Efficient Acoustic Thermometry Method for Power Plant Boilers Based on the LMS Quadratic Cross-Correlation

Le résumé fourni par la source

Aiming to achieve an accurate time delay estimation in acoustic thermometry for power plant boilers, this study proposes a time delay estimation algorithm that combines the least-mean-square (LMS) adaptive filtering algorithm and generalized quadratic cross-correlation. First, numerical simulations are conducted, followed by the experimental study performed both in a laboratory environment and on a 750 tons/day waste incineration boiler test platform. In addition, the proposed algorithm is compared with a generalized quadratic cross-correlation algorithm. The results show that the LMS quadratic cross-correlation algorithm can effectively filter out noise under both numerical simulation and laboratory conditions. The results also indicate that in a harsh environment of power plant boilers, the proposed algorithm can achieve accurate time delay estimation, significantly improving the accuracy of single-path acoustic temperature measurement.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.