Acoustic tomography system for online monitoring of temperature fields

Yan, Hua; Ma, Zhiyong; Zhou, Ying

doi:10.1049/iet-smt.2016.0303

Cited by 21 publications

(16 citation statements)

References 18 publications

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“…Details about the robust and accurate measurement of TOF data can be found in referenceYan et al 1 and Ewan and Ireland. 39 The transceiver layout shown in Figure 1 was used.…”

Section: Experiments Systemmentioning

confidence: 99%

“…Due to the low thermal mass of the exposed tip, it has an extremely fast response time. 1 Table 3 shows a comparison between the measured temperature of the thermocouple and the reconstructed temperature of the different reconstruction algorithms. The error ( E %) of the reconstructed temperature relative to the measured temperature is also given in Table 3.…”

Section: Experimental Studiesmentioning

confidence: 99%

“…Temperature measurement techniques can be classified as contact measurement (where the sensor such as a thermocouple is installed in the medium of interest) and non-contact measurement (where the monitoring system observes the medium of interest remotely). 1 Acoustic tomography (AT) [2][3][4] is one of a few non-contact measurement techniques that can present information about the temperature distribution. Due to its advantages, such as non-intrusive sensing, wide measuring range, low cost, convenient maintenance, and strong environment adaptability, AT is considered to be a promising temperature distribution measurement technology.…”

Section: Introductionmentioning

confidence: 99%

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Temperature Distribution Reconstruction Method for Acoustic Tomography Based on Compressed Sensing

et al. 2022

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Acoustic tomography (AT) is one of a few non-contact measurement techniques that can present information about the temperature distribution. Its successful application greatly depends on the performance of the reconstruction algorithm. In this paper, a temperature distribution reconstruction method based on compressed sensing (CS) is proposed. Firstly, a measurement matrix of an AT system in a CS framework is established. Secondly, a sparse basis is selected based on the mutual coherence between the measurement matrix and sparse basis. Thirdly, an improvement of the orthogonal matching pursuit (OMP) algorithm, called the IMOMP algorithm, is proposed for pursuing efficiency in recovering sparse signals. Reconstruction experiments of Gaussian sparse signals showed that IMOMP was better than OMP in both success ratio and running time, and the selection method of sparse basis was effective. Finally, a temperature distribution reconstruction algorithm based on compressed sensing, that is, the CS-IMOMP algorithm, is proposed. Simulation and experiment results show that, compared with the least square algorithm and the Simultaneous Iterative Reconstruction Technique algorithm, the CS-IMOMP algorithm has smaller reconstruction errors and provides more accurate information about the temperature distribution.

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“…Details about the robust and accurate measurement of TOF data can be found in referenceYan et al 1 and Ewan and Ireland. 39 The transceiver layout shown in Figure 1 was used.…”

Section: Experiments Systemmentioning

confidence: 99%

Section: Experimental Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Temperature Distribution Reconstruction Method for Acoustic Tomography Based on Compressed Sensing

et al. 2022

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“…In addition to these applications, acoustic tomography also gains a great deal of interest in atmospheric imaging to monitor the temperature and wind velocity distributions of air. Reported research on atmospheric imaging based on acoustic tomography includes the atmosphere vertical temperature structure monitoring using acoustic waves from powerful explosions on the ground [14,15], the horizontal temperature and wind velocity field monitoring of the near surface atmosphere [16,17], the indoor climate monitoring system [18][19][20][21], and the furnace or boiler temperature field monitoring system [22][23][24].…”

Section: Background and Motivationmentioning

confidence: 99%

“…The algebraic-based algorithms are the most widely used approach throughout the literatures [13,17,18,20,21,28,32,33,[53][54][55][56] However, there are two difficulties before this least square solution is applied.…”

Section: Algebraic-based Algorithmsmentioning

confidence: 99%