Acoustic far-field prediction based on near-field measurements by using several different holography algorithms.

Near-field acoustical holography (NAH) is a useful tool for sound field reconstruction and sound source identification. In NAH, a basis model is first selected to represent the physical sound field, and then a near-field measurement is made with a microphone array. Next, the parameters in the selected model can be estimated based on the measurements by using an inverse approach, resulting in the sound field near the source being reconstructed so that the sound source location can be identified. But, in addition to being able to reconstruct the near-field of a source, the far-field can also be predicted with the identified sound source model. A significant amount of work has been performed to study the near-field reconstruction capability of different NAH algorithms, but there has been a limited number of publications in which the far-field prediction accuracy, based on the near-field measurement constructed model, has been considered. In the present experimental work, two multi-transducer loudspeakers were placed side-by-side to create a multi-component sound source, and two sets of measurements were conducted: an intensity probe scanned the sound field generated by the loudspeakers in both the near-field (0.05 m) and far-field (0.48 m) such that the true near- and far-field intensity spatial distributions and total sound power could be identified. Then, based on the near-field pressure measurements, four acoustical holography algorithms, statistically optimized near-field acoustical holography, wideband acoustical holography, l1-norm minimization, and a hybrid compressive sampling method were used to predict the near- and far-field sound intensity distributions. The near- and far-field prediction results were compared with the direct measurement, and the sound field reconstruction accuracy was studied. It was found that all of the algorithms were able to reconstruct the near-field well when the near-field measurements were used to construct the model. It was found that with the abovementioned models, far-field reconstructions could correctly predict the spatial sound field distribution, but in all of the cases, the total sound power was underestimated.

Spatially sparse sound source localization in an under-determined system by using a hybrid compressive sensing method.

Near-field Acoustical Holography is a powerful tool for sound source identification and sound field reconstruction. Generally, many microphone measurements are required to construct a source model that can span the whole sound source region while simultaneously avoiding measurement errors and ensuring a high spatial sampling rate. That type of measurement is economically costly and hard to perform in industrial environments. Motivated by the desire to be able to use a relatively small number of microphone measurements to reconstruct a sound field and to accurately identify sound source locations, an Equivalent Source Method (ESM) is considered here. In particular, the focus is on the combination of a monopole-distribution ESM and a relatively small number of microphone measurements, thus creating an under-determined system. Wideband Acoustical Holography and l1-norm Convex Optimization are introduced to solve this under-determined inverse problem. Based on the attributes of these two methods, a hybrid method combining the best features of each is proposed to identify sound source locations.

Occurrence, distribution, and ecological risk assessment of artificial sweeteners in surface and ground waters of the middle and lower reaches of the Yellow River (Henan section, China).

As a new class of water contaminants, artificial sweeteners (ASs) have attracted much attention due to their environmental persistence and potential adverse effects to human and the environment. This study systematically investigated the occurrence and distribution of four commonly used ASs in the effluent of wastewater treatment plants (WWTPs), surface water and groundwater in the middle and lower reaches of the Yellow River (Henan section). Sucralose (SUC) was dominant in WWTP effluents and had the highest mass loading. Acesulfame (ACE), cyclamate (CYC), saccharin (SAC), and SUC were consistently detected in surface water at concentrations ranging from 1.364 ng/L (CYC) to 7786 ng/L (ACE). Spatial analysis showed that the pollution level of ASs in the trunk stream was lower than that in most tributaries. The total concentrations of ASs detected in surface water ranged between 308.7 and 10,498 ng/L, while in groundwater, the total concentration of ASs detected was between ND-4863 ng/L. ACE and SUC are the main pollutants in surface water and groundwater within this survey area. The risk assessment showed that the risks of the four target ASs to aquatic organisms were negligible (risk quotient (RQ) values < 0.1), and the maximum risk quotient of the mixtures (MRQ) values of all rivers were all much less than 0.1.