编码器采集正常状态下行星齿轮箱和太阳轮故障状态下行星齿轮箱的信号,计算得到IAS信号,并在角域和阶次域进行分析。设置伺服电机转速为30 r/min,磁粉制动器的电压设置为10 V,采样时长设为180 s。
正常状态和太阳轮故障状态下自带编码器获得的IAS信号分别如图13(a)和(b)所示,从图中可以看出,两种状态下编码器的转速大体一致,但故障状态下IAS信号中存在大量的速度波动。
在角域信号中对两种状态下自带编码器获得的IAS信号进行对比分析,如图14所示。从图14中可以看出,与正常状态相比,太阳轮局部故障引起了周期性的转速波动。
在阶次域中对两种状态下自带编码器获得的IAS信号进行对比分析,IAS信号阶次谱分别如图15(a)和(b)所示。可以看出,在正常状态下自带编码器获得的IAS信号阶次谱中,与故障阶次Ors相关的谱线及边带不明显;在太阳轮局部故障状态下自带编码器获得的IAS信号的阶次谱中,与故障阶次Ors相关的谱线边带明显增高。验证了低转速工况下采用自带编码器信号进行故障检测方法的有效性。
为证明变转速工况下采用伺服电机自带编码器信号进行故障特征提取的可行性,分别以自带编码器采集正常状态和太阳轮故障状态下行星齿轮箱的信号,计算得到IAS信号,并分别在角域和阶次域进行分析。
研究中,设置伺服电机的转速从20 r/min升至100 r/min。两种状态下伺服电机自带编码器获得的IAS信号分别如图16(a)和(b)所示,可以看出两种状态下太阳轮的转速大体一致。
在角域信号中对两种状态下自带编码器获得的IAS信号进行对比分析,如图17所示,从图中可以看出太阳轮故障引起了转速的周期性波动。
在阶次域中对两种状态下自带编码器获得的IAS信号进行对比分析,IAS信号阶次谱分别如图18(a)和(b)所示。可以看出,正常状态下自带编码器获得的IAS信号阶次谱中与故障阶次Ors相关的谱线及边带不明显;太阳轮局部故障状态下IAS信号的阶次谱中出现了与故障阶次Ors相关的谱线边带。验证了变转速工况下,采用自带编码器信号进行故障检测的有效性。
本文针对现有齿轮局部故障检测方法均需要安装外置传感器的不足,提出一种基于伺服电机自带编码器信号的故障检测方法。得出如下结论:
(1)利用伺服电机自带编码器的信号,可实现齿轮的局部故障检测,该检测方式无需安装外置传感器。
(2)伺服电机自带编码器信号转换的IAS信号包含丰富的故障转速信息,可以有效克服固定位置安装传感器采集到的信号受时变传递路径影响严重和变转速工况下信号处理复杂的缺点。
  • 国家自然科学基金资助项目(52165067)
  • 云南省重点领域科技计划项目(202002AC080001)
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2025年第38卷第4期
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doi: 10.16385/j.cnki.issn.1004-4523.2025.04.022
  • 接收时间:2023-06-15
  • 首发时间:2026-02-12
  • 出版时间:2025-04-10
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  • 收稿日期:2023-06-15
  • 修回日期:2023-10-17
基金
国家自然科学基金资助项目(52165067)
云南省重点领域科技计划项目(202002AC080001)
作者信息
    昆明理工大学机电工程学院,云南 昆明 650550

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郭瑜(1971—),男,博士,教授。E-mail:
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
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