1. 华北电力大学能源动力与机械工程学院
2. 深圳量云能源网络科技有限公司
纸质出版:2026
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李盛之, 张世平, 袁俊, 等. 垃圾焚烧炉SNCR系统温度场声感知时间延迟估计方法研究[J]. 热力发电, 2026,(8).
李盛之, 张世平, 袁俊, et al. 垃圾焚烧炉SNCR系统温度场声感知时间延迟估计方法研究[J]. Thermal Power Generation, 2026, (8).
李盛之, 张世平, 袁俊, 等. 垃圾焚烧炉SNCR系统温度场声感知时间延迟估计方法研究[J]. 热力发电, 2026,(8). DOI: 10.19666/j.rlfd.202511071.
李盛之, 张世平, 袁俊, et al. 垃圾焚烧炉SNCR系统温度场声感知时间延迟估计方法研究[J]. Thermal Power Generation, 2026, (8). DOI: 10.19666/j.rlfd.202511071.
【目的】为垃圾焚烧炉SNCR系统在850~1 100℃温度窗口内实现精准声学控温,提供高可靠性的时延估计数据与方法支持。【方法】提出一种基于声学测温的VMD-WT-GCC时延估计方法,该方法通过变分模态分解(VMD)与小波阈值(WT)降噪的协同处理,以提升强噪声环境下的时延估计精度,并利用现场噪声数据进行模拟验证,同时在受控实验室环境及工业现场开展实验测试。【结果】基于现场噪声数据的模拟表明,在信噪比5~–10 dB的范围内,所提VMD-WT降噪法在模拟信噪比增益、结构相似性指数和相关系数等指标上均显著优于单一的小波阈值降噪法;实验室实验在(–3.2±0.5)℃的受控环境下进行,在1~5 m的不同传播路径上,测温平均绝对误差均低于0.20℃;现场工业试验进一步证实,于距离地面30.1 m高的垃圾焚烧炉SNCR系统所在断面上,单路径声学测温结果与基准数据的偏差平均稳定在50℃以内。【结论】该研究所提方法在强噪声背景下展现出优越的时延估计精度与稳定性,为垃圾焚烧炉SNCR系统的高精度温度监测提供了有效技术途径,具有显著的工程应用前景。
[Objective] Precise temperature monitoring within the optimal reaction window(850~1 100 ℃) is critical for the efficiency and low-emission operation of selective non-catalytic reduction(SNCR) systems in waste incineration furnaces. Conventional contact-based measurement methods often suffer from time lag
mechanical fragility
and limited adaptability to harsh
high-temperature environments. This study aims to develop a robust acoustic thermometry technique to provide highly reliable time-delay estimation
thereby enabling accurate and real-time temperature monitoring for SNCR system control. [Methods] To address the challenge of strong background noise in industrial settings
an enhanced time-delay estimation method named VMD-WT-GCC is proposed. The core innovation lies in the synergistic combination of variational mode decomposition(VMD) and wavelet threshold(WT) denoising as a pre-processing step for the generalized cross-correlation(GCC) algorithm. The VMD adaptively decomposes the acquired acoustic signal into intrinsic mode functions
effectively separating the useful signal components from noise. Subsequently
the WT technique is applied for further refinement and thresholding of these components. This two-stage denoising strategy significantly enhances the signal quality before performing GCC for precise time-of-flight calculation
which is then converted to temperature via the known sound speed-temperature relationship. The method's performance was rigorously evaluated through simulation
laboratory experiment
and industrial field trials. [Results] Simulation analysis
utilizing actual on-site noise data
was conducted across a challenging signal-to-noise ratio(SNR) ranging from 5 dB to –10 dB. The proposed VMD-WT denoising method demonstrated superior performance compared to the conventional wavelet threshold method alone
showing marked improvements in key metrics: simulated SNR gain
the structural similarity index(SSIM)
and the correlation coefficient(CC). Laboratory experiments were performed in a controlled acoustic environment with a stable temperature of(–3.2 ± 0.5) ℃. Results confirmed the method's high accuracy
with the average absolute error of temperature measurement remaining below 0.20 ℃ across various propagation paths ranging from 1 m to 5 m. A field trial was implemented on a 750 t/day waste incinerator
specifically at the SNCR ammonia injection plane located 30.1 m above the furnace grate. The single-path acoustic temperature measurements showed consistent stability
with the average deviation from benchmark reference data maintained within 50 ℃
validating the method's robustness under real industrial operating conditions. [Conclusion] The developed VMD-WT-GCC method exhibits exceptional accuracy and stability for time-delay estimation in strong noise backgrounds
overcoming a major limitation of acoustic thermometry in practical applications. It provides a viable and effective technical solution for high-precision
non-contact temperature monitoring in complex industrial environments like waste incineration furnaces. The successful validation from simulation to field deployment underscores its strong engineering applicability and promising potential for optimizing SNCR system performance
contributing to improved combustion control and emission reduction.
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