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1、摘 要基于嵌入式处理器的红外火焰检测装置的设计摘 要随着国民经济的高速发展，我国工矿企业等国民经济生产单位对电能和热能的需求量正在迅猛地增长。这促使大型火力发电站、石油化工型动力站、城市集中式供热站和厂矿废料燃烧站等重要国民经济生产单位使用的大型锅炉日益增多。大型锅炉炉膛内燃烧情况复杂且燃料供给量大，监控锅炉的整体燃烧情况显得尤为重要，检测装置的性能直接影响到在役电站锅炉的安全性和经济性。研发出高性能的火焰检测装置将具有良好的社会效益和经济效益。大型锅炉运行情况复杂，运行人员在做控制决策时往往希望能够掌握尽可能多的工况参数。同时大型锅炉用户更希望关键性设备能在故障发生之前的合理时间范围内给出告
2、警信息以便有针对性地安排设备检修，避免非计划性停产造成经济损失。客户已迫切要求火焰检测装置不仅能可靠地判定出火焰是否存在，而且能提供火焰燃烧稳定度的定量分析结果。本文首先对火焰的物理特性进行了进一步的分析，并使用傅里叶变换、短时傅里叶变换和小波变换等多种分析方法对采样的火焰数据进行分析和对比，并结合具体硬件处理平台分析这几种分析方法在判定火焰存在及火焰燃烧质量方面的优缺点，以确定最优效能的信息提取方法。只有对被检测对象的特性进行深入了解之后才能有针对性地开展工作。因此首先对炉膛煤粉火焰的物理特性进行详细的分析，特别涉及到对煤粉火焰的红外辐射特性的分析，通过分析后认为煤粉火焰信号是一类“准平稳”
3、信号。确定红外型火焰检测装置的检测视场的选取原则。根据煤粉火焰的特性确定了火焰检测装置所应采用的系统采样频率，并确定了抗混叠滤波器的相关参数的取值范围。傅里叶变换是信号处理中最常用的处理方法之一，文中对傅里叶变换理论基础进行了简单介绍，详细地描述了快速傅里叶变换算法的具体数学实现。对煤粉火焰数据使用快速傅里叶变换方法进行信息提取，对提取到的信息进行了分析。由于标准傅里叶变换只在频域中具有局部分析能力，而在时域内不具备局部分析能力，文中介绍了短时傅里叶变换的理论基础，较为详细地描述了短时傅里叶变换算法的具体数学实现过程，并对煤粉火焰数据使用短时傅里叶变换方法进行信息提取。经过分析后认为这种方法不
4、但可以准确地识别出燃烧器处是否存在煤粉火焰信号，而且较为准确提供判断燃烧稳定度方面的信息。小波变换是在傅立叶变换无法满足非平稳信号的分析要求而产生的一种新变换方法。它在本质上是一种时频分析方法，具有多分辨率分析的优秀品质，成功地克服了短时傅立叶变换的单一分辨率的缺陷。小波变换具备在时频域内表征信号特征的能力。文中简略地介绍了小波变换的理论基础，对选择母小波的进行了分析，同时较为详细地描述Mallat算法的具体数学实现过程，并对煤粉火焰数据使用小波变换方法进行信息提取。经过分析后认为这种方法不仅可以准确地识别出燃烧器处是否存在煤粉火焰信号，而且能准确提供出判断燃烧稳定度方面的信息，并且能够精准地
5、提供关键的时频域信息。考虑到火焰检测装置的硬件系统当前的发展和使用情况，认为短时傅里叶变换是目前综合效能较佳的一种用于煤粉火焰信号信息提取的方法。小波分析方法具有非常显著的信息提取效果，在系统硬件允许的情况下，应重点考虑使用小波分析方法对煤粉火焰信号进行信息提取，小波分析方法在今后会日益广泛地具体应用到火焰分析的工程实践中。针对传统火焰检测设备的探头输出信号容易出现饱和失真的情况，在探头电路中引入了对数放大电路，将动态范围压缩到便于处理的程度之内。将传统火焰检测设备的信号滤波方式由无源滤波方式改进为有源滤波方式，更高效地滤除了有用频带外的干扰信号，利于后继的数字信号处理。本火焰检测装置的核心处
6、理器是AT91SAM9G45嵌入式处理器，拥有强大数据处理能力和业务管理能力。成功地在该火焰检测设备上分别实现基于短时傅里叶变换的信息提取和基于小波变换的信息提取。目前该型号火焰检测设备已应用于多个不同炉型的大型锅炉上。它们均能正确地识别煤粉火焰的存在，并能较准确地给出燃烧稳定度的信息，取得了良好的社会效益和经济效益。关键词： 火焰检测装置 红外 傅里叶变换 短时傅里叶变换 小波变换 对数放大 嵌入式处理器VIIAbstractDesigning of embedded processor-based infrared flame detection deviceIntroduction of
7、 the author: LiYiping, male, was born in July, 1983 whose tutor was Professor HuangHu. He graduated from Chengdu University of Technology in Electronics and Communications Engineering major and was granted the Master Degree in June, 2013.AbstractDue to the complexity of the operation of large-scale
8、boiler, run control decisions tend to want to be able to grasp as much as possible working parameters. Large boiler users are more critical equipment within a reasonable time prior to the failure alarm information is given in order to arrange equipment maintenance, to avoid unplanned shutdown caused
9、 economic losses. The customer has an urgent requirement flame detection device not only be able to reliably determine the presence of the flame, and flame stability Qualitative and quantitative analysis results. Firstly further analysis on the physical characteristics of the flame, and the use of F
10、ourier transform, short time Fourier transform and wavelet transform a variety of analytical methods for sampling Fire data analysis and comparison, and combined with a specific hardware processing platform analysis of the advantages and disadvantages of several analytical methods to determine the p
11、resence of a flame and the flame quality, information extraction method to determine the optimal performance.Only after depth understanding of the characteristics of the object to be detected can be targeted to work. First to conduct a detailed analysis of the physical characteristics of the furnace
12、 pulverized coal flame, and in particular relates to the analysis of the infrared radiation characteristics of the pulverized coal flame, and through analysis that the pulverized coal flame signal is a quasi-stationary signal. Determine the infrared flame detection device detection field of view of
13、the principle of selecting. Flame detection device to be used by the system sampling frequency is determined according to the characteristics of the pulverized coal flame, and to determine the range of the anti-aliasing filter parameters.The Fourier transform is one of the most commonly used approac
14、h in modern signal processing, a brief introduction of the theoretical basis of the Fourier transform, fast Fourier transform algorithm mathematical process is described in more detail. Pulverized coal flame using the fast Fourier transform method of information extraction, and extract the informati
15、on. Since the standard Fourier transform in the frequency domain with local analytical capacity, and do not have the local analysis capabilities in the time domain, the Dennis Gabor in 1946 introduced the concept of short-time Fourier transform. This paper introduces the theoretical basis of the sho
16、rt time Fourier transform, a more detailed description of the short time Fourier transform algorithm mathematical process, and the pulverized coal flame data using the short time Fourier transform method of information extraction. After the analysis that this method can accurately identify the existence of a pulverized coal flame at the burner signal, but more accurately determine the combustion stability information.The wavelet trans
