Acoustic metamaterials based on Helmholtz resonance have perfect sound absorption characteristics with the subwavelength size, but the absorption bandwidth is narrow, which limits the practical applications for noise control with broadband. On the basis of the Fabry–Perot resonance principle, a novel sound absorber of the acoustic metamaterial by parallel connection of the multiple spiral chambers (abbreviated as MSC-AM) is proposed and investigated in this research. Through the theoretical modeling, finite element simulation, sample preparation and experimental validation, the effectiveness and practicability of the MSC-AM are verified. Actual sound absorption coefficients of the MSC-AM in the frequency range of 360–680 Hz (with the bandwidth Δf₁ = 320 Hz) are larger than 0.8, which exhibit the extraordinarily low-frequency sound absorption performance. Moreover, actual sound absorption coefficients are above 0.5 in the 350–1600 Hz range (with a bandwidth Δf₂ = 1250 Hz), which achieve broadband sound absorption in the low–middle frequency range. According to various actual demands, the structural parameters can be adjusted flexibly to realize the customization of sound absorption bandwidth, which provides a novel way to design and improve acoustic metamaterials to reduce the noise with various frequency bands and has promising prospects of application in low-frequency sound absorption.

An acoustic metamaterial absorber of parallel–connection square Helmholtz resonators is proposed in this study, and its sound absorption coefficients are optimized to reduce the noise for the given conditions in the factory. A two–dimensional equivalent simulation model is built to obtain the initial value of parameters and a three–dimensional finite element model is constructed to simulate the sound absorption performance of the metamaterial cell, which aims to improve the research efficiency. The optimal parameters of metamaterial cells are obtained through the particle swarm optimization algorithm, and its effectiveness and accuracy are validated through preparing the experimental sample using 3D printing and measuring the sound absorption coefficient by the standing wave tube detection. The consistency between the experimental data and simulation data verifies feasibility of the proposed optimization method and usefulness of the developed acoustic metamaterial absorber, and the desired sound absorption performances for given conditions are achieved. The experimental results prove that parallel–connection square Helmholtz resonators can achieve an adjustable frequency spectrum for the low frequency noise control by parameter optimization, which is propitious to promote its application in reducing the noise in the factory.

Porous metal is widely used in the fields of sound absorption and noise reduction, and it is a critical procedure to identify acoustic characteristic parameters and to improve sound absorption performances. Based on the constructed theoretical sound absorption model and experimental data, acoustic characteristic parameters of the porous metal were identified through the cuckoo search identification algorithm, and their reliabilities were certified through comparing with these labeled parameters and further experimental validation. By adding the microperforated metal panel in front of the porous metal, a composite sound-absorbing structure was formed, which aimed to improve the sound absorption performance of the original porous metal by optimizing the parameters. Finite element simulation and a standing wave tube measurement were conducted to validate the effectiveness and practicability of the optimal composite sound-absorbing structure. Consistencies among theoretical predictions, simulation results, and experimental data proved the effectiveness of the identification and optimization method. When the target frequency ranges were 100–1000 Hz, 100–2000 Hz, 100–3000 Hz, and 100–4000 Hz. Actual average sound absorption coefficients of the optimal composite structures were 0.5154, 0.6369, 0.6770, and 0.7378, respectively, which exhibited the obvious improvements with a tiny increase in the occupied space and a small addition in weight.

The composite structure of a microperforated panel and porous metal is a promising sound absorber for industrial noise reduction, sound absorption performance of which can be improved through parameter optimization. A theoretical model is constructed for the composite structure of a microperforated panel and porous metal based on Maa’s theory and the Johnson–Champoux–Allard model. When the limited total thickness is 30 mm, 50 mm, and 100 mm respectively, dimensional optimization of structural parameters of the proposed composite structure is conducted for the optimal average sound absorption coefficient in the frequency range (2000 Hz, 6000 Hz) through a cuckoo search algorithm. Simulation models of the composite structures with optimal structural parameters are constructed based on the finite element method. Validations of the optimal composite structures are conducted based on the standing wave tube method. Comparative analysis of the theoretical data, simulation data, and experimental data validates feasibility and effectiveness of the parameter optimization. The optimal sandwich structure with an actual total thickness of 36.8 mm can obtain the average sound absorption coefficient of 97.65% in the frequency range (2000 Hz, 6000 Hz), which is favorable to promote practical application of the composite structures in the fields of sound absorption and noise reduction.

Sound absorption performance of polyurethane foam could be improved by adding a prepositive microperforated polymethyl methacrylate panel to form a composite sound-absorbing structure. A theoretical sound absorption model of polyurethane foam and that of the composite structure were constructed by the transfer matrix method based on the Johnson–Champoux–Allard model and Maa’s theory. Acoustic parameter identification of the polyurethane foam and structural parameter optimization of the composite structures were obtained by the cuckoo search algorithm. The identified porosity and static flow resistivity were 0.958 and 13078 Pa·s/m² respectively, and their accuracies were proved by the experimental validation. Sound absorption characteristics of the composite structures were verified by finite element simulation in virtual acoustic laboratory and validated through standing wave tube measurement in AWA6128A detector. Consistencies among the theoretical data, simulation data, and experimental data of sound absorption coefficients of the composite structures proved the effectiveness of the theoretical sound absorption model, cuckoo search algorithm, and finite element simulation method. Comparisons of actual average sound absorption coefficients of the optimal composite structure with those of the original polyurethane foam proved the practicability of this identification and optimization method, which was propitious to promote its practical application in noise reduction.