廖辉, 周国荣. 大型混合干扰系统真实信号的实时辨识与提取[J]. 信息与控制, 2003, 32(5): 413-417.
引用本文: 廖辉, 周国荣. 大型混合干扰系统真实信号的实时辨识与提取[J]. 信息与控制, 2003, 32(5): 413-417.
LIAO Hui, ZHOU Guo-rong. REAL-TIME IDENTIFICATION AND EXTRACTION OF REAL SIGNAL IN LARGE-SCALE MIXED DISTURBANCE SYSTEM[J]. INFORMATION AND CONTROL, 2003, 32(5): 413-417.
Citation: LIAO Hui, ZHOU Guo-rong. REAL-TIME IDENTIFICATION AND EXTRACTION OF REAL SIGNAL IN LARGE-SCALE MIXED DISTURBANCE SYSTEM[J]. INFORMATION AND CONTROL, 2003, 32(5): 413-417.

大型混合干扰系统真实信号的实时辨识与提取

REAL-TIME IDENTIFICATION AND EXTRACTION OF REAL SIGNAL IN LARGE-SCALE MIXED DISTURBANCE SYSTEM

  • 摘要: 在存在大量混合随机干扰的系统中,采用一种特征值信号的智能提取方法.通过对对象信号波形的特征搜索,实时地辨识和提取能反映被测对象真实状态的特征信号,有效地抑制干扰对波形信号的影响,大大提高整个系统的检测和监控精度.文章给出了对象模式特征的表述、特征信号的生成与提取的理论描述和实现方法.实际工程项目中的成功应用表明,该方法具有很强的处理信号干扰的能力,尤其适用于受现场混合干扰影响的系统的分析与监控,具有很好的应用和推广价值.

     

    Abstract: This paper presents an intelligent method of eigenvalue extraction for the systems with a great deal of mixed and stochastic disturbances. Through searching features of waveform signal of objects, this method can identify and extract feature signals which can indicate real state of the measured objects and restrain the influence of disturbance in field signal. As a result, the testing and monitoring accuracy is greatly improved. Theoretic description and application of the expression of object features, and formation and extraction of feature signal are presented in this paper. Successful application of this method to practical projects shows that it has a good ability to process disturbance signals. Especially, it is very suitable for the cases of system analysis and monitoring under the influence of field mixed disturbance.

     

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