Method for designing A-weighting filter in sound level meter based on improved whale optimization algorithm
•Identified the key error source in conventionally designed A-weighting filters.•The proposed method focuses on this error source for higher accuracy and simpler optimization.•Improved the conventional whale optimization algorithm for better performance. A-weighting filter is one of the critical com...
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| Veröffentlicht in: | Measurement : journal of the International Measurement Confederation Jg. 257; S. 118720 |
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| Hauptverfasser: | , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Ltd
15.01.2026
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| Schlagworte: | |
| ISSN: | 0263-2241 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | •Identified the key error source in conventionally designed A-weighting filters.•The proposed method focuses on this error source for higher accuracy and simpler optimization.•Improved the conventional whale optimization algorithm for better performance.
A-weighting filter is one of the critical components of a sound level meter (SLM). The bilinear transformation method (BTM) is usually used to design the A-weighing filter, which is simple but has significant deviations in the high-frequency range. This paper proposes a method for designing an A-weighting filter based on the improved whale optimization algorithm (IWOA). In this method, the initialization strategy of adding Sobol sequences to the classic Whale Algorithm (WOA) is adopted, and an adaptive iteration strategy is combined in the solving process, which can solve the problem of the classic Whale Algorithm easily obtaining local optimal solutions and accelerate convergence speed. Moreover, the errors of the A-weighting filter are analyzed, and the parameters of the A-weighting IIR filter are solved by using this IWOA algorithm. The experimental results show that the maximum error of the A-weighting filter in sound level meters with this proposed IWOA algorithm is less than 0.1 dB, which reduces the errors caused by the bilinear transformation algorithm and fully meets the requirements of Class 1 SLM defined by IEC61672-1. |
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| ISSN: | 0263-2241 |
| DOI: | 10.1016/j.measurement.2025.118720 |