Online monitoring of the two-dimensional temperature field in a boiler furnace based on acoustic computed tomography. (22nd January 2015)

• Record Type: Journal Article
• Authors: Zhang, Shiping; Shen, Guoqing; An, Liansuo; Niu, Yuguang
• Is Part Of: Applied thermal engineering. Volume 75(2015:Jan.)
• Page Start: 958
• Page End: 966
• Publication Date: 2015-01-22
• Subjects: Online monitoring -- Optimal adjustment -- Acoustic computed tomography -- Time delay estimation -- Generalized cross-correlation technique; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2014.10.085
• Languages: English
• ISSNs: 1359-4311

Abstract

Abstract: Online monitoring of the temperature field is crucial to optimally adjust combustion within a boiler. In this paper, acoustic computed tomography (CT) technology was used to obtain the temperature profile of a furnace cross-section. The physical principles behind acoustic CT, acoustic signals and time delay estimation were studied. Then, the technique was applied to a domestic 600-MW coal-fired boiler. Acoustic CT technology was used to monitor the temperature field of the cross-section in the boiler furnace, and the temperature profile was reconstructed through ART iteration. The linear sweeping frequency signal was adopted as the sound source signal, whose sweeping frequency ranged from 500 to 3000 Hz with a sweeping cycle of 0.1 s. The generalized cross-correlation techniques with PHAT and ML were used as the time delay estimation method when the boiler was in different states. Its actual operation indicated that the monitored images accurately represented the combustion state of the boiler, and the acoustic CT system was determined to be accurate and reliable. Highlights: An online monitoring approach to monitor temperature field in a boiler furnace. The paper provides acoustic CT technology to obtain the temperature profile of a furnace cross-section. The temperature profile was reconstructed through ART iteration. The technique is applied to a domestic 600-MW coal-fired boiler. The monitored images accurately represent the combustion state of the boiler.