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作 者:王兴 郑飂默[3] 张晋塬 高菲 王雨竹 WANG Xing;ZHEN Liaomo;ZHANG Jinyuan;GAO Fei;WANG Yuzhu(School of Electronic Information Engineering,Shenyang Institute of Computing Technology,Chinese Academy of Sciences,Shenyang 110168;School of Computer Science and Technology,University of Chinese Academy of Sciences,Beijing 100049;School of Computer Science and Technology,Taiyuan University of Science and Technology,Taiyuan 030024)
机构地区:[1]中国科学院沈阳计算技术研究所自动化装备事业部,沈阳110168 [2]中国科学院大学计算机科学与技术学院,北京100049 [3]太原科技大学计算机科学与技术学院,太原030024
出 处:《高技术通讯》2023年第2期176-184,共9页Chinese High Technology Letters
基 金:山西省专利推广实施资助专项(20210521);国家自然科学基金面上项目(41372350);山西省重点实验室项目(202204010931026)资助。
摘 要:针对铁路货车在高速重载行车状态下的轮轴智能检测和轴承故障难以诊断问题,研究设计了一种高速重载铁路货车轮轴智能检测系统。通过构建系统的软件和硬件结构模型,制定通信指令集的编码和解码规则,设计智能化指令调度策略,编写专家控制产生式规则。同时采用基于有限脉冲响应-经验模态分解(FIR-EMD)和改进支持向量机(SVM)的铁路轴承故障诊断方法,实现铁路轴承故障有效分类。提出一种高速重载轮轴检测领域中可编程的智能化测控方法,能够对现场设备的控制程序进行重构和功能扩展。实验测试及结果表明,该系统设备的设计满足铁路货车轮轴高速度、大重载、智能化检测的需求。Aiming at the problem of intelligent detection about axle and bearing fault diagnosis of railway wagons under high-speed and heavy-duty driving condition,this paper designs an intelligent detection system for wheel and axle of railway heavy trucks with high speed.The effective classification of railway bearing faults is realized by constructing the software and hardware structure model of the system,formulating coding and decoding rules of communication instruction set,designing intelligent scheduling strategy of instruction,writing expert control generation rules and using the fault diagnosis method of railway bearing based on finite impulse response-empirical mode decomposition(FIR-EMD)and improved support vector machine(SVM).This paper presents a programmable intelligent measurement and control method in the field of detection on axle with high speed and heavy load,which can reconstruct the controlled program of field equipment and implement functional extensions.The experimental results show that the design of the system realizes intelligent detection of truck axles with high speed and heavy load.
分 类 号:TP274[自动化与计算机技术—检测技术与自动化装置] U279.323[自动化与计算机技术—控制科学与工程]
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