摘要
针对压电式选针器在提花过程中故障特征难以判断的问题,提出了一种基于随机共振-反向传播(SR-BP)算法的压电选针器渐变失效检测方案。研究压电选针器提花过程中驱动件的运动状态及其双向压电效应产生的电信号,对渐变失效状态下的压电陶瓷驱动件内部电信号进行随机共振(SR)故障诊断。提取振动序列的时域及频域参数与SR参数生成训练样本,通过算法使特征参数匹配出最优SR参数,将压电选针器振动信号与噪声信号混入SR参数形成的非线性系统中,观察该系统输出量的时域和频域变化达到快速检测故障的目的。研究结果表明:选针器失效后时域特征在30~350 Hz将发生明显差异,全参数的SR-BP故障检测方法的精确度可达到97.5%,信噪比达到7.36 dB,可有效地对压电选针器进行故障检测。
Objective Piezoelectric needle selector is the driver of jacquard needles.Its performance is related to the quality of jacquard knitting production during the process of needle hooking and looping.Aging of piezoelectric crystal or peeling off intermediate bonding layer would cause gradual failure of the actuator.Once the needle selector fails to act normally during knitting process,it would lead to defects such as off-pattern,holes in cloth surface,and even machine failures e.g.,pin impact and pin breakage.The existing piezoelectric needle selector uses open loop control,and the results of needle selector would not be perceived.Hence,the control system would not be able to judge whether the action of the knife head of the needle selector is accurate,and the abnormal operation of the piezoelectric needle selector often causes mechanical failure or abnormal jacquard knitting.Method Given the difficulty in identifying fault characteristics of the piezoelectric needle selector during the jacquard process,a gradient failure detection scheme based on the stochastic resonance-BP(SR-BP)algorithm for the piezoelectric needle selector was proposed.The study investigated the motion state of the driving component:the twin-crystal piezoelectric cantilever beam during the jacquard process of the piezoelectric needle selector,as well as the electric signal generated by its dual-directional piezoelectric effect.For the internal electric signals of the piezoelectric ceramic driver in a gradient failure state,SR fault diagnosis was conducted,and the SR-BP model was established.By extracting the time-domain and frequency-domain parameters of the vibration sequence and SR parameters to generate training samples,the algorithm was made to match the feature parameters to obtain the optimal SR parameters.The vibration signal of the piezoelectric needle selector was mixed with the noise signal into the nonlinear system formed by the SR parameters,and the time-domain and frequency-domain changes of the system output was observed to achiev
作者
齐育宝
汝欣
李建强
周悦欣
彭来湖
QI Yubao;RU Xin;LI Jianqiang;ZHOU Yuexin;PENG Laihu(Key Laboratory of Modern Textile Machinery&Technology of Zhejiang Province,Zhejiang Sci-Tech University,Hangzhou,Zhejiang 310018,China;Zhejiang Sci-Tech University Longgang Research Institute,Wenzhou,Zhejiang 325000,China)
出处
《纺织学报》
EI
CAS
CSCD
北大核心
2024年第3期202-208,共7页
Journal of Textile Research
基金
浙江省博士后科研项目(ZJ2020004)。
关键词
针织机械
压电选针器
随机共振
共位检测
BP神经网络
失效分析
knitting machinery
piezoelectric needle selector
stochastic resonance
colocation detection
BP neural network
failure analysis
