The Acoustic Temperature Signal Of The Boiler Furnace Temperature Field Optimization

The research on distribution of the temperature field in the furnace is significant to the combustion optimization and the boiler control.The temperature distribution,flames' location and the heat transfer of the furnace can be obtained by detecting the distribution of the temperature field and its change.However,due to the poor working environment,the complex equipment structure and the numerous transmission path in the practical engineering application,the acoustic temperature measurement signal which is often disturbed by the boiler operating factors and the strong boiler noise is abnormal.For this reason,it is very important to find an efficient and efficient method for optimizing the acoustic temperature measurement signal.According to the characteristics of boiler noise and the characteristics of acoustic temperature measurement device,the paper studies the optimization and enhancement technology of acoustic temperature measurement signal for the temperature field.The main research contents include:1)The principle and the basic theory of signal feature extraction and the design of the classifier are introduced.The characteristics of statistical feature extraction and wavelet packet coefficient extraction are compared,and the characteristics of energy distribution of four types of signals in different frequency bands are extracted.Feature extraction based on Energy distribution after wavelet packet and classification algorithm is put forward.2)The paper studies the characteristics of the noise of the furnace and discusses the principle and algorithm of the modulus maxima denoising of the temperature field acoustic temperature signal.The temperature field acoustic temperature measurement signal is improved by combining the results of the threshold selection process.Then the paper proposes a threshold to improve the modulus maximum denoising algorithm.Finally,the simulation results are simulated and compared by using the modulus maxima algorithm.3)The feasibility and effectiveness of the threshold-modified modulus maxima algorithm are verified under the conditions of stable operating conditions and the conditions of boiler start and stop,air volume adjustment and so on.The study provides a wealth of practical experience for the application of the acoustic temperature measurement signal optimization technology.