| 引用本文: | 温熙森,唐丙阳,鄢斌.基于 AR 模型和SPRT 检验法的过程状态监测.[J].国防科技大学学报,1992,14(2):1-4.[点击复制] |
| Wen Xisen,Tang Bingyang,Yan Bin.Process State Detection Based on Auto-Regressive Model and Sequential Probabllities Ratio Test[J].Journal of National University of Defense Technology,1992,14(2):1-4[点击复制] |
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| 基于 AR 模型和SPRT 检验法的过程状态监测 |
| 温熙森, 唐丙阳, 鄢斌 |
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(精密机械与仪器系)
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| 摘要: |
| 本文利用自适应卡尔曼滤波器原理建立机械系统过程监测模型-AR模型，并根据 AR 模型系数的变化可以表征系统过程状态这一特点，通过序贯概率比 (SPRT）这一假设检验法，对机械系统的运行状况进行判别。实验表明，该方法行之有效，最后，本文给出了实验结果。 |
| 关键词: 过程状态监测，AR 模型，卡尔曼滤波，序贯概率比检验法 (SPRT) |
| DOI： |
| 投稿日期：1991-12-18 |
| 基金项目:国家“863”高技术发展基金资助项目 |
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| Process State Detection Based on Auto-Regressive Model and Sequential Probabllities Ratio Test |
| Wen Xisen, Tang Bingyang, Yan Bin |
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(Department of Precision Machinery and Instrument)
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| Abstract: |
| The machining system process monitonig model is built on basis of the kalman filter theory and Auto-Regressive model in this paper. The system process condition can be determined by the parameters variation of the AR-model and the hypothesis testing method of sequential probability ratio test on parameter derivation covariance matrix. |
| Keywords: process condition monitoring,AR-model Kalman filter,SPRT method |
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