CAJ | 학술논문

信号趋势包含重要的过程状态信息,识别趋势可以进行故障诊断.但由于随机噪声、外部干扰及信号波动等因素的影响,很难准确识别线性基元.从统计学的角度出发,引入导数值置信区间.把线性基元导数值阈值的设定转换成置信度的设定,从而提高了趋势识别算法的适应性和鲁棒性.实例验证表明该方法能准确识别线性基元.
신호추세포함중요적과정상태신식,식별추세가이진행고장진단.단유우수궤조성、외부간우급신호파동등인소적영향,흔난준학식별선성기원.종통계학적각도출발,인입도수치치신구간.파선성기원도수치역치적설정전환성치신도적설정,종이제고료추세식별산법적괄응성화로봉성.실례험증표명해방법능준학식별선성기원.
Signal trend comprises important process state information, and trend identification can be used for fault diagnoses. But under the influence of random noise, external disturbance and signal fluctuation, it’s hard to identify linearity primitives. According to statistics, this paper inducts confidence interval of derivative value. It converts the enactment of linearity primitive derivative threshold into confidence degree enactment, improving the adaptability and robustness of trend identification arithmetic. Examples indicate that this way can identify linearity primitives exactly.