尘埃粒子计数器光电传感器信号熵特性研究

【作者】 赵亚民；

【导师】 卞保民；

【作者基本信息】 南京理工大学 ， 光学工程， 2008， 硕士

【摘要】 信息论是在长期的通信工程的实践中,与概率论、随机过程和数理统计这些数学学科相结合而逐步发展起来的一门新兴科学。随着信息概念的不断深化,它在科学技术上的重要性早已超越了狭义的通信工程的范畴,在许多领域中日益受到科学工作者的重视。首先,本文用信息论的方法分析传感器系统。论述了测量系统的组成部分(待测对象、测量过程以及测量结果)具有不确定性,这种不确定性反映出测量系统具有信息的特性,总结出测量系统的信息熵。根据测量系统的信息熵,具体分析尘埃粒子技术光电传感器系统所具有的信息的特性,逐步建立了尘埃粒子计数测量过程的信息熵模型,并且分析了噪声熵、损失熵等各种熵的物理意义。其次,通过对颗粒物单粒子光散射幅度分布信息熵的研究,分析获取传感器系统测量过程的信息的不同方法。通过颗粒物单散射信号幅度计数分布的测量实验,反演尘埃粒子计数器测量信号幅度分布的信息熵,通过测量误差与信息熵之间的关系,选取划分通道数的优化方式。更多还原

【Abstract】 In the long-term telecommunications projects in practice, Information Theory, combined with Probability Theory, Random Process of Mathematics and Statistics, is an emerging science developed gradually. With the continuous deepening of the concept of information, it has been far beyond the narrow scope of the telecommunications projects. In many areas, science workers pay more and more attention on it.First, this paper uses information theory to analyze measurement system. According to the components of the measurement system (object under test, measurement results and measuring process) is uncertainty; this uncertainty reflects the measurement system with the characteristics of information. Then, this article descripts the measurement system in entropy. According to the information entropy of the measurement system, this paper specifically analyzes the information characteristics of photoelectric sensor system in the optical particles counter, and gradually establishes an entropy model of optical particle count measurement process.Secondly, according to the information entropy of the signal range probability distribution, this paper analyzes two different ways to partition counting channels. Also this paper calculates the information entropy of the signal range probability distribution. Considering the relationship between precision in the measuring and the information entropy, it helps optimizing the selection of channels.更多还原