CAJ | 학술논문

基于一种新的机车齿轮箱振动信号去噪的模型及算法，在分析总结大量实际振动信号的基础上，探讨运用盲反卷积去噪的方法以提高信号信噪比和信号质量，通过提取机车齿轮的故障特征信息并与TSA（时间同步平均）方法相比较，其在准度和精度方面都有较大改善。不仅能满足在线监测和故障诊断的实时性和可靠性的要求，同时显示出属性的可靠性、耐用性和高置信度性，提高了诊断和预警的技术。
기우일충신적궤차치륜상진동신호거조적모형급산법，재분석총결대량실제진동신호적기출상，탐토운용맹반권적거조적방법이제고신호신조비화신호질량，통과제취궤차치륜적고장특정신식병여TSA（시간동보평균）방법상비교，기재준도화정도방면도유교대개선。불부능만족재선감측화고장진단적실시성화가고성적요구，동시현시출속성적가고성、내용성화고치신도성，제고료진단화예경적기술。
This paper introduced a new gearbox vibration signal de-noising locomotive model and algorithm based on the analysis of a lot of the actual vibration signals,to discusses the use of blind deconvolution de -noising methods so as to improve the noise ratio and signal quality,by extracting characteristic information of the motorcy-cle gear and comparing with TSA (time Synchronization average)method,by which the results were greatly im-proved in accuracy and precision.The proposed method can not only meet the requirements of real-time charac-teristics and reliability in the respect of online monitoring and fault diagnose,but also show the reliability proper-ties,durability and high degree of confidence,which improves the diagnosis and early warning techniques.